leveraging bi technologies to lift the burden of big data

Leveraging BI Technologies to Lift the Burden of Big Data

MarketBridge | Leveraging BI Technologies to Lift the Burden of Big Data

LEVERAGING BI TECHNOLOGIES

TO LIFT THE BURDEN OF BIG DATA

INTRODUCTION

The emergence of new technology and web-based platforms has had a profound effect on the amount of data

available both online and offline. This massive increase in data has significant implications for today’s sales

and marketing professionals (Figure A).

Almost every company endeavors to leverage and better understand this expanding universe of data, to

better manage their business, but many struggle to do so. One major reason for this is that they lack a solid

strategic and business outcome focused framework for managing their data and analytics plans. The

companies who are successfully able to leverage this data are able to better understand how customers

make purchase decisions, to intervene in the most relevant ways to impact those decisions, and then to

measure these results to continue to drive competitive advantage.

In this whitepaper, we will discuss technology’s impact on sales and marketing analytics and business

intelligence by examining the difference between analytics today vs. the future, the business user implications

of these technological changes, and recommended actions for executives to harness these exciting

opportunities.

SALES AND MARKETING: TODAY VS. THE FUTURE

One of the biggest changes we envision impacting the sales and marketing analytics space in the coming

months and years is technology. We see the growing power of the cloud, coupled with the steadily increasing

volume and accessibility of data as a key turning point in the evolution of business analytics.

The vision sales and marketing professionals have of analytics has not really changed in that the goal is to

use data and reporting and modeling to make better business decisions more in tune with the continually

evolving needs of their customers. That said, the reality of business analytics and reporting has frequently

fallen short of this goal for a variety of reasons, a primary one being technological limitations in our view.

That is all changing now with these emerging technologies that allow for more flexibility, speed to market, and

scalability than ever before. Three areas companies can expect to see the biggest changes as a result of

these technological advancements include time horizon, business intelligence and infrastructure footprint.

1. TIME HORIZON

• TODAY: Output remains heavily historically focused.

• FUTURE: Output is shifting to become real-time and future-focused.

2. BUSINESS INTELLIGENCE

• TODAY: The definition of “business intelligence” has devolved into series of slice and dice reports.

• FUTURE: “Business Intelligence” will begin to encompass its original meaning and intent – true

decision support

3. INFRASTRUCTURE FOOTPRINT

• TODAY: Analytics have a heavy infrastructure footprint and high IT involvement.

• FUTURE: Analytics will have light infrastructure, be user-driven as opposed to IT managed, and be

based in cloud distributed models.


TECHNOLOGY’S IMPACT ON SALES AND MARKETING

The way that we think about Analytics technology is through a “stack” which connects data all the way

through reporting and business intelligence. Our perspectives on how technology is impacting each

component of this “stack” are as follows (see also, Figure B):

DATA - Variety of in-house and external sources (Omniture, Marketo, Microsoft

Dynamics)

When considering the impact of technology on data, the first thing a business user should be thinking about is

the emergence of “Big Data”.

Fundamentally, “Big Data” means large datasets that are difficult to store, manage, and work with. In order to

best understand the impact for business users, it is helpful to take a step back and look at the differences

between “traditional” and “Big Data”.

With “traditional” data, the interactions with customers are episodic or periodic (i.e., once a month, once a

year). While traditional data answers the question “what happened in the past”, traditional data can’t answer

how customers are using a product or service in the interim – (i.e., how are they using, thinking and talking

about it?).

With the emergence of Big Data, the amount of information and insight available about a customer greatly

increases, making it possible for Best-in-Class companies to monitor these activities and start to connect with

customers in real-time.

FIGURE A. - TRADITIONAL VS.

EMERGING DATA SOURCES


What Does This Mean for Business Users?

The exponential increase in data is both a huge opportunity and a potential impediment. In analytics, one of

the most common pitfalls professionals make is gathering data simply because it’s available. The reality,

however, is that not all data needs to be collected, stored and aggregated. Best-in-class firms are able to turn

Big Data into an opportunity by adhering to a systematic and consistent process. Figure C shows an outline of

critical questions business users must ask when determining which data to collect and analyze.

FIGURE C. - DETERMINING DATA

TO COLLECT AND ANALYZE

FIGURE B. - DATA STACK


DATA MANAGEMENT - Design, build and manage databases (Oracle, MySQL,

Greenplum)

The next level of the “stack” is data management. Here, the largest impact technology has had is a significant

increase in processing with corresponding decreased costs. It is important for business owners to understand

the current state of data management which we view as a combination of both expanded and enhanced

relational systems and a migration to existing and emerging data warehousing systems. Figure D gives an

overview of the benefits and pitfalls of using traditional relational systems and/or data warehousing systems.


Data management can be a huge investment (in some cases millions of dollars). Before taking the plunge and

investing in data management software, business users must define the outcomes they need the system to

accomplish:

A stable, flexible data environment. The system needs to be able to accommodate the data identified.

Acceptable amount of time for generating results. Time is a huge driver of system functionality and cost, but the faster a business wants the system to render data, the more expensive it will be. Business users must be deliberate and thoughtful about the amount of time needed vs. wanted when making their decision.

Seamlessly generated output for one of two purposes: - Datasets for advanced analytics (statistics, predictive modeling, etc.) - Datasets for basic analytics and reporting

ADVANCED ANALYTICS - Descriptive stats, causal & predictive models (SAS, SPSS)

With the emergence of new technologies, the utility of Advanced Analytics tools has greatly increased. While

the core elements of these tools are not changing drastically, the world of Advanced Analytics continues to

evolve and expand.

As Data Management platforms continue to evolve and improve, the amount of information and insight that

can be derived via queries and basic tools like Excel is growing. Proprietary platforms such as SAS and

SPSS continue to evolve their offerings while open source platforms such as R continue to grow.

FIGURE D. – BENEFITS & PITTFALLS

OF TRADITIONAL DATA SYSTEMS


There is also a significant focus on embedding next best action capabilities into CRM tools. A

convergence between tools and analytics in the CRM world is helping users not just learn additional

information about customers, but incorporate real-time analytics to help sales reps decide what to

do next with each customer.


Advanced Analytics tools are very powerful; however they are also over-purchased and underused

assets. Just because your organization owns a suite of SAS licenses does not mean that effective

analytics or anything remotely close to them are being conducted. Figure E outlines critical

questions for avoiding a breakdown and developing a clear process to establish Advanced

Analytics needs.

REPORTING AND BUSINESS INTELLIGENCE - Reporting & BI solutions (Dundas,

Cognos, QlikView)

One of the greatest sources of frustration that analytics and business professionals alike encounter

is dissatisfaction with Reporting and BI tools. However, technology is quickly evolving in this space

bringing enhanced versions of traditional enterprise systems as well as new, emerging technologies

and approaches. Both Traditional Enterprise and Emerging In-Memory Reporting Systems have

positive and negative aspects, outlined in Figure F.


In many respects, none of the other analytics elements matters if the BI and reporting engine falls

apart, as it frequently does. Data and insight are only as good as an analytics team’s ability to

deliver it and as a result the business users’ ability to act on it. Figure G outlines several strategies

for building a successful reporting and BI function.

FIGURE E. – AVOIDING A

BREAKDOWN


RECOMMENDED ACTIONS

The development of an effective analytics strategy is a significant obstacle to building an effective

foundation for supporting critical data-driven business decisions and as highlighted here rapidly

evolving technology provides but a significant opportunity but also a challenge for firms lacking a

coherent, integrated analytics strategy. Following the steps below or something closely

approximating them, firms can begin to develop a strategy today that will give their organization the

ability to make timely, cost-effective business decisions built on fully leveraging and taking ad-

vantage of the exciting technological innovations occurring in this space:

Restate and clarify business objectives as they relate to sales/marketing and analytics; how is the business acquiring, growing, or retaining customers?

FIGURE F. - BENEFITS & PITFALS OF

TRADITIONAL ENTERPRISE AND EMERGING

IN-MEMORY REPORTING SYSTEMS

FIGURE G. - STRATEGIES FOR BUILDING A SUCCESSFUL REPORTING

AND BI FUNCTION


ABOUT DEMANDANALYTICSTM

Our DemandAnalyticsTM methodology integrates customer, marketing and channel data to drive customer performance and

profitability and optimize sales and marketing investment. By integrating our suite of solutions with best in class technologies, we

capture and leverage data from a wide range of customer interaction touch points – including online digital footprints, campaign

responses, and point-of-sale purchases. To learn more about how DemandAnalytics™ can help you acquire, penetrate and retain

new customers, and for more examples of our analytics work with clients, visit our website, www. market-bridge.com, or contact us at

[email protected].

ABOUT MARKETBRIDGE

MarketBridge is a leading global provider of technology-enabled sales and marketing methodologies and solutions for Fortune 1000

and emerging growth companies. The firm offers the following methodologies: MarketBluePrint, RevenueEngines, and

DemandAnalytics. We work closely with CEOs and their senior Marketing and Sales leaders to solve their toughest business

challenges and create scalable, sustainable competitive advantage. Visit our website, Market-Bridge.com.

Headquartered in Bethesda, MD with offices in San Francisco, MarketBridge works with partners and associates across the globe to

build and execute our clients’ initiatives.

www.market-bridge.com • 1-888-GO-TO-MKT

Develop an 18-month analytics roadmap; understand the capabilities needed in place and leverage emerging technology to get there

Establish a clear data strategy; determine why new data sources are critical for the business (i.e., why is social media critical to the business and how will it drive ROI?).

View analytics through an ROI prism; while there are many exciting technologies coming onto the market, it is important to clearly define how they will help the company make money.

Leverage existing tools; understand that emerging technologies do not mean existing tools must be tossed. Determine how existing investments can be adapted to emerging and changing needs.