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

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: [email protected]
Henna Kärkkäinen
Aalto University School of Science, Department of Industrial
Engineering and Management
E-mail: [email protected]
Reetta Maila
Aalto University School of Science, Department of Industrial
Engineering and Management
E-mail: [email protected]
* 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
1
•
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,
2
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 valuein-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)
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 20092010 2 Action
research C3 Health
Minibar Developing a delivery service of healthy snacks for
seniors, based on a minibar/pay-per-use logic 20092010 1 Action
research C4 Call Your
Grandma Developing a guerrilla campaign to sensitize
people to the issue of seniors' loneliness 20092010 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 OnThe-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 4
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
FIDELITY /
RESOLUTION
Which technique?
How to plan it?
What data can I expect?
How generalizable are the
results of the experiment?
What exactly did I learn?
VALIDITY
ion cr
AUTHOR
PURPOSE
POSITION
IN PROCESS
What is the the simplest way Was the prototype plausible
available to implement the for my audience? Was their
best possible experiment?
feedback reliable?
AUDIENCE
What is the service hypothesis I am testing?
What do I want to learn?
iteria
implem
TECHNIQUE
Prototype
t
evalua
entatio
n crite
ria
What needs to be verisimilar for the
prototype to work? What needs to be
functional, and to what degree?”
Learn
Early stages [General purposes = exploration & evaluation]
Later stages [General purposes = evaluation & communication]
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
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).
TECHNIQUE
VALIDITY
TECHNIQUE
AUTHOR
AUTHOR
The purpose determines
the resources the author needs to prototype,
and together they influence 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.
FIDELITY/
RESOLUTION
FIDELITY/
RESOLUTION
AUDIENCE
VALIDITY
AUTHOR
PURPOSE
VALIDITY
AUDIENCE
TECHNIQUE
VALIDITY
PURPOSE
The resources available
will determine how well
the experiment can be
performed. However,
depending on the purpose, certain results will
be useful and reliable
only if the prototype is
implemented in a specific way, i.e. if certain
resources or a certain
user group are utilized.
AUDIENCE
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. However, it might happen
that the right technique 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 prototype plausible for the
audience. Knowing
who/how is the audience can suggest the
proper fidelity/
resolution to adopt in
order to obtain reliable
feedback. Moreover,
depending on the audience, some techniques
can stimulate better
engagement and
feedback than other
techniques.
Figure 3 Mutual influences among different dimensions of the SPPF
6
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).
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”.
8
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?”
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
10
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?”
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.
12
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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