Prototyping
as a resource to investigate
future states of the system
Research proposal by: de la Rosa, Kohler & Ruecker

Juan de la Rosa
Associate professor Universidad Nacional de Colombia
Ph.D. Student, University of Illinois at Urbana-Champaign
Stan Ruecker
Anthony J. Petullo Professor in Graphic Design
University of Illinois at Urbana-Champaign
Karolina Kohler
Design Researcher, Kaiser X Labs, Munich
MDes Institute of Design, Chicago

Research statement
Design theory states that design objective is to envision a preferred future and plan
and articulate to facilitate it (Simon, 1969; Banathy, 1996). Regardless of this
statement, since the notion of future is reduced to the not-yet-existing object of
design, design practices in many cases tend to avoid reviewing collective notions of
future, self-determination of users and undesirable consequences for their users and
for the system.
This paper continues an argument about the need for design to build methods that
allow design researcher to produce reusable models of knowledge of the future
system and for design practitioners, to successfully face complexity on their design
process.

Research background
What is the specific knowledge to design that is produced on a research process?
How do we collect this knowledge and build reusable models from it?
4
The use of prototypes as an experimental
research tool for designers (Ruecker, S.)
>>

5
Research background
Design
inquiry
Imageofthefuturesystem
Inflectionpoint
Prototyping process
Research into the past
Banathy’s model (1996)
introduces a series of
advances that reconcile
Simon’s definition of design
(1969) with the Analysis and
Synthesis model presented by
Alexander (1964). Adding the
idea of an initial inflection point
of convergence where the
designer produces an image of
the future that is going to
support the definition of the
following process of design.
Not-yet-existing
Banathy, B. A. (1996).
Information-based design of social systems.
Behavioral Science, 41(2).

6
Research background
Design
inquiry
Imageofthefuturesystem
Inflectionpoint
Prototyping process
Research into the past
Not-yet-existing
Some of the concerns found
with the way in which this
model is applied to design
practice and its implications to
research are: the apparent
representation in the model of
a linear process between the
initial inquiry and the final
result, that might imply a
deterministic view of the
process that is common on the
engineer process. Also, the
idea of research into the past
as a way to gain knowledge of
the future, assuming a
probabilistic approach based
on trends and patterns. And
finally, the use of prototypes
just as a tool to validate this
notions.

7
Research background
Design
inquiry
Imageofthefuturesystem
Not-yet-existing
Inflectionpoint
Research into the future
Prototyping process
Designgoal
Research into the past
Modifying the model to
include: the tension of the
displacement produced
between initial assumption
and the knowledge gained on
the design process; the notion
of future as an extended view
of the preferred system; and
the use of prototypes as a tool
to reconcile the tacit
knowledge of humans and
their different views in the
construction of those notions
of future; could result in a more
thorough model of design
research
Displacement
based on
uncertainty

Case study 1:
Storyboard prototypes

Storyboard prototypes
Timing: July 2016
Partners: Kaiser X Labs, Allianz Germany
Project purpose: Design the future of car insurance
based on user needs
Initial prototyping goal: Understand which of these
concepts have potential from the user perspective
Prototyping mechanism: Conversational prototypes
with a diffuse image of the future
Scope: 6 in-person interviews with test participants
9
Case study 1

10
Case study 1: Method
onboarding main interaction main benefit
Repeated value
proposition and
product category
The 6 ideas were presented on cards
with the following information on front and
back side:
Front: Back:
Value proposition

Low fidelity, open prototypes may be producing
user ideas of the future and what that future requires
on a systemic level.
The results suggest that by deploying prototypes
on the periphery of the problem, we could produce
a better view of the system.
Participants shared their image of the future
The prototype made one part of the future tangible for
participants and they took this part as given. They imagined
themselves in the future where that prototype exists and
started describing that future. The fact that is was
intentionally vague raised lots of questions from the user
which we asked them to answer themselves.
System that the prototype is part of
(values, consequences, related concepts etc.)
The prototype started with the idea of concept proof, but the
most interesting conversation happened around what the
prototype would change for the user. Learnings were not
specific to the prototype itself but consequences of its
introduction, values and about mobility in general – which
was highly interesting data that couldn’t be use for
immediate needs of the project, however.
11
Case study 1: Results
Storyboard prototypes
Intentionally vague, open
concept (to explore,
to have a conversation)
Conversation
is surrounding
the prototype
Common practice
As specific as possible
(to validate)
Conversation
is focused
on the prototype

Research statement
This paper seeks to introduce system related notions like resolution, scale,
complexity and uncertainty, to the model of displaced prototypes for design research
presented by de la Rosa (2016) with the intention to determine the possible problems
presented by current design models when facing complex system based problems.
It also seeks to support the use of experimental techniques based on prototyping to
reconcile the view of a preferred future in the design process.

Design seeks to unveil
holistic knowledge about
the initial problemDesign is systemic by
nature (Sevaldson, 2017)
Some knowledge can
only be achieved through
human experience
(Polanyi, 1967)
Our view of the future
and the past becomes
more diffuse with time
(Simon, 1969)
New affordances
arise on human
interaction
Planning and
imagining new
futures
Design
Systemic
Nature
Embodied
Knowledge
Futuristic
Perspective
13
Conceptual structure

UncertaintyTangibility
Complexity
Systemic
Nature
Embodied
Knowledge
Futuristic
Perspective
14
Conceptual structure

UncertaintyTangibility
Complexity
Modeling
Prototyping Foreseeing
Intrinsic
Extrinsic
Systemic
Nature
Embodied
Knowledge
Futuristic
Perspective
15
Conceptual structure

Elements
Connections
Scale/ scope
Resolution
Weight
Tension
Density
Systemic
Nature
Embodied
Knowledge
Futuristic
Perspective
UncertaintyTangibility
Complexity
Modeling
Prototyping Foreseeing
To validate
Provocative
Behavioral
Fictional
As Probes
into the
future system
Primary scope
based on what I know
Secondary
What I don’t know yet
16
Conceptual structure

17
Conceptual bases
How can we use prototypes to increase the resolution
of the image of the future system?
Image resolution can be improved when the
relative displacements in image sequences are
known accurately, and some knowledge of the
imaging process is available. (Irani, M., & Peleg, S.)
>>

Case study 2:
Metaphoric prototypes

19
Timing: June 2017
Partners: Kaiser X Labs, Allianz SE
Project purpose: Define design principles for a new
digital service based on the needs of Allianz employees
Initial prototyping goal: Gain an understanding of
desirable qualities of interactions with the new service
Prototyping mechanism: Displaced prototypes
Scope: 13 remote interviews with international Allianz
employees
Case 2:
Metaphoric prototypes
Case study 2

20
Case study 2: Method
input
output
process
The 3 metaphors were presented as
illustrations implying several notions
and interactions:

Participants shared their image of the future
The prototype made one part of the future tangible for
participants and they took this part as given. They imagined
themselves in the future where that prototype exists and
started describing that future. The fact that is was
intentionally vague raised lots of questions from the user
which we asked them to answer themselves.
System that the prototype is part of
(values, consequences, related concepts etc.)
The prototype started with the idea of concept proof, but the
most interesting conversation happened around what the
prototype would change for the user. Learnings were not
specific to the prototype itself but consequences of its
introduction, values and about mobility in general – which
was highly interesting data that couldn’t be use for
immediate needs of the project, however.
Storyboard prototypes
Intentionally vague, open
concept (to explore,
to have a conversation)
Conversation
is surrounding
the prototype
Common practice
As specific as possible
(to validate)
Conversation
is focused
on the prototype

When deploying several ideas, each one of them
produces new notions of what the future could be –
resulting in a higher resolution image of the model
of the future system.
Participants shared their image of the future
system that the prototype is part of
(values, consequences, related concepts etc.)
As discussed with storyboard prototypes.
Acentric, overlapping images of the future
Instead of testing a single idea, using three displaced ideas
created several acentric images of the future.
22
Case study 1: Results
Metaphoric prototypes
Focus on desirable
qualities of interaction
(future system)
Use prototype
to exemplify different values
of the system (open concept,
conversational)
3 different perspectives
on the system
Common practice
Focus on pain points
in current system
Use prototype
to demonstrate idea
(validation)
1 idea

Conclusions

Modified from De la Rosa (2017). IASDR 2017 conference proceedings. Cincinnati, OH

- Real Dynamic Systems are infinitely complex, and impossible to map on their
totality. Therefore a systemic approach will always use be based on a
simplified image of that complexity.
- Uncertainty is a constant of design and is what defines the need for more
systemic approaches. On a model, it is a factor between the complexity used
to map the model and the distance into the future.
- Complexity depends on the model produced, and it could be defined as a
factor of the scale or scope of the system and the resolution applied to the
image.
- Scope is usually an initial parameter of the design research, therefore it is
harder to modify along the process.
- The farther we move in time the more uncertainty of the system and the less
resolution.
- When uncertainty is higher we should be able to use prototypes as a way to
gain some knowledge on the systemic level.
Conclusions
- Resolution can be increased by repetitive displaced
prototypes with different focus.

References

- Akrich, M. (1992) The de-scription of technical objects. In BIJKER, W. E., & LAW, J. (eds.) Shaping
technology/building society: Studies in sociotechnical change. MIT press.
- Alexander, C. (1964) Notes on the Synthesis of Form. Harvard University Press.
- Allen, P. M. (2014). Evolution: complexity, uncertainty and innovation. Journal of Evolutionary Economics,
24(2), 265-289.
- Arenas, A., Fernandez, A., & Gomez, S. (2008). Analysis of the structure of complex networks at different
resolution levels. New Journal of Physics, 10(5), 053039.
- Banathy, B. A. (1996). Information‐based design of social systems. Behavioral Science, 41(2).
- Bødker, S. (1998). Understanding representation in design. Human-Computer Interaction, 13(2),
- 107-125.
- Cross, Nigel (1982). Designerly ways of knowing. Design Studies, 3(4) pp. 221–227.
- Von Bertalanffy, L., & Rapoport, A. (1956). General systems. Yearbook of the society for the Advancement
of General System Theory, 1, 1-10.
- De la Rosa, J. (2017). Prototyping the not-yet-existing for research and innovation: a possible process
model for design research. Re:Research IASDR 2017 Conference. Cincinnati, OH.
- Edmonds, B. M. (1999). Syntactic measures of complexity. Manchester, UK: University of Manchester.
- Funes, P., & Pollack, J. B. (2001). Evolution of complexity in real-world domains. Waltham, MA: Brandeis
University.
References

- Galey, A., & Ruecker, S. (2010) How a prototype argues. Literary and Linguistic Computing, 25(4).
- Irani, M., & Peleg, S. (1991). Improving resolution by image registration. CVGIP: Graphical models and
image processing, 53(3), 231-239.
- Latour, B. (1990) Technology is society made durable. The Sociological Review, 38(S1).
- Maturana, H. R. & Varela, F. J. (1987). The tree of knowledge: The biological roots of human understanding.
Boston: Shambhala Publications.
- Muratovski, G. (2015). Research for Designers: A Guide to Methods and Practice. Sage.
- Sevaldson, B. (2017). Redesigning Systems Thinking. Form Akademisk-Research Journal of Design and
Design Education, 10(1).
- Simon, H. A. (1969). The sciences of the artificial. MIT press.
- Simondon, G. (1958). Du mode d'existence des objets techniques: thèse complémentaire pour le doctorat
ès lettres présentée à la Faculté des Lettres de l'Université de Paris (Doctoral dissertation).
- Rittel, H. W., & Webber, M. M. (1973). 2.3 planning problems are wicked. Polity, 4, 155-169.
- Verganti, R. (2009). Design driven innovation: changing the rules of competition by radically innovating what
things mean. Harvard Business Press.
- Voros, J. (2003). A generic foresight process framework. foresight, 5(3), 10-21.
References