Prototyping Canvas: Design Tool for Planning Purposeful Prototypes

Abstract

While prototypes are critical to the creation of successful products and innovative solutions, building a prototype is characterized by large sunk costs and a plethora of unknowns. The versatility and effectiveness of prototypes paired with the ambiguous nature of developing a prototype can lead to wasted resources. Recent studies support this claim, demonstrating that under certain circumstances, designers often prototype without a clear purpose, building prototypes as a function of the design process rather than as a function of the design. These findings motivated the creation of the Prototyping Canvas, a tool to aid designers in planning for purposeful prototypes by identifying critical assumptions and questions to guide development. Business and engineering design literature influenced the development of the canvas, which was first tested with a client project in the SUTD-MIT International Design Centre (IDC). The feedback and insights from the design team guided revisions to the canvas. The updated canvas was then validated with 55 professionals during a design project sprint. The purpose of this paper is to present the Prototyping Canvas as a valid and effective design tool.

Full text

Cite this article: Lauff, C., Menold, J., Wood, K.L. (2019) ‘Prototyping Canvas: Design Tool for Planning Purposeful
Prototypes’, in Proceedings of the 22nd International Conference on Engineering Design (ICED19), Delft, The
Netherlands, 5-8 August 2019. DOI:10.1017/dsi.2019.162
ICED19
INTERNATIONAL CONFERENCE ON ENGINEERING DESIGN, ICED19
5-8 AUGUST 2019, DELFT, THE NETHERLANDS
ICED19
PROTOTYPING CANVAS: DESIGN TOOL FOR PLANNING
PURPOSEFUL PROTOTYPES
Lauff, Carlye (1); Menold, Jessica (2); Wood, Kristin L. (1)
1: SUTD-MIT International Design Centre; 2: Pennsylvania State University
ABSTRACT
While prototypes are critical to the creation of successful products and innovative solutions, building a
prototype is characterized by large sunk costs and a plethora of unknowns. The versatility and
effectiveness of prototypes paired with the ambiguous nature of developing a prototype can lead to
wasted resources. Recent studies support this claim, demonstrating that under certain circumstances,
designers often prototype without a clear purpose, building prototypes as a function of the design process
rather than as a function of the design. These findings motivated the creation of the Prototyping Canvas,
a tool to aid designers in planning for purposeful prototypes by identifying critical assumptions and
questions to guide development. Business and engineering design literature influenced the development
of the canvas, which was first tested with a client project in the SUTD-MIT International Design Centre
(IDC). The feedback and insights from the design team guided revisions to the canvas. The updated
canvas was then validated with 55 professionals during a design project sprint. The purpose of this paper
is to present the Prototyping Canvas as a valid and effective design tool.
Keywords: Design methods, Prototype, Design practice, New product development
Contact:
Lauff, Carlye Anne
SUTD-MIT
International Design Centre
Singapore
carlye_lauff@sutd.edu.sg
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1 INTRODUCTION
1.1 Importance of prototyping
Prototyping is an important design activity that can enhance communication (Buchenau and Suri, 2000;
Brandt, 2007), learning (Leifer and Steinert, 2011), and decision making (Kriesi et al., 2016) throughout
the entire design process (Ulrich and Eppinger, 2000; Otto and Wood, 2001; Lauff et al., 2018a). A
prototype refers to both physical and digital representations of a design, regardless of fidelity, that serves to
answer a question or test an assumption (Lauff, 2018; Menold et al., 2018). Prototypes can be classified as
a stage of the design process; they can also be described as a tool to further product development.
Prototypes are essential to all design process models, ranging from waterfall, V-model, to sprint-scrum.
Previous work has highlighted the ability of prototypes to improve students’ technical understanding of the
design space and help designers uncover “unknown unknowns,” as well as explore fundamental user
insights (Jensen et al., 2017; Tiong, et al., 2018). Andreasen and Hein (1987), for example, demonstrated
that building prototypes in the early stages of the design process can help students visualize problems and
highlight incorrect design assumptions. Additionally, prototypes have been shown to boost design
performance (Neeley et al., 2013; Dow et al., 2009), influence stakeholder buy in (Greenberg et al., 2013),
supplement designers’ mental models (Lin and Seepersad, 2007; Lemons et al., 2010), and enhance both
technical and social skills development (Lauff et al., 2018b). Observational and ethnographic work from
the fields of cognitive psychology and sociology further demonstrate the importance of prototypes in
organizations, through their ability to create shared tacit knowledge (Rhinow et al., 2012; Henderson,
1991), enhance stakeholder communication (Star, 2010), and improve design outcomes (Bucciarelli, 2002;
Schrage, 2000).
Prototypes clearly offer a myriad of benefits to both professional designers and students, yet multiple
studies point to students’ tendency to limit prototyping activities to later stage design during authentic
design challenges (Deineger et al., 2017). Research has also shown that engineering students often have a
narrow perception of prototypes, believing that prototypes are only meant to test functionality of a full-
scale final design (Lauff et al., 2017). Further, while studies underscore the abilities of professional
designers to leverage prototypes more effectively than student designers in many cases, professionals still
face uncertainty (Gerber and Carroll, 2012) and must balance competing demands due to budget and
schedule constraints (Moe et al., 2004). This work is motivated by the belief that prototypes are necessary
tools during the design process, and that both professional and student designers could benefit from
additional guidance in prototype development efforts.
1.2 The need for the prototyping Canvas
To increase the efficiency and effectiveness of prototype practice, researchers have proposed multiple
prototyping methods and strategies from the Prototype for X (PFX) framework (Menold et al., 2017) to a
strategic design prototyping methodology that includes seven prototyping techniques (Camburn et al.,
2015). Please refer to Menold’s dissertation for an extensive review of current prototyping strategies
(Menold, 2017), including these additional references (Camburn et al., 2017a; Christie et al., 2012; Hamon,
2017; Moe et al., 2004; Dunlap et al., 2014). Many of these strategies have been tested with student
designers and are helpful in guiding them through prototyping practices, while also teaching fundamental
principles about the importance of prototypes. While these methods and strategies are useful for designers
and are grounded in best practices and empirical studies, research from Menold et al. (2018) demonstrates
that students lacked a fundamental awareness of their own prototyping behaviors, even when prototyping
strategies or methods were introduced through educational modules. In other words, this study found that
while these methods and strategies were beneficial and lead to improved design outcomes, students may
not be aware of these methods, and may be less likely to implement these methods independently during
authentic design challenges (Menold et al., 2018). While previous research has been incredibly valuable
and has empirically validated the utility and effectiveness of prototyping methods and strategies, to date,
researchers have not explored how communication of these methodologies affects their adoption. We
hypothesize that that by building upon past work and improving the delivery modes of prototyping
methods, we can increase their use by practitioners and students. As such, the purpose of this work is to
propose a new prototyping planning tool drawing on the empirical evidence of previous literature, that can
be more readily implemented in design practice.
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There are several design tools that have been adopted by universities and corporations and are grounded in
empirical evidence and best practices from literature. Yilmaz, Seifert, and Daly, for example, developed the
77 design heuristic cards (Daly et al., 2012; Yilmez et al., 2016), which have been widely adopted as
simple, yet effective tool during concept generation. Gerber developed Mockups as a tool to teach
prototyping principles and mindsets, while engaging teams at the start of a project (Gerber, 2015). User
journey diagrams, empathy maps, and personas are commonly used tools during the discovery phase of a
project to gain empathy and understanding of the opportunity and users (IDEO, 2015; Camburn et al.,
2017b). The popularity of online platforms that share design tools and methods, like IDEO’s Design Kit
(designkit.org; IDEO, 2015) or Berkeley and MIT’s Design Exchange (thedesignexchange.org; Roshuni
et al., 2015), points to the utility and need for such design tools.
A common theme amongst these tools is their simplicity; each tool can be easily integrated into existing
design practices increasing the likelihood of their adoption by practitioners, educators, and students. We
argue that while many researchers have identified prototyping best practices, and have empirically
validated these practices with students, findings from research remain difficult to translate to practice due to
the lack of simple and effective design tools for prototyping. In this work, we propose the Prototyping
Canvas, a design tool that effectively guides designers through prototyping processes, facilitates a common
prototyping language amongst team members, and encourages intentional prototyping practice. The
following sections describe the development of the Prototyping Canvas tool, which includes testing its
usefulness during an industry project and then iterating on the tool and testing it again with 55 professionals
during multi-day design innovation project sprints.
2 PROTOTYPING CANVAS DEVELOPMENT
2.1 Inspiration from Business Model Canvas
The structure of the Prototyping Canvas was heavily influenced by the success of the Business Model
Canvas (BMC). The Business Model Canvas translates key business activities into a simple, yet effective
tool for companies to rapidly create and validate business models (Osterwalder and Pigneur, 2010). The
BMC is arguably the most recognizable and successful business design tool in use. Strategyzer reports that
in 2015 there were over 5 million downloads of the canvas (strategyzer.com). Research has found that
using the BMC leads to shared language amongst teams, better conversations on strategy, more ideas
shared, and a structured plan to implement concepts (Amarsy, 2015). The BMC has been adapted for other
situations, such as the Mission Model Canvas for mission-driven organizations (Blank, 2016) and the Lean
Canvas for start-ups (Maurya, 2010). Likewise, we have evolved the BMC for prototyping during product
development, thus creating the Prototyping Canvas.
2.2 Methodology for development
The main contribution of this paper is the development of the Prototyping Canvas planning tool, which is
grounded in existing evidence and translates validated prototyping methods to practice. The methodology
for developing the Prototyping Canvas is depicted in Figure 1. The process began with a literature review
surveying relevant prototyping literature in engineering design to build a strong evidence base. From these
articles, prototyping strategies, frameworks, and approaches were identified. Findings from research were
used as the building blocks for the content of version 1 (V1) of the Prototyping Canvas, which was then
tested with an industry project in the SUTD-MIT International Design Centre (IDC, idc.sutd.edu.sg). Four
professional designers, with industrial design and engineering backgrounds, used the Prototyping Canvas
during this project and provided continuous feedback to improve the tool. From their feedback, version 2
(V2) of the Prototyping Canvas was developed. Then, the revised V2 canvas was tested with 55
professionals during 2 and 3-day design sprints to validate the usefulness of the canvas. Future research
studies will be conducted to further validate the utility of the Prototyping Canvas. The remainder of this
section details the development and validation of the Prototyping Canvas.
Figure 1. Methodology for developing and revising the prototyping Canvas
Prototyping
Literature
Review
Distill Key
Aspects in
Prototyping
Canvas V1
Pilot Test V1
with an Industry
Project
Revise
Prototyping
Canvas tool into
V2
Validate V2
usefulness with
55 Professionals
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2.3 Synthesizing prototyping literature into Prototyping Canvas V1
The content of the Prototyping Canvas is grounded in empirical evidence from literature. Most notably, the
two dissertations from the co-authors influenced the development of the canvas as they were on the topics
of “prototyping in the wild” studying companies’ usage of prototypes throughout the entire design process
(Lauff, 2018), and developing a “prototyping for x” (PFX) framework to prototype creation (Menold,
2017). After surveying literature in the field of engineering design, three principles were identified as
critical to prototyping efforts: identifying the (1) purpose of the prototype, (2) resources to build the
prototype, and (3) strategy to execute building and testing the prototype. The literature related to each of
these principles is listed below, and exemplars of each principle are described in Table 1.
Purpose: All prototypes should answer a question, and thus have a purpose for the prototype
development. One must identify assumptions and questions that motivate the need to build and test a
prototype. This was based on the following literature: (Lauff, 2018; Lauff et al., 2018a; Houde and
Hill, 1997; Rhinow et al., 2012; Lande and Leifer, 2009; Deiniger et al., 2017; Ulrich and Eppinger,
2000; Otto and Wood, 2001). On the canvas, this motivates the creation of three categories:
“Stakeholders”, “Assumptions and Questions” and “Critical Assumption/Question.”
Resources: When building a prototype, one must take note of all the resources that are available and
sources for these resources, including the materials, time, and cost, to guide development of the
simplest prototype possible. This was based on the following literature: (Yang, 2005; Menold, 2017;
Menold et al., 2017; Thomke, 1998; Dow et al., 2009; Buchenau and Suri, 2000; Gerber and Carroll,
2009; Viswanathan and Linsey, 2011). On the canvas, this motivates the creation of one category:
“Resources Available.”
Strategy: To prototype effectively, one should formulate a strong plan and approach to building and
testing the prototype. Many strategies aim to minimize the resources used to maximize the desired
outcome. This was based on the following literature: (Menold 2017; Menold et al., 2017; Menold et
al., 2018; Camburn et al., 2015; Camburn et al., 2017a; Christie et al., 2012; Hamon, 2017; Moe et
al., 2004; Dunlap et al., 2014). On the canvas, this motivates the creation of three categories:
“Building Plan”, “Testing Plan”, and “Insights.”
Table 1. Exemplars of prototyping literature influence on Canvas’ three principles
Exemplar
Literature
Prototyping Insights
from Exemplar Literature
Key
Principle
Lauff, 2018; Lauff
et al., 2018a
Prototypes are tools for communication, learning, and decision making.
Prototypes are active objects that impact social situations. Prototypes need
to have an underlying purpose to test assumptions.
Purpose
Moe et al., 2004;
Camburn et al.,
2017a
Moe et al. proposed a method for prescribing a partitioning strategy that is
tailored to the specific characteristics of a project and is based upon the
three components of requirement flexibility: cost, schedule, and
performance. Camburn et al. identified six techniques for prototyping that
can minimize resources used during development: iteration, parallel
concepts, scaling, subsystem isolation, requirement relaxation, and virtual
prototypes.
Resources
Menold 2017;
Menold et al.,
2017; Menold
et al., 2018
The Prototype for X (PFX) framework is a strategy that breaks prototyping
efforts into three key phases: (1) Frame, (2) Build, and (3) test. Through
these phases, PFX helps designers develop a strategy to focus resources and
efforts on building prototypes that test core assumptions and lead to deeper
and richer learning about specific aspects of the design, at the time of
testing.
Strategy
The layout of the canvas was influenced by the layout of the Business Model Canvas (Osterwalder and
Pigneur, 2010). A user can fill out the canvas in any order, with the most structured approach starting with
the “Stakeholders” and “Assumptions & Questions”, moving left-to-right, until the “Insights” are
documented. The contents of the Prototyping Canvas are described next.
Stakeholders. Stakeholders refer to all people who have some stake in the project. This can include
end-users, consumers, clients, project managers, investors, manufacturers, or similar. The
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stakeholders need to be considered throughout the building and testing of their prototype, especially in
how they will be communicated with using the prototype.
Assumptions & Questions. This section is meant to identify all the assumptions about the problem or
design, along with all questions that are unanswered. There are three sub-categories related to
feasibility, desirability, and viability to encourage deeper thinking about the problem or solution.
Critical Assumption/Question. This section assesses the assumptions and questions listed prior to
determine which is the most critical to the success of the project. This validates why it is necessary to
prototype. The critical assumption/question should guide the prototype development.
Resources Available. Resources refers to materials, money, people, and time collectively. You must
first consider what resources are readily available, and the sources of those resources, followed by
what resources you must obtain, so that the simplest prototype can be built to test the critical
assumption/question.
Testing Plan. This section acts as a guide to create a simple, yet comprehensive testing plan for the
prototype. The guiding questions include: How will you test your assumption/question using a
prototype? How will you assess success or failure? What metrics are needed to assess the
performance? How will the stakeholders be impacted? Where, when, and with whom will you test?
Building Plan. This section is used for sketching the intended prototype and documenting a plan
before building and testing occurs. The previous answers to the resources block will guide material
selection, prototype medium, and construction method for the prototype. The goal is to determine the
simplest way to build and test the critical assumption/question, while keeping the relevant
stakeholders in mind.
Insights. The final section is meant for reflections, insights, and documenting any new assumptions
and questions that arose after testing the prototype. The intent is that prototypes are iterative, meaning
there are more assumptions, questions, and unknowns to test. This section may lead to the next
prototype iteration or development of an entirely new concept to prototype.
2.4 Testing of Prototyping Canvas V1
The first version of the Prototyping Canvas was tested with the SUTD-MIT International Design Centre
(IDC) team working on an industry-client project. The IDC team was tasked with designing a launch
mechanism for a large construction kick-off event. There were four professional designers on the project,
and they each used the Prototyping Canvas to guide their prototyping efforts. Before using the canvas, one
of the researchers gave a 20-minute presentation that covered the importance of prototyping in the design
process and walked the designers through the Prototyping Canvas. The team then spent 15-minutes filling
out the canvas in pairs, followed by a larger 30-minute discussion amongst the team. They then spent two
days developing and testing six different parallel prototypes based on the canvas’ before filling in the final
“Insights” section.
Figure 2. Completed Prototyping Canvas with call-outs (left) and scaled prototype (right)
One completed V1 Prototyping Canvas is shown in Figure 2, alongside images of the tested prototype
entitled “Sandcastle.” The designers started with the Sandcastle concept, and then used the canvas to
develop a prototyping plan. They documented eight assumptions and questions about the concept and listed
available resources in the IDC to build the prototype. The engineer chose to create a scaled down version of
the Sandcastle to test appeal to the client, the ease of movement of sand, the overall “wow” factor, and
structural integrity of the system. They built the scaled Sandcastle prototype in less than one day, using
materials and resources in-house. A digital model was created in CAD, acrylic was laser engraved and cut
built a scaled ver sion using
resour ces availa ble in-hous e to test
multipl e assumptio ns/question s
new q uestions ar ose from
testing that influe nced the
next ro und of de velopment
identif ied
eight r elated
assum ptions
and qu estions
to test
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to size, sand and LED lights were found in the IDC, and the entire structure was assembled. As shown on
the right of Figure 2, a locking mechanism releases sand from the upper reservoir when the acrylic tabs are
pulled, resulting in the “IBEW” logo in the lower reservoir being filled with sand. This movement of sand
also displays the engraved futuristic city-scape in the upper reservoir, which is illuminated by the LEDs.
New insights arose after testing the prototype, such as what materials would be used in the final version and
how the scaled-up design would support the weight of the sand. These insights were recorded on the canvas
and influenced further prototype development.
The IDC designers completed a survey after they finished using the Prototyping Canvas. This survey
included four 5-point-scale Likert-type questions (1=low, 5=high) and three open-ended questions. The
survey questions, in an abbreviated form, and the summarized results and feedback from the designers are
displayed in Table 2. In addition to the survey, the designers were provided with a blank Prototyping
Canvas and asked to “mark” the canvas with suggestions, noting elements that were confusing, useful, or
needed improvement. Based on feedback from the IDC designers, as shown in Table 2, the research team
summarized seven benefits of using the Prototyping Canvas: 1) provides utility, 2) saves resources, 3)
prepares a plan to build and test, 4) systematic and objective focused, 5) decreases mental burden, 6)
identifies unforeseen issues, and 7) aids in communication amongst the team. Based on the survey, with an
average survey score of 4 on a 5-point-Likert scale, the designers believed that the Prototyping Canvas
provides utility, saves resources, and prepares a plan to build and test. This validates, even in a small
sample size, that the Prototyping Canvas is an effective design tool for planning intentional prototypes.
Additionally, seven suggestions to improve the canvas were captured from the designers’ feedback: 1)
improve ability to inspire, 2) show more examples of how to use the canvas, 3) add more specifics, like
prototyping strategies and types of materials listed, 4) create a larger format, including more space to
sketch, 5) include a section for how to communicate the prototype to stakeholders, 6) further emphasize
‘simplest’ prototype possible, and 7) improve aesthetics of the canvas. This important feedback guided the
research team in revising the Prototyping Canvas tool into V2.
Table 2. Prototyping Canvas (PC) quantitative and qualitative survey results
Survey Qs
Quant. Results
Qualitative Feedback
How much utility does
PC provide?
Avg: 4/5
“Assumptions/questions and critical assumptions were very
helpful and the breakdown was great to guide through that.”
How well does PC aid
in saving resources?
Avg: 4/5
“Wanted to start ‘fiddling with things’ when it got time to identify
resources and build and test instead of writing them down…”
How prepared for
building/testing?
Avg: 4/5
“Emphasize building and testing the simplest prototype possible
even more throughout the canvas, as this is a key takeaway.”
How well does PC
inspire you?
Avg: 2.75/5
“The current version works well for distinct separate ideas, but it’s
cumbersome if I just want variants of the same idea.”
List 3 things you love
about PC.
Systematic
stated 3x
Systematic; Objective focused; ensuring “the point” of the prototype;
Decrease mental load, structure thoughts; Identify assumptions and
unforeseen issues; define metrics; determine materials/resources
List 3 surprising
aspects of PC.
Reduce mental
burden stated
3x
Simple yet effective; Reduce mental burden; Worked well
discussing in pairs; Thinking about human resources
List 3 ways to improve
PC.
Improve
aesthetics 3x
Scale to A3; examples; visual/intuitive interface; less text; more
room to sketch; communicate to stakeholders; hard to remember
strategies
2.5 Incorporating feedback into Prototyping Canvas V2
The feedback from the IDC team was used to guide revisions to the Prototyping Canvas. The revised
version is shown in Figure 3. To increase the size and spacing, the revised canvas is scaled from A4 to A3,
the text descriptions for the categories were streamlined, and descriptive icons were added to represent the
main goal of each box. Additionally, changes were made to the font, text size, and colour scheme to
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improve the overall aesthetics. The research team also launched a free online Design Innovation (DI)
learning module on the Prototyping Canvas (www.dimodules.com/prototypingcanvas). On this website,
there are guidelines for how to use the canvas, examples working through the canvas, and a free
downloadable canvas for anyone to use.
The content of the canvas changed to include two new categories: 1) “Communication Strategy for
Prototype”, which lists four types of communication that are often associated with prototyping: explain,
feedback, negotiate, and persuade, and 2) “Prototyping Approaches”, which lists thirteen prototyping
strategies, including: parallel prototyping, sequential prototyping, sub-system isolation, scaling,
requirements relaxation, remove unessential features, wizard-of-oz, repurpose existing products, experience
prototyping, paper prototyping, role playing, storyboarding, and mockups. The Communication Strategy
section was added so that teams would be more explicit about how the prototype would be used to explain
the concept, gather feedback, negotiate requirements, or persuade stakeholders (Lauff, 2018). The
Prototyping Approaches section was added to directly link validated prototyping strategies and reduce
cognitive load of participants. This section lists thirteen different prototyping strategies, which were
identified from the literature review on prototyping strategies in engineering design (Menold 2017; Menold
et al., 2017; Camburn et al., 2015; Camburn et al., 2017a; Christie et al., 2012; Hamon, 2017; Moe et al.,
2004; Dunlap et al., 2014). The content of both categories was discussed in the presentation given before
the earlier version of the Prototyping Canvas was tested, but they were not explicitly listed on the canvas in
the previous version. Overall, these changes to the Prototyping Canvas directly address the seven areas of
improvement from the designs’ feedback.
Figure 3. Revised version 2 of Prototyping Canvas, available for download at
www.dimodules.com/prototypingcanvas
2.6 Validating Prototyping Canvas V2
The revised Prototyping Canvas was tested with three groups of professionals over the course of three
different design innovation sprint workshops. The first group had 12 professionals over 3-days, the second
group had 17 professionals over 3-days, and the third group had 27 professionals over 2-days. In each
session, teams were divided by business unit and had between 3 and 7 team members. This totalled 55
engineering and design professionals that engaged in a multi-day design innovation sprint on their own
company challenge. The professionals were from two large organizations, groups one and two were from
the same engineering and defense company and group three was from a telecommunications company.
These professionals were trained in the Design Innovation process over 2 or 3 days, where they actively
engaged in all 4 stages of the process: Discover, Define, Develop, and Deliver on their own company
PROTOTYPIN G CANVAS
SKETCH & BU ILD PLA N
Build t he sim ple st pro tot ype p ossible (le ast cost, ti me, a nd ma teri als
requi red) t o te st crit ical assum ptio n an d/o r an swer critic al qu estio n.
STAKEHOLD ERS
COMM UNI CATION STRATEGY FOR P ROTOTYPE
Expla in
Feed bac k
Neg otia te
Persu ade
ASSUMP TIONS & Q UESTION S
About the user a nd thei r nee ds
About the tec hnica l fea sibilit y & fu nctio nal ity
About the cost a nd b usine ss
INSIGH TS GAINED FROM T ESTING
Wh at d id yo u lea rn? Di d you answ er t he cr itica l assum pt ion/ quest ion?
CRITICAL A SSUMPTI ON/ QUESTION
Assess abo ve list: w ha t is th e m ost crit ica l to t he suc cess of t he pr oject ?
TESTING PLA N
Wh at a re y ou te sting ?
Wh at m et rics ar e ne eded ? Qua lita tive /Qu ant ita tive assessm ent .
Time, P lace , Peop le, & Ma te rials re quir ed t o test
RESOURCES TO B UILD
Mat eria ls rea dily a va ilab le or n eede d
Time, M one y, & Peop le Allo tte d
PROBLE M/OP PORTUNI TY__________________________________________ CONC EPT/SOLUTI ON__________________________________________
PROTOT YPING AP PROACH ES
Para llel P roto typin g Seque ntia l Pro tot yping
Sub-syst em I solat ion Scalin g
Requir eme nts Re laxa tio n Rem ove Un essent ial Feat ures
Wiz ard- of-Oz Repu rpose Ex isting Prod ucts
Experie nce P roto typin g Pap er Pr otot yping
Role Pla ying Storyb oar ding
Mock ups Oth er:___________________________
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design challenges (Camburn et al., 2017b). These challenges ranged from designing for autonomous
vehicles to enhancing safety protocol in the field to planning for the future of 5G networks.
The Prototyping Canvas was introduced on the final day of each workshop at the start of the Deliver phase.
The researchers described the canvas and walked through an example with the group before they were
asked to use it for their own projects. The teams then used the Prototyping Canvas to plan for a prototype,
build and test their solution, and reflect on the experience. At the end of the workshop, the teams each
pitched their final prototyped solution. Finally, the 55 professionals completed a survey at the end of the
workshop, after they finished using the Prototyping Canvas. This survey included four 5-point-scale Likert-
type questions (1=high, 5=low) about using the canvas. The summarized questions and results of the
survey are displayed in Figure 4. The first question asked if they learned new prototyping strategies using
the canvas, and the average response was 1.67. The second question asked if the canvas supported
intentional prototyping practices, and the average score was 1.69. The third question asked if the canvas
enhanced team communication, with average score of 1.62. The fourth question asked if the canvas added
value during the Deliver phase of the design process, with an average score of 1.44. Overall, there was a
very positive response to using the canvas, with only six responses as neutral and one response in
disagreement out of 220 total responses (4 questions x 55 people).
Figure 4. Survey responses from 55 professionals after using Prototyping Canvas V2
3 FUTURE RESEARCH
The revised Prototyping Canvas (Figure 3) will be validated for its usefulness in immediate future studies
with senior capstone Engineering Product Development students working on industry-sponsored projects
and with professional engineers and designers. This future work will focus on answering the following
research questions: 1) Does using the prototyping canvas improve teams’ strategy for prototyping? 2) Does
using the prototyping canvas aid teams in creating more purposeful prototypes? 3) Does using the
prototyping canvas reduce cognitive load on individuals? For each of the research questions, we will
compare individuals and teams using the Prototyping Canvas against individuals and teams who prototype
“freely.” Answering these questions will extend our understanding of how the Prototyping Canvas affects
individuals and teams and provide more rigorous validation of the tool.
4 CONCLUSION
The Prototyping Canvas is a strategic prototyping tool that guides users to build the simplest prototype
possible to answer critical assumptions or questions about their design. This tool was systematically
developed from surveying prototyping literature and distilling three key principles related to prototyping
purpose, resources, and strategy. The layout and structure of the canvas was also inspired by the highly
successful and widely adopted Business Model Canvas. This Prototyping Canvas acts as a roadmap to
guide designers through identifying their assumptions and questions around the desirability, feasibility, and
viability of aspects related to their opportunity or concept; then, the canvas lists all the “key ingredients”
necessary to plan for building that minimal viable prototype, including the resources, strategies, prototyping
principles, and testing plan. Finally, the canvas prompts users to reflect, listing insights and lessons-learned
from the testing of the prototype. The Prototyping Canvas effectively guides designers through creating a
prototyping plan, and it also facilitates a common prototyping language amongst teams. To encourage
purposeful prototyping, the researchers launched a free online Design Innovation (DI) learning module on
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Strongly Agree Agree Neutral Disagree Strongly Disagree
Q1: Learn new prototyping strategies
Q2: Supports intentional prototyping practices
Q3: Enhance team communicartion
Q4: Adds value during Deliver phase
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the Prototyping Canvas, which includes guidelines for using this tool, worked examples, and a free
downloadable canvas (www.dimodules.com/prototypingcanvas).
REFERENCES
Amarsy, N. (2015), Why and How Organizations Around the World Apply the Business Model Canvas. [online]
Strategzer. Available at: blog.strategyzer.com/posts/2015/2/9/why-and-how-organizations-around-the-
world-apply-the-business-model-canvas (Accessed 26 Nov. 2018).
Andreasen, M.M. and Hein, L. (1987), Integrated Product Development, Springer-Verlag / IFS Ltd, UK.
Blank, S. (2016), The Mission Model Canvas - An Adapted Business Model Canvas for Mission-Driven
Organizations. [online] Steve Blank. Available at: steveblank.com/2016/02/23/the-mission-model-canvas-
an-adapted-business-model-canvas-for-mission-driven-organizations/ (Accessed 26 Nov. 2018).
Buchenau, M. and Suri, J.F. (2000), “Experience Prototyping”. Designing interactive systems: processes,
practices, methods, and techniques, ACM, pp. 424–433.
Brandt, E. (2007), “How tangible mock-ups support design collaboration”, Knowledge, Technology & Policy,
Vol. 20 No. 3, pp. 179–192.
Camburn, B., Dunlap, B., Gurjar, T., Hamon, C., Green, M., Jensen, D., Crawford, R., Otto, K. and Wood, K. (2015),
“A Systematic Method for Design Prototyping”, Journal of Mechanical Design, Vol. 137 No. 8, p. 081102.
Camburn, B., Viswanathan, V., Linsey, J., Anderson, D., Jensen, D., Crawford, R., Otto, K. and Wood, K.
(2017a), “Design Prototyping Methods: State of the Art in Strategies, Techniques, and Guidelines”, Design
Science, Vol. 3 No. 13. https://doi.org/10.1017/dsj.2017.10
Camburn, B.A., Auernhammer, J.M., Sng, K.H.E., Mignone, P.J., Arlitt, R.M., Perez, K.B., Huang, Z., Basnet,
S., Blessing, L.T. and Wood, K.L. (2017b), “Design Innovation: A Study of Integrated Practice”, ASME
2017 IDETC/CIE, p. V007T06A031.
Camburn, B. and Wood, K. (2018), “Principles of maker and DIY fabrication: Enabling design prototypes at low
cost”, Design Studies, Vol. 58, pp. 63–88. https://doi.org/10.1016/j.destud.2018.04.002
Christie, E.J., Jensen, D.D., Buckley, R.T., Menefee, D.A., Ziegler, K.K., Wood, K.L. and Crawford, R. (2012),
“Prototyping strategies: literature review and identification of critical variables”, American Society for
Engineering Education Conference.
Daly, S.R., Yilmaz, S., Christian, J.L., Seifert, C.M. and Gonzalez, R. (2012), “Design heuristics in engineering
concept generation”, Journal of Engineering Education, Vol. 101 No. 4, pp. 601–629.
Deininger, M., Daly, S.R., Sienko, K.H. and Lee, J.C. (2017), “Novice designers' use of prototypes in
engineering design”, Design Studies, Vol. 51, pp. 25–65. https://doi.org/10.1016/j.destud.2017.04.002
Dow, S.P., Glassco, A., Kass, J., Schwarz, M. and Klemmer, S.R. (2009), The effect of parallel prototyping on
design performance, learning, and self-efficacy, Stanford Tech Report.
Dunlap, B.U., Hamon, C.L., Camburn, B.A., Crawford, R.H., Jensen, D.D., Green, M.G., Otto, K. and Wood,
K.L. (2014), “Heuristics-based prototyping strategy formation: development and testing of a new
prototyping planning tool”, ASME 2014 IDETC/CIE, p. V011T14A019.
Gerber, E. and Carroll, M. (2012), “The psychological experience of prototyping”, Design Studies, Vol. 33, pp.
64–84. https://doi.org/10.1016/j.destud.2011.06.005
Gerber, E. (2015), Mockups Bracket Tournament: A Prototype is Born. [online] Northwestern University Segal
Design Institute. Available at: design.northwestern.edu/news-events/articles/2015/mockups-launch.html
(Accessed 26 Nov. 2018).
Greenberg, M.D., Pardo, B., Hariharan, K. and Gerber, E. (2013), “Crowdfunding support tools: predicting
success & failure”, CHI’13 Human Factors in Computing Systems, ACM, pp. 1815–1820
Hamon, C.L. (2017), “Virtual versus physical prototypes: development and testing of a prototyping planning
tool”, Master’s Thesis, University of Texas at Austin.
Henderson, K. (1991), “Flexible sketches and inflexible data bases: Visual communication, conscription devices, and
boundary objects in design engineering”, Science, Technology, & Human Values, Vol. 16 No. 4, pp. 448–473.
Houde, S. and Hill, C. (1997), “What do prototypes prototype?”, In Handbook of Human-Computer Interaction,
Second Edition, Elsevier Science B.V., pp. 367–381
IDEO, Design Kit (2015), The field guide to human-centered design. [online] IDEO Design Kit. Available at:
http://www.designkit.org/ (Accessed 26 Nov. 2018).
Jensen, M.B., Elverum, C.W. and Steinert, M. (2017), “Eliciting unknown unknowns with prototypes:
Introducing prototrials and prototrial-driven cultures”, Design Studies, Vol. 49, pp.1–31.
https://doi.org/10.1016/j.destud.2016.12.002
Kriesi, C., Blindheim, J., Bjelland, Ø. and Steinert, M. (2016), “Creating dynamic requirements through
iteratively prototyping critical functionalities”, 26th CIRP Design Conference.
Lande, M. and Leifer, L. (2009), “Prototyping to learn: Characterizing engineering students’ prototyping
activities and prototypes”, 17th International Conference on Engineering Design.
Lauff, C.A., (2018), Prototyping in the Wild: The Role of Prototypes in Companies, Doctoral dissertation,
University of Colorado at Boulder.
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ICED19
Lauff, C.A., Kotys-Schwartz, D. and Rentschler, M.E. (2018a), “What is a Prototype? What are the Roles of
Prototypes in Companies?”, Journal of Mechanical Design, Vol. 140 No. 6, p. 061102.
Lauff, C., Weidler-Lewis, J., Kotys-Schwartz, D., Rentschler, M.E. (2018b), “Prototypes as Intermediary
Objects for Design Coordination in First-Year Design Courses,” International Journal of Engineering
Education, Vol. 34 No. 3, pp. 1085–1103.
Lauff, C., Kotys-Schwartz, D. and Rentschler, M.E. (2017), “Perceptions of prototypes: pilot study comparing
students and professionals”, ASME 2017 IDETC/CIE, p. V003T04A011.
Leifer, L.J. and Steinert, M. (2011), “Dancing with ambiguity: Causality behavior, design thinking, and triple-
loop-learning”, Information Knowledge Systems Management, Vol. 10, pp. 151–173.
Lemons, G., Carberry, A., Swan, C., Jarvin, L. and Rogers, C. (2010), “The benefits of model building in teaching
engineering design”, Design Studies, Vol. 31 No. 3, pp. 288–309. https://doi.org/10.1016/j.destud.2010.02.001
Lin, J. and Seepersad, C.C. (2007), “Empathic lead users: the effects of extraordinary user experiences on
customer needs analysis and product redesign”, ASME 2007 IDETC/CIE, pp. 289–296.
Maurya, A. (2012), Running lean: iterate from plan A to a plan that works. O’Reilly Media, Inc.
Menold, J.D. (2017), Prototype For X (PFX): A Prototyping Framework to Support Product Design, Doctoral
dissertation, Pennsylvania State University.
Menold, J., Jablokow, K. and Simpson, T.W. (2017), “Prototype for X (PFX): A holistic framework for
structuring prototyping methods to support engineering design”, Design Studies, Vol. 50, pp. 70–112.
https://doi.org/10.1016/j.destud.2017.03.001
Menold, J., Simpson, T.W. and Jablokow, K. (2018), “The prototype for X framework: exploring the effects of a
structured prototyping framework on functional prototypes”, Research in Engineering Design, pp.1–15.
https://doi.org/10.1007/s00163-018-0289-4
Moe, R.E., Jensen, D.D. and Wood, K.L. (2004), “Prototype partitioning based on requirement flexibility”,
ASME 2004 IDETC/CIE, pp. 65–77.
Neeley, W.L., Lim, K., Zhu, A. and Yang, M.C. (2013), “Building fast to think faster: exploiting rapid
prototyping to accelerate ideation during early stage design”, ASME 2013 IDETC/CIE, p. V005T06A022.
Osterwalder, A. (2004), The business model ontology: A proposition in a design science approach, Doctoral
dissertation, University of Lausanne.
Osterwalder, A. and Pigneur, Y. (2010), Business model generation: a handbook for visionaries, game changers,
and challengers. John Wiley & Sons.
Otto, K., and Wood, K. (2001). Product design: techniques in reverse engineering and new product
design. Prentice-Hall.
Rhinow, H., Köppen, E. and Meinel, C. (2012), “Prototypes as boundary objects in innovation processes”,
International Conference on Design Research Society, Bangkok, Thailand.
Roschuni, C., Kramer, J., Zhang, Q., Zakskorn, L. and Agogino, A. (2015), “Design talking: an ontology of design
methods to support a common language of design”, International Conference on Engineering Design.
Schrage, M. (2000), “Serious play: The future of prototyping and prototyping the future”, Design Management
Journal, Vol. 11 No. 3, pp. 50–57.
Star, S. L. (2010), “This is not a boundary object: Reflections on the origin of a concept”, Science, Technology,
& Human Values, Vol. 35 No. 5, pp. 601–617.
Thomke, S.H. (1998), “Managing experimentation in the design of new products”, Management Science, Vol. 44
No. 6, pp.743–762.
Tiong, E., Seow, O., Teo, K., Silva, A., Wood, K.L., Jensen, D.D. and Yang, M.C. (2018), “The Economies and
Dimensionality of Prototyping: Value, Time, Cost and Fidelity”, ASME 2018 IDETC/CIE, p. V007T06A045.
Ulrich, K. T. and Eppinger, D. S. (2000), Product design and development. McGraw-Hill.
Viswanathan, V. and Linsey, J. (2011), “Design fixation in physical modeling: an investigation on the role of
sunk cost”, ASME 2011 IDETC/CIE, pp. 119–130.
Yang, M. (2005), “A study of prototypes, design activity, and design outcome”, Design Studies, Vol. 26 No.6,
pp. 649-669. https://doi.org/10.1016/j.destud.2005.04.005
Yilmaz, S., Daly, S.R., Seifert, C.M. and Gonzalez, R. (2016), “Evidence-based design heuristics for idea
generation”, Design Studies, Vol. 46, pp. 95–124. https://doi.org/10.1016/j.destud.2016.05.001
ACKNOWLEDGMENTS
The team would like to acknowledge the SUTD-MIT International Design Centre (IDC). The IDC design
engineers were critical to the testing and iterations on the Prototyping Canvas. Additionally, many
conversations with other IDC members influenced the direction and evolution of this tool.
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