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When, how, why prototyping? A practical framework for service development

Stefania Passera* Aalto University School of Science, Department of Industrial Engineering and Management E-mail: stefania.passera@aalto.fi

Henna Kärkkäinen Aalto University School of Science, Department of Industrial Engineering and Management E-mail: henna.karkkainen@aalto.fi

Reetta Maila Aalto University School of Science, Department of Industrial Engineering and Management E-mail: reetta.maila@aalto.fi * Corresponding author

Abstract: Service prototyping is still an emergent field and although more frameworks are appearing in literature, they are not offering yet clear indications on how, when and why to prototype. In our research and teaching activity, we noticed that these are not banal questions, especially for teams that are trying to create new, innovative services. This paper proposes a Service Prototyping Practical Framework (SPPF), which makes sense of previous theoretical contributions and helps manage the prototyping process in practice. The Service Prototyping Practical Framework builds on Blomkvist’s (2011) prototyping framework and develops it further towards practice on the basis of empirical cases. The framework is a practical tool that can be used for planning and evaluating service prototypes, but also for describing them in a formalized way.

Keywords: service prototyping; service development process; service innovation; prototyping framework; prototype implementation; prototype evaluation; prototype fidelity and resolution

1 Introduction

The practice of iterative, rough prototyping has been seen as directly related to innovation in product development. A deeper understanding on how to introduce such prototyping practices into service development could help envision and manage innovative services, since prototyping allows for:

• Early user involvement (Brown 2008); insights about what creates value for the user/customer

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• Early validation of solutions and lower project risks (Drews 2009),

• “Thinking by doing” (Saloner 2011), which enhances ideation, problem-solving (Thomke & Nimgade 2000) and knowledge sharing between stakeholders (Fraser 2009)

• A stronger belief in the creative ability of the development team, and a sense of progressing forward (Gerber & Carroll 2012)

These are important ingredients when aiming for strategic innovations, rather than for incremental enhancement (Tuulenmäki & Välikangas 2011). When something is truly novel we cannot plan it into existence, but we need experimentation to learn through trial-and-error (Schrage 1999; Ries 2011). Too much remains unknown about how customers will react to the new service, interact with it and accept it: capturing such knowledge requires structured approaches. Prototyping offers an empirical, user-centred, rapid solution, but it is a practice still not easily understood and applied in the service domain (Parker 2009).

Service design is complex, mainly because of the intangibility of the design scope and the overwhelming amount of elements to be coherently “orchestrated” (Shostack 1984). Prototyping services is even trickier than prototyping products: we can design “scaffolds for experiencing”, but not, ultimately, experiences and interactions (Sanders, 2002). Although frameworks for service prototyping are appearing in literature, they are not offering yet clear indications on how, when and why to prototype. In our research and teaching activity, we noticed that these are not banal questions, especially for teams trying to create new, innovative services.

Prototypes are visual manifestations of ideas (Lim et al. 2008), and visualizations help to “make the ideas more tangible, complexity more readable and alternatives shareable” (Diana et al 2009). But how to provide practical indications to help reduce the experimentation hurdle? How to promote the necessary “hands-on” attitude? A basic “service prototyping literacy” should belong to the professional baggage of all service developers, not only of trained designers.

This paper aims at linking theory and practice through a pragmatic approach to service prototyping. The Service Prototyping Practical Framework (SPPF) is a tool for service development teams, but also a way for academics and practitioners to build common mindset and terminology.

2 Service prototyping: current approaches

Service prototyping is still an emergent field of study (Blomkvist & Holmlid 2009; Holmlid & Evenson 2007). There are various tools and techniques to deal with the complex nature of services, and their main functions are research and conceptual exploration (Clatworthy 2011; Segelström & Holmlid 2009), planning and innovating the service logic (Bitner et al. 2008), testing and validating service concepts (Blomkvist & Holmlid 2009), facilitating communication among stakeholders (Buchenau & Fulton Suri 2000; Houde & Hill 1997), and keeping empathy towards the users (Iacucci et al. 2000; Mattelmäki 2005).

However, the distinctions between different service development techniques are blurred. For instance, service blueprinting can be considered a prototyping technique (Tassi, 2009), a way to visualize the results of research and/or ideation (Segelström,

2009), or a plan for service implementation (Moritz, 2005). Since the concept of prototype/prototyping is used in different contexts and disciplines, it is important to understand what a service prototype is and what it does.

Blomkvist (2011) defines prototypes as representations or manifestations of ideas and the assumptions behind them. Prototypes are artefacts that designers create and use when prototyping, while prototyping is an activity and a mindset. Their role is to test the idea against specific criteria to see if its hypothesis holds true. It can be said that prototypes are basically anything that can communicate, prove or reveal a service concept.

An encompassing definition of service prototype/prototyping fits well with the holistic approach of service design. Practitioners emphasize how services should be designed considering the whole service environment (Stickdorn & Schneider 2010). Prototyping helps deal with complexity, for instance by showing how different touchpoints fit together and how they are created also through tangible elements (Blomkvist 2011). Grönroos (2008) argues that users ultimately create the service value-in-use, and this is an indicator of how much user experience matters. Techniques like experience prototyping (Buchenau & Fulton Suri 2000), role-playing (Sato & Salvador 1999) and bodystorming (Oulasvirta et al. 2003) are utilized to investigate the experiential aspects of service encounters.

All these prototyping techniques can be categorized in different manners. Fidelity (Rudd et al. 1996) or to the project’s stage of development (Bryan-Kinns & Hamilton 2002) are the recurrent criteria, but both are problematic. Fidelity is misleading because service prototypes can be both refined and rough in different aspects (Wong 1992). A process view is also dissatisfactory, because it anchors specific techniques to specific stages, while the same technique might be used in different stages for different purposes (cfr. Tassi 2009). A third categorization focuses on prototype purpose (Houde & Hill 1997). Its merit stands in underlining that prototypes should produce answers to their designer’s questions, and that how-to-prototype depends on what needs to be discovered.

Blomkvist (2011) collected all the crucial dimensions of service prototyping into a conceptual framework (Figure 1), which, to our knowledge, is the most complete and detailed in the field, Consequently, it the choice to start developing a Service Prototyping Practical Framework (SPPF) (Figure 2). Blomkvist’s framework was utilized to analyze several service prototyping cases (Table 1). The Authors identified common “prototyping dilemmas” faced by service innovation teams, and created guidelines to assist practitioners in efficient and effective experimentation.

Figure 1 Prototyping framework (adapted from Blomkvist 2011)

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Table 1 Selected service prototyping cases

Code Case Description Year Prototyped concepts Method

C1   Senior Taxi   Developing a car sharing service to help the movements of the seniors in the neighbourhood   2009   2   Action

research  

C2   Language Café  

Developing a service where seniors and expats create social value to each other  

2009-2010   2   Action

research  

C3   Health Minibar  

Developing a delivery service of healthy snacks for seniors, based on a minibar/pay-per-use logic  

2009-2010   1   Action

research  

C4   Call Your Grandma  

Developing a guerrilla campaign to sensitize people to the issue of seniors' loneliness  

2009-2010   1   Action

research  

C5   Wellbeing TV  

Developing interactive programs and services for seniors on a TV-based platform  

2010   4   Action research  

C6   Climate Info Center  

Designing the service concept of a center that provides sustainability advice to citizens   2010   1   Action

research  

C7   Immaterial Shop  

Developing a concept store that sells immaterial gifts   2011   1   Action

research  

C8   Nightclub   Developing service concepts to innovate the nightclub industry   2011   4   Action

research  

C9   Happier Everyday  

Designing novel services based on the needs of a lead-user group of intellectually disabled people   2011   9   Action

research  

C10   Best Park in the World  

Developing new services and activities to enhance the experience of a city park   2011   5   Observation  

C11   Bicycle Helmet  

Developing concepts to increase bicycle helmet usage among teenagers   2011   5   Observation  

C12   Art On-The-Go  

Developing a service providing art and creativity workshops in organizations   2011   2   Observation  

C13   Home Gnome  

Developing a service where plushie characters monitor your home and send mobile notifications   2011   1   Observation  

C14 Teleport Developing a service for creating virtual spaces to support different interactions (e.g teaching ). 2011 2 Observation

C15   Good Community  

Developing concepts to support a stronger and positive sense of community in neighbourhoods   2012   4   Observation  

C16   Lifestyle packaging  

Developing service concepts based on (but not limited to) innovative uses of packaging   2012   2   Observation  

C17   Hairdresser   Developing service concepts to innovate the hairdressing business   2012   4   Observation  

C18   Shopper App  

Developing mobile app concepts that can enrich the relationship between customers and retailers   2012   3   Observation  

C19   Year-round Lapland  

Developing new offerings to boost the tourism industry year-round in strongly seasonal areas   2012   6   Observation  

C20   Recycling Center  

Developing new offerings to promote sustainable and responsible consumerism  

2012   4   Observation  

C21   Machine Vision  

Developing innovative consumer service concepts based on machine vision technology 2012   3   Observation  

3 Data

The SPPF is built on data from 21 prototyping cases (Table 1), in which the Authors participated either as external observers or as action researchers involved in prototyping. The observed teams consisted of students or entrepreneurs. Data was gathered through observation and interviews, while action research cases were documented through learning diaries and weekly discussions. The cases are not presented in detail, but some of them provide examples of the framework in practice.

All teams aimed to develop novel service concepts for a partner organization (or for their own start-up), rather than incrementally improve existing services. Prototyping was utilized as a way to explore and validate ideas. The scope of all cases was limited to the fuzzy front end of the innovation process. The goal was to provide inspiration and user insight for further decision-making, not to bring new services to market. However, few concepts proved so promising that were scaled up and established as real services.

4 The Service Prototyping Practical Framework

Figure 2 The Service Prototyping Practical Framework

Well-designed, small-scale prototypes are an efficient way to learn and test specific

hypotheses of new concepts (Ries 2011; Brown 2008), but there is not a single way to “do it right”. All observed teams had a different process, and had to compromise between the desired learning goal and the available resources (time, costs, persons…). This is why the proposed framework helps generate ad-hoc prototyping solutions, rather than provide ready-made ones. The SPPF is envisioned as an aid for thinking and asking fundamental questions when prototyping. It builds on Blomkvist’s (2011) prototyping dimensions (Figure 2), which were utilized to analyze our rich qualitative data and identify the logic of service prototyping in practice. By observing specific decisions, the reasons behind

What is the service hypothesis I am testing?What do I want to learn?

Early stages [General purposes = exploration & evaluation]Later stages [General purposes = evaluation & communication]

AUTHOR AUDIENCE

TECHNIQUE VALIDITY

FIDELITY /RESOLUTION

PURPOSE

What is the the simplest way available to implement the best possible experiment?

Which technique? How to plan it?

What data can I expect?

Prototype

Learn

What needs to be verisimilar for the prototype to work? What needs to be

functional, and to what degree?”

evaluation criteriaim

plem

enta

tion

crite

ria

Was the prototype plausible for my audience? Was their

feedback reliable?

How generalizable are the results of the experiment? What exactly did I learn?

POSITIONIN PROCESS

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them and by evaluating their success, it was possible to draft guidelines to help manage the service prototyping process.

The framework illustrates the order in which each dimension influences the next one. The position in the process affects the reasons for prototyping, exploration, evaluation and communication being the most important ones (Voss & Zomerdijk 2007). In practice, it is necessary to define a more specific purpose and a prototyping hypothesis. After that, the prototype author (individual or team) needs to implement a prototype that reflects the hypothesis, firstly by identifying the resources available for the experiment, and secondly by choosing a suitable prototyping technique: these decisions will affect the resolution of the service prototype. After prototyping, it is crucial to evaluate the results. Validity and audience need to be considered. Understanding the context and the nature of the prototype helps evaluate the reliability of the feedback, while understanding the audience is a key to interpret results. Since validity and audience influence the evaluation, they need to be kept in mind already when planning the prototype, so as to effectively match resources, techniques and resolution. This suggests a second way to read the framework, which considers the interdependencies among its dimensions (Figure 3).

Figure 3 Mutual influences among different dimensions of the SPPF

AUTHOR AUDIENCE

TECHNIQUE VALIDITY

AUTHOR

PURPOSE

TECHNIQUE

TECHNIQUE VALIDITY

FIDELITY/RESOLUTION

AUTHOR AUDIENCE

VALIDITY

PURPOSE

VALIDITY

FIDELITY/RESOLUTION

AUDIENCE

The purpose determines the resources the au-thor needs to prototype, and together they influ-ence which techniques to select. However, resources’ limitations might force to rethink what is possible to test. In other cases, if a certain purpose can be obtained only through a certain technique, the author will have to procure the needed resources even if not easily available.

The resources available will determine how well the experiment can be performed. However, depending on the pur-pose, certain results will be useful and reliable only if the prototype is implemented in a spe-cific way, i.e. if certain resources or a certain user group are utilized.

Available resources and the chosen technique will determine how reliable and insightful the results are. The reliability of the results is also influenced by the audience, who can get better engaged or provide better feedback depending on what technique is used.

Every technique produces a determined type of results. How-ever, it might happen that the right tech-nique is implemented in the wrong way, i.e. including too many or too few details, and this affects the validity of the results.

The fidelity/resolution should make the pro-totype plausible for the audience. Knowingwho/how is the audi-ence can suggest the proper fidelity/resolution to adopt in order to obtain reliable feedback. Moreover,depending on the audi-ence, some techniques can stimulate betterengagement and feedback than other techniques.

It is important to understand how each dimension influences the others, because compromises are needed in order to achieve the “optimal minimum setup” of a prototype. Prioritizing simple actions over costly/time-taking preparations is an approach to manage reiterative experimentation (Thomke 1998; Brown 2008; Maurya 2010). The “optimal minimum setup” can represent the balance between how much time, effort and money is invested in the prototype versus the usefulness of the expected feedback and insights.

4.1 Position in process and purpose

The position in process affects the purpose of prototyping, prioritizing exploration and evaluation at early stages, and communication with the stakeholders at later stages (Buchenau & Fulton Suri 2000; Voss & Zomerdijk 2007).

However, in order to work efficiently and effectively, we observed that prototyping teams need to be able to formulate their purpose on a much more fine-grained level. According to Schneider (1996), the developers need to be aware of “what the prototype is supposed to tell you”, in order to define what the experiment is supposed to demonstrate. Houde and Hill (1997) also highlight the importance of knowing “what prototypes prototype”.

In the SPPF, the guiding questions to define this prototyping dimension are summarized as “What is the service hypothesis I am testing? What do I want to learn?”

Example C2: A language café where seniors teach Finnish language to expats The team initially tested the concept in a real café and observed if the mix of seniors and expats would work together. After this first, successful validation, a new issue had to be addressed: many seniors would not join the language café in the winter, because of the fear of slipping on ice and snow. A new hypothesis of service setup was tested: a librarian facilitated the language café at a city library, while seniors could participate to the session through Skype. This test proved that the experience was still valuable for both groups, despite the remote presence.

4.2 Author In the SPPF, the role of the author is to manage and take responsibility of the prototyping to progress: in practice, it means to maintain efficiency and effectiveness (Thomke 1998) by controlling and making decisions about different alternatives available. The author dimension focuses on identifying what resources and skills the author can harness for prototype implementation. The guiding questions for this dimension are “What is the simplest available way to implement the best possible experiment? To what resources do we have access?”

Research suggests that it is often difficult for developers to determine how to prototype (Schneider 1996) and what are the existing limitations. This difficulty was also consistently observed in our empirical cases. Defining the prototype setup means to orchestrate the basic, core dimensions needed to build a service hypothesis. Paraphrasing Bitner (1992), the defining elements of servicescapes are the environment, the “actors” (staff and users) and the physical dimension of the service – e.g. spatial layout and different artifacts. This corresponds with what we observed, and a set of heuristics was developed in order to guide the teams in assessing the available resources and how to use them (Table 2).

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Controlling core resources is crucial, because they influence which prototyping techniques can be chosen, the resolution of the prototype, how it is possible to engage the test subjects and what aspects of the prototype can be validated. Table 2 Heuristics to assess the prototyping resources available to the prototype author

Example C17: Innovating the hairdressing business The team had difficulties in prototyping and evaluating their ideas, because they could not use a real salon and real staff. When they managed to involve a professional hairdresser in prototyping “in lab”, they finally had access to valuable feedback on their solutions. Many ideas were improved and co-redesigned on the spot, leading to more innovative and viable concepts. The team defined the experience of working in the service prototyping lab and with real staff as “eye-opening and incredibly beneficial”.

4.3 Technique

The resources available to the author generally determine which techniques can be utilized. While developing teams can rely on several categorized technique repositories (e.g. Moritz 2005; Tassi 2009; Segelström & Holmlid 2009; Stickdorn & Schneider 2010), it is more important to understand what a technique does and what type of results can provide. From a practical perspective, the team should also be aware of the different amount and type of preparations, props, and pre-requisite knowledge that each technique – and case – requires. Moreover, it is fundamental to consider what sorts of experiences each technique enables, and if the chosen testers (audience) can understand and relate to them.

Consequently, the guiding questions for this framework dimension are “Which technique is suitable? How to plan/prepare it? What data can I expect?”

Example C14: Developing a service for creating virtual environments to support different interactions The team of entrepreneurs wanted to investigate possible scenarios of use for their new offering, but the technological solution was not implemented yet. With the help of scenario scripts, bodystorming (and by simply creating the desired environment with recorder sounds and a projector) they were able to compare the appeal of different applications, for example a language course with a virtual immersion in a foreign city.

4.4 Fidelity/Resolution

Since fidelity is a problematic approach to define prototypes (Lim et al. 2008; McCurdy et al. 2006), we suggest instead the concept of resolution when dealing with the representational dimension of service prototypes. Houde & Hill (1997) defined resolution as the “amount of details” and fidelity as the “closeness to the eventual design” of a prototype. We argue that fidelity should be used for single aspects of a prototype, while resolution (as the sum of the fidelity of distinct aspects) can represent the general level of verisimilitude of the service prototype (Figure 4). The resolution graph can be used to control the quality of implementation of different service aspects. If a prototype fails, the graph allows to pinpoint which dimensions were possibly unsuitable for the audience and context. Research has shown how too high or too low prototype quality can prevent the audience to focus and generate useful feedback (Bryan-Kinns & Hamilton 2002; Houde & Hill 1997; Rudd et al. 1996). In some cases, it is possible to modify the fidelity of certain aspects to make the prototype fit for its audience, but when these changes cannot be done, a different technique should be considered instead. There is no consensus on prototypes’ optimal level of details so reiterative trial-and-error can be, once again, a beneficial practice.

Summarizing, the guiding questions for the fidelity/resolution dimension are “What needs to look and feel verisimilar for the prototype to succeed? What needs to be functional, and to what degree?”

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Figure 4 A comparison between the concepts of fidelity and validity. Fidelity can be

used for single aspects, while resolution for the whole service prototype

Example C9: Improving everyday services for inclusion and happier life The “slow cashier” concept was developed on the needs of a lead-user group of intellectually disabled people. Since a partner supermarket was found, it was possible to have a high-resolution prototype from the beginning. No dramatic changes to the shop setup were required: extra signage was cheaply printed, few borrowed armchairs were positioned along the queue and the personnel were trained about the right service attitude. The pilot was a success: it attracted different customers – so not only seniors or persons with a disability – and the staff preferred to work there. The slow cashier sold as much as the normal ones, and so it proved that it is possible to reconcile efficiency and a relaxed mood.

4.5 Validity

The ability to evaluate the results of prototyping is as important as the ability to implement it. Schneider (1997) warns about the risk of prototypes becoming “developers’ toys” if there is no serious attempt to capture insight. Validity is the core of the evaluation process, and requires honesty in considering if:

• The prototype correctly expressed its purpose and scope

• The prototype was “talking the right language” with the audience

• The developers elicited informative feedback

• The developers learnt something new and valuable

Common shortcomings include not knowing enough about the purpose of the prototype (Schneider 1997), or users focusing on irrelevant aspects of the prototype due to

excessive/insufficient verisimilitude (Bryan-Kinns & Hamilton 2002). Generalizations when employing “artificial” users or location should also be avoided, because it is beyond the scope of certain type of experimentation. A single prototype cannot provide knowledge on each of its aspects, so multiple and different prototypes are needed (Buchenau & Fulton Suri 2000). The guiding questions for the validity dimension are “How generalizable are the results of the experiment? What exactly did I learn from what I tested?”

Example C7: Developing a gift shop that sells immaterial gifts The team had the opportunity of running a pilot pop-up store in the premises of a partner company. However, in order to prevent disadvantages to the partner and its customers, the service logic of the immaterial gift shop had to be first rehearsed in lab. Many different setups were tried out and students and researchers were employed as test customers. After having identified the best alternative, reiterative experiments were conducted in order to fine-tune the service “look-and-feel” and blueprint. When pilot went “on-site”, it allowed collect feedback and test customer acceptance. The service was not perfect, but already plausible for its audience.

4.6 Audience

As already mentioned, the audience influences the validity of the prototyping results. For testers to express their point of view, the resolution should be at par with their ability to interpret the role and purpose of the prototype (Buxton 2007; Blomkvist 2011). This factor could be called plausibility of the prototype, and it indicates the nature of the encounter between person and prototype. While resolution is an aspect of the prototype, plausibility is experiential (Figure 5).

Figure 5 Plausibility is an experiential quality arising from the user encounter with the prototype

A plausible prototype encourages testers to make believe and grasp the meaning of

the service hypothesis: this should elicit more reliable feedback. In order to build a plausible prototype, developers should consider their audience from the very start, and think how to best represent the service hypothesis (Blomkvist 2011). The main questions in relation to the audience are “Was the prototype plausible for my audience? Was their feedback reliable?”

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Example C10: Developing services to make a city park “the best park in the world” The team had to experiment “on-site” from the very beginning, despite their ideas were preliminary, because a park cannot be simulated meaningfully otherwise. The services offered and the props used were functional, but still rough. However, the prototype resolution was plausible for the audience, because of the mood (relaxed, easy-going) and the context (free time). Many were open in trying out new activities and providing feedback.

5 Discussion and conclusions

This paper proposes a practical service prototyping framework that builds on previous theoretical contributions and helps manage the prototyping process. The framework can be beneficial in planning, evaluating and formally describing service prototypes, because it helps:

• Understand the core dimensions of service prototyping

• Manage the complex, abstract nature of services in development

• Make informed decisions on why and how to prototype services

• Communicate and explain the logic and the practices of service prototyping

• Create a common focus and terminology for researchers and practitioners to discuss

Additionally, our research introduces few concepts that are useful in the operationalization of service prototyping theories:

• The concept of resolution expands and integrates the concept of fidelity, which proved insufficient in describing the representational dimension of service prototypes. Different elements have different levels of finishedness or functionality, which cannot be reconciled under the mono-dimensional concept of fidelity.

• The “optimum minimum setup” concept helps debunk the belief that rough prototypes are for early stages and refined ones are for later stages. If the resources are available, it is possible to have high verisimilitude already in early prototypes. However, it is true that prototypes are progressively improving during the development process, because the teams aim at gaining more fine-tuned and reliable insights.

• The concept of plausibility highlights the “theatrical” nature of prototyping and the importance of engaging the testers in ways they can understand and contextualize. As in theatre, the audience has to suspend its disbelief to make the most out of the experience.

• Service prototyping labs are spaces that can are useful when the utilization of real service environment is not allowed or too risky. The labs and their props, as already noticed for other visual and tangible service tools (Clatworthy 2011), help transform abstract concepts into something concrete, modifiable and criticisable by supporting embodied communication and cognition. Motor processing can contribute to mental manipulation of objects (Sirigu & Durhamel 2001), and this suggests that prototyping makes possible to ideate and evaluate servicescapes.

However, the correct application of the framework does not necessarily imply successful prototyping outcomes: a mix of scientific rigor, hands-on creativity and understanding of human factors are needed. There is no single recipe for prototyping, and the skills and experience of prototype authors affect how efficiently preparations are done, and how effectively insights are captured.

Another open question is when to prototype. Our research could not find a precise answer. However, if the goal of prototyping is to inject knowledge in the development process, then the answer is “prototype whenever you are in doubt, and as early as possible”.

Although all cases are limited to the fuzzy front end of the innovation process, we see potential in utilizing the framework also in later stages. The SPPF strongly focuses on the purpose and implementation of each prototype, and we do not expect the importance of these factors to diminish at the back end of innovation. For the same reason the framework could be potentially suitable also for product development. Further research might shed light on these two directions.

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