process modeling for sales managementprocess and sales organization are an essential item in the...
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PROCESS MODELING FOR SALES MANAGEMENT
Carla Sofia Silva Bastos
Critical analysis and improvement through
Information Management Technologies
Dissertation report presented as partial requirement for
obtaining the Master’s degree in Information Management
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NOVA Information Management School
Instituto Superior de Estatística e Gestão de Informação
Universidade Nova de Lisboa
PROCESS MODELING FOR SALES MANAGEMENT
by
Carla Sofia Silva Bastos
Dissertation report presented as a partial requirement for obtaining the Master’s degree in
Information Management, with a specialization in Information Systems and Technologies
Management
Advisor: Prof. Dr. Vítor Santos
November 2018
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ABSTRACT
Nowadays with the emergence of new technologies, the evolution of the environments and the
empowerment of the customers, it is crucial to find new strategies, structures and ways to improve
the performance, reduce costs, increase profit and improve customer satisfaction and experience.
The solution passes by the adoption of Business Process Management by sales organizations that
desire to be efficient and competitive in their marketplaces. It is known that it is vital to understand,
implement, document, update and improve processes, more specifically, the sales processes. The
main goal of this dissertation is to perform a critical analysis of the current sales management
processes through the identification of their limitations and propose an improvement by modeling
new sales processes and sub-processes as well to present the benefits that will arise from this
change. To achieve this goal, it will be proposed new technologies and approaches like artificial
intelligence, robotic process automation, Internet of Things, among others, that allows companies to
generate what they want in terms of return on investment and drive up their efficiency levels.
At the end of this dissertation is intended to provide a holistic view of the sales management process
and help companies to use a new mechanism to plan and allocate resources and to have a clear
governance structure based on continuous learning and improvement.
KEYWORDS
Business Process Management; Sales; Sales Management Processes; IoT; BPMN; Robotic Process
Automation; Artificial Intelligence;
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RESUMO
Hoje em dia com a emergência de novas tecnologias, a evolução dos ambientes empresariais e o
fortalecimento dos clientes é crucial encontrar novas estratégias, estruturas e formas de melhorar a
performance, reduzir custos, aumentar o lucro e melhorar a satisfação e experiência do cliente. A
solução passa pela adoção da gestão de processos de negócio pelas organizações de vendas que
desejam ser eficientes e competitivas no mercado inserido. É conhecido que é vital perceber,
implementar, documentar, atualizar e melhorar os processos, mais especificamente, os processos de
venda. O principal objetivo desta dissertação é a realização de uma análise crítica dos processos de
venda atuais através da identificação das suas limitações e propor uma melhoria através de uma
nova modelação dos processos e subprocessos de vendas, bem como apresentar as principais
vantagens que irão surgir com esta mudança. Para atingir este objetivo, serão propostas novas
tecnologias e abordagens como, por exemplo, artificial intelligence, robotic process automation,
Internet of Things, entre outras, que permitirão às empresas gerar o que pretendem em termos de
return on investment e aumentar os seus níveis de eficiência. No final desta dissertação, pretende-se
obter uma visão holística dos processos de venda e ajudar as empresas a utilizar novos mecanismos
para planear e alocar recursos e a obter uma estrutura de governança clara baseada na
aprendizagem e melhoria contínua.
PALAVRAS-CHAVE
Gestão de Processos de Negócio; Vendas; Gestão de Processos de Vendas; IoT; BPMN; Robotic
Process Automation; Inteligência Artificial;
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INDEX
1. Introduction .................................................................................................................. 1
1.1. Background and Problem Identification................................................................ 1
1.2. Study Relevance and Importance .......................................................................... 3
1.3. Study Objectives .................................................................................................... 4
2. Literature review .......................................................................................................... 5
2.1. Business Process Management ............................................................................. 5
2.1.1. Concepts ......................................................................................................... 5
2.1.2. Lifecycle .......................................................................................................... 7
2.1.3. Disciplines ....................................................................................................... 9
2.1.4. Maturity model............................................................................................. 17
2.2. Sales Management .............................................................................................. 20
2.2.1. Concepts ....................................................................................................... 20
2.2.2. Characteristics of Selling .............................................................................. 22
2.2.3. Sales Management Information Systems .................................................... 23
2.2.4. Customer Journey ........................................................................................ 26
2.2.5. Challenges .................................................................................................... 27
2.2.6. Sales processes ............................................................................................. 29
2.3. Information Management Technologies ............................................................. 34
2.3.1. Business Intelligence .................................................................................... 34
2.3.2. Data Mining .................................................................................................. 36
2.3.3. ERP / CRM ..................................................................................................... 39
2.3.4. Big Data ........................................................................................................ 40
2.3.5. Decision Support Systems (DSS) ................................................................... 42
2.3.6. Robotic Process Automation ........................................................................ 42
3. Methodology .............................................................................................................. 44
3.1. Scientific methodology ........................................................................................ 44
3.2. Research Phases .................................................................................................. 46
3.3. Selection of the modeling tool ............................................................................ 47
4. Modeling of the current standard sales processes .................................................... 48
4.1. Prospecting .......................................................................................................... 48
4.2. Pre-Approach ....................................................................................................... 49
4.3. Approach ............................................................................................................. 50
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4.4. Sales presentation ............................................................................................... 51
4.5. Handling Objections and Overcoming Resistance............................................... 52
4.5.1. Satisfaction survey ........................................................................................ 53
4.5.2. Improvement process .................................................................................. 54
4.6. Close Sale ............................................................................................................. 55
4.7. Post-Sale Follow-Up ............................................................................................. 56
5. Critical analysis and improvement proposal .............................................................. 57
5.1. Critical analysis .................................................................................................... 57
5.2. Discussion and proposal ...................................................................................... 62
6. Conclusions ................................................................................................................. 70
6.1. Synthesis of work developed............................................................................... 70
6.2. Limitations and recommendations for future works .......................................... 70
Bibliography..................................................................................................................... 71
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LIST OF FIGURES
Figure 1 - BPM Lifecycle ............................................................................................................. 8
Figure 2 - Characteristics of selling .......................................................................................... 22
Figure 3 - Customer decision journey ...................................................................................... 27
Figure 4 - Business Intelligence components ........................................................................... 35
Figure 5 - Design Science Research Phases .............................................................................. 45
Figure 6 - Research Phases ....................................................................................................... 47
Figure 7 - Process "Prospecting" .............................................................................................. 48
Figure 8 - Process "Pre-approach" ........................................................................................... 49
Figure 9 - Process "Approach" .................................................................................................. 50
Figure 10 - Process "Sales Presentation" ................................................................................. 51
Figure 11 - Process "Handling objections and overcoming resistance"................................... 52
Figure 12 - Subprocess "Satisfaction Survey" .......................................................................... 53
Figure 13 – Subprocess “Improvement” .................................................................................. 54
Figure 14 – Process “Close Sale” .............................................................................................. 55
Figure 15 – Process “Post-Sale Follow-up” .............................................................................. 56
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LIST OF TABLES
Table 1 - Flow Objects .............................................................................................................. 11
Table 2 - Connecting Objects ................................................................................................... 12
Table 3 - Swimlanes .................................................................................................................. 12
Table 4 - Artifacts ..................................................................................................................... 13
Table 5 - Comparison of low and high maturity and the five maturity stages ........................ 18
Table 6 - Challenges of the Prospecting process ...................................................................... 58
Table 7 - Challenges of the Pre-approach process ................................................................... 59
Table 8 - Challenges of the Approach process ......................................................................... 59
Table 9 - Challenges of the Sales Presentation process ........................................................... 60
Table 10 - Challenges of the Handling objections and overcoming resistance process .......... 60
Table 11 - Challenges of the Close Sale process ...................................................................... 61
Table 12 - Challenges of the Post-Sale Follow-up process ....................................................... 61
Table 13 - Suggestions for new technologies in the Prospecting process ............................... 62
Table 14 - Suggestions for new technologies in the Pre-approach process ............................ 63
Table 15 - Suggestions for new technologies in the Approach process .................................. 64
Table 16 - Suggestions for new technologies in the Sales presentation process .................... 65
Table 17 - Suggestions for new technologies in the Handling objections and overcoming
resistance process ............................................................................................................ 66
Table 18 - Suggestions for new technologies in the Close Sale process .................................. 67
Table 19 - Suggestions for new technologies in the Post-Sale Follow-Up process .................. 68
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LIST OF ABBREVIATIONS AND ACRONYMS
AI Artificial Intelligence
BI Business Intelligence
BPD Business Process Diagram
BPM Business Process Management
BPML Business Process Management Language
BPMM Business Process Maturity Model
BPMN Business Process Management Notation
CHAID Chi-Square Automatic Interaction Detector
CMM Capability Maturity Model
CRM Customer Relationship Management
DSS Decision Support System
EPM Enterprise Process Management
ERP Enterprise Resource Planning
IoT Internet of Things
IT Information Technology
OMG Object Management Group
ROI Return on Investment
RPA Robotic Process Automation
SEO Search Engine Optimization
SEM Search Engine Marketing
SFA Sales Force Automation
XPDL XML Process Definition Language
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1. INTRODUCTION
Nowadays, organizations are giving a lot of attention and importance to their business process
management aiming at the performance and effectiveness improvement (Schmiedel, Vom Brocke, &
Recker, 2014). So, emerge the need to document business processes in a simple and easiest way to
be understood by all the interested parties. That is achieved by using Business Process Management,
that allows the visualization and documentation of business processes, but more importantly allows
the evaluation and management of them to identify improvements, errors, and inefficiencies. The
purpose of this dissertation is the identification of the sales management business processes and
modeling the improvement proposal of them using BPMN.
1.1. BACKGROUND AND PROBLEM IDENTIFICATION
Business Process Management has gained recognition in the Information Systems discipline
(Schmiedel et al., 2014). Is a “disciplined approach to identify, design, execute, document, measure,
monitor, and control both automated and non-automated business processes to ensure targeted and
consistent outcomes” aligned with the strategic goals of the organization as well to take advantage
of improvement opportunities (ABPMP, 2009,p.24; Schmiedel et al., 2014). It allows a company to
align their business strategy with their processes, increasing the performance through improvements
in the precise activities of a department or across the enterprise (Association of Business Process
Management Professionals, 2009).
With the intensification of the globalization, the effective management and identification of key
business processes became even more important, emphasizing that in order to achieve success it is
crucial to understand the definition of business process (Ko, Lee, & Wah Lee, 2009; Lemańska-
Majdzik & Okręglicka, 2015). If a company desires to be competitive in the market it must identify
the key processes using structured approaches, designing appropriated measures, allocating the right
resources and aligning the outcomes for their improvement and to deliver the business mission
(Lemańska-Majdzik & Okręglicka, 2015). During the past century, business models became the main
strategy to reduce costs, improve quality, and customer satisfaction. However, implementing them is
hard and entails significant risks but, even though, it helps organizations to respond to changes
(Euchner & Ganguly, 2014; Lindsay, Downs, & Lunn, 2003).
Digital technology, predominantly the Internet, is an enabler of a global marketplace, characterized
by the access of information about goods, products, prices, and specifications to everyone (Strauss et
al., 2006). The increasing use of information and communication technologies is shifting market
power from suppliers to consumers. The task of selling goods is no longer considered a simple
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exercise as meeting the buyer and seller at a marketplace and carrying out the exchange. It involves
so much more. The consumer has become the focal point of many economic, social, psychological
and cultural aspects. He seems to dictate production, to be the actor of innovation, the creator of
new services sectors in highly developed economies and the one capable of protecting and saving
the environment of the planet (Gabriel & Lang, 2008).
Consumers have the right to choose. Due to consumer’s empowerment, a real concern was born:
improve customer’s experience. Customer experience is characterized as being a set of interactions
between a customer and a product, a company, or part of its organization, which provoke a reaction.
This experience is strictly personal and implies the customer's involvement at different levels:
rational, emotional, sensorial, physical and spiritual (Pires, Stanton, & Rita, 2006). This concern in
customer experience guarantees better results, more exactly the customers stay loyal for a long
time, pay less attention to other brands and products, are less sensitive to prices, buy more as the
company launches new products and spread a good word-of-mouth. The constant need of getting
loyalty consumers by companies, the powerful global competition, the slow growth of the markets
and the demanding customers are making companies change their sales strategies and structures as
well as their sales processes. From that emerges the need to consider that reinventing the sales
process and sales organization are an essential item in the agenda as companies streamline to lower
costs and leverage their capabilities to build customer satisfaction (Cravens, 1995).
Researchers indicate that major changes to traditional sales strategies to increase the efficiency and
effectiveness of the sales processes are crucial. (Paesbrugghe, Rangarajan, Sharma, Syam, & Jha,
2017). This change incorporates the idea that the sales workforce needs to manage and translate the
work of the other departments causing a rise in the importance of sales management to business
(Ştefan & Crăciun, 2011). Every sales company knows that to have success is necessary to first
analyze the market, establish a strong relationship with consumers and invest in an efficient sales
system to have an exponential growth and be able to compete in the market. Furthermore, the
solution starts by analyzing the current sales processes and evaluate the need for changes made
through business process management and innovation.
According to these statements, the questions that require answers are the following:
1. Using the current sales processes, are companies getting all the benefits of the sales
management?
2. Are they doing it in the best possible way?
3. Is it important to change the current processes?
4. Could they be improved?
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1.2. STUDY RELEVANCE AND IMPORTANCE
“Researchers have been suggesting major changes to traditional sales strategies” (Paesbrugghe et
al., 2017, p. 1). To survive and succeed in the current competitive markets, manage costs efficiently,
raise brand awareness and improve the overall performance it is crucial to adopt new methodologies
and approaches. Business process management is the main key to these changes. Over the past
years, companies are increasing their focus on business processes. The sudden interest derives from
the necessity to optimize business operations, reduce costs and consolidate organizations
(Association of Business Process Management Professionals, 2009). Agility, integration, customer
focus, performance, innovation and compatibility combined matches the dreams of every company.
The possibility of business strategy alignment, value chain and business processes as well the
development of action plans to overcome the goals and success are some advantages of the BPM
discipline (Association of Business Process Management Professionals, 2009).
Customer satisfaction and retention are the reasons why it is important to change and restructure
the sales organization. With the goals to reduce costs and increase profits, emerge the conclusion
that the current processes are not fulfilling the actual company’s needs. (Cravens, 1995; Paesbrugghe
et al., 2017). Another reason is the constantly changing competitive environment, that requires
attention to business models because of the need for adaptation and strength over time as the
competitive environment evolves (Euchner & Ganguly, 2014).
The BPM approach brings value to every company. Their power of automation, continuous
improvement continuous learning and good customer experience are the proofs that BPM is the
future. Successful process innovation in companies involves the development of a suitable business
model, however, it is vital that the model can be resistant to change (Euchner & Ganguly, 2014). As
organizations mature in business process management it is important to be aware of procedural
questions, so it is critical the use of new mechanisms to plan and allocate resources and to have a
clear governance structure to clarify decisions that enables the improvement and transformation of
inter-functional and departmental processes (Association of Business Process Management
Professionals, 2009). Knowing that change is inevitable, it is essential to investigate and analyze the
actual performance and limitations of the current sales processes to be able to improve and provide
ways, strategies, and models that companies can adopt to get all the benefits of a BPM approach,
and reach higher levels of customer trust and satisfaction.
This research and analysis will provide a holistic view of the sales management process with the
introduction of the new technologies like social media, IoT – Internet of things –, artificial intelligence
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and robotic process automation. These technologies will allow companies to acquire more relevant
information for decision-making and reduce costs, since these technologies could replace humans
that have the function of monitoring and maintaining the quality and the viability of the supplies and
at the same time generate what companies want in terms of ROI and drive up the efficiency levels as
well gain insights for the future.
1.3. STUDY OBJECTIVES
The main objective of this dissertation is to perform a critical analysis of the current sales processes
management by identifying their limitations and to propose an improvement through the modeling
of new sales processes and sub-processes as well the benefits that will arise from this change.
To achieve the proposed main goal, the following specific objectives are defined:
1. Identify the main sales processes and sub-processes.
2. Analyze the current sales management processes performance (Prospecting, Pre-approach,
Approach, Sales Presentation, Handling Objections and Overcoming Resistance, Closing the
Sale, Post-Sale Follow-up).
3. Propose and simulate new BPM models that could improve processes’ performance by the
changing the current workflow or/and use new technologies and approaches;
4. Discuss the main advantages of the proposed models.
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2. LITERATURE REVIEW
This chapter aims to provide detailed concepts for the development of this dissertation based on
scientific and specific articles concerned with this topic. The literature review is one of the most
important phases of academic research because it focuses on uncovering what is already known “in
the body of knowledge”(Levy & Ellis, 2006). It is defined as “the use of ideas in the literature to justify
the particular approach to the topic, the selection of methods, and demonstration that this research
contributes to something new”(Levy & Ellis, 2006, p. 182).
2.1. BUSINESS PROCESS MANAGEMENT
2.1.1. Concepts
Business Process Management is considered the art and science of overseeing how work is
performed in an organization and to understand it, is crucial to, first , understand the definition of a
business process (Dumas, La Rosa, Mendling, & Reijers, 2012). A business process is a defined set of
activities or behaviors with a beginning and an end performed by humans or machines that create
value for the customer and have clearly defined inputs and outputs. It is considered the basic unit of
business value in a company and his main objective is to achieve one or more goals of the
organization (Association of Business Process Management Professionals, 2009; Lemańska-Majdzik &
Okręglicka, 2015).
There are three types of business processes (Aguilar-Savén, 2004):
• Primary processes that represent the essential activities that an organization performs to
fulfill its objectives and constitute the primary activities of the value chain with an inter-
functional nature;
• Support processes that create and manages the appropriate conditions (resources and
infrastructure) to uphold the core processes;
• and management processes that are used to measure, monitor and control business
activities, but also to ensure that primary and support processes achieve the organization’s
overall strategies and objectives.
However, processes can also be divided by its nature (Ko, 2009):
• Public processes or collaborative business processes defined as being those processes that
involve communications and exchange of something with external organizations, in other
words, transversal processes.
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• And Private processes that are those processes that can be at operational, management and
strategic levels and are only for internal use.
Business processes are also defined as the collection of inter-related events, activities, decision
points and even , more important, several actors and objects defined across time and space that
together produce a specific outcome with value to at least one customer (Dumas et al., 2012).
Due to several factors, such as the need to adapt to change, the constant need for access to
information in a faster way, shorter cycle times and quick decision-making it emerged a challenge for
companies. That challenge was the management of the business processes to achieve profitability
and survive in the marketplace that evolved into what is business process management nowadays
(Ko et al., 2009). Business process management is defined as “supporting business processes using
methods, techniques, and software to design, enact, control and analyze operational processes
involving humans, organizations, applications, documents and other sources of information” (Ko et
al., 2009, p. 745) and it implies a strong importance on the way processes are designed and
performed since affects the perceived quality and efficiency of service delivery in the eyes of the
customer (Lemańska-Majdzik & Okręglicka, 2015). It is a management discipline that relies on the
assumption that organizational objectives can be better achieved through an effective business
process management and to do that it is crucial to possess the three main pillars: processes, people,
and technology. Considered a “body of knowledge” is mainly used to define best practices and
principles (Moore, Benedict, Bilodeau, & Vitkus, 2013).
The essence of business process management resides in looking beyond functional boundaries to
offer valor to customers and to see business processes as independent elements of a formal
organizational structure (Tang, Pee, & Iijima, 2013). The main purpose is to increase the efficiency
and effectiveness of organizational processes through improvement and innovation (Schmiedel et al.,
2014). The implementation of BPM requires the commitment of all the organization because induces
new roles, responsibilities, and tasks derived from the shift from a vertical or functional focus to a
horizontal or process focus (Schmiedel et al., 2014).
Over the past few years, business process management is gaining a lot of attention and being
recognized as a critical approach to support innovation, change management and transformation
(Lemańska-Majdzik & Okręglicka, 2015). Their strategy to apply a shift from a vertical to a horizontal
process orientation and their change of thinking and working that gives a special emphasis on
processes, outcomes, and customers rather than on hierarchical or functional effectiveness became
the essential keys to the success of business process management (Tang et al., 2013).
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To achieve successfully BPM results is necessary to also take in consideration some factors that
include organizational, process, management, and technology practices (Association of Business
Process Management Professionals, 2009) such as:
• Alignment between business strategy, value chain definitions, and business processes;
• Definition of goals for business units in a way that exists agreement with the strategy;
• Development of action plans and tactics to achieve organizational goals and business
success;
• Designation of executive sponsorships, responsibility and process authorities;
• Identification of the process owners as well the authority to make changes;
• Establishment of metrics, measurements, and processes;
• Institutionalization of practices such as continuous improvement research, change
management, change control and products;
• Standardization and automation of business processes and related methodologies.
2.1.2. Lifecycle
BPM is mainly a cross-discipline “theory in practice” subject involving knowledge from several areas
such as organization management theory, mathematics, and linguistics. Given its multi-disciplinary
nature, there are many views of the generic business process modeling lifecycle since each business
reality, and each project is unique, it is impossible to predict how its implementation will be (Ko,
2009). The generic BPM lifecycle is known as a continuous and iterative lifecycle of integrated
activities that include: Planning, Analysis, Design and Modeling, Implementation, Monitoring and
Control and Transformation influenced by primary factors such as leadership, values, culture, and
beliefs (Association of Business Process Management Professionals, 2009).
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Figure 1 - BPM Lifecycle Source: (Association of Business Process Management Professionals, 2009)
Planning: In this phase, a process-driven strategy and a plan are developed to set the goals,
responsibilities, performance, methodologies, and direction to BPM processes to ensure the delivery
of value to the customer and the inclusion of customer’s expectation. It is very important to spread
an understanding of the organizational structure for customer-centric process management to
guarantee an alignment with people, processes, and systems with the strategy across functional
boundaries (Association of Business Process Management Professionals, 2009).
Analysis: In this phase, business processes problems are identified, delimited, documented and
addressed according to the desired objectives and goals. This analysis incorporates different
methodologies and provides an overall view of business processes models, performance, resilience
and their relationships. During this phase, several points like business modeling objectives, business
environment, the stakeholders and the modeling scope are analyzed (Dumas et al., 2012).
Design and modeling: In this phase, it is defined what the organization wants the process to be and
answers the questions: what, when, where, who and how the work is executed.
The Design covers not only the existing business process identification and design but also the future
process improvements (to-be). It is crucial to underline the importance of component design to
ensure that the appropriate metrics and controls are implemented to allow the performance and
compliance measurement. Is supported by modeling software in which the flow of processes, actors
involved, messages, notifications or other operational procedures are designed for a system that
already exists or for a future system (Juric & Sasa, 2009).
The Modeling phase is defined as the set of activities focused on creating complete and precise
representations of an existing or proposed business process where the level of detail and the specific
type of models are fundamental (Moore et al., 2013). The main purpose is to analyze in detail the
drawings produced in the Design and to introduce combinations of variables that allow the
evaluation of process consistency, that is, to understand how the process reacts to different
circumstances or unforeseen scenarios (Hajiheydari & Dabaghkashani, 2011).
Implementation: In this phase, occurs the transition between the theoretical models to executable
models, in other words, the processes seen as mere abstractions become executable processes and
the changes required to move from the “as-is” process to the “to-be” process are prepared and
performed (Association of Business Process Management Professionals, 2009). The implementation
involves two complementary facets: process automation that involves the configuration or
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implementation of an information system to support both “as-is” and “to-be” processes and
organizational change management that are defined as the set of activities required to change the
way of how things are being done by the actors involved in the processes (Dumas et al., 2012).
Monitoring and Control: In this phase, occurs the monitoring of processes individually to identify
necessary resources adjustments and generate performance statistics acquired through key
measurements related to goals and value to the organization that can result in improvement,
redesign or re-engineering to better control the execution of the process (Association of Business
Process Management Professionals, 2009). “Every good process eventually becomes a bad
process”(Vom Brocke & Rosemann, 2010), unless it is carried out a continuous measuring and
monitoring of business processes to keep up with the ever-changing environment, customer needs
and competition (Dumas et al., 2012).
Transformation: In this phase, the outputs and data of the iterative process lifecycle are
implemented to optimize the information flow, in other words, process improvement. It is identified
the possible organizational change management constraints and challenges to achieve process
optimization, reduced execution time, human intervention and costs. The process optimization is
managed to be able to respond to the environmental changes and achieve consistent results. If the
process optimization doesn’t reach the expected outcome it is recommended business process re-
engineering that is been used to achieve efficiency and productivity (Association of Business Process
Management Professionals, 2009).
2.1.3. Disciplines
Business process management is composed of eight disciplines: Modeling, Analysis, Design,
Performance Measurement, Transformation, Organization, Enterprise Process Management, and
Technology.
Modeling:
Process modeling is considered the fundamental basis for managing a business. (Moore et al., 2013).
Requires a combination of a set of processes and techniques that give a vision and an understanding
of the business process to allow the analysis, design and performance measurement (Association of
Business Process Management Professionals, 2009). It should be capable to “support emerging
consumer-technology-driven and take a stronger role in communicating to the business in different
ways”, that is, focus more on business services and capabilities instead of process maps (Moore et
al., 2013, p. 84).
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Is also defined as the group of activities that are involved in the creation of existing or proposed
business processes to provide an end-to-end perspective of the primary processes, support, and
management of an organization (Association of Business Process Management Professionals, 2009).
The main purpose of process modeling is to create an accurate and sufficient representation for the
process and it should be noted that the level of detail and specific type of model need to be based on
the expectation for the outcome (Moore et al., 2013). Its focus passes by document an existing
process clearly, understand how a process behaves in different situations or in response to some
anticipated change, serve as a basis for identification of improvements and use as training support
and an assessment of standards and requirements (Association of Business Process Management
Professionals, 2009). In 2004, with the growing need for a common language or symbology to
facilitate understanding and acceptance arose a modeling standard for process modeling – Business
Process Management Notation (White, 2004).
Business Process Modeling Notation is a simple notation proposed by Business Process Management
Initiative with the main objective to create a language and a universal architecture for business
process management that provides the understanding of modeling to all users that are involved in
business and support process improvement and management (White, 2004). “Being a graphical
notation, BPMN hopes to bridge the gap between IT and business analysts”(Ko et al., 2009, p. 756).
BPMN is a visual model of BPML - Business Process Modeling Language and defines a single BPD -
business process diagram to express business processes based on a flowcharting technique
(Association of Business Process Management Professionals, 2009; White, 2004).
A BPD is made up of a set of graphical elements divided into four categories: flow objects, connecting
objects, swimlanes and artifacts.
Flow objects are graphical elements that determine the course of the business process and are
composed of three core elements: event, activity, and gateway.
• An event is something that happens during the course of a process, affecting the process
flow and normally have a cause or an impact. There are three types of events, based on
when they affect the flow: Start, Intermediate, and End.
• An activity is task or tasks carried out by members of the organization. They stand for manual
or automatic tasks performed by an external system or user and can be classified into tasks
or sub-processes.
• A gateway is used to control the divergence and convergence of sequence flows. It implies
that there is a decision that either allows or disallows passage through the gateway.
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Category Element Type Representation
Flow objects
Event
Start
Intermediate
End
Activity
Atomic
Compound
Gateway
Table 1 - Flow Objects
Connecting objects represent the connections between the flow objects in a diagram to create the
basic skeletal structure of a business process. They are composed of three elements: sequence flow,
message flow, and association.
• A sequence flow is used to show the order (the sequence) that activities will be performed in
a process.
• A message flow is used to show the flow of messages between two separate process
participants (business entities or business roles) or processes that send and receive them.
• Association is used to associate information and artifacts with flow objects and is used to
show the inputs and outputs of activities.
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Category Element Representation
Connecting objects
Sequence Flow
Message Flow
Association
Table 2 - Connecting Objects
Swimlanes are described as a mechanism to organize activities into separate visual categories to
illustrate different functional capabilities or responsibilities. Are divided into two types: pools and
lanes.
• A pool is a container of a single process that contains the sequence flows between activities
and expresses a participant in a process. Is used when the model involves two or more
business entities that are physically separated in the diagram.
• A lane is a sub-division within the process. Is used to differentiate elements such as roles or
positions and represent functional areas responsible for tasks.
Category Element Representation
Swimlanes
Pool
Lane
Table 3 - Swimlanes
Artifacts are used to provide the ability to add context or extra information to a specific situation,
but also to represent entries or exits of documents, information, etc. There are three types:
• A data object is a mechanism to show how the data is produced or required by activities and
is connected to activities by associations.
• A group is a mechanism that allows the grouping of activities for documentation or analysis.
• An annotation is a mechanism to provide additional information about the process.
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Category Element Representation
Artifacts
Data object
Group
Annotation
Table 4 - Artifacts
Analysis:
Process analysis creates the foundation for process design. (Moore et al., 2013). It is considered an
essential tool to create a common understanding of the process activities and their current state but
also to measure the outcomes of those activities according to the defined organizational objectives.
Can be applied to evaluate the current and future improvement opportunities and to generate useful
information for decision-making because, without it, decisions are made based on opinion or
intuition rather than documented or validated facts. This information generated should include some
factors such as business environment, process context, process inputs and outputs, strategy,
objectives, goals, business rules, performance metrics and roles of each business unit that must
achieve the goals regardless of some inefficiencies (Moore et al., 2013).
Process analysis creates also an understanding of process efficiency and effectiveness that is defined
as the measure calculated through the attainment of a purpose or a process need and whether the
process meets the needs of the customer or reaches the business objectives. It can be done at any
time by the organization or in response to single events, but it is recommended that the company
carry out continuous monitoring of processes instead of waiting that specific events trigger the
analysis. This continuous monitoring is essential since alerts to the possibility of reduced process
performance and supports the discovery of the root-cause to take immediate action to resolve them
(Moore et al., 2013). It must be noted that the process analysis should not be seen as an event, but
rather as a commitment that will enable organizations to optimize processes and monitor their
performance, thereby increasing organizational performance(Moore et al., 2013).
Design:
Process design is the definition of objectives, rules, and deliverables that could be logical or physical
to create a result, service or product that is beneficial for everyone involved. Implicates the
identification of current activities, functions, information systems and mechanisms and the
understanding of the existing processes, sub-processes and the interaction between them and the
business units responsible for their performance (Moore et al., 2013).
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The first step to being taken before starting any process design is to review the deliverables from the
previous phase (analysis phase), more specifically: it should include documentation of the current
process state, list of constraints, as well as the clear scope. Is main objective passes by the creation of
specifications for the new and the modified business processes considering the process performance,
the data resources, business objectives and technology platforms to improve the ability to grow and
change in a quicker way. The outcome should be measurable because it will define the quality of the
new process design and to be attainable it is essential to understand how the business work today
and how it should work tomorrow (Moore et al., 2013). “A process design can be simple and static,
but it tends to evolve, taking on an intelligent and dynamic nature as the business context gets more
complex and differentiating” (Moore et al., 2013, p. 157).
Performance Measurement:
Performance Measurement is defined as the foundation for performance management to specify the
management of a business operation at a process level and a workflow level that belongs to a
business unit. The first step to take in consideration when initiating any performance measurement is
to look at the effectiveness of the processes that will be measured and monitored because they must
be justified by their impact on the end-product or service but also if processes are defined and
understood by the customer and organization (Moore et al., 2013). Once this step is accomplished, it
is possible to develop a method to define and measure the performance avoiding common mistakes
such as the lack of understanding of processes, their way of work and the inexistence of sufficient
maturity to support a complex performance measurement.
All processes have a metric and measurement associated with the work or output of the process that
is executed. The four fundamental dimensions of metrics are (Moore et al., 2013):
• Time: is a measurement of process duration, that is, the time it takes between the start and
end of a process.
• Cost: is a measurement of the monetary value associated with a process, that includes
resource and opportunity costs.
• Quality: is a measurement of actual percentage to the optimal maximum in process terms,
that can be expressed by satisfaction, variation, and error or defect rate.
• Capacity: is an amount/volume of a viable output associated with a process.
The measurement results are related to many factors: level of flexibility in data access, process
maturity level, definition and agreement on what to measure and how, ability to report through
presentation and the acceptance of the users that will carry out the measure (Moore et al., 2013).
The key aspects of performance management are the focus on people and processes, the guarantee
understanding of the whole process, not only individual tasks, the understanding of how the process
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is tied to operational performance metrics and aligned with performance compensation and the
guarantee that those who draw up and approve the activities are the same persons who carry out
the activities (Moore et al., 2013).
Transformation:
Process Transformation is defined as the planned evolution of business processes using a clearly
defined methodology and a disciplined approach to ensure that the process continues to achieve
business objectives. It is considered the fundamental rethink of a process with the main objective of
innovating and creating new business techniques, technology and so much more. Being cross-
organizational, their scope must involve all business units, whose existence is crucial for a definition
of the processes that are involved in the transformation, due to the invasive and disruptive nature
(Moore et al., 2013). The main goal is to optimize process work. However, there are some limiting
aspects that need to be discovered at the beginning of the process transformation to avoid time and
resource waste.
Process transformation can deliver high-quality outcomes faster and at a reduced cost, leverage the
competitiveness and production capability as well as improve the long-term strategy. It involves
pursuing ideas, though and opinions from the inside and outside of the environment, but it must be
noted that what results in one company may not work in the other company even if it is similar. So, it
is extremely important to analyze all the information and inputs gathered to “fit” in the company at
the beginning of the process transformation. Process transformation contains a much bigger change
than improvements even when is applied to every aspect of the transformation (Moore et al., 2013).
Includes several methodologies such as Six Sigma, Lean, Total Quality Management and Activity
Based Costing. Six Sigma is considered the measure of organization business process performance
and focuses on increasing customer value and efficiency by improving product or service quality and
cost to leverage profit. It identifies and eliminates unnecessary costs. In other words, costs that don’t
bring value to the customer and can be used to predict the future, because it provides to the
organization a better understanding of customer needs (Pyzdek & Keller, 2010).
Lean methodology is a management philosophy based on the reduction or elimination of seven
wastes (overproduction, waiting time, transport, processing, stock, handling, and defects). Is
reflected as an instrument for improving operational processes and, therefore, a mean of re-
engineering or designing new processes (Freire & Alarcó N, 2002).
Total quality management is characterized by the cooperation between the organization and their
business processes to achieve continual improvement and better-quality products and services that
exceed the needs and expectations of customers. It has a set of principles to manage the
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organization such as everyone should be involved, quality for profit, competition standards and
ownership (Dale, 2015).
Activity Based Costing is a methodology that defines and measures the costs and objects, resources
performance that an organization needs to perform logistic activities. Incorporates relationships
between cost objects and activities and between activities and resources (Bartolacci, 2004).
“Today, business transformation, leveraging emerging technologies and BPM methods and
techniques, is positioned to change the way business is conducted”(Moore et al., 2013, p. 262).
Organization:
Every enterprise has its own culture, structure, values and business processes tailored to its own
business which makes it unique. (Moore et al., 2013). However, most of the organizations are still
structured around functional structures or products instead of being around their business
processes. Instead of managing the resources and responsibility delegation by hierarchical levels and
with a restricted control as traditional organizational structures do, the organizations that made the
transition to a process-driven organization assign horizontal responsibility by delivering value to the
customer, involving process design, documentation, measurement, and transformation achieving
more success. Changing organization’s approaches is very challenging but it is strongly important
since processes achieve new maturity levels, emerge new skills, roles and new ways to align the
employee’s motivation (Moore et al., 2013). A process-driven organization is a structured, organized,
managed, and measured organization through its primary business processes. Having a process-
oriented organization does not mean that processes are the only dimension of management,
performance measurement, or organizational structure, there are also financial dimensions and
functional capabilities involved (Moore et al., 2013). It is an integrated approach for performance
improvement that takes into account the organization as a whole and the inclusion of processes and
roles of individuals in the process and organization. By fostering a process culture companies should
identify their business processes, communicate and make it visible to all the organization because
this new culture covers a set of rules, procedures, tools to achieve a specific goal.
Enterprise Process Management:
Enterprise process management characterizes a new approach to business operations. It involves the
transition from strategy thinking in general or financial terms to a strategy in terms of observable
cross-functional activity and is concerned with all processes. By using a higher-level perspective, it
allows the control of the impact and the change benefits in business operations and individual
business units, but also the management of performance, cost, and quality. Requires careful thinking,
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change of vision, and a new set of leadership behaviors and it aims to align the processes with the
objectives of the organization and achieve efficiency (Moore et al., 2013).
It ensures the alignment of the end-to-end business process portfolio and process architecture with
the organization's business strategy and resource allocation, providing a governance model for
management by involving planning, collaboration and the growing definition of technologies to
uphold, upgrade, innovate and manage end-to-end business processes that drive business agility. The
role of measurement is essential to maintain a customer-centric focus and ensure accountability for
the performance of the organization's large cross-functional business processes (Moore et al., 2013).
Technology:
Nowadays, BPM technology is evolving and changing quickly going from “simple workflow modeling
tools to complex integrated tools that provide a complete operating platform and environment”
(Moore et al., 2013, p. 373). It is characterized by two types: standalone single-purpose tools and
integrated group of tools called Business Process Management Suites (Moore et al., 2013). The
standalone single-purpose tools provide model reuse, operation visibility and rules rationalization
within their focus area. However, they cannot offer the capability to change and optimize the
organization’s operations or provide a complete operating environment that generates applications
that runs inside them that BPMS delivers. Business Process Management Suites enables the
integration between business and IT and the implementation of change management with a focus on
processes when it is necessary. “BPM technology supports the entire lifecycle of a business process,
from design through implementation to execution and controlling of processes. It supports the
linking of strategy to processes through an appropriate design using Business Process Analysis (BPA)
tools and converts that strategy into an agile execution using BPM automation engines” (Moore et
al., 2013, p. 367). Nevertheless, the agile BPM technology needs a well-defined governance to create
value with agility and scalability and to be certain that their technology is aligned, consistent and in
conformance with organization requirements (Moore et al., 2013).
2.1.4. Maturity model
Business process management “is widely recognized as a foundation for contemporary management
approaches as it goes via the analysis of business processes to the roots of an organization”
(Rosemann & Bruin, 2005, p. 3). With the increasing importance of BPM, organizations start to focus
on the analysis of the different maturity level of their processes. Maturity is defined as a way to
assess “the state of being complete, perfect, or ready” and the “fullness or perfection of growth or
development” (Rosemann & Bruin, 2005, p. 3). As organizations that implement BPM can be in
different stages/levels of maturity, it is crucial that they implement a model of maturity to know in
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which levels of maturity they are and to be guided to future improvements. There are several
proposed models to measure the maturity of BPM, being the most common basis of comparison, the
capability maturity model (CMM). CMM was created by the Software Engineering Institute at
Carnegie Mellon University to enrich software-development and maintenance capability. It helps
companies to gain control of their process improvement and determine their current process
maturity to identify critical issues (Paulk, Curtis, Chrissis, & Weber, 1993). CMM argues that the
greater the maturity of a process, the greater the predictability and quality of the results achieved
and to set “sensible goals for process improvement it is required an understanding of the difference
between immature and mature software organizations”(Paulk et al., 1993, p. 19). An immature
organization is an organization that doesn’t follow any guide or plan for software processes. It is
reactive, in other words, take immediate actions when something goes wrong and improvises along
the way (Paulk et al., 1993). Is impossible to measure/predict product quality because “when hard
deadlines are imposed, product functionality and quality are often compromised to meet a schedule”
(Paulk et al., 1993, p. 19). A mature organization is an organization where plans, schedules, budget,
and objectives are well defined and fulfilled. The software processes, roles, and responsibilities are
communicated and known by everyone and the product quality is monitored constantly as well as
the process that produces them (Paulk et al., 1993).
Immature organization Mature organization
Uncoordinated and isolated
projects
Coordinated BPM activities
Low BPM skills High BPM Expertise
Key personnel Organizational-wide coverage
Reactive Proactive
Manual Automation
Internally Focused Extended Organization
Low Resourcing Efficient resourcing
Naive Comprehensive understanding
Static Innovative
Table 5 - Comparison of low and high maturity and the five maturity stages Source: (Rosemann & Bruin, 2005)
Nowadays, the Business Process Maturity Model developed by OMG derived from the CMM is one of
the more than 200 existing maturity models. BPMM is a model created to monitor the improvement
of business processes “characterized as workflows across organization boundaries”(Weber, Curtis, &
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Gardiner, 2008, p. 4). It incorporates improvements in coverage, structure, and interpretation, and
contains several principles such as (Weber et al., 2008):
• If the organization is not mature enough will not be able to support capable processes.
• To define process capability, their attributes could be assessed to achieve organizational
goals.
• “Each stage or maturity level lays a required foundation on which future improvements can
be built” (Weber et al., 2008, p. 3).
• Process improvement should be an organizational change program to reach more predictable
stages of organizational capability.
BPMM is divided into 5 maturity levels that represent different stages that a company achieves as
they improve their processes and skills like all maturity models that follow the CMM framework
(Weber et al., 2008). The five maturity stages are the following (Weber et al., 2008):
Level 1 – Initial level: organizations included in this stage typically produce their own products and
services, however, they spend too much money or exceed schedule. Some of their characteristics are
lack of commitment and specific goals, processes rarely defined or documented, documented
processes are not followed, practices and inconsistent process results, excessive difficulty to adapt to
change, and the inexistence of a stable environment for process implementation.
Level 2 – Managed level: organizations included in this stage already have basic planning and
management processes that perform all the crucial activities to support and improve their products
and services. Some of their characteristics are: being aware of key costs, schedule, and quality,
control of management needs, existing support of senior management positions, assignment of roles
and responsibilities, commitments and supplier sourcing agreements made.
Level 3 – Standardized level: organizations included in this stage are in a growing state of
development of their BPM capabilities, increasing the number of individuals seeing the organization
from a process perspective. Some of their characteristics are the creation of documentation for the
use of the whole organization, standard processes synthesized from best practices, consistent
performance of work activities, assignment of a team responsible for coordinating the activities, use
of mechanisms to improve standard processes and elaboration of a guideline that compiles all
questions and clarifications.
Level 4 – Predictable level: organizations included in this stage already have a solid implementation
of BPM in their business and benefit with that. Some of their characteristics are the management of
the infrastructure capacity of organizational processes and the compliance with established goals for
quality and performance, existing integration of processes, predict performance and outcomes to be
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achieved to manage organization assets, use of different approaches and measures, implementation
of changes to reduce process variation and achieve expected performance and quality goals.
Level 5 – Innovating level: organizations included in this stage view BPM as an integral part of its
strategic and operational management and addresses its critical business issues or areas of concern.
Some of their characteristics are: the definition of improvement objectives in all stages of the
organization, implementation of changes to fill the gaps between the current performance, capability
and the expected outcomes, execution analysis of defects and problems to determine their causes
and implementation of corrective actions.
It is important to take in consideration that these models are suggestions and best practices that
indicate what should be done, but not how it should be done (Weber et al., 2008). It is
recommended that every organization define their strategies and approaches according to their
objectives and desired outcomes.
2.2. SALES MANAGEMENT
2.2.1. Concepts
Nowadays, every person in their daily lives deals with goods and services transactions. Selling is
defined as the act of convincing people to satisfy a need or want and the exchange of something
between two parties - the vendor, and the buyer - for money (Kundu & Bishnoi, 2009). “Selling is the
act, sales are the result of this act” (Kundu & Bishnoi, 2009, p. 18). It has been gaining importance
due to a simple reason: the person that performs the sale defined as a salesman is the most
significant connection with the buyer (Jobber & Lancaster, 2009) but is also the major point of
failure. Therefore, emerged the concept of salesman coordination and control called Sales
Management (Kundu & Bishnoi, 2009).
Sales management “meant management of all marketing activities, including advertising, sales
promotion, marketing research, physical distribution, pricing, and product merchandising” (Kundu &
Bishnoi, 2009, p. 3). It is also defined as “the planning, direction, and control of the personnel, selling
activities of a business unit including recruiting, selecting, training, assigning, rating, supervising,
paying, motivating, as all these tasks apply to the personnel salesforce” (Singh et al., 2011, p. 4). And
“sales management refers to the control and form of the personal sales contact, the sales system
(sales structures, processes, and channels) and distribution in national and international markets”
(Dannenberg & Zupancic, 2009, p. 4).
The person who performs sales management is called sales manager. This manager has the
responsibility to guarantee that the sales activities generate the most effective contribution to the
accomplishment of the organization goals and objectives, determine the goals of the salesforce,
forecast and budgeting, salesforce selection, recruitment and training, motivating the salesforce
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team, organize the sales force size and planning and evaluate and control the salesforce (Jobber &
Lancaster, 2009).
Sales management is composed of four elements: planning, coordination, controlling and motivating
(Kundu & Bishnoi, 2009).
Planning: organizations must create some strategy to plan. First, they need to be aware of the
future, the way they want to do their work and decide who should do it. Then develop a plan after
doing some market research and studies, identifying the competitors and types of products. This plan
should be flexible, continually updated and communicated to all people that execute activities in the
organization.
Coordination: “ is all pervasive and permeates every function of the management process”(Kundu &
Bishnoi, 2009, p. 7). It involves principles and good practices to build up organizational skills, support
the workers and help them to have a total vision of their activities and how to coordinate them with
the team. The sales manager has an important role in this phase because he needs to motivate,
develop a close relationship, promote direct contact among the organization and guarantee the flow
of information about the objectives.
Controlling: involves the constant revision of the sales activities direction and the conformance of
sales activities with the organization objectives and goals. The sales manager need to guide and lead
the team to anticipate problems that can occur in the future and avoid them by taking corrective
measures. In this phase, the budget and schedule are controlled and the level of efficiency of the
salesman’s work.
Motivating: only motivated salespeople can achieve business goals (Kundu & Bishnoi, 2009). To join
a different type of people in a team and leverage their productivity is crucial to analyze and
understand behavior patterns in the first place.
Every organization has goals and objectives that aims to achieve. The most common ones are
reasonable profitability, sales volume, market share, continuous growth, and good corporate image.
All objectives have their importance. However, they must be represented in a measurable,
quantitative way, must be realistic, achievable, integrated and organized in a hierarchical manner.
They must be defined and formulated not only by the top management but must involve the
salesforce and should only be defined after some studies and analysis of the market and trends.
These objectives are affected by the efficiency and effectiveness of the sales management that helps
the organization to achieve economies of scale (Kundu & Bishnoi, 2009; Singh et al., 2011).
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2.2.2. Characteristics of Selling
There are some very essential characteristics of selling that the sales force need to know and engage
with them to succeed in their job that are: customer retention and deletion, database and
knowledge management, customer relationship management, marketing the product, problem
solving and system selling, satisfying needs and adding value (Jobber & Lancaster, 2009).
Figure 2 - Characteristics of selling
Source: (Jobber & Lancaster, 2009)
Customer retention and deletion: it is known that 80 percent of the organizations sales come from
20 percent of their customers (Jobber & Lancaster, 2009; Kotler & Keller, 2016).
This means that the organization should dedicate some time and resources to identify, satisfy and
retain highly profitable, valuable and high-volume customers. From that emerges the concept of key
account management that allows sales team to target and serve a specific group of customers with
complex needs and give them special treatment. However, organizations shouldn’t focus only on
their profitable customers but also analyze and identify the customers that cost more to retain than
to generate profit. In that case, it is crucial to define a strategy and take actions to transform them
into valuable customers or discard them (Kotler & Keller, 2016).
Database and knowledge management: the information gathered from customers, products and
competitors should be stored in an organized, simple and integrated repository. Sales force needs to
be able to use and create databases to store information and generate knowledge from it.
Nowadays, with the technological advances, it is easier to find information and communicate with
customers and potential customers, so organizations should take advantage of that and store them
electronically (Jobber & Lancaster, 2009).
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Customer relationship management: The customer is always right, so the sales team need to focus
on long-term and close relationships with customers and not only on closing the sale. The idea is that
the organization start to create win-win interactions, where customers gain more trust and become
loyalty (Beverland, 2001).
Marketing the product: face-to-face communications are starting to lose their value, because of
content that customers have access to in the internet that allows them to receive up-to-date
information easily and more-time convenient. Sales force is dealing with so much more activities
than only planning and presenting the product or service to the customer such as product
development, market segmentation and database management (Jobber & Lancaster, 2009).
Problem-solving and system selling: “Customers are increasingly looking for a systems solution
rather than the buying of an individual product” (Jobber & Lancaster, 2009, pág.30). Therefore, sales
force need to communicate and follow the customer to identify problems, determinate needs and
propose solutions. It involves multiple interactions, follow-ups and sales force analytical skills (Jobber
& Lancaster, 2009).
Satisfying needs and adding value: customers sometimes don’t know they have a need, and in this
type of situation is where salesforce enters. They should be able to identify customer needs and
persuade them to be aware of that need (Jobber & Lancaster, 2009). With that recognition “the
salesperson will have added value to the customer’s business by reducing costs and created a win-
win situation for their company and the customer”(Jobber & Lancaster, 2009, p. 30).
2.2.3. Sales Management Information Systems
An information system is a set of interrelated components that collect or retrieve, manipulate, store
and distribute timely, relevant and accurate information to achieve an objective and to support
decision making. It is used to help workers to analyze issues and problems, complex subjects and
create new products or services (Donaldson, 1998; Laudon & Laudon, 2012; Reynolds & Stair, 2010).
To truly understand the power and the definition of information systems it is necessary to go deeper
and deeper into their structure such as organization, management and information technology
dimensions of information systems. The area of management information systems embraces the
understanding of all the following sub-dimensions: organizational, managemental and technical
(Laudon & Laudon, 2012). A management information system is a systematized collection of people,
software, databases, machines, and techniques that provide repetitive information to support
decision makers. It is focused on operational efficiency and an integrated database (Reynolds & Stair,
2010).
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A sales management information system belongs to a management information system and is a set
of business activities and related information process operation connected with the delivery of goods
and services to customers to provide the product, in a certain place, on the right time. It is composed
of four business activities, namely: sales order, delivery, billing and accounts receivable, and cash
receipts (Alianto, FernandiWijaya, & Arlan, 2012).
It is also characterized as a system that integrates people, equipment and procedures to machines to
deliver information to support the sales activity and is considered essential to run a business
(Setiawati & Rohayati, 2014).
In the past few years, customers have become more demanding, informed and more complex. The
need to present timely and accurate information, personalized services, market expertise and, at the
same time, develop strong and lasting relationships with customers in a competitive environment
implies the adoption and implementation of custom-design sales force automation tools (Boujena,
Johnston, & Merunka, 2009; Maynigo et al., 2005).
Sales automation systems consist of computerized hardware, software, telecommunication devices
to offer automated collection, analysis, assimilation and delivery of information to improve
productivity, manage contacts, monitor customer relationships and sales processes, schedule
meetings and track sales leads (Buttle, Ang, & Iriana, 2006; Maynigo et al., 2005; Morgan & Inks,
2001). This information can contain market data, competition and customer profiles, pricing lists and
any other data required to carry out the business where it is inserted (Buttle et al., 2006). Consists of
an integrated database system that can be accessed through a modem by remote access from a
computer using SFA software. It allows a salesperson to get updated information in real time for the
performance of their duties (Buttle et al., 2006). It is also defined as being an information technology
application that supports sales functions by improving the quality and speed of information flow
across the organization (Boujena et al., 2009; Buttle et al., 2006).
SFA systems contain contact management, mechanization of administrative tasks, computer-based
training, strategic information exchange and development of sales presentations (Morgan & Inks,
2001). They have three main defined goals that are: increase customer retention and acquisition,
improve customer relationships and integrate them into contact management (Buttle et al., 2006).
Although this system reduces time spent on repetitive activities, it increases productivity, efficiency
and customer relationship quality and improves quality and speed of communication within the
organization. This is a great challenge for organizations to implement because of the change it
implies. However, organizations that adapt their processes to the sales automation system, and thus
have a robust solution, have an advantage over their competition (Boujena et al., 2009; Maynigo et
al., 2005; Morgan & Inks, 2001).
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With the emergence of the Internet and its connectivity, the world of sales as changed (Greg W.
Marshall, Moncrief, Rudd, & Lee, 2012). Salesperson now has the possibility to search for new
potential customers in a more efficient way, as well as, to serve the existing customers and develop
stronger relationships with them (Long, Tellefsen, & Lichtenthal, 2007).
The possibility of reducing costs has led organizations to decide to focus on sales technology rather
than people (Greg W. Marshall et al., 2012). However, investing in technology is not enough. It is
necessary to integrate sales technology with sales processes and human capacity to increase sales
performance (Rodriguez, Ajjan, & Peterson, 2016), but also make this adoption useful and easy to
use for sales person (Long et al., 2007; Rodriguez, Peterson, & Krishnan, 2012).
Sales technology is defined as any communication and technological information used by the sales
organization to carry out its main activities (Rodriguez et al., 2012). Enabling accelerated mobility,
productivity, and efficiency of salespersons (Greg W. Marshall et al., 2012).
With the increasing difficulty in managing relationships with customers due to their strong
interactivity with technology and the need to better understand customers, arise the need for
integration of social media applications, internet of things and robotic process automation into sales
management information systems (Rodriguez et al., 2016).
Social media is defined as being digital content and network interactions that are created and
developed by individuals. It is a group of Internet-based applications that have been created in the
foundations of Web 2.0 that allows the exchange and creation of user-generated content (Agnihotri,
Kothandaraman, Kashyap, & Singh, 2012). With the integration of social media in organizations now,
it is possible to exchange ideas, knowledge, content, perform sales-tasks by the salesperson
(Rodriguez et al., 2016), and communicate with customers, but also with suppliers, business partners
and their employees (Schuldt & Totten, 2015). Even more importantly, integrating social media with
sales processes enables organizations to reach new customers and get accurate and important
information to more quickly identify the needs, desires of its customers (Rodriguez et al., 2016), as
well as share information about its products and services and enable customers to express their
opinions and feelings about a product or service they have purchased (Rodriguez et al., 2012).
With this information collected from social networks, organizations are able to improve decision-
making, how they serve their customers and create solutions that are more appropriate to their
target group (Rodriguez et al., 2012), as well as build stronger, trust-based relationships that help
create bonds and network expansion that increase the reach of salesperson and customer loyalty
(Agnihotri et al., 2012). However, it is important to emphasize that the implementation of social
media differs from organization to organization depending also on its size and the market in which
they are inserted (Rodriguez et al., 2016; Schuldt & Totten, 2015).
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With the integration of Internet of Things in sales management information systems, the data that is
collected online will have more quality and will be collected in greater quantity since IoT has
technology incorporated into all the unimaginable items, from the walls to small appliances that
everyone has at home, which allows the collection of relevant information (Schuldt & Totten, 2015).
The IoT is defined as a physical device consisting of several items in the network that contains
software, electronics, network connectivity and sensors to collect objects that allow the exchange of
data. It allows the connection of objects or devices to the Internet to interconnect them in an
intelligent way that allows the communication between them, their components and people (Bhatt,
Dey, & Ashour, 2017). To achieve efficient and effective use of IoT systems, organizations need to use
advanced technologies, algorithms, tools, and models to be able to process a large amount of data
they collect in different formats and to extract value from them. Due to this pre-requisite, there were
developed several technologies like wireless communication, cloud computing, machine learning and
big data analysis (Bhatt et al., 2017).
It is also important to note that Artificial Intelligence also plays a crucial role because it is defined as
the ability to perceive, think and learn as humans indicating the possibility of using
computers/machines to simulate human intelligence. AI, over time, has transformed itself in a
phenomenal way of enhancing intelligent hybrid systems combined with people and machines, new
crowd intelligence systems and more complex intelligent systems for cities that combine human,
societies and cyber systems (Pan, 2016).
2.2.4. Customer Journey
The emergence and use of new technologies, new business models and rapidly changing markets
have generated a need for organizations to realize their customers' needs, wants, and the way and
motivations that they shop and make decisions (Gordon, Gruntges, Smith, & Staack, 2016). To do
that it is important that the customer journey is analyzed when making a purchase.
The customer journey is defined as the sequence of events that customers spend in informing
themselves, buying and interacting with the products or services that an organization provides
(Norton & Pine, 2013). It is also considered as the description of how people consider buying a
product or service initially until its effective purchase and then the bonding with the brand, that is,
the sequence of interactions that customers perform before reaching a certain goal (Edelman &
Singer, 2015a). To define the customer journey, customer journey maps are used to improve the
customer experience, identify business opportunities and clarify what customers have been trying to
do, what obstacles occur and how customers feel during each interaction with the product or service
27
(Richardson, 2016). The classic customer journey consists of seven steps: consider, evaluate,
consider, buy, enjoy, advocate and bond. In this classic journey, customers spend a lot of time in the
consideration and evaluation phase before entering the loyalty loop, leading to brand switching for
the final purchase (Edelman & Singer, 2015a).
Nowadays, organizations have taken a new vision of the customer decision journey that has become
a key part of the consumer experience of their brand as well as a competitive advantage (Edelman &
Singer, 2015b). This new vision of customer journey allows organizations to reduce or even eliminate
consideration and evaluation steps by getting customers to enter the loyalty loop and stay there as
shown in the figure below.
Figure 3 - Customer decision journey Source: (Edelman & Singer, 2015a)
Through customer journey management, organizations are able to innovate, effectively allocate
resources (Norton & Pine, 2013), improve customer satisfaction, increase revenue and reduce churn,
but to do that they need to initially identify how to attract the right customers, identify the journeys
they need to improve, and identify how they are doing in each, create cross-functional processes to
support the journeys and implement the continuous improvement and cultural change in the
organization (Rawson et al., 2013).
2.2.5. Challenges
Today, sales organizations face several challenges that they need to overcome to achieve their goals
and succeed in their business. These challenges are divided into three major types: environmental
challenges, customer challenges, and resource challenges.
The challenges of the environment identified are: the extreme competition in the market (Jones,
Brown, Zoltners, & Weitz, 2005; Piercy, 2005; Rodriguez et al., 2016, 2012), also known as Red Ocean
(Kotler & Keller, 2016), where products have become commoditized (Rodriguez et al., 2012), that is,
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they are produced in a standardized, cheaper and common way, causing suppliers to lower prices
and organizations cannot differentiate themselves from others. Another factor is the definition of
boundaries between organizations and their partners, that in some cases, partners are also
considered competitors (Jones et al., 2005) ; the slowed world economy (Rodriguez et al., 2012) that
implies the reduction of costs in equipment, contracting and innovations in products due to the
decrease in sales revenues and profits and to reduce costs and avoid bankruptcy, organizations can
compromise the quality and desirability of services and products provided (Shatonhoka, 2015); the
regulatory oversight (Jones et al., 2005) that may induce compliance costs, additional risks and
inhibition or disruption of innovation (Wiener, 2013); and the growing selling costs (Piercy, 2005).
The challenges derived from customers are: the current customer evolution (Jones et al., 2005),
customers nowadays have free access to all the information that they need to make decisions
(Rodriguez et al., 2016) and compare products (Molinillo, Gómez-Ortiz, Pérez-Aranda, & Navarro-
García, 2017) which makes the work of the sales team hard, because they do not have as much
power of influence and may not be able to persuade the customer (Dannenberg & Zupancic, 2009).
Another factor is the rapid change of preferences and expectations of customers according to their
needs (Jones et al., 2005), which makes sales cycles longer due to the increased time used to
complete a purchase (Rodriguez et al., 2016) ; the customer demand, that is, customers nowadays
want to have all the information they need available in real time (Jones et al., 2005; Ştefan & Crăciun,
2011), making the sales team feel they must be ready 24 hours a day to clarify and help them and at
the same time carry out and manage the other responsibilities arising from their duties (Greg W.
Marshall et al., 2012); the product and customer complexity (Jones et al., 2005), today's customers
act emotionally and can change their decisions according to the emotion at the time and are
extremely different from their preferences, needs and ways of dealing with, making their
management very difficult and forcing organizations to develop individual solutions for each
customer or group of customers (Jones et al., 2005; Ştefan & Crăciun, 2011); and the customer
retention: today, customers make choices according to the proposal that they think is the best, that
is, they can change quickly from "supplier" (Oakes, 1990). Organizations need to identify and
implement measures so that customers become loyal and want to maintain relationships with them
(Molinillo et al., 2017).
The challenges of resources identified are: the difficulty in allocating the available effort to customers
and prospects, the sales team has at their disposal a lot of information, making it difficult to
distinguish which is the most relevant and with added value (Jones et al., 2005). Another difficulty is
determining which are the types of intended customers. In other words, the target customers
(Rodriguez et al., 2012); the implementation impact of technology, the biggest challenge for an
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organization in terms of technology is to define and implement the best and the right tools for their
business (Jones et al., 2005; Piercy & Lane, 2005; Rodriguez et al., 2012). With the increasing
innovation in technology, the tools must be updated or changed, if organizations do not do that,
their current tools start to present high failure rates and low user acceptance (Rodriguez et al.,
2012); and the lack of clear guidelines for sales techniques, the sales team still do some non-planned
activities, that is, they work in an unstructured way which makes it harder to carry out their work and
achieve their goals (Dannenberg & Zupancic, 2009).
2.2.6. Sales processes
Every organization needs to identify and adopt guidelines and good practices for the standardization
of their activity and the development of their employees as well as the organization. For this, they
need to define processes that reflect key activities of each service provided as well as the industry
where they belong. In the case of sales organizations, there are seven generic sales processes
defined that are: prospecting, pre-approach, approach, sales presentation, handling objections and
overcoming resistance, closing the sales and sales follow-up (Dwyer, Hill, & Martin, 2000; Moncrief &
Marshall, 2005).
However, there are other authors who identify the generic sales processes as being: understanding
the customer, approaching the customer, needs discovery, presentation, closing the sale and service
and follow-up (Andzulis, Panagopoulos, & Rapp, 2012; Schuldt & Totten, 2015). By comparing the
different processes, it is concluded that there are few differences between them, except for the
given name and the exclusion of the process ‘handling objections and overcoming resistance’ by
Andzulis, Panagopoulos, & Rapp (2012) and Schuldt & Totten (2015). For this study, the seven sales
processes will be analyzed because they are complete and specific.
Prospecting is the first step in an effective sales cycle and is defined as the search and identification
of potential customers who may be interested in an organization's product or service (Moncrief &
Marshall, 2005; Singh et al., 2011). Before targeting itself, it is crucial to define the target audience
according to the organization's vision and strategy. In this step, it is very important to define several
characteristics:
• In case the target audience is a company/organization, it is necessary to identify the industry,
size, and area of influence.
• In case the target audience is an individual, it is necessary to identify the role, age, interests, and
groups.
With the target audience defined, the stage of searching for potential customers is initiated. At this
stage, several strategies can be used to attract new customers such as search marketing which
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consists of search engine optimization (SEO) and search engine marketing (SEM) that are used by
customers to search for more information about the product or service or search for reviews and
feedback from users.
SEO is a long-term strategy to apply as it is a time-consuming process. However, combining with
SEM, which allows organizations to identify and associate keywords or phrases more relevant to the
business, increases the likelihood that the audience will find the organization because it allows the
organization to be placed on the first pages of results. Other techniques, such as word-of-mouth, are
essential, because nowadays people rely more on peers than on advertising or other material
developed by the organization. Knowing this, organizations should bet on developing close
relationships with customers to spread good experiences through their contacts. Social networking
makes everything easier; inbound prospecting that focuses on the use of social selling (use of social
networks to explore relationships with leads) and emailing; and outbound marketing that supports
cold calling (unsolicited calls to leads) and social spamming (unsolicited messages through social
networks) to try to sell the product or service (Aggour, 2015). After collecting and identifying new
leads, it is filtered and selected leads from the CRM system, digital and non-digital campaigns,
website, conferences, referrals, networking and trade associations to create a final list of leads which
correspond to the previously defined target audience. With the list created, it follows the
categorization of leads into two categories: company or individual. If it is a company, it is necessary
to gather more information about it that can be collected using the internet and visiting the website
of the company in question (Finley, 2013), to analyze and identify contacts, industry, products, and
services it offers, location and other necessary information (Hassan, Nadzim, & Shiratuddin, 2015). In
both cases, it is crucial to research if they have an online presence, that is, it is necessary to check out
social media accounts like Facebook, Instagram, Twitter, Snapchat, Pinterest to extract new
information, ideas, opinions, tastes, mutual connections, identify the best forms of contact
(channels) and finalize with the compilation of a report with all the additional information obtained
(Andzulis et al., 2012). By aggregating all the information from the various sources identified above, it
is possible to create a profile for each lead that contains customer value, customer targeting
information, customer rating and behavior tracking (Rygielski, Wang, & Yen, 2002) and register in the
CRM system so that it is available for the entire sales area. With the help of complete and well-
defined profiles, it is easier and more efficient to prioritize the leads, that is, identify in terms of need
or desire, ability to buy, authority and eligibility to buy (Dwyer et al., 2000). With the prioritized
leads, it is possible to plan how best to allocate material and human resources and devise a
communication strategy to achieve the best results. This process allows the increase in the sales
volume and consequently the increase in profit and customers (Singh et al., 2011).
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Pre-approach is the second step in the sales cycle and is defined as the set of activities that need to
be performed and prepared prior to the contact with the potential customer (Moncrief & Marshall,
2005). Starts with the search for new and additional leads information, such as needs, habits,
preferences, nature, behavior, economic status, and purchase history to facilitate the beginning of a
connection and be prepared to attract the lead attention (Kotler & Armstrong, 2016). After becoming
familiar with this information, it is verified in the CRM system if the lead is already an organization's
customer, or if it is a new customer. Within the CRM system, it is necessary to search the accounts
and verify whether it is an existing account or not. If there is no account for this lead, it must be
created and inserted all the data collected in the previous phase. If there is an account, it is necessary
to enter the account and search if there are records of previous contacts with this lead, if they exist
proceed to analyze them. After reviewing previously made contacts, it is crucial to identify whether
the customer has given positive or negative feedback. If feedback is negative, the salesperson needs
to find solutions to overcome the previous problems and find out how to improve customer
satisfaction. With these points, all identified, the preparation and rehearsal phase is started. At this
stage, it is necessary to rehearsal how to present the product/service and verify if it has the essential
information/materials for the initial contact. If not, proceed with the search (Dwyer et al., 2000;
Moncrief & Marshall, 2005). When everything is ready to go to the initial contact phase, it is crucial
to enter the CRM system, retrieve the contact of the lead and make the call to schedule a meeting
(Dwyer et al., 2000). Cold calling over the phone is arguably the most effective way to make
appointments, although many salespeople are quite successful using other channels such as email,
social media, and in-person visits. It is also recommended to use at least two different contact
methods such as phone and email, so the salespeople have a better chance of getting in touch with
each lead. If the call is not answered, it is registered in the CRM system and tried again. If the call is
answered, the salesperson must propose the meeting and agree on a date and location (Kotler &
Armstrong, 2016). After the call, it is recorded the meeting time, date, and location in CRM and
Outlook.
Approach is the third step in the sales cycle and is defined as the initial contact with the lead and its
subsequent qualification (Andzulis et al., 2012; Moncrief & Marshall, 2005). It starts with the call
scheduled in the previous phase and aims to get the attention and curiosity of the lead in the
products, services, and brand of the organization, the discovery of uncovered needs and the
development of a close relationship to build targeted and custom deals aligned with customer’s
value (Kotler & Armstrong, 2016). After the call, the first action to take is to record all the
information gathered and enter into the CRM system. Within CRM, the salesperson needs to analyze
sales history and match customer data and use an analytical system to extract behavioral data and
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analyze it to gather insights and enrich leads profiles. With the profiles updated, the qualification or
not qualification proceeds (Andzulis et al., 2012). Typically, this qualification involves the use of the
BANT method, meaning,that the salesperson needs to determine whether the customer has the
necessary budget, whether he has the authority to buy, whether there is a genuine need for the
product or service, and whether his timeline for delivery of the product/service is in line with
customer expectations (Giamanco & Gregoire, 2012). If the lead is qualified, the salesperson enters
the CRM, looks for the lead and turns it into opportunity. It then updates the covered specific needs
and inserts the estimated budget, decision-maker, stakeholders, and competitor's information. The
process is finalized with CRM registration of motivation and opportunity preferences.
Sales presentation is the fourth step in the sales cycle and is defined as the conduction of one or
more product/service presentations to the prospective customer. It starts with the analysis of the
customer needs seen in the CRM system and by searching the company/organization's products and
services to create an evaluation plan with all the options that fit what the customer wants (Kotler &
Armstrong, 2016). After the search, if no suitable products or services are identified, the salesperson
needs to communicate with the organization's development team to find out if there are any
developing solutions that apply to what is being sought. The development team informs the
salesperson about the actual developing solutions, so the sales team can review and verify if they
have found the ideal products/services. If they don’t find the ideal solution, they continue to look for
products/services offered by the company/organization that meet some of the requirements. With a
list of suitable products/services, the planning and creation of an evaluation plan and presentations
start (Andzulis et al., 2012). In these presentations, the salesperson needs to give the customer the
necessary and appropriate information about the product, features and offerings he or she is trying
to sell, demonstrate the product (G. W. Marshall, Moncrief, & Lassk, 1999), needs to clarify the
prospect's questions and explain the benefits of the product in a clear and objective way (Dwyer et
al., 2000; Moncrief & Marshall, 2005). Creating the evaluation plan is a very important step because
it demonstrates the ability of the company/organization to meet the customer's needs. With the
presentations and evaluation plan created, it is necessary to set appropriate dates for marking
presentations and recording them in Outlook. After registration, calls are made to potential
customers and the final dates of the presentations are defined and scheduled. Finally, the final dates
are entered into the CRM system and if necessary updated in Outlook.
Handling objections and overcoming resistance is the fifth step in the sales cycle and is defined as the
identification and resolution of objections and resistance of the customers, that is, questions and
hesitations regarding the product, service or organization (Moncrief & Marshall, 2005). Starts with
the communication of errors, questions or objections of the potential customer to the sales team.
33
Upon receipt, the salesperson proceeds to the analysis of the communication and verifies if it has the
necessary information to solve or needs more detail. If the salesperson needs more detail, he should
communicate with the customer and ask for additional information and, when the customer sends,
analyze it. With the necessary information, the order is categorized into issues, objections or other
problems having different treatments.
• If it is a question regarding the product/service or company/organization, the salesperson sees
the issues and verifies if it is able to respond, if not it sends to the hierarchical superior who
makes the response and informs the salesperson to inform the customer.
• If it is an objection, the salesperson needs to register it in the company/organization database
and seek a suitable solution. When the salesperson finds the right solution, he should document
it and inform the customer.
• If it is other problems, the salesperson needs to diagnose the problem and check if the problem
is known. If it is a problem that has never been reported, it is necessary to estimate the time to
solve the problem and inform the client. Then he needs to find a solution, document it, store it
in the company/organization database and inform the customer.
When the sales team manages to resolve objections and resolve customer resistance, a customer
satisfaction survey is sent to customers, who must fill out and send it to the company/organization.
Close sale is the sixth step in the sales cycle and is defined as the completion of a sale of a product or
service of an organization/company (Kotler & Armstrong, 2016). Its main objective is to negotiate the
terms and details of the sale and reach the agreement of both parties through a contract (Andzulis et
al., 2012). This process begins with the development of a proposal by the sales team and the
subsequent sending to the future client. The client analyzes the proposal and if it does not agree with
the defined terms, the negotiation phase begins. This phase is carried out through various
communications with the customer and the supplier until a consensus is reached between both
parties. Once this consensus has been reached, the final proposal accepted by the client is stored in
the organization's database and the creation and signing of the contract begin.
The contract is created by the salesperson and evaluated by their superior, sales manager, who upon
their approval is sent to the customer sign and in parallel to the sales director. With the signature of
both parties, the sale is completed with success (Finley, 2013).
Post-sale follow-up is the seventh step in the sales cycle and is defined as being the constant follow-
up of customer experiences, motivations, desires, and needs. Its main objective is to create a
relationship with the customer, maintaining constant contact to know if the product/service offered
is in accordance with expectations. This process begins with making periodic follow-up calls and
34
communications with customers to understand their concerns and answer their questions (Kotler &
Armstrong, 2016). In addition, at the end of the purchase, a satisfaction survey is sent about the
experience the customer had on the sale, which is subsequently subjected to several analyzes to
evaluate the quality of the service, the strengths and weaknesses to continuously improve it. A very
important step in this process is the subscription of the customer in the organization newsletters so
that he can be always informed of the news, promotions, and campaigns of the
organization/company and the request of reviews and referrals to the customers through social
networks like Facebook, Instagram, Twitter, among others, specialized blogs to the product/service
offered and the company's own website to boost the interest of other potential consumers (Andzulis
et al., 2012).
2.3. INFORMATION MANAGEMENT TECHNOLOGIES
2.3.1. Business Intelligence
Today, Business Intelligence continues to be a top priority in organizations (Işik, Jones, & Sidorova,
2013; Watson & Wixom, 2007) because of its power to combine data gathering, data storage, and
knowledge management with analysis to provide input to the decision-making process and provide
information and knowledge at the right time, location, and form which helps increase an
organization's competitiveness (Gray & Negash, 2008).
There are several definitions of BI that have emerged over time, such as:
"Business intelligence (BI) is a set of methodologies, processes, architectures, and technologies that
transform the raw data into meaningful and useful information that allows users to make informed
business decisions with real-time data" (Llave, 2017, p. 195), that is, a set of software solutions to
collect and analyze data so that the organization has access to it and is able to make better decision-
making.
BI is “a system comprised of both technical and organizational elements that present its users with
historical information for enabling effective decision making and management support, with the
overall purpose of increasing organizational performance" (Işik et al., 2013, pp. 13–14).
It is composed of several components (Gray & Negash, 2008): OLAP, Data Mining, Visualization,
CRM/DB marketing, Geographic information systems, Knowledge management, DSS / Executive
information system (EIS) and Database mining as described in the image below. That allows analyzing
and evaluating large volumes of complex information that, consequently, allows faster and easier
access to information, better customer satisfaction (Llave, 2017), less IT infrastructure costs (Llave,
35
2017; Watson & Wixom, 2007), more efficient data delivery (Watson & Wixom, 2007), the ability to
predict changes in product demand and to improve profitability and efficiency (Işik et al., 2013).
Figure 4 - Business Intelligence components Source: (Gray & Negash, 2008)
A BI system includes the identification of KPI's, data mining, OLAP, digital dashboards, reporting and
data warehousing (Llave, 2017) and a lot of techniques such as statistics, data and text mining,
forecasting, econometrics, and optimization (Gray & Negash, 2008).
There are several transformative business intelligence (BI) platforms available in the market that aim
to improve the decision-making process. A BI and analytics platform is “characterized by easy-to-use
tools that support a full range of analytic workflow capabilities and do not require significant
involvement from IT to predefine data models upfront as a prerequisite to analysis”(Howson et al.,
2018, p. 1). After a detailed evaluation, several applications that have the most benefits for the
organization were identified (Howson et al., 2018):
Microsoft Power BI suite: is a suite of business analytics tools connected to multiple data sources,
which simplify the preparation and ad-hoc analysis of the data to extract important insights for the
organization (Microsoft, 2018). It allows data discovery, data preparation (Howson et al., 2018), the
creation of interactive dashboards that allow a 360-degree view of the organization and the
production of reports to be used via the web and through mobile devices (Microsoft, 2018). The
main key features are: the ease of use that offers complex analyzes, low cost (free desktop product
as well as low subscription per user per month) and an active community that extends the product
with prebuilt apps, visualizations and video tutorials (Howson et al., 2018).
Tableau: consists of three primary products - desktop tableau, tableau server and tableau online -
that offers a very interactive and intuitive visual experience to users for easy access, preparation and
36
analysis of data without programming (Howson et al., 2018). It is considered a powerful, flexible and
secure platform (Tableau, 2018). The main features are: the intuitive and interactive visualization,
analytic and exploration capabilities using any data source, the focus on consumer experience and
success (offer a wide choice of tutorials, webinars and classes to empower their users), flexible
deployment options (possibility of deployed in the cloud, online or on-premises) and expanding
deployments and standardization rates (Howson et al., 2018).
Qlik Sense: is a BI and analytics platform that let's discover insights, explore and analyze data, and
combine all data sources into a single view (Qlik, 2018). With its full flexibility and a cloud-ready data
analytics platform, it can support a spectrum of use cases, including dashboards, deployed guided
analytics apps and custom and embedded analytics. It consists of three products - Qlik Sense
Desktop, Enterprise and Cloud (Qlik, 2018). The main features are: rapid deployment (with their
scalable engine it is possible to rapidly mash data from diverse data sources and then make them
accessible by visually appealing dashboards), user enablement (with the various types of training
offered via tutorials and forums and a modern BI architecture enable its users to become content
developers) and partner network (partners offers not only extensions and complementary
capabilities, but also professional services) (Howson et al., 2018).
2.3.2. Data Mining
Data mining is “the process that uses statistical, mathematical, artificial intelligence and machine-
learning techniques to extract and identify useful information and subsequently gains knowledge
from large databases” (Ngai, Xiu, & Chau, 2009, p. 2593), that is, a process of extracting and
detecting hidden patterns, behaviors and correlations (Rygielski et al., 2002) in large databases using
the techniques that allows the construction of data models such as association, classification,
clustering, forecasting, regression, sequence discovery and visualization that must be based on data
characteristics and business requirements (Ngai et al., 2009). The classification and regression
models focus on forecasting and the clustering model focuses on data description and forecasting
(Ngai et al., 2009; Rygielski et al., 2002).
Also, data mining is defined as "the discovery of interesting, unexpected, or valuable structures in
large datasets" (Bramer, 2016, p. 621). Being known as knowledge discovery and enduring of
statistics and data search sophisticated technology manages to find meaningful knowledge through
data analysis to build different models according to their purpose and offer a technical reference for
a better decision-making (Rygielski et al., 2002).
There are numerous data mining techniques available for each type of data mining models such as
RFM analysis, CHAID and logistic regression.
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RFM analysis is an a priori predictive technique widely used for direct marketing due to its simplicity
and ease of use (Suh & Alhaery, 2015) and its main objective is to predict the probability of response
and purchase of each customer (Blattberg, Kim, & Neslin, 2008). By identifying customer behavior
and its characteristics (Hosseini, Maleki, & Gholamian, 2010) it quantifies the transaction history
(Blattberg et al., 2008) using three purchased-related metrics:
(R) Recency - represents the time between the latest consumer behavior and the present
(Blattberg et al., 2008; Hosseini et al., 2010).
(F) Frequency - represents how many times the customer has made purchases within a certain
period of time (Blattberg et al., 2008; Hosseini et al., 2010; Suh & Alhaery, 2015).
(M) Monetary - represents the amount of money that the customer spent on purchasing during
a certain time period (Blattberg et al., 2008; Hosseini et al., 2010; Suh & Alhaery, 2015).
These metrics are typically used to distinguish likely responders from those who are unlikely to
respond to marketing attempts (McCarty & Hastak, 2007; Suh & Alhaery, 2015).
RFM analysis focuses on the classification/categorization of each customer into groups according to
their metric RFMs and relates them to behaviors such as likelihood to respond to an offer (Blattberg
et al., 2008). Usually, the first steps are to order the customer file according to how many customers
have purchased from the organization/company and then divide the database into equal quintiles
and these quintiles are assigned the numbers 5 to 1 (Hosseini et al., 2010).
Chi-Square Automatic Interaction Detector - CHAID is one of the decision tree algorithms used for
classification and prediction (Suh & Alhaery, 2015). It focuses on the modeling of differences
between groups based on a set of independent variables (categorical and continuous) and identifying
new variables capable of predicting or explaining specific customer behaviors (Suh & Alhaery, 2015).
CHAID is described as a three-step process: merging, splitting and stopping and presents the results
of modeling in a graphical tree, making it possible to perform analysis and interpretation in an easier
and simpler way even when analyzing large data sets (Suh & Alhaery, 2015). Similarly, with RFM
analysis, its main purpose is to identify customers who are likely to respond to marketing offers and
to divide them into segments/groups with similar characteristics (McCarty & Hastak, 2007; Suh &
Alhaery, 2015). However, it differs from RFM analysis because the groups are not created a priori as
in RFM, but rather divided using a statistical algorithm after a mailing test has been performed
(McCarty & Hastak, 2007). The main difference between CHAID and RFM is that CHAID can use
several independent variables such as transaction and demographic variables and not just recency,
frequency and monetary value like RFM (McCarty & Hastak, 2007).
Logistic regression is a modeling technique that uses independent variables to model a dichotomous
criterion variable and identify customers who are likely to respond/do not respond to marketing
38
mailing (McCarty & Hastak, 2007). Initially, this model focused on determining a probability of
response from individual members, that is, customers of the database instead of creating discrete
groups of customers such as RFM analysis and CHAID. After this determination, it focuses on
modeling relations between independent variables with the dichotomous dependent variable
(McCarty & Hastak, 2007). Like CHAID, logistic regression is not restricted to variables - recency,
frequency and monetary value - being able to analyze several independent variables and calculate
the response probability for the entire customer file (McCarty & Hastak, 2007).
There are several data science and machine-learning platforms available in the market that enables
organizations to adopt end-to-end approaches to building and deploy data science models. A data
science and machine-learning platform is defined as “A cohesive software application that offers a
mixture of basic building blocks essential both for creating many kinds of data science solution and
incorporating such solutions into business processes, surrounding infrastructure and
products”(Idoine et al., 2018, p. 1). After a detailed evaluation, several applications that have the
most benefits for the organization were identified (Idoine et al., 2018):
H2O.ai: is an open-source machine learning and predictive analytics platform that combines the
power of highly advanced algorithms to build real-time machine learning models on big datasets,
take these models to production and make predictions in an enterprise environment. It is composed
of five products – Driverless AI, H2O, H2O4GPU, Sparkling Water and steam (H2O.ai, 2018). The main
features are: technology leader (it has deep-learning capability, automation capability, hybrid cloud
support, and open-source integration) (Idoine et al., 2018), fast and accurate (it can run fast
serialization between nodes and clusters due to the responsiveness of in-memory processing), easy
to use and scalable (H2O.ai, 2018).
KNIME Analytics Platform: is an open solution for data-driven innovation, that helps you discover the
potential hidden in data, mine for fresh insights, or predict new futures (KNIME, 2018). Their open-
source approach allows organizations to minimize the costs of data science software without
compromising quality and with access to data, methods, and techniques allow a collective
innovation. Being a cohesive platform, it offers a single consistent framework that allows the access,
use and manipulating highly rated data and algorithms, integrating with other platforms and tools,
and being a comprehensive platform for both beginners and data science experts (KNIME, 2018). The
main features are: fast to deploy, powerful, easy to scale, intuitive to learn, strong data access and
data preparation capabilities, very strong and active user community and growth prospects (aims to
extend existing capabilities with KNIME Server to improve automation, collaboration and
deployment functionalities) (Idoine et al., 2017; KNIME, 2018).
39
RapidMiner: is a software platform for data science teams that unites data preparation, machine
learning, and predictive model deployment by introducing new productivity and performance
capabilities. (RapidMiner, 2018). The main features are: platform breadth (could be used in several
industries, provide a large selection of algorithms, flexible modeling capabilities, and data source
integration), ease of use (enabling productivity) , model development speed, positive market
response, open source capabilities, user community (Idoine et al., 2017).
SAS Enterprise Miner: is a descriptive and predictive modeling tool that provides insights that drive
better decision making. With its interactive, documented, and simple process flow diagram it is
possible to efficiently map the entire data mining process to produce better results, and because of
the ease of use of its interface, it allows users to extract insights from graphs and models that use
innovative algorithms to compare different predictions and evaluate the models to improve all the
decision making and to serve as a template to document new obstacles (Idoine et al., 2018). The
main features are: easy to use GUI, sophisticated data preparation, summarization and exploration,
model comparisons reporting and management, automated scoring, advanced predictive and
descriptive modeling, open source integration with R, scalable processing, high-performance
capabilities, fast, easy and self-sufficient way for business models to generate models (SAS Institute,
2018).
2.3.3. ERP / CRM
Enterprise systems is a software that offers integrated solutions for organizations and represents a
crucial investment to improve business performance. It includes several applications such as
Enterprise Resource Planning (ERP), Supply Chain Management (SCM), and Customer Relationship
Management (CRM) systems (Hendricks, Singhal, & Stratman, 2007).
Enterprise Resource Planning was born from the Material Requirements Planning and Manufacturing
Resource Planning systems (Yanjing, 2009) and is defined as a packaged software solution used to
integrate business processes, data and functions in a comprehensive structure (Klaus, Rosemann, &
Gable, 2000), that is, a real-time data warehouse (Okrent & Vokurka, 2004), and provide a holistic
view of the business from a single information and IT architecture with the ability to support the
organization needs and identify improvements (Hendricks et al., 2007; Klaus et al., 2000) . It is
divided into integrated application modules, which allows high configuration for various industries
and supports all core processes and all the functions of an organization, such as material
management, production, logistics, sales, financial accounting, asset management and many more
(Klaus et al., 2000). The main objectives of an ERP system are improving quality, customer
satisfaction, profit and reduce costs and inventory (Okrent & Vokurka, 2004).
40
Customer relationship management is a new type of management system (Yanjing, 2009) and it is
characterized as the "comprehensive strategy and process of acquiring, retaining and partnering with
selective customers to create superior value for the company and the customer" (Hosseini et al.,
2010, p. 5259), that is, a strategy that integrates technologies, people, processes and business
activities (Hosseini et al., 2010) to manage relationships with customers. Also known as a discipline
that “focuses on automating and improving the business processes associated with managing
customer relationships in the area of sales, management, customer service, and support" (Hosseini
et al., 2010, p. 5259) and "an enterprise approach to understanding and influencing customer
behavior through meaningful communications in order to improve customer acquisition, customer
retention, customer loyalty, and customer profitability" (Ngai et al., 2009, p. 2592). Its main
objectives are to carry out proactive market research and analysis and processing of customer
feedback to help decision-making and personalized service (Rygielski et al., 2002). CRM systems offer
several features like sales force automation, data warehousing, data mining, decision support and
reporting tools to reduce duplicates and improve the maintenance of a centralized database with
customers' information (Hendricks et al., 2007; Rygielski et al., 2002).
2.3.4. Big Data
Over the years, the amount of data has grown significantly in several areas (Li, 2015). With this,
emerged the term “Big data”:
Big data is composed by “large volumes of high velocity, complex and variable data that require
advanced techniques and technologies to enable the capture, storage, distribution, management,
and analysis of the information" (Gandomi & Haider, 2015, p. 138). It is characterized by the four V's:
Volume - high amounts of data stored and retrieved from datasets, Velocity - high-rate data flow,
Variety - various types of data with different structures and formats (structured, unstructured and
semi-structured (Sagiroglu & Sinanc, 2013)) and Veracity - uncertainly of data quality and accuracy
(Li, 2015; Sikos, 2015).
Considered as a term to represent a massive amount of data generated through emails, videos,
transactions, images, logs, blogs, interactions, sensors and many more sources (Sagiroglu & Sinanc,
2013) with a varied and complex structure it becomes quite tricky to capture, manage, analyze and
extract meaningful value using only basic tools (Sagiroglu & Sinanc, 2013), that is, it is crucial to use
data processing tools, applications, and databases (Sikos, 2015). However, it is also very important
that organizations have processes capable to transform large amounts of diverse data into
meaningful insights (McAfee & Brynjolfsson, 2012). After applying big data analytics, organizations
can achieve more accurate business insights that can transform business, customer-based
41
segmentation, better-targeted marketing, recognition of sales opportunities, translate directly the
knowledge extracted into better decision-making and performance, and allows evidence-based
decision-making rather than intuition (McAfee & Brynjolfsson, 2012; Sagiroglu & Sinanc, 2013).
There are several data science platforms available in the market to create innovative machine-
learning solutions. Data science platforms are defined as being "cohesive software application that
offers a mixture of basic building blocks essential for creating all kinds of data science solution, and
for incorporating those solutions into business processes, surrounding infrastructure and products"
(Idoine et al., 2017, p. 1).
After a detailed evaluation, several applications that have the most benefits for the organization
were identified (Idoine et al., 2017):
IBM SPSS Modeler: is a graphical data science and predictive analytics platform that enables users of
all skill levels to deploy insights to improve the business. It is considered a powerful tool (with several
algorithms and capabilities that support the complete data science cycle), easy to use (user-friendly,
intuitive drag-and-drop interface), scalable (grows with choice of the licensing option) allows to
acquire insights quickly, open source integration and deliver predictive intelligence through
embedded services, business intelligence integration or simple reporting. The main key features are:
text analytics, multiple deployment methods, automated modeling, visual analysis streams, support
for many data sources, automatic data preparation, algorithmic methods and support for open
source technologies (IBM, 2018).
SAS Enterprise Miner: is a descriptive and predictive modeling tool that provides insights that drive
better decision making. The main features are: easy to use GUI, sophisticated data preparation,
summarization and exploration, model comparisons reporting and management, automated scoring,
advanced predictive and descriptive modeling, open source integration with R, scalable processing,
high-performance capabilities, fast, easy and self-sufficient way for business models to generate
models (SAS Institute, 2018).
RapidMiner: is a software platform for data science teams that unites data preparation, machine
learning, and predictive model deployment (RapidMiner, 2018). The main features are: platform
breadth (could be used in several industries, provide a large selection of algorithms, flexible
modeling capabilities, and data source integration), ease of use, model development speed, open
source capabilities, user community (Idoine et al., 2017).
KNIME Analytics Platform: is an open solution for data-driven innovation, that helps you discover the
potential hidden in data, mine for fresh insights, or predict new futures (KNIME, 2018). The main
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features are: fast to deploy, easy to scale, intuitive to learn, strong data access and data preparation
capabilities, very strong and active user community (Idoine et al., 2017).
2.3.5. Decision Support Systems (DSS)
Decision support systems arise because of the need for a computerized structure for information
management systems that support organizations in decision-making (Power, Sharda, & Burstein,
2014). It is defined as being "an interactive computer-based system or subsystem intended to help
decision makers use communications technologies, data, documents, knowledge and/or models to
identify and solve problems, complete decision process tasks, and make decisions" (Power et al.,
2014), that is, an information system that improves the ability of professionals to perform better
complex decision-making activities. Over time, new definitions have emerged as, for example, DSS is
"interactive computer-based systems which help decision-makers use databases and models to solve
ill-structured problems" (Sol, Takkenberg, & Robbé, 1987, p. 1). In this definition, the focus is on the
support for personal computing with faster and more efficient development tools and not so much
on the decision process. Also, DSS is considered the "exploitation of intellectual and computer-
related technologies to improve creativity in decisions that really matter" (Sol et al., 1987, p. 2), that
is, the use of systems and technologies available and adequate to improve the effectiveness of the
activities of the organization.
DSS consists of components that provide database management capabilities that allow access to
data, information, and knowledge, and a powerful and simple user interface design that enables the
creation of interactive queries, graphical functions and reporting (Shim, Warkentin, Courtney, &
Power, 2002).
2.3.6. Robotic Process Automation
Robotic process automation is defined as being a technological imitation of a human that automates
rule-based business processes, structured, repetitive and non-value-added tasks in a fast, effective
and cost-efficient way (Aguirre & Rodriguez, 2017; Asatiani & Penttinen, 2016). However, RPA is not
a physical tool, but rather a software-based solution (Willcocks, Lacity, & Craig, 2015) that is
integrated through front-end information systems, which is able to communicate with back-end
information systems and can be integrated with any existing software in the organization (Aguirre &
Rodriguez, 2017; Asatiani & Penttinen, 2016).
RPA is a tool to achieve a high return on investment because it aims to reduce the amount of
repetitive and simple actions performed by humans, allowing the organizations to direct their
workers to perform core activities and with more value, since routine, manual and highly structured
activities are the responsibility of a robot (Aguirre & Rodriguez, 2017). RPA tools work by mapping a
43
process in the RPA tool language so that the robot software can understand and execute the tasks
(Van der Aalst, Bichler, & Heinzl, 2018). It offers many advantages such as quality, accuracy and risk
mitigation, multitasking, reduced cycle time, application integration via user interface, cost and error
reduction (Diepeveen, Matcher, & Lewkowicz, 2016), increased process speed and increased
compliance (Aguirre & Rodriguez, 2017) due to its versatility and flexibility (Asatiani & Penttinen,
2016). However, not all business processes are suitable their use, that is, to be adequate they need
to be composed of activities carried out regularly, do not require creativity, interpretation and
decision making, and tasks that are prone to errors because they are performed manually (Aguirre &
Rodriguez, 2017).
Currently, RPA has many dedicated vendors, such as AutomationEdge, Automation Anywhere, Blue
Prism, Kryon Systems, Softomotive, and UiPath, which offer only RPA software (Van der Aalst et al.,
2018). It has gained importance due to its ease of configuration and the lightness of its IT
components that do not disturb the underlying computing systems. It also enables people without
programmatic skills to configure and automate business processes quickly and easily. Basically, its
interface works like many BPM tools, that is, by dragging, dropping and linking icons it is possible to
represent stages of a process (Willcocks et al., 2015).
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3. METHODOLOGY
This chapter aims to present the methodology used in the accomplishment of the dissertation. It will
be composed of six steps described in the next section.
3.1. SCIENTIFIC METHODOLOGY
The objective of this dissertation is to analyze sales processes and their limitations and to propose
improvements to them. To accomplish this, it is necessary the support of an adequate scientific
methodology to obtain the expected result of this study. After analyzing several methodologies, it
was found that the most appropriate was Design Research Science due to its focus on describing and
explaining how things and phenomena behave and interact with each other (Kanellis &
Papadopoulos, 2009).
Design research science is a paradigm of research in information systems drawing on design science
(Kanellis & Papadopoulos, 2009). Provides a unique perspective on addressing concrete practical
problems through the construction of innovative systems, that is, information technology artifacts
that correspond to the needs of the business (Amrollahi & Lukyanenko, 2016). These artifacts are
defined as "things", that is, "entities that have some separate existence and can be in the form of a
construct, model, method, and an instantiation" (Kanellis & Papadopoulos, 2009, p. 22; Ostrowski &
Helfert, 2014, p. 111). The primary aspect of an artifact is the functionality it provides to the system.
With its power to create and evaluate visual artifacts it aims to create new realities, identify and
solve organizational problems (Hevner & Chatterjee, 2010; Kanellis & Papadopoulos, 2009) such as
unstable requirements and constraints, complex interactions between subcomponents, inherent
flexibility to change design processes and critical dependence of human abilities (Hevner &
Chatterjee, 2010). With this creation of new realities and innovations that define ideas, practices,
and products (Hevner & Chatterjee, 2010), they can change the state of the world through the
introduction of new artifacts that are shaped according to the interests and values of their
researchers (Kanellis & Papadopoulos, 2009).
Design science research can be characterized as "knowing through making" (Kanellis &
Papadopoulos, 2009, p. 23), and aims to contribute to the addition of knowledge in an area of
expertise and to develop knowledge for the design and implementation of initiatives of information
systems (Kanellis & Papadopoulos, 2009). It can be connected to theory building in two ways: by
providing a methodical construction of an artifact in theory, including an experimental proof of the
theoretical model, or by making the relationships between an artifact and its components more
visible in the construction phase or evaluation of the artifact (Kanellis & Papadopoulos, 2009).
45
The design of a design science research process involves six phases:
1. Awareness of a problem: In this stage, the specific problem identified and the justification,
motivation for the execution of the study are defined. It is necessary to identify the state of
the art of the problem, its relevance and whether the solution could be the construction of a
new artifact (Goncalves, Freitas Junior, Ceci, & Woszezenki, 2017; Kanellis & Papadopoulos,
2009).
2. Definition of objectives: In this stage, the basic knowledge/theory of the problem is analyzed
and the objectives of the solution development are defined (Goncalves et al., 2017; Kanellis
& Papadopoulos, 2009).
3. Design and Development: In this stage, we proceed to define the functionalities and
architecture of the artifact, proceeding to its creation considering the suggested theory
(Goncalves et al., 2017; Kanellis & Papadopoulos, 2009).
4. Demonstration: In this stage, the use of the artifact and the demonstration is done through a
simulation, case study, formal proof or experiment. It is necessary to have knowledge of how
to use the artifact to solve the problem (Goncalves et al., 2017).
5. Evaluation: In this stage, a partial or complete evaluation of the implementation of the
artifact is carried out by observing and measuring the way the artifact responds as a solution
to the problem. It compares the proposed objectives in the suggestion phase with the results
of the use of the artifact. The outcome of the evaluation is the feedback to development
(Goncalves et al., 2017; Kanellis & Papadopoulos, 2009).
6. Communication: In this stage, the artifact developed as a solution is presented and marked
as the end of a specific design project (Kanellis & Papadopoulos, 2009).
Figure 5 - Design Science Research Phases Source: (Peffers, Tuunanen, Rothenberger, & Chatterjee, 2007)
46
This methodology is considered recursive and iterative since it can return several times to previous
steps to improve the artifact. The return from the evaluation and communication phase to the
definition of objectives and design and development phase happens to gain understanding through
the construction, detection, and analysis of contradictions and “allows to add constraint knowledge
to the understanding of theories that underpin the suggestion and development”(Kanellis &
Papadopoulos, 2009, p. 23) and to enable the researcher to identify some concepts that do not work
in reality how they were supposed to work in theory (Kanellis & Papadopoulos, 2009).
3.2. RESEARCH PHASES
To develop a critical analysis of the current sales management processes and propose improvements,
the following five steps will be performed:
1. Problem Definition: In this phase, it will be defined the specific research problem, as well it
will be collected the key sales processes, which will be subject to a first analysis and then
modeled with improvements that will be identified in the next phases.
2. Literature Review: In this phase, the main objectives are: identify the level of expertise of this
specific problem, study the more relevant publications about the theme, find the best way to
analyze and approach the subject to anticipate the possible problems that could emerge and
how it could be resolved.
3. Process Gathering and Modeling: In this phase, it will be started the modeling of the current
sales processes identified in the problem definition phase using the BPMN notation 2.0.
BPMN is a simple modeling notation that has as main objective to be understandable by all
users. It defines a Business Process Diagram that is based on flowcharts techniques to create
graphical models (White, 2004). The development of BPMN arises from the need to manually
translate business process models into execution models.
4. Identification of improvement opportunities: In this phase, it will be done the observation,
demonstration, and analysis of the model efficiency of the current sales processes.
5. Evaluation of the proposed improvement recommendation: the core objective is to evaluate
the final processes based on the opinion of experts and scientific articles and try to find
inefficiencies, redundant activities, and errors.
6. Discussion and Conclusions: In this phase, it will be discussed the main advantages of the
proposed technologies and described the final conclusions.
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Figure 6 - Research Phases
3.3. SELECTION OF THE MODELING TOOL
Modeling business processes using the best practices require a tool capable of fulfilling the objectives
of this dissertation. There are many modeling support tools in the market like Bizagi Process
Modeler, Oracle BPM Studio, and iFlowBPM, but before choosing one it is necessary to do a
comparison between them to choose the best for the context of this study.
Bizagi Process Modeler is a free business process modeling and documentation tool that enables the
visualization of diagrams and models and the documentation of business processes in BPMN. It
allows users to publish in different formats like Word, PDF, SharePoint and gives the possibility to
export the processes to other tools (Visio, XML). Their Modeler’s IntelliSense helps to position the
elements and to quickly map and document them (Bizagi, 2016).
Oracle BPM Studio is a paid application that enables process developers to create process-based
applications and to model business processes using the BPMN 2.0. It is a component of the Oracle
BPM Suite and presents the concept of zero coding and process simulation (Terceros & Leslie, 2011).
iFlowBPM is an open source platform to design, implement and execute business processes. Their
design was created to allow a quick implementation, low resources consumption, and a fast learning
curve. As main functionalities there were identified the integration with manage documental systems
and external databases and the design of integrated forms (InfoSistema, 2013).
According to this statements, the tool chosen will be Bizagi Process Modeler because is a free and
simple tool that makes it possible to create a web application without coding that automates
business processes (Gjoni, 2015), have an error checker that helps to avoid the misuse of the
elements and have the functionality to export the diagrams to a lot of formats like PDF, PNG, BMP,
and import files with the standard patterns BPMN and XPDL.
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4. MODELING OF THE CURRENT STANDARD SALES PROCESSES
The purpose of this chapter is to present the BPM models developed from current sales processes. Process modeling is considered a fundamental activity for the management of a company because it requires an important set of
techniques and skills to be able to understand, communicate and manage all the components of the business processes. The main objective of this modeling is to create a complete and accurate representation of sales procedures and
their operation, but also to manage and analyze process performance and determine changes (Moore et al., 2013).
4.1. PROSPECTING
Prospecting is the first step in an effective sales cycle. In this process, it is sought and identified new potential customers who are interested in buying one or more products of the organization via networking, referrals, trade
associations, conferences, and searching in the customer database for opportunities (Moncrief & Marshall, 2005; Singh et al., 2011). The main objectives of this search are to create or to expand a customer database powered by
accurate and timely information and knowledge about the needs, tastes and personal information of opportunities in the marketplace (Moncrief & Marshall, 2005). But also, the determination of communication styles, the calculation of
risks that each customer represents for the organization and the qualification of a prospect to a customer (Andzulis et al., 2012).
Figure 7 - Process "Prospecting"
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4.2. PRE-APPROACH
Pre-approach is the second step in an effective sales cycle. This process includes all the activities that need to be performed and prepared prior to the contact with the potential customer. These activities include continuing to research
and obtaining more information about the prospect (individual or organization), confirming and reviewing if there has already been any contact with it, becoming familiar with the needs of the customer, talking to gatekeepers, gathering
material that consider important and appropriate for initial contact with the customer and prepare or rehearse how the salesperson will approach the prospect and how will present their product (Dwyer et al., 2000; Moncrief &
Marshall, 2005). Usually, this process ends with scheduling a meeting with the prospect (Dwyer et al., 2000).
Figure 8 - Process "Pre-approach"
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4.3. APPROACH
The approach is the third step in an effective sales cycle. In this process, the initial contact with the prospect takes place and some strategies are applied to gain the attention and interest of the prospect, to create a good first impression
of the organization, to build an initial rapport and to establish a relationship of trust and credibility, and to later qualify the prospect (Andzulis et al., 2012; Moncrief & Marshall, 2005). This contact allows the salesperson to identify
specific needs and wants that had not been collected before and to perceive the motivation of the prospect by conducting a series of well-founded questions (Andzulis et al., 2012). There are several strategies that are being used at this
stage which are the introductory approach, the assessment approach, the product approach, the consumer-benefit approach, and the referral approach and the consultative approach (Moncrief & Marshall, 2005). The goal of this
process is to keep the prospect's interest to follow for the presentation (Dwyer et al., 2000).
Figure 9 - Process "Approach"
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4.4. SALES PRESENTATION
The sales presentation is the fourth step in an effective sales cycle. This process is performed after the customer needs and wants identification, and consists of a presentation or more over time (Moncrief & Marshall, 2005). In this
presentation, the salesperson needs to give the customer the necessary and appropriate information about the product, features and offerings he or she is trying to sell, needs to create an evaluation plan to demonstrate the ability to
meet their needs, and needs to clarify the prospect's questions and explain the benefits of the product in a clear and objective way (Dwyer et al., 2000; Moncrief & Marshall, 2005). The success of this presentation depends on the ability
of the salesperson to present one or more products of their organization according to the needs of the prospect and persuade or convince the prospect that he or she needs the product, feature or service. This process is quite complex
and needs a lot of preparation of the salesperson as well as managing the resources of the organization (Andzulis et al., 2012).
Figure 10 - Process "Sales Presentation"
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4.5. HANDLING OBJECTIONS AND OVERCOMING RESISTANCE
Handling objections and overcoming resistance is the fifth step in an effective sales cycle. In this process, the prospect's objections to the presentation are identified, that is, questions and hesitations regarding the product, service or
organization (Moncrief & Marshall, 2005). These objections can be considered as a delay to the sales process but should be seen as useful as they may reveal more prospect needs and can define whether it is to continue the sales
process with them or not (Moncrief & Marshall, 2005). The salesperson needs to be able to overcome customer resistance to the purchase of the product or service by enhancing the benefits of them and by responding to customer
issues and reluctance (Dwyer et al., 2000).
Figure 11 - Process "Handling objections and overcoming resistance"
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4.5.1. Satisfaction survey
The "Satisfaction survey" subprocess begins with the receipt of the completed survey by customers and the analysis performed using analytical methods (for example, scoring) and techniques available in the data mining system. After
the analysis of the surveys, satisfaction reports are generated that serve to evaluate the service and subsequent improvement. If reports are positive, they are placed in the company database. If they are negative, an improvement
subprocess begins.
Figure 12 - Subprocess "Satisfaction Survey"
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4.5.2. Improvement process
The "Improvement" subprocess emerged from the subprocess of customer satisfaction where there is a need for improvement/change in the company/organization. This sub-process starts with a request for an improvement from the
salesperson to the technology department. The IT analyst analyzes the request and decides if the change/improvement is important and have an impact on the functioning of the company/organization. If it is not relevant, notify the
sales team. If it is relevant, defines the level of impact, documents the change and the possible advantages of its implementation in the company/organization and escalates the request to the change department. The change team,
usually composed of the directors and process owners of the company/organization after receipt of the request for change, evaluate it and approve or not the change request. In case of non-approval of the order, the sales team is
informed of the decision. In the case of approval, the change team informs the IT analyst who initiates the modification of the current documentation and designs the processes with the proposed improvement. After the process design,
the programming team starts the implementation, which is finally tested by the test team. By performing the tests, it is checked whether it is necessary to fix bugs or whether it can proceed to production. If it is possible to proceed, the
test cases are stored in the company/organization database and the IT analyst is informed that the changes have been placed in the production environment. The IT analyst has the function of informing company/organization
employees, evaluating changes and supporting training for users.
Figure 13 – Subprocess “Improvement”
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4.6. CLOSE SALE
The close sale is the sixth step in an effective sales cycle. This process is defined as the successful completion of a sales presentation that results in a commitment on the part of the prospect to purchase the product or service (Dwyer et
al., 2000; Moncrief & Marshall, 2005). After overcoming the prospect’s objections it is necessary to determine and negotiate the terms of the sale and their respective details and begin the conclusion of the sale. When these steps
become completed successfully there is a great possibility of this prospect becoming a customer of the organization (Andzulis et al., 2012). The process of closing a sale is considered somewhat complicated, but there are several tactics
available to be used by the salesperson to overcome these difficulties (Moncrief & Marshall, 2005).
Figure 14 – Process “Close Sale”
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4.7. POST-SALE FOLLOW-UP
The post-sale follow-up is the seventh step in an effective sales cycle. In this process, the salesperson follows-up after closing the sale. This follow-up serves to ensure that the customer is satisfied and that everything that has been
promised is being fulfilled and delivered (Moncrief & Marshall, 2005). After purchasing, several activities are performed such as periodic follow-up calls and communications with the customer to reduce some of the customer's existing
concerns, ensure facilities or training, and respond to complaints and issues (Dwyer et al., 2000). These activities enable the organization to build a lasting relationship with the customer and discover future opportunities,
recommendations, sales odds and cross-selling and up-selling. It is considered one of the key components of a successful sales process (Andzulis et al., 2012).
Figure 15 – Process “Post-Sale Follow-up”
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5. CRITICAL ANALYSIS AND IMPROVEMENT PROPOSAL
5.1. CRITICAL ANALYSIS
The first step in defining a new process or updating an existing one is to create a common
understanding of its current state and evaluate how that process is achieving the defined business
objectives (Association of Business Process Management Professionals, 2009). The way to create this
common understanding is through process analysis. Process analysis is a crucial tool for assessing the
current level of business efficiency based on documented and validated facts as it enables companies
to redesign/transform their processes and better achieve their business objectives (Moore et al.,
2013).
The area of study in question, the sales area, requires constant changes due to the appearance and
proliferation of new technologies and new forms of communication with customers. With the
current level of easy and unlimited access to all information regarding companies, their products and
services, their competition and the recommendations and criticisms about them that consumers
today have access to, many difficulties arise for the teams of sales to exceed and reach what they
want: customer acquisition, customer retention and customer loyalty. These difficulties have as their
main cause the lack of plans and strategies to achieve their objectives, but also the lack of tools and
integration between them to support their work.
This analysis focused on performance measurement, that is, the performance of a process in terms of
extrapolations of time, cost, quality and capacity with the main objective of understanding the
performance of the processes to contribute to its transformation. Performance Measurement also
allows companies to define the level of flexibility of access to information from multiple applications,
to obtain and understand the level of process maturities, and to define the ability to use IT to build
flexible applications. To overcome many of salespeople difficulties, companies need to invest in new
technologies, such as artificial intelligence, robotic process automation, IoT, big data and sales force
automation, as well as the integration of these new technologies with their CRM systems.
Through this analysis, it was possible to identify the main factors that are not allowing the sales
companies to surpass their objectives and obtain a better performance. These factors were analyzed
and divided by the main sales processes and described below.
Process Prospecting
Quality
1. The lack of a target prospecting plan/strategy: the search and access to information have
become a lot easier over time, however, it is not enough if salespeople don’t have a
method that allows a better use of data and how to reach out to prospects.
2. The insufficient use of various media channels: the use of traditional channels such as
calls, mail, radio and television, and newspapers are no longer sufficient and do not
guarantee full and effective prospect identification. The introduction of digital channels
such as social networks, websites/blogs, and video conference is essential.
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Cost and Time
1. The difficulty in categorizing and segmenting prospects: with the vast network of
prospects it is difficult to analyze all the information one by one from each prospect, and
the non-differentiation of prospects causes wastage of time and resources as it does not
distinguish prospects with greater probability of response and does not allow the
allocation of time and resources in the best prospects.
2. The struggle to get accurate and structured information easily and quickly: there is a
massive amount of data prospects available, however, not being structured became
more difficult to extract relevant information that is necessary to get a better
relationship with the prospect.
3. Poor targeting and salespeople spend too much time on bad prospects: if the salespeople
are not targeting the right people, their company messages/products and services are
not going to resonate and it's unlikely to convert to a sale. Spending too much time with
bad prospects will spend a lot of resources, there will be no return, and the time spent
on these prospects could be better applied in other prospects.
Capacity
1. Lack of research and customization: given the scarcity of resources, there is no capacity
for specialized handling (specific messages) of each lead and for the search for sufficient
information on prospects before reaching out.
2. Difficulty in tracking results: with the abundance of resources and information systems
available for tracking prospects and activities it is hard to have a complete summary of
every activity in one place, that is, an integrated system.
Table 6 - Challenges of the Prospecting process
Process Pre-approach
Quality
1. Get past the gatekeeper and lack of access to the right decision-makers: to get to the
decision-maker it is first necessary to interact with the gatekeeper, which can sometimes
become difficult as its function is to analyze the proposals and realize whether they are
spam or appealing to the decision-maker.
2. Getting a target to agree to an appointment: everyday prospects are faced with various
contacts from different salespeople, making it difficult to schedule an appointment if
they are being oversaturated with every prospecting tactic imaginable.
Time
1. Difficulty in managing accounts: with the increasingly complex sales accounts that
require more follow through, salespeople have less time to pursue new opportunities.
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Capacity
1. Lack of integrated information systems: with the abundance of resources and
information systems available for tracking prospects and activities it is hard to have a
complete resume of every activity in one place, that is, an integrated system.
2. Not enough web traffic to support sales efforts: web traffic is a vital asset for
salespeople, because it provides a steady stream of prospects, however, if the web
content does not reflect all the different buyer personas/target audiences it does not
exist capacity to support sales efforts.
Table 7 - Challenges of the Pre-approach process
Process Approach
Quality
1. Salespeople are not asking the right questions in calls: to define the right solution for the
prospect and to provide the best service, it is important to ask the right questions to
uncover the prospects needs, however, salespeople focus only on talking about the
product or service, resulting this in miss opportunities to build trust with decision-
makers that do not believe what the salesperson is selling.
Time
1. Difficulty to manage, analyze and extract meaningful value of the amount of information
available: companies collect an enormous amount of information about their prospects
and it is very time-consuming to analyze them and extract value manually, rapidly and
still be prepared to respond to the prospect's needs.
2. Salespeople spends too much time with wrong prospects: it is considered counter-
intuitive to give up on a lead that has shown interest in the company, but the time spent
pursuing that lead that will not bring advantages to the company and can be spent on
pursuing leads that are a better fit.
Table 8 - Challenges of the Approach process
Process Sales Presentation
Quality
1. Difficulty in defining the perfect solution for the prospect: sometimes salespeople have
difficulty defining a solution/product/service that is according to the customer's needs,
either due to the lack of features that the buyer is looking for or lack of knowledge of the
products/services of the company that is making the sale.
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Time and Cost
1. Lack of focus on sales due to extra administrative tasks: salespeople are loaded with the
burden of extra administrative activities that consume their working hours and their
sales performance.
2. Tailored - presentations created manually: most companies have a master sales deck that
was created to be a perfect presentation, however, one size fits all approach no longer
works for sales, needing customized ones. However, creating custom presentations
manually is time-consuming and sometimes does not work out as expected, that is, the
result is somewhat poor end-product.
3. Recording and making reports for every presentation: after each presentation,
salespeople must collect all the information and create reports to have an accurate
record of all contacts with the prospect which becomes a time-consuming task due to
the extensive list of presentations made over time.
Table 9 - Challenges of the Sales Presentation process
Process Handling objections and overcoming resistance
Quality
1. Unsatisfied customers causing negative online buzz: salespeople are failing to engage
with dissatisfied clients or to escalate the problem to the customer care representative.
This problem affects the reputation of the company as well as the confidence of future
customers.
Cost and Time
1. Prospects constantly asking unexpected questions: there are different types of prospects,
so there are very different subjects and type of information that prospects want to know.
The main problem is that companies are not prepared for all kinds of questions, as it
requires preparation time and available resources, such as a public FAQ to address
questions for each person, causing them to lose credibility.
Table 10 - Challenges of the Handling objections and overcoming resistance process
Process Close Sale
Quality
1. Lack of trust: salespeople need to stop rushing the sale, show the desperation to reach a
sales quota and push the product or service to the prospect, but rather focus on genuine
conversations with the prospects in order to identify their needs and then communicate
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as these needs can be met with the product/service they are selling. They cannot close a
deal if they do not know how to build trust and a relationship with prospects.
2. Lack of knowledge about the product/service offered: sometimes salespeople do not
know much about what they are selling, thus failing in their recommendations for
prospects. As a result, prospects will be unable to understand how the product or service
will benefit them and will neglect to make a purchase.
3. Wrong closing strategy: salespeople are not closing sales due to lack of knowledge of
how to properly close a sale, that is, a method or several methods that work with
salespeople's specific approaches to selling.
4. Documents, agreements or proposals are too complex: Most proposals are very
complicated and require legal review, which makes the prospect consider that it will not
be easy to work with the company. Also, salespeople may be giving proposals to
prospects who are not qualified enough to receive the final documentation.
Table 11 - Challenges of the Close Sale process
Process Post-Sale Follow-up
Quality
1. Lack of an email nurture plan: salespeople are being overly aggressive with leads that are
not yet ready to buy. This happens because they lack an email nurture plan that allows
the buyer to get to know the business first until they are ready to buy. This plan allows
the company to be present in channels where buyers are present, engage with them and
increase the chance that they will start a relationship with the business.
Cost
1. Difficulty in continuing customer relationships post-sale: salespeople after the sale focus
on generating more revenue and gaining new clients, and therefore, fail to follow up on
existing clients which generate discontent on them.
Time
1. Long sales cycle: salespeople are not doing the follow-up on time, causing prospects to
stay in the pipeline for quite a while, which consequently lowers the likelihood of
converting a deal into a sale.
Table 12 - Challenges of the Post-Sale Follow-up process
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5.2. DISCUSSION AND PROPOSAL
Process transformation is the fundamental rethinking of a process and aims to innovate or
implement new applications, new production equipment, new infrastructures of information
technologies and new business approaches. It is considered more comprehensive than process
improvement due to the inclusion of redesign, re-engineering, and change of process paradigms.
There are several reasons to focus on process transformation, such as increasing productivity,
improving quality, reducing process cycle time, reducing defects, risks and costs, increasing capacity,
but more importantly, building customer focus. However, not all transformations have the same
results, so it is important to emphasize that what works in one company may not work in another. All
information obtained in post-transformation stages, in terms of ideas, resource level, approaches,
and best practices, should be checked for their suitability for the company (Moore et al., 2013).
In this chapter, suggestions are presented for new technologies that allow companies to overcome
the difficulties presented in the previous analysis in terms of cost, time, quality and capacity and are
divided again by the main sales processes.
Prospecting:
Process > Quality < Cost < Time > Capacity
Prospecting RFM analysis
RFM analysis
Artificial
intelligence
software tool
RPA
RFM analysis
Artificial
intelligence
software tool
RPA
Artificial
intelligence
software tool
Table 13 - Suggestions for new technologies in the Prospecting process
Nowadays, companies are in a competitive market and, therefore, they need to focus on one of the
key points of success: prospecting. This endless search for new potential customers lacks the
existence of new ways/techniques that go beyond reading address books, cold calls, buying contact
lists or door-to-door presentations. The solution is an Artificial Intelligence software tool. With an AI-
powered software tool that looks for customers faster and more efficiently than a human on a
variety of communication channels and then matches with prospective customers by validating the
data in different sources and allowing a more accurate collection, it is possible to automatically send
pre-defined introductory messages, initiate a relation/contact with the lead, and even schedule
meetings. This tool is composed of several algorithms, for example, predictive lead scoring algorithm,
which searches the profiles of potential customers, categorizes them by the likelihood of response
and gives insights into why one prospect is more profitable than another. But, it also identifies
patterns that determine which leads are most likely to become a deal. AI looks for diverse
information like geography, size of the company, and titles to engagement such as signing up for a
trial or downloading the white paper. These types of insights and information allow the creation of
more personalized content and engagement in more targeted outreach. An AI system also allows the
construction of customer profiles based on their behavior and habits. These profiles allow the system
to predict in an easy and simple way what people need or would like to buy. As the business grows, it
is also crucial to identify/prioritize customers who are most likely to respond to promotions,
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campaigns and any kind of contact made. It is from here that the need arises to segment customers
in order to improve marketing performance and make campaigns more relevant to more customers.
The solution is to use customer segmentation techniques like RFM analysis. This technique uses past
purchase behavior in order to segment customers into several categories or clusters using three
parameters: recency, frequency, and monetary value. With this segmentation, companies increase
customer retention, response rate, conversion rate, and revenue. Another very effective solution
that must be implemented in companies is Robotic Process Automation. This solution allows
companies to find the high-quality deals faster, shorten the deal time, and let sales team focus on
high-value leads and concentrate on the conversation with the customer. That, consequently,
improves productivity, increases ROI and improves accuracy. RPA with its market research power can
analyze trends and take rules-based decisions, in order to help forecast sales revenue without the
guesswork. With its reporting power, it can collect data automatically from multiple systems,
combine it and produce full sales and marketing reports and, with its power of lead management,
can collect and update information (such as “About us” information from customer’s websites),
augment the existing customer data, and automate simple sales and marketing tasks like new
customer forms to move leads through the pipeline quicker.
Pre-approach:
Process > Quality < Cost < Time > Capacity
Pre-approach IoT + CRM
Big data platform
Artificial
intelligence
software tool
Table 14 - Suggestions for new technologies in the Pre-approach process
Customers are the top priority and feature of the sales business. That is why, the more knowledge
and information about the customers the sales teams have access to, the more prepared they will be
to initiate contact with customers and succeed in it. The solution is to integrate the CRM system with
IoT. This integration would work this way: the IoT devices would collect essential data and
information, which would later be stored and organized automatically within CRM. CRM should also
be integrated with Big Data that associates customers and combine them with data from social
media, devices, and sensors. With this information (preferences, opportunities, possibilities) within
the CRM, the sales team has the possibility to identify, predict and satisfy the needs of customers in a
differentiating and effective way to build more personalized customer experiences, but also
customize prices and services by customer. This need for integration arises due to the increasing
information available on the internet about companies, services, and markets that customers have
access to. Having access to that, customers expect companies to be able to respond instantly to all of
their specific issues based on in-depth and specialized knowledge. The integration achieves improved
sales, through the possibility of trend analysis, sales history, and online browsing. This let sales team
implement targeted strategies and upsells, but also increases the speed of a sale, customers will get
what they need on time, it’ll reduce customer churn and develop loyalty by creating a better
customer experience. It is also important to note that an Artificial Intelligence platform should also
be implemented because it can automate activity logging, identify high-priority emails, and create
new contacts/accounts, allowing the sales force to engage in customer contact and work in high-level
meetings.
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Approach:
Process > Quality < Cost < Time > Capacity
Approach Big data platform
Big data
platform
IoT + CRM
Table 15 - Suggestions for new technologies in the Approach process
Today, due to the use of various communication channels, companies collect a large amount of data
from their customers, allowing them to develop complete and accurate customer profiles. However,
the excess of information, usually unstructured and in large quantities, makes it difficult to manage
and extract value from it. The solution is the implementation of Big Data analytics that with its power
of data collection, analysis and structuring can help companies to improve various aspects of sales
strategies. Using big data technologies and improved customer analytics, it allows companies to
increase customer acquisition and the amount of revenue they draw from each purchase. But their
capacity goes further. Using big data companies: can identify who buys their products, which
consequently allows the distinction of personas; can discover what the various buyer personas feel
and transmit information about the brand, products and services; are able to identify what buyers
want, that is, what needs and products are trending and what buyers are asking for and complaining
about; can identify which information sources buyers use, that is, big data platform performs a data
analysis that provides the sources of information used and which information influences more the
purchase decisions; and finally, allows to unveil the buyer's journey, that is, allows to identify how
buyers gather information, establish options and make decisions. Customers are the primary
resource and the driving force behind any business, while providing long-term relationships has a
great economic value. Nowadays, customers are able to gain unlimited access to large quantity of
information about companies, their products and services, which makes them do their own shopping
instead of working with salespeople. Thus, salespeople need to improve or modify their strategies
and techniques. The solution involves integrating IoT with a robust CRM. IoT collects data requested
from different sources and transfer the same to devices and systems automatically, allowing to
resolve daily personal issues and business tasks with ease and flexibility. But also, by organizing the
information collected in the CRM, salespeople have the possibility to connect with the prospect that
allows to automate and improve customer service because the company can identify the problems
through alerts received by the sensors of the products and solve them before customer experiences
dissatisfaction. With this integration, salespeople can take their sales to another level, through
analysis of previous purchases, online browsing and search trends, which in turn allow the
implementation of target strategies and upsells, pipeline management, set prices based on demand
due to possibility of obtaining real-time data on the availability of products, customized marketing
promotions, reduce in response time and marketing research cost.
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Sales Presentation:
Process > Quality < Cost < Time > Capacity
Sales
presentation
Sales Force
Automation (SFA)
Artificial
intelligence
software tool
Sales Force
Automation (SFA)
Sales Support
System - Sales
Activity
Management
Table 16 - Suggestions for new technologies in the Sales presentation process
The on-demand nature of salespeople job requires that they are connected 24/7 and always ready to
respond to requests from prospects. That is why it is crucial for companies to invest in technologies
that focus on the operational aspect of sales and automate sales processes. The solution is a Sales
Force Automation tool. With this tool, salespeople can invest their time in relationship building,
instead of spending time on manual activities, web browsing, and repetitive administrative tasks.
With its power of automation, SFA marks appointments where it offers a variety of available dates
for the presentation, and as soon as the customer chooses one, the appointment is soon
automatically marked and allows for the creation of tailored slide presentations. Nowadays, a
presentation is not effective in all companies and the task of manually creating several tailored slide-
decks is quite time-consuming for salespeople, so the solution is to use sales force automation tools
that automatically assembles slides proven for specific sales situations. However, SFA has more
features such as preparing quarterly sales reports, sending automated pre-defined emails, dialing
direct to leads from CRM and sending reminders to salespeople. After the presentation, the collected
information must be recorded because it is necessary to keep an accurate record of call outcomes.
Being a time-consuming task, it must be automated using SFA that allows for automatically logging
call outcomes and helps managers gain a deeper insight into the quality of certain leads. Other
technologies that are also quite important and that should be considered in the sales presentation
process are an Artificial Intelligence tool and Sales Activity Management system.
An artificial intelligence tool can not only rate what a good deal or account looks like, but also predict
which solutions and discounts should be offered to each customer based on previous successes. This
tool allows finding the ideal product for each group of customers, increasing customer satisfaction
and consequently increasing loyalty. The other tool is Sales Activity Management which, like sales
automation tool, has calendars to assist the planning of key customer events such as proposal
presentations and product demonstrations, but also an activity management system helps to get the
most out of the salespeople by uncovering, tracking and motivating the activities that lead to sales.
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Handling objections and overcoming resistance:
Process > Quality < Cost < Time > Capacity
Handling
objections and
overcoming
resistance
Community site Community site
Satisfaction
survey
Online Survey
Management
System
Improvement
process
Document
Management
System
Table 17 - Suggestions for new technologies in the Handling objections and overcoming resistance process
Handling objections are considered one of the most crucial factors in managing to close a sale, gain
new customers and retain current company customers. However, salespeople are having difficulty in
answering all customer objections in a quick and satisfying way. The solution is to encourage
customers to find the answers themselves, but for this, it is necessary to create a community site
that offers products documentation, articles, updates, testimonials and the FAQ. With a community
site, the single piece of online content can answer a lot of customer questions and reduce the
company's support calls. It also allows to increase the acquisition of new customers, brand and
product awareness, customer engagement, improve retention rates, increase customer lifetime
value by increasing upsell, cross-sell and add-on purchases, nurture customer advocates and drive
product innovation. This online community must be designed to initiate conversations about the
company and its products and services, allowing companies to track the most common customer
complaints and new features to improve the product in the way that becomes more efficient and
appealing to the market. Customer satisfaction is one of the most important factors that contribute
to the success or failure of a business because the product or service of a company revolves around
customers and their experiences. Customer opinions and feedback are considered the most essential
components for the sustainability and growth of companies so it is necessary to know the levels of
customer satisfaction, their expectations, and needs. To validate the consumer experience, it is
crucial to invest in an Online Survey Management System interconnecting it with CRM. By adding the
power of combining data and automated capabilities of CRM with marketing research capabilities of
surveys, it is possible to build sales strategies that are more focused without losing the ability to
scale. Online surveys are a good way to reach and engage with the target audience, but it also allows
companies to increase response rates by reaching the target audience, conduct market research in a
cheaper way and get real-time results for a quick and easy analysis. With an Online Survey
Management System, it is possible to obtain information automatically, because being online the
response is almost instantaneous, it reduces the research costs because the answers are processed
automatically and the results are accessible at any time and saved in a single database. It allows
more accurate analyzes because participants respond directly to the system, unlike traditional
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methods when it was the staff putting all responses into the system increasing the probabilities of
errors and offers insights to improve the product and overall customer experience. This system
performs the collection and analysis of the results using the scoring technique. That is, assign a value
to each question code, and then calculate analysis using the score instead of the code, which allows
to summarize the whole satisfaction (positive or negative) in a simple, fast and efficient way. At the
moment of implementation of changes in companies and their business processes arises a need for
planned management of resources, information, and risks. Developing a small and/or medium-sized
project lacks support tools prepared to handle the entire workload that will exist. One of the key
solutions before moving to the implementation of changes is the implementation of a document
management system that will allow companies to keep compliant with recordkeeping regulations,
streamline the overall workflow, avoid security risks and increase productivity. A document
management system has, as main objective, helping companies to manage risks, regulatory
compliance and information governance, and is divided into two types: paper document
management systems and electronic document management systems. With their implementation,
companies can gain greater control over the creation and authentication of their documents, version
management of documents, document location management in order to facilitate retrieval of a
document when necessary, security of documents preventing unauthorized access of documents and
quick recovery of lost or damaged documents and most importantly allows the creation of a policy of
archiving old documents with a date of preservation. But it also enables the company to increase
competitiveness by improving business processes, reducing costs and preventing major losses. Rapid
access to information helps improve customer satisfaction and help salespeople respond/deliver
quickly and efficiently what customers are looking for.
Close Sale:
Process > Quality < Cost < Time > Capacity
Close Sale
DSS
Document
Management
System
Table 18 - Suggestions for new technologies in the Close Sale process
Nowadays, closing a sale is considered very important and sometimes a little difficult factor. This is
because salespeople are not prepared to communicate with the customer and demonstrate the
benefits of their product or service, but also because they have not defined a strategy to close the
sale and the lack of a system that allows to set appellant prices, analyze data and make very
important decisions. The solution involves the implementation of a decision-support system that
must be adapted to the needs and should be used to evaluate the operations of each business. There
are several ways managers can use this system to their advantage. The first way is inventory
management. DSS offers a guidance in establishing supply chain movement and allows salespeople
to evaluate the stock level quickly and efficiently. The second way is to use DSS for sales optimization
and sales projection, where the tool allows the analysis of sales data and make predictions or
monitor existing patterns. The third way is to use DSS to optimize industry-specific systems, that is,
to make good projections that determine the company's progress and determine expenditures, price
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strategy and revenues due to its financial projections. DSS allows increased market share, the
profitability of the organization and increased productivity and efficiency of salespeople, as it allows
salespeople to be aware of the potential customers around a real-time basis that increases the
likelihood of closing a sale. With almost unlimited product information and comparative analysis
available online, customers only engage with salespeople when they are almost ready to make the
final decision. Therefore, instant access to information and tools for outstanding customer
experiences is crucial. The solution is a document management system because content quality is
seen today as one of the key drivers of winning deals. A document management system allows the
delivery of the right content to the right prospect at the right moment of the sales journey. With its
power of organization of files and business documents, centralization, real-time and workflow
automation allows documents to be traced anytime, anywhere and by everyone that is allowed. This
makes it easier for salespeople to work by allowing them to capture, access and share prospect and
customer information in seconds. It also allows for the digitization, management, and sharing of
contracts for collective collaboration between salespeople, and legal and executive reviewers,
ensuring data integrity across systems.
Post-Sale Follow-Up:
Process > Quality < Cost < Time > Capacity
Post-Sale
Follow-Up
Automated email
marketing tool
Gift Card System
Automated
marketing tool
Table 19 - Suggestions for new technologies in the Post-Sale Follow-Up process
The key to have a profitable long-term business is to focus on retaining past customers as they are
more valuable than one-time customers. However, with the lack of a nurturing plan and a follow-up
strategy, it is difficult to retain them. At this point, it does not make sense for salespeople to spend a
lot of time writing individual emails or sending general emails to the entire customer list because if
customers receive messages that are irrelevant to them, they are more likely to unsubscribe or mark
the company's spam messages. The solution is the implementation of an email marketing
automation tool that allows to increase customer engagement, increase opportunities for cross-
selling and up-selling, save time, allow greater communication with customers and increase revenue.
This tool has the role of sending targeted emails at specified times or in response to certain client
actions, and allows the inclusion of custom fields such as the name of the client or company name to
which it belongs and the sending of more relevant messages due to its power of segmentation that
tailor different messages for groups based on their interests, demographics or purchase behavior.
Another very effective solution that must be implemented in order to improve the consumer
experience is a gift card system. This system allows companies to spread the company brand because
it makes customers offer cards to their family and friends, and in turn, customers are able to buy
more products by paying less thanks to the gift card. The company gets new customers and upfront
cash whenever one of the gift cards is handed out. Also, this allows companies to obtain free
publicity, that is, with customizable gift cards, customers will better recognize the brand and will
want to continue to buy and, more importantly, it allows the simplification of business operations
because leaving operations to be done by the system is possible to ensure that the transaction report
adds up and can begin to track trends and make important business decisions. With its extensive
69
reporting capability, it enables companies to track sales and outstanding balances, which allows
them to have a complete view of the business, but also, reduces errors, easily reconcile transactions,
build customer loyalty, and gain deeper insights about business operations.
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6. CONCLUSIONS
Given the demands that companies face today, it is important that they use various methods or
methodologies that make their adaptation and success possible. One of these methodologies is BPM
with its focus on continuous improvement of business processes through their analysis, modeling,
and transformation. This dissertation was started with the intention of identifying and modeling the
main sales processes and obtaining a deeper knowledge of the area in question in order to suggest
improvements. Despite the common knowledge that people have about this area, it does not
compare with the immensity and depth of it that is unknown. The work done by salespeople is
underestimated, but after the study was conducted, there were revealed various nuances and it was
demonstrated their interconnectedness and importance with all areas of a company.
6.1. SYNTHESIS OF WORK DEVELOPED
The first phase was the production of literature review, which is considered an essential prerequisite
for the analysis and modeling of business processes in order to understand the current state of the
art, that is, the BPM methodology, sales area, its components, and current technologies used.
Process modeling was followed in BPMN 2.0 with the help of the Bizagi Process Modeler tool. The
modeling phase was the most interesting of this dissertation since it was possible to perceive the
globality of the processes in which the salespeople were involved and allowed a later analysis and
evaluation of the business processes. This evaluation was able to identify the positive and negative
points of each activity, which made it possible to perceive the needs of the sales area and to suggest
new technologies to meet those needs. With the implementation of new technologies such as
artificial intelligence, robotic process automation, IoT and salesforce automation, the sales area
reaches a whole new level. These technologies will enable companies to increase customer
retention, increase loyalty and satisfaction, but also increase productivity, improving quality,
reducing process cycle time, reducing defects, risks and costs.
6.2. LIMITATIONS AND RECOMMENDATIONS FOR FUTURE WORKS
For any research done in any area, there are always ways of improvement that can be made to
achieve better results. This investigation is one of them. Due to the need for constant change in
organizations, but also to the growth and development of reality, the market and the emergence of
new technologies and maturation of existing ones, all sales processes must be constantly analyzed
and subject to further improvements and new ideas.
For future work, the next step is to model the "TO-BE" business processes of the sales area identified
in this dissertation considering the presented improvement suggestions that are reflected through
the insertion of new technologies during the whole sales cycle, but should also be adapted to each
company because of its needs, size, maturity and market. After modeling and adapting processes, I
think it would be interesting to move from theory to practice. That is, its implementation, passing
later on tests that will allow monitoring differences in performance before and after the analysis and
transformation of business processes. With the focus on continuous improvement and the use of
BPM, there will always be a focus on finding new needs and ways to innovate. The main limitation of
this dissertation was the lack of recent information regarding sales processes, their interlocutors and
their techniques, which made it difficult to detail the various steps and activities of each phase of the
sales lifecycle.
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BIBLIOGRAPHY
Aggour, A. (2015). 5 ways to acquire new sales leads. Retrieved May 4, 2018, from
https://www.nutshell.com/blog/5-ways-to-acquire-new-sales-leads/
Agnihotri, R., Kothandaraman, P., Kashyap, R., & Singh, R. (2012). Bringing “Social” into Sales: The
Impact of Salespeople’s Social Media Use on Service Behaviors and Value Creation. Journal of
Personal Selling and Sales Management, 32(3), 333–348. https://doi.org/10.2753/PSS0885-
3134320304
Aguilar-Savén, R. S. (2004). Business process modelling: Review and framework. International Journal
of Production Economics, 90(2), 129–149. https://doi.org/10.1016/S0925-5273(03)00102-6
Aguirre, S., & Rodriguez, A. (2017). Automation of a Business Process Using Robotic Process
Automation (RPA) : A Case Study (Vol. 742). Springer International Publishing.
https://doi.org/10.1007/978-3-319-66963-2
Alianto, H., FernandiWijaya, S., & Arlan, F. (2012). AN ANALYSIS OF SALES INFORMATION SYSTEM
AND COMPETITIVE ADVANTAGE (Study Case of UD. Citra Helmet). International Journal of
Communication & Information Technology (CommIT), 6(2), 69–75. Retrieved from
http://msi.binus.ac.id/commit/
Amrollahi, A., & Lukyanenko, R. (2016). A Multi-Paradigmatic Approach to Theorising in Design
Science Research. In Advances in Qualitative IS Research Methodologies (pp. 1–4).
Andzulis, J. “Mick,” Panagopoulos, N. G., & Rapp, A. (2012). A Review of Social Media and
Implications for the Sales Process. Journal of Personal Selling and Sales Management, 32(3),
305–316. https://doi.org/10.2753/PSS0885-3134320302
Asatiani, A., & Penttinen, E. (2016). Turning robotic process automation into commercial success -
Case OpusCapita. Journal of Information Technology Teaching Cases, 6(2), 67–74.
https://doi.org/10.1057/jittc.2016.5
Association of Business Process Management Professionals. (2009). Business Process Management
CBOK Version 2.0 : Guide to the Business Process Management Common Body of Knowledge
(2nd ed.). Chicago: Association of Business Process Management Professionals. Retrieved from
http://s.itb.ac.id/home/[email protected]/Magister Informatika ITB/IF5131-ABPMP -
CBOK-v2-0.pdf
72
Bartolacci, F. (2004). Activity Based Costing in the Supply Chain: Logistics activities cost analysis, 1–
10.
Beverland, M. (2001). Contextual influences and the adoption and practice of relationship selling in a
business-to-business setting: An exploratory study. Journal of Personal Selling and Sales
Management, 21(3), 207–215. https://doi.org/10.1080/08853134.2001.10754272
Bhatt, C., Dey, N., & Ashour, A. S. (2017). Internet of Things and Big Data Technologies for Next
Generation Healthcare (1st ed.). Springer International Publishing. https://doi.org/10.1007/978-
3-319-49736-5
Bizagi. (2016). Bizagi Process Modeler User Guide. Retrieved May 3, 2017, from
http://help.bizagi.com/process-modeler/en/
Blattberg, R. C., Kim, B.-D., & Neslin, S. A. (2008). RFM Analysis. Analysis, 18(M), 323–337.
https://doi.org/10.1007/978-0-387-72579-6_12
Boujena, O., Johnston, W. J., & Merunka, D. R. (2009). The Benefits of Sales Force Automation: A
Customer’s Perspective. Journal of Personal Selling and Sales Management, 29(2), 137–150.
https://doi.org/10.2753/PSS0885-3134290203
Bramer, M. (2016). Principles of Data Mining (3rd ed., Vol. 30). Springer-Verlag London.
https://doi.org/10.1007/978-1-4471-7307-6
Buttle, F., Ang, L., & Iriana, R. (2006). Sales force automation: Review, critique, research agenda.
International Journal of Management Reviews, 8(4), 213–231. https://doi.org/10.1111/j.1468-
2370.2006.00128.x
Cravens, D. (1995). The Changing Role of the Sales Force. Marketing Management, 4(2), 48–57.
Dale, B. (2015). Total Quality Management. Wiley Encyclopedia of Management (Vol. 10).
https://doi.org/10.1002/9781118785317.weom100042
Dannenberg, H., & Zupancic, D. (2009). Excellence in Sales: Optimising Customer and Sales
Management. (H. Dannenberg & D. Zupancic, Eds.) (1st ed.). Wiesbaden, Germany: Gabler
Verlag.
Diepeveen, B., Matcher, J., & Lewkowicz, B. (2016). Robotic process automation Automation ’ s next
frontier.
Donaldson, B. (1998). Sales Management. (A. Editorial, Ed.) (2nd ed.). Macmillan Press LTD.
73
Dumas, M., La Rosa, M., Mendling, J., & Reijers, H. A. (2012). Fundamentals of business process
management.
Dwyer, S., Hill, J., & Martin, W. (2000). An empirical investigation of critical success factors in the
personal selling process for homogenous goods. The Journal of Personal Selling and Sales, XX(3),
151–159. https://doi.org/10.1080/08853134.2000.10754235
Edelman, D. C., & Singer, M. (2015a). Competing on Customer Journeys. Retrieved November 25,
2017, from https://hbr.org/2015/11/competing-on-customer-journeys
Edelman, D. C., & Singer, M. (2015b). Shaping the Digital Customer Journey. Retrieved November 25,
2017, from https://hbr.org/webinar/2015/11/shaping-the-digital-customer-journey
Euchner, J., & Ganguly, A. (2014). Business Model Innovation in Practice. Research-Technology
Management, o. Jg.(December), 33–40. https://doi.org/10.5437/08956308X5706013
Finley, W. E. (2013). Using personal selling techniques in embedded librarianship. Journal of Business
and Finance Librarianship, 18(4), 279–292. https://doi.org/10.1080/08963568.2013.825111
Freire, J., & Alarcó N, L. F. (2002). Achieving Lean Design Process: Improvement Methodology. Journal
of Construction Engineering and Management, vol: 128(3), pp: 248-256.
https://doi.org/10.1061/(ASCE)0733-9364(2002)128:3(248)
Gabriel, Y., & Lang, T. (2008). New Faces and New Masks of Today’s Consumer. Journal of Consumer
Culture, 8(3), 321–340. https://doi.org/10.1177/1469540508095266
Gandomi, A., & Haider, M. (2015). Beyond the hype: Big data concepts, methods, and analytics.
International Journal of Information Management, 35(2), 137–144.
https://doi.org/10.1016/j.ijinfomgt.2014.10.007
Giamanco, B., & Gregoire, K. (2012). Tweet me, friend me, make me buy. Harvard Business Review,
90(7–8), 1–9.
Gjoni, O. (2015). Comparison of Two Model Driven Architecture Approaches for Automating Business
Processes, Moskitt Framework and Bizagi Process Management Suite. Mediterranean Journal of
Social Sciences MCSER Publishing, Rome-Italy, 6/2(2), 615–625. https://doi.org/10.5901
Goncalves, A. L., Freitas Junior, V., Ceci, F., & Woszezenki, C. R. (2017). Design Science Research
Methodology As Methodological Strategy for Technological Research. Espacios, (February).
Gordon, J., Gruntges, V., Smith, V., & Staack, Y. (2016). New insights for new growth: What it takes to
74
understand your customers today. Retrieved November 25, 2017, from
http://www.mckinsey.com/business-functions/marketing-and-sales/our-insights/new-insights-
for-new-growth-what-it-takes-to-understand-your-customers-today
Gray, P., & Negash, S. (2008). Business Intelligence. In F. Burstein & C. W. Holsapple (Eds.), Handbook
on Decision Support Systems 2: Variations (1st ed., pp. 175–193). Springer-Verlag Berlin.
https://doi.org/10.1007/978-3-540-48716-6
H2O.ai. (2018). H2O.ai. Retrieved May 2, 2018, from https://www.h2o.ai/
Hajiheydari, N., & Dabaghkashani, Z. (2011). BPM Implementation Critical Success Factors: Applying
Meta-synthesis Approach. International Conference on Social Science and Humanity, 5, 38–43.
Hassan, S., Nadzim, S. Z. A., & Shiratuddin, N. (2015). Strategic Use of Social Media for Small Business
Based on the AIDA Model. Procedia - Social and Behavioral Sciences, 172, 262–269.
https://doi.org/10.1016/j.sbspro.2015.01.363
Hendricks, K. B., Singhal, V. R., & Stratman, J. K. (2007). The impact of enterprise systems on
corporate performance: A study of ERP, SCM, and CRM system implementations. Journal of
Operations Management, 25(1), 65–82. https://doi.org/10.1016/j.jom.2006.02.002
Hevner, A., & Chatterjee, S. (2010). Design Research in Information Systems, 22, 9–23.
https://doi.org/10.1007/978-1-4419-5653-8
Hosseini, S. M. S., Maleki, A., & Gholamian, M. R. (2010). Cluster analysis using data mining approach
to develop CRM methodology to assess the customer loyalty. Expert Systems with Applications,
37(7), 5259–5264. https://doi.org/10.1016/j.eswa.2009.12.070
Howson, C., Sallam, R., Richardson, J. L., Tapadinhas, J., Idoine, C. J., & Woodward, A. (2018). Magic
Quadrant for Analytics and Business Intelligence Platforms. Retrieved May 2, 2018, from
https://www.gartner.com/doc/3861464/magic-quadrant-analytics-business-intelligence
IBM. (2018). IBM SPSS Modeler. Retrieved April 10, 2018, from https://www.ibm.com/pt-
en/marketplace/spss-modeler
Idoine, C. J., Krensky, P., Brethenoux, E., Hare, J., Sicular, S., & Vashisth, S. (2018). Magic Quadrant for
Data Science and Machine-Learning Platforms. Retrieved April 10, 2018, from
https://www.gartner.com/doc/3860063/magic-quadrant-data-science-machinelearning
Idoine, C. J., Krensky, P., Linden, A., Hare, J., Sicular, S., & Vashisth, S. (2017). Magic Quadrant for
75
Data Science Platforms. Retrieved April 10, 2018, from
https://www.gartner.com/doc/reprints?id=13TKR16P&ct=170215&st=sg
InfoSistema. (2013). Optimização de processos empresariais. Retrieved May 3, 2017, from
https://www.infosistema.com/pt-pt/artigos-estudos/
Işik, Ö., Jones, M. C., & Sidorova, A. (2013). Business intelligence success: The roles of BI capabilities
and decision environments. Information and Management, 50(1), 13–23.
https://doi.org/10.1016/j.im.2012.12.001
Jobber, D., & Lancaster, G. (2009). Personal Selling and Sales Management (8th ed.). Pearson
Education Limited.
Jones, E., Brown, S. P., Zoltners, A. A., & Weitz, B. A. (2005). The changing environment of selling and
sales management. Journal of Personal Selling and Sales Management, 25(2), 105.
https://doi.org/10.1080/08853134.2005.10749052
Juric, M., & Sasa, A. (2009). Effective Process Modeling with BPM and BPMN. RefCardz.
Kanellis, P., & Papadopoulos, T. (2009). Conducting Research in Information Sytems: An
Epistemological Journey. In Information Systems Research Methods, Epistemology, and
Applications (pp. 1–34). Hershey: Information Science Reference.
Klaus, H., Rosemann, M., & Gable, G. G. (2000). What is ERP? Information Systems Frontiers, 2(2),
141–162. https://doi.org/10.1023/A:1026543906354
KNIME. (2018). KNIME Analytics Platform. Retrieved April 10, 2018, from
https://www.knime.com/knime-analytics-platform
Ko, R. K. L. (2009). A computer scientist. Crossroads, 15(4), 11–18.
https://doi.org/10.1145/1558897.1558901
Ko, R. K. L., Lee, S. S. G., & Wah Lee, E. (2009). Business process management (BPM) standards: a
survey. Business Process Management Journal (Vol. 15). Emerald Group Publishing Limited.
https://doi.org/10.1108/14637150910987937
Kotler, P., & Armstrong, G. (2016). Principles of Marketing. Pearson Education Limited (15th ed.).
Harlow, England.
Kotler, P., & Keller, K. L. (2016). Marketing Management. Pearson Education Limited (15th ed.).
Harlow, England.
76
Kundu, S. S., & Bishnoi, V. . (2009). Sales Management : an Overview, 1–202.
Laudon, K. C., & Laudon, J. P. (2012). Management information systems: managing the digital firm.
(B. Horan, Ed.) (12th ed.). New Jersey: Prentice Hall. https://doi.org/10.1590/S1415-
65552003000100014
Lemańska-Majdzik, A., & Okręglicka, M. (2015). Identification of Business Processes in an Enterprise
Management. Procedia Economics and Finance, 27(15), 394–403.
https://doi.org/10.1016/S2212-5671(15)01011-4
Levy, Y., & Ellis, T. J. (2006). A systems approach to conduct an effective literature review in support
of information systems research. Informing Science, 9, 181–211.
https://doi.org/10.1049/cp.2009.0961
Li, G. (2015). Big data related technologies, challenges and future prospects. Information Technology
& Tourism (Vol. 15). https://doi.org/10.1007/s40558-015-0027-y
Lindsay, A., Downs, D., & Lunn, K. (2003). Business processes - Attempts to find a definition.
Information and Software Technology, 45(15), 1015–1019. https://doi.org/10.1016/S0950-
5849(03)00129-0
Llave, M. R. (2017). Business Intelligence and Analytics in Small and Medium-sized Enterprises: A
Systematic Literature Review. Procedia Computer Science, 121, 194–205.
https://doi.org/10.1016/j.procs.2017.11.027
Long, M. M., Tellefsen, T., & Lichtenthal, J. D. (2007). Internet integration into the industrial selling
process: A step-by-step approach. Industrial Marketing Management, 36(5), 676–689.
https://doi.org/10.1016/j.indmarman.2006.05.001
Marshall, G. W., Moncrief, W. C., & Lassk, F. G. (1999). The current state of series force activities.
Industrial Marketing Management, 28(1), 87–98.
Marshall, G. W., Moncrief, W. C., Rudd, J. M., & Lee, N. (2012). Revolution in Sales: The Impact of
Social Media and Related Technology on the Selling Environment. Journal of Personal Selling
and Sales Management, 32(3), 349–363. https://doi.org/10.2753/PSS0885-3134320305
Maynigo, R., Baysan, C., Bertman, A., Norville, G., Osborne, N., & Taylor, T. (2005). The Design and
Development of a Sales Force Automation Tool Using Business Process. Proceedings of the 2005
Systems and Information Engineering Design Symposium, 318–327.
77
McAfee, A., & Brynjolfsson, E. (2012). Big Data: The Management Revolution. Harvard Business
Review, (October). Retrieved from tarjomefa.com/wp-content/uploads/2017/04/6539-English-
TarjomeFa-1.pdf
McCarty, J. A., & Hastak, M. (2007). Segmentation approaches in data-mining: A comparison of RFM,
CHAID, and logistic regression. Journal of Business Research, 60(6), 656–662.
https://doi.org/10.1016/j.jbusres.2006.06.015
Microsoft. (2018). Power BI. Retrieved May 2, 2018, from https://powerbi.microsoft.com/en-us/
Molinillo, S., Gómez-Ortiz, B., Pérez-Aranda, J., & Navarro-García, A. (2017). Building Customer
Loyalty. Clothing and Textiles Research Journal, 35(3), 156–171.
https://doi.org/10.1177/0887302X17694270
Moncrief, W. C., & Marshall, G. W. (2005). The evolution of the seven steps of selling. Industrial
Marketing Management, 34(1), 13–22. https://doi.org/10.1016/j.indmarman.2004.06.001
Moore, C., Benedict, T., Bilodeau, N., & Vitkus, P. (2013). BPM CBOK Version 3. 0: Guide to the
Business Process Management Common Body of Knowledge (3.0). ABPMP, 2013.
Morgan, A. J., & Inks, S. A. (2001). Technology and the Sales Force: Increasing Acceptance of Sales
Force Automation. Industrial Marketing Management, 30(5), 463–472.
https://doi.org/10.1016/S0019-8501(99)00115-7
Ngai, E. W. T., Xiu, L., & Chau, D. C. K. (2009). Application of data mining techniques in customer
relationship management: A literature review and classification. Expert Systems with
Applications, 36(2 PART 2), 2592–2602. https://doi.org/10.1016/j.eswa.2008.02.021
Norton, D. W., & Pine, B. J. (2013). Using the customer journey to road test and refine the business
model. Strategy & Leadership, 41(2), 12–17. https://doi.org/10.1108/10878571311318196
Oakes, G. (1990). The sales process and the paradoxes of trust. Journal of Business Ethics, 9(8), 671–
679. https://doi.org/10.1007/BF00383394
Okrent, M. D., & Vokurka, R. J. (2004). Process mapping in successful ERP implementations. Industrial
Management & Data Systems, 104(8), 637–643. https://doi.org/10.1108/02635570410561618
Ostrowski, L., & Helfert, M. (2014). Business Process Modelling in Design Science Paradigm, 111–122.
https://doi.org/10.1007/978-3-319-13936-4_10
Paesbrugghe, B., Rangarajan, D., Sharma, A., Syam, N., & Jha, S. (2017). Purchasing-driven sales:
78
Matching sales strategies to the evolution of the purchasing function. Industrial Marketing
Management, 62, 171–184. https://doi.org/10.1016/j.indmarman.2016.09.002
Pan, Y. (2016). Heading toward Artificial Intelligence 2.0. Engineering, 2(4), 409–413.
https://doi.org/10.1016/J.ENG.2016.04.018
Paulk, M. C., Curtis, B., Chrissis, M. B., & Weber, C. V. (1993). Capability maturity model, version 1.1.
IEEE Software, 10(4), 18–27. https://doi.org/10.1109/52.219617
Peffers, K., Tuunanen, T., Rothenberger, M. A., & Chatterjee, S. (2007). A design science research
methodology for information systems research. Journal of Management Information Systems
(JMIS), 24(3), 45–78. https://doi.org/10.2753/MIS0742-1222240302
Piercy, N. F. (2005). The Strategic Sales Organization. The Marketing Review, 15(1), 329–342.
Piercy, N. F., & Lane, N. (2005). Strategic imperatives for transformation in the conventional sales
organization. Journal of Change Management, 5(3), 249–266.
https://doi.org/10.1080/14697010500175094
Pires, G. D., Stanton, J., & Rita, P. (2006). The internet, consumer empowerment and marketing
strategies. European Journal of Marketing, 40(9/10), 936–949.
https://doi.org/10.1108/03090560610680943
Power, D. J., Sharda, R., & Burstein, F. (2014). Decision Support Systems. (C. L. Cooper, Ed.), Wiley
Encyclopedia of Management. John Wiley & Sons, Ltd.
Pyzdek, T., & Keller, P. (2010). The Six Sigma handbook. Mc Graw Hill.
https://doi.org/10.1036/0071415963
Qlik. (2018). Qlik Sense. Retrieved May 2, 2018, from https://www.qlik.com/us/products/qlik-sense
RapidMiner. (2018). RapidMiner. Retrieved April 10, 2018, from https://rapidminer.com/
Rawson, A., Duncan, E., Jones, C., MacBeth, P., Thomas, J. C., Tombazian, C. M., & Iordanova, K.
(2013). The Truth About Customer Experience: Interaction. Harvard Business Review, 91(11),
26. Retrieved from http://www.redi-
bw.de/db/ebsco.php/search.ebscohost.com/login.aspx?direct=true&db=bth&AN=91570254&si
te=ehost-live
Reynolds, G. W., & Stair, R. M. (2010). Principles of Information Systems, A managerial approach. (J.
Calhoun, Ed.) (9th ed.). Boston, MA: Course Technology, Cengage Learning.
79
Richardson, A. (2016). What You Can and Should Be Doing with Your Customer Journeys. Retrieved
November 25, 2017, from https://hbr.org/2016/03/what-you-can-and-should-be-doing-with-
your-customer-journeys?referral=03759&cm_vc=rr_item_page.bottom
Rodriguez, M., Ajjan, H., & Peterson, R. M. (2016). Social Media in Large Sales Forces: An Empirical
Study of the Impact of Sales Process Capability and Relationship Performance. Journal of
Marketing Theory and Practice, 24(3), 365–379.
https://doi.org/10.1080/10696679.2016.1170538
Rodriguez, M., Peterson, R. M., & Krishnan, V. (2012). Social Media’s Influence on Business-To-
Business Sales Performance. Journal of Personal Selling and Sales Management, 32(3), 365–378.
https://doi.org/10.2753/PSS0885-3134320306
Rosemann, M., & Bruin, T. De. (2005). Towards a Business Process Management Maturity Model.
ECIS 2005 Proceedings of the Thirteenth European Conference on Information Systems, (May),
26–28. https://doi.org/10.1109/EUROMICRO.2007.35
Rygielski, C., Wang, J.-C., & Yen, C. D. (2002). Data mining techniques for customer relationship
management. Technology in Society, 24(4), 483–502.
Sagiroglu, S., & Sinanc, D. (2013). Big Data : A Review, 42–47.
SAS Institute. (2018). SAS Enterprise Miner. Retrieved April 10, 2018, from
https://www.sas.com/en_us/software/enterprise-miner.html
Schmiedel, T., Vom Brocke, J., & Recker, J. (2014). Development and validation of an instrument to
measure organizational cultures’ support of Business Process Management. Information and
Management, 51(1), 43–56. https://doi.org/10.1016/j.im.2013.08.005
Schuldt, B. A., & Totten, J. W. (2015). Application of social media types in the sales process. Academy
of Marketing Studies Journal, 19(3), 236–249.
Setiawati, D. W., & Rohayati, Y. (2014). Implementing enterprise resource planning (ERP) in sales
information system (SIS) of SME (small medium enterprise) Abo Farm Indonesia. Proceedings -
2014 International Conference on ICT for Smart Society: “Smart System Platform Development
for City and Society, GoeSmart 2014”, ICISS 2014, 169–175.
https://doi.org/10.1109/ICTSS.2014.7013168
Shatonhoka, E. N. (2015). The Challenges of Managing an Organisation during and after the Economic
Crisis. International Journal of Economics & Management Sciences, 04(02), 2–5.
80
https://doi.org/10.4172/2162-6359.1000222
Shim, J. P., Warkentin, M., Courtney, J. F., & Power, D. J. (2002). Past , present , and future of
decision support technology. Elsevier Science B.V., 33, 111–126.
Sikos, L. (2015). Mastering Structured Data on the Semantic Web: From HTML5 Microdata to Linked
Open Data. Apress.
Singh, M. R. P., Anand, S. B., Davar, S. C., Bansal, H., Bodla, B. S., & Dhingra, A. (2011). Sales
Management. Distance Education, 202.
Sol, H. G., Takkenberg, C., & Robbé, P. (1987). Expert systems and artificial intelligence in decision
support systems (1st ed.). Springer Science+Business Media Dordrecht.
Ştefan, B. D., & Crăciun, M. B. (2011). The Importance of Sales Management Improving in the Current
Economic Context. Importanţa Perfecţionării Managamentului vâNzărilor În Contextul Economic
Actual., 63(4), 105–113. Retrieved from
http://ezproxy.net.ucf.edu/login?url=http://search.ebscohost.com/login.aspx?direct=true&db=
aph&AN=90515732&site=ehost-live
Suh, E., & Alhaery, M. (2015). Predicting Cross-Gaming Propensity Using E-CHAID Analysis. UNLV
Gaming Research & Review Journal, 19(1), 31–49. Retrieved from
http://sfx.scholarsportal.info/ottawa?url_ver=Z39.88-
2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&genre=article&sid=ProQ:ProQ%253Aabiglobal
&atitle=Predicting+Cross-Gaming+Propensity+Using+E-
CHAID+Analysis&title=UNLV+Gaming+Research+%2526+Review+Journal&i
Tableau. (2018). Tableau. Retrieved May 2, 2018, from https://www.tableau.com/products
Tang, J., Pee, L. G., & Iijima, J. (2013). Investigating the effects of business process orientation on
organizational innovation performance. Information & Management, 50(8), 650–660.
https://doi.org/http://dx.doi.org/10.1016/j.im.2013.07.002
Terceros, C. A., & Leslie, S. (2011). Oracle Fusion Middleware Modeling and Implementation Guide for
Oracle Business Process Management (Vol. 1).
Van der Aalst, W. M. P., Bichler, M., & Heinzl, A. (2018). Robotic Process Automation. Business &
Information Systems Engineering, 1. https://doi.org/10.1007/s12599-018-0542-4
Vom Brocke, J., & Rosemann, M. (2010). The Six Core Elements of Business Process Management.
81
Handbook on Business Process Management 1. https://doi.org/10.1007/978-3-642-00416-2_5
Watson, H. J., & Wixom, B. H. (2007). The Current State of Business Inteligence. Computer, 40(9), 96–
99. https://doi.org/10.1109/MC.2007.331
Weber, C., Curtis, B., & Gardiner, T. (2008). Business Process Maturity Model (BPMM). Business
Process Trends (1st ed.). Object Management Group. Retrieved from
http://www.omg.org/spec/BPMM/1.0/PDF
White, S. (2004). Introduction to BPMN. IBM Cooperation, 2(0), 1–11.
https://doi.org/10.3727/000000006783982421
Wiener, J. B. (2013). The Diffusion of Regulatory Oversight. The Globalization of Cost-Benefit Analysis
in Environmental Policy, 123–141.
https://doi.org/10.1093/acprof:oso/9780199934386.003.0008
Willcocks, L., Lacity, M., & Craig, A. (2015). The IT Function and Robotic Process Automation. The
Outsourcing Unit Working Research Paper Series, (October), 1–38.
Yanjing, J. (2009). Integration of CRM and ERP in E-commerce Environment. In International
Conference on Management and Service Science (pp. 1–4).