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Session T1A
San Juan, PR July 23 – 28, 2006
9
th
International Conference on Engineering Education
T1A-1
Idea Engineering: Teaching Students how to Generate
Ideas
Graham Horton
University of Magdeburg, Computer Science Department,
Magdeburg, Germany. graham@sim-md.de
Abstract - The ability to generate ideas for solving
problems and producing innovations is undoubtedly an
important skill for any engineer. Usually, this is
accomplished using well-known, but generic creativity
techniques. These methods tend to be unstructured and
somewhat random in their approach, and there are no
clear guidelines available for their application. At the
University of Magdeburg, we have taken an Engineering
approach to the problem of producing ideas. We have
reduced the large number of published creativity
techniques to a small number of fundamental principles
which can provide a basis for a systematic methodology for
producing ideas. Based on our research results, we have
created an undergraduate course entitled "Idea
Engineering" which is attended by students from
Engineering, Management, Computer Science and Social
Sciences programs. Students work together in teams to
design and build an "idea factory" which they then apply
to real-life problems supplied by industry.
Index Terms – Creativity Techniques, Idea Engineering,
Ideation, Netstorming.
O
VERVIEW
The ability to generate ideas for solving problems and
producing innovations is undoubtedly an important skill for
any engineer. In times of growing competitive pressure,
innovations are a key to economic success for most
corporations.
Usually, idea generation is accomplished using well-
known, but generic creativity techniques. These methods tend
to be unstructured and somewhat random in their approach
and there are no clear guidelines available for their
application. As a result, they can be quite unpredictable, which
has given "creative workshops" a bad reputation, especially
among managers and engineers.
Even a brief survey of the literature on creativity
techniques reveals that from an academic point of view, the
field has hardly been touched. There is no unified
terminology, no structure, and no theoretical basis. Small
wonder then, that idea generation has not been able to
establish itself in academic curricula.
At the University of Magdeburg, we have taken an
Engineering approach to the problem of producing ideas. Our
goal is to raise the level of idea production to an Engineering
technology which can be used in practice effectively and
taught to students at the University level. We are therefore
closer in tone to De Bono's "Serious Creativity"
[1] than to a
typical playground-like approach to creativity.
In our ongoing research project, we have been able to
reduce the large number of published creativity techniques to a
small number of fundamental principles which can provide a
basis for a systematic Engineering-type approach to producing
ideas.
Once these principles have been understood, they can be
used to generate tailor-made idea production techniques for
any given problem. These can be considerably more reliable
and efficient than the generic methods which are commonly
used in practice.
Based on our research results, we have created an
undergraduate course entitled "Idea Engineering". This course
is attended by students from Engineering, Management,
Computer Science and Social Sciences programs. Students
work together in teams to design and build an "idea factory"
which they then apply to real-life problems supplied by
industry.
Since the ideation techniques are basically a sequence of
questions and answers, they can easily be implemented on a
computer. We have therefore created a software tool called
"Netstorming", which allows groups of students to work
together on idea production via the Internet. Students in the
course use this software to familiarise themselves with the
techniques, and students from the Computer Science
Department have the opportunity to develop the software as
part of their study program.
Together with two former students, the author has
founded a company which uses the Idea Engineering
technology in ideation projects for a wide variety of
customers. This gives the students the added opportunity of
participating in professional idea production projects and thus
enhancing their understanding of the course material.
T
HE CURRENT STATE OF CREATIVITY TECHNIQUES
The search for ideas is usually carried out using so-called
creativity techniques. Creativity techniques go back to the
Classical Brainstorming approach by Alex Osborn
[6]. Some
of the most well known methods are the 6-3-5 Method, the
Morphological Matrix and the Random Input Method. These
and many more can be found in any popular book on creativity
techniques.
More than 100 creativity techniques have been published;
anyone who searches the literature will be confronted by a
Session T1A
San Juan, PR July 23 – 28, 2006
9
th
International Conference on Engineering Education
T1A-2
bewildering assortment of methods, many of which only differ
minimally. VanGundy's recent book
[9] is a case in point.
Furthermore, it is hard to recognise which method is most
applicable for any given idea development task, and it is easy
to inadvertently choose an inappropriate method and be
disappointed by the results obtained. Furthermore, standard
creativity techniques are generic, i.e. they are presented in a
general form, and it often remains unclear how they can be
optimised to a given task.
For these reasons, creative workshops and brainstorming
sessions have acquired a bad reputation with many
professionals – they are considered to be undisciplined and
unproductive, and therefore a waste of time.
I
DEA ENGINEERING
For two years, there has been a research project at the
Computer Science Department of the University of
Magdeburg called Idea Engineering. This project is based on
the premise that idea production can be viewed as an
Engineering task. Its goal is to develop both a theoretical
understanding and practically applicable idea production
methods. These methods should meet the criteria that
characterise traditional Engineering disciplines.
We consider Idea Engineering to be a technology, and
therefore prefer the term idea production technique to
creativity technique. We refer to the graduates of the course as
Idea Engineers and the workshop in which the ideas are
produced as an Idea Factory (rather than "creative
workshop").
In the first phase of this research project, a large number
of well-known creativity techniques were analysed in order to
gain a theoretical understanding of the different routes by
which ideas are generated. This analysis showed that there are
essentially only six basic methods for creating ideas. These
basic methods can be described both simply and abstractly.
Requirements of an Engineering Discipline
With an understanding of these basic principles, tailor-made
idea production techniques can be developed for each new
ideation task. In order to qualify as an Engineering discipline,
these techniques should fulfil (at least) the following
conditions:
• Reliability. The methods should produce good ideas
reliably, i.e. the methods minimise the probability of
something going wrong.
• Predictability. The methods should be able to produce a
given number of ideas of predefined quality using
specified resources (e.g. number of participants, duration
of production).
• Transparency. The methods should be understandable
and learnable for anyone. It should be possible to explain
the process of designing the idea production methods, and
workshop participants should be able to recognise the
purpose of the questions they are presented with.
• Efficiency. The methods should produce a large number of
good ideas with the resources available. Idea production is
a random process based entirely on human effort, so this
criterion implies both maximising the human output with
skilful facilitation as well as designing idea production
techniques with a high signal to noise ratio.
• Well-Foundedness. The methods should arise from the
basic principles of idea production and the properties of
the task to be solved. The process of creating an idea
production method should be well-defined.
• Measurability. The performance of the methods should be
quantifiable; there are effective measures available for
describing both their output and their efficiency.
• Optimisability. It should be possible to compare, analyse
and optimise the methods. This implies that the methods
have free parameters, whose influence on the output can be
analysed and measured.
Such requirements go without saying in any traditional
Engineering discipline such as Mechanical Engineering; for
this reason, they must also hold for Idea Engineering, if the
premise of the research project is to be validated. So far, we
have been successful in achieving these standards, although
much work is still needed in order to fully establish Idea
Engineering as a well-founded field.
One example of our success in this area is that we are able
to control important attributes such as the conservativeness,
randomness or generality of the ideas produced. Furthermore,
by adopting an algorithmic approach to idea production, we
are able to measure the efficiency of our methods in a
repeatable way, which is a prerequisite for optimising our
techniques.
Reducing Scattering Losses
Idea production is a random process, as it relies on the
associations in the minds of the participants. Different people
will give different answers to questions such as "Who is a
leader in their field?" or "How would Elvis Presley have
solved this problem?" The answers to these questions
therefore differ greatly in their relationship with the problem
at hand and in their usefulness for generating a good idea. For
this reason, all idea production is based on the principle of
first generating a large number of raw ideas quickly and
spontaneously, and then selecting from these the best ones to
be improved upon.
Typical statistics for creativity techniques indicate a yield
of up to 5%, in other words only one idea in 20 at best turns
out to be of high quality. Indeed, one company specialising in
idea production states that it can produce 58000 raw ideas in
its flagship product. Assuming the customer is only looking
for at most a handful of ideas, this indicates an even lower
yield. By contrast, in a recent project carried out for a major
international corporation using Idea Engineering technology,
the participants rated 80 out of the 400 ideas produced as
"grade A", which corresponds to a yield of 25%.
Change of Perspective
Over the course of time, we get to know our environment:
school, college and everyday experience make us all into
experts for our own personal situations. This of course has the
Session T1A
San Juan, PR July 23 – 28, 2006
9
th
International Conference on Engineering Education
T1A-3
advantage that we can memorise solutions to known problems.
These solutions occur to us quickly, often even automatically.
However, when we need new solutions, our expertise is often
a drawback, since we are not able to free ourselves of our
established thought patterns – this is the so-called
occupational blindness or tunnel vision. One famous example
of this is the story of the engineers who told Henry Ford I that
it was impossible to build a six-cylinder engine – to which
Ford is said to have replied: "Someone find me some
engineers who haven't learned what isn't possible!"
One basic requirement that Idea Engineering therefore
makes of any idea production technique is that it introduces a
change of perspective (Figure 1). This change of perspective
helps us to leave our well-trodden thought paths and overcome
occupational blindness. The simplest example of a change of
perspective is what we call the "Random Mr. X technique".
Here, we simply ask, "How would X solve the problem?" We
can insert anyone at all for X, such as "a witch", "Microsoft"
or "Elvis Presley". Considering how Elvis Presley might have
solved the problem can yield insights that were previously
unseen. Clearly, the change of perspective used will have a
significant effect on the ideas produced.
FIGURE 1
A
CHANGE OF PERSPECTIVE YIELDS AN EASIER WAY TO NEW IDEAS.
Idea production techniques differ in the methods used to
generate the change of perspective and in the properties of the
perspectives thus generated. Examples of such properties are
conservative or bold, obvious or exotic, and general or
specific. Our research has shown that these properties have
strong influence on the quality and quantity of the ideas
produced. Remarkably, this topic does not yet seem to have
been addressed in the literature on creativity techniques. A
good Idea Engineer can precisely control the properties of the
change of perspective, and a significant portion of Idea
Engineering is devoted to finding productive changes in
perspective for any given task as well as to finding appropriate
questions to help workshop participants to use these changes
in perspective efficiently.
All idea production techniques can be used in an idea
factory in a step by step manner under the guidance of a
facilitator. They can be designed very simply, and – apart
from the willingness to participate in the process – they do not
require any particular skills from the participants. With the
right training and a little practice, the techniques become
automatic and become a new type of thought process, making
that person a little more "creative".
In the Idea Engineering course, students are shown the
principles behind the changes of perspective and a large
variety of methods for generating them. They are encouraged
to develop their own techniques which should be optimised to
the ideation problems given as homework assignments.
Algorithm, Format and Story
The second step necessary for making sense of published
creativity techniques is to distinguish between three different
aspects of idea production which are normally not viewed
separately. This is a fundamental premise of Idea Engineering.
We call these aspects Algorithm, Format and Story (Figure 2).
Algorithm
Format
S
t
o
r
y
Single group
+ facilitator
Individual,
written
Te a m s of four,
self directed
A
n
a
l
o
g
y
N
o
n
e
P
r
o
v
o
c
a
t
i
o
n
Olympic race
None
Fairy tale
Classical
Brainstorming
Problem Ideas
New
perspective
The direct route to new
ideas is often blocked by
occupational blindness.
Construction using
an idea production
technique
The new perspective
leads to ideas more
easily.
FIGURE 2
T
HE THREE ASPECTS OF IDEA PRODUCTION.
The Algorithm is the set of instructions for producing
ideas. In the above example, this would be simply to present
the problem from the point of view of a witch, Microsoft and
Elvis Presley. The Algorithm is formulated independently of
its implementation in the idea factory.
The Format refers to the organisation of the Algorithm
when carried out. It is primarily concerned with the
organisation of the participants, the role of the facilitator, and
the media used. Thus Classical Brainstorming simply has the
format of putting all participants in one group, who call out
their ideas to a facilitator, who in turn visualises the ideas, for
example using a flip chart. Alternative formats include
creating smaller groups, removing (or cloning) the facilitator,
and having the participants write down their ideas rather than
call them out (occasionally referred to as "Brainwriting"). The
choice of format can have a significant effect on the efficiency
of the idea factory. Students of the course are required to
choose or design optimal formats for each phase of the idea
production.
A "Story" can be added to the idea production to add
flavour and fun to the idea factory. Thus teams can be created
which compete with each other to produce the most ideas
Session T1A
San Juan, PR July 23 – 28, 2006
9
th
International Conference on Engineering Education
T1A-4
within a given time limit, or the idea factory can be given an
overall metaphor, such as an alchemist's laboratory or a
Hollywood film production. The Story is particularly useful
for presenting the more challenging idea production
techniques such as Provocation, where the participants are
presented with hypothetical situations which directly
contradict their perception of reality. In such cases,
transporting the workshop to a distant planet or into a cartoon
world can help free the participants' imaginations.
FIGURE 3
T
EAM "BRAINBALL" USED THE 2006 WORLD CUP AS A METAPHOR FOR THEIR
IDEA FACTORY.
The coordinates of Classical Brainstorming in this three-
dimensional scheme are shown in the diagram in Figure 2; the
format is a single group with one facilitator, no story is used,
and there is no algorithm for a change of perspective. The
latter property is one reason that Classical Brainstorming is
often unsuccessful – the participants are expected to produce
new solutions to the problem without the aid of a change of
perspective. However, without the change of perspective, they
can remain trapped in their occupational blindness. It takes
either talent or training to be able to overcome this handicap
on one's own. Learning this ability is considered by some
students to be the principal benefit from attending the Idea
Engineering course.
Quality control
Quality control is an important aspect of an idea factory. In a
typical three-hour session, the first hour may be spent
generating between 100 and 300 raw ideas. These will vary
greatly in quality, precision and relevance, and must be
filtered and enhanced before they qualify as legitimate
solutions to the problem. Indeed, a significant proportion of
them will be irrelevant or even impossible. In addition, the
customer is usually only looking for a small number of good
ideas.
For this reason, a comprehensive briefing is carried out.
The briefing describes not only the customer's problem, but
also goals, quality criteria and boundary conditions. The
quality criteria are the measures by which the customer will
judge the success of an idea; examples are the amount of
additional revenue earned, the total costs saved or the number
of new clients acquired. Examples of boundary conditions are
budget restrictions or the maximum time available for
implementation. In the course project, students are required to
conduct briefing meetings with the customers, and they very
often underestimate the subtleties involved.
The boundary conditions are integrated into the idea
factories in the form of quality controls; every idea must pass
through a filter which checks whether it satisfies the boundary
conditions or not. The quality criteria are used to rank the
ideas at the end of the session. The students in the course may
not allow any idea to leave their idea factory which does not
satisfy the boundary conditions.
A
N EXAMPLE
We give a simple example to illustrate one method for
generating ideas. The problem to be solved is to produce ideas
for a local supermarket which wishes to improve service to its
customers. The technique to be used is known as the analogy
technique, which is illustrated in Figure 4.
Problem
Attribute
Analogy
Solution
What is an attribute
of the given situation?
Who or what else
has this attribute?
1.
2.
How have/might they
solve(d) the problem?
3.
How can we apply
this to our problem?
4.
FIGURE 4
T
HE ANALOGY IDEA PRODUCTION TECHNIQUE
The analogy technique uses attributes of the given
problem to find analogous situations. Then it is asked how the
analogous problem has been or might be solved there. In the
case of real analogies which are known to the participants,
these answers are given from their general knowledge; in the
case of unknown or fictional analogies, the answers come
from their imagination. Finally, it is tested whether these
solutions can be applied to the original problem. There are
many methods for generating analogies, which yield very
different results. The following list gives four attributes of a
supermarket which were suggested during a student project:
a) A supermarket has long walls.
b) A supermarket displays a large number of items.
Session T1A
San Juan, PR July 23 – 28, 2006
9
th
International Conference on Engineering Education
T1A-5
c) You can lose your way in a supermarket.
d) A supermarket is an important local amenity.
We now perform step 2:
a) Another place with long walls is an art gallery.
b) Another place which displays a large number of items is a
museum.
c) Another place you can get lost is in a big city.
d) Another important local amenity is the town hall.
In step 3 we ask what service or solution is provided
there:
a) An art gallery displays paintings for the enjoyment of its
visitors.
b) A museum publishes a guidebook which provides
information on its exhibits.
c) To avoid getting lost in a big city you might use a map.
d) In the town hall you can find information on forthcoming
events and local groups and the banns of marriage.
The raw ideas generated are:
a) Decorate the walls with paintings by local artists or
kindergarten children.
b) Publish a guidebook which gives interesting information
on selected products.
c) Give customers a map of the store which indicates the
major sections.
d) Display information about forthcoming events and
marriages or feature local clubs and sports teams.
The required skill in this example is to choose attributes
which best characterise a supermarket and thus lead to better
ideas. "Often has queues of customers" is a very general
attribute which will lead to a broad range of analogies and thus
a large variety of ideas, and the scattering losses will be
higher. "All the staff wear white coats", on the other hand, is
quite a specific attribute of a supermarket, so it will yield a
small number of analogies. However, since the wearing of
white coats by the staff is not a particularly significant aspect
of a supermarket, the analogies will probably not yield good
ideas. "Offers a large variety of items", on the other hand, is a
specific and important attribute of a supermarket and will
likely yield a good crop of ideas via analogies such as
museum, online-shop, yard sale, or Chinese restaurant.
Other idea production techniques involve similar
parameters which can be tuned. In the Idea Engineering
course, students learn to identify and use these in their idea
factories to produce a set of ideas with the desired
specifications.
F
ORMAT OF THE COURSE
The course offered at the University of Magdeburg currently
has the format of a traditional lecture accompanied by a
project. The lecture includes an introduction to creativity and
creative thinking, the principles of Idea Engineering, including
several examples of idea production techniques, creative
problem-solving techniques, methods for evaluating ideas, and
guidelines for facilitating group workshops.
Whereas the idea production techniques are presented
from a unique Idea Engineering perspective, the problem
analysis methods are used in a standard way, as described for
example in
[8] and [9].
Students are divided into teams of five, and each team has
the assignment to design and build an idea factory according
to the principles outlined in the lectures. Each team has a
coach, who is a student or teaching assistant who has already
graduated from the course. The coach meets with the team
once per week to discuss the current project milestone, to
answer questions and to provide guidance.
During the semester, each team must produce two
prototype idea factories, which they use to test their methods
and to train their facilitation abilities. These prototype
milestones are accompanied by presentations, in which team
representatives report on their team's progress and on the
difficulties encountered and overcome.
At the end of the semester, which lasts for 14 weeks, each
team is given a genuine idea production assignment to carry
out. Assignments come from local companies and institutions,
charitable organisations and international corporations. They
include a newly-opened coffee house looking for marketing
ideas, a soul band needing entertainment ideas for its
Christmas concert, and the research department of a well-
known corporation searching for new product ideas for some
of its leading brands. The final result of the project is a
comprehensive results document which is presented to these
"customers" and which typically contains between 100 and
200 raw ideas and three to ten more intensively worked out
solutions.
N
ETSTORMING: THE VIRTUAL IDEA FACTORY
By distinguishing between Algorithm, Format and Story in
idea production, we are able to dispense with Format and
Story and consider the Algorithms in an abstract manner. It
quickly becomes clear that almost all approaches are
essentially question and answer techniques. These can be
easily implemented on a computer and made available on the
Internet. This allows the creation of a virtual idea factory, in
which participants log in to a server program via a web
browser.
This approach has been implemented in a recent Masters
thesis
[3], resulting in the software tool Netstorming.
Netstorming is used to illustrate the principles of Idea
Engineering using a different format and allows students to
carry out idea production projects from home or a computer
lab. In addition, it provides interesting programming
opportunities for students of the Computer Science
Department. Idea production using Netstorming is very
efficient – a group of five to six students typically generates
about 200 raw ideas within one hour.
Further development of Netstorming will involve students
of Psychology, who will look into the participants' behaviour
online and develop methods for compensating the
disadvantages of online cooperation compared to the
Session T1A
San Juan, PR July 23 – 28, 2006
9
th
International Conference on Engineering Education
T1A-6
traditional face-to-face workshop. Also, since Netstorming
stores a large amount of data during the idea production, it can
be used to analyse and compare the performance of the
different techniques used. By providing the means to perform
controlled quantitative experiments, Netstorming is an
important tool for establishing the Engineering criteria listed
above.
Other software tools produced by Idea Engineering
students at the Computer Science Department include a more
playful version involving a genie and a crystal ball in the Story
[2], and a more formal version in which the idea production
methods are specified as a formal language and displayed as a
hyperbolic tree
[5].
K
EY COMPETENCIES
Key competencies play an increasingly important role in
German academic education. These competencies include
giving presentations, organizing and leading teams, project
management and meeting facilitation. New recommendations,
both from the government and from accreditation agencies
require all academic programs to provide training in these
abilities, which are considered essential for a modern
professional.
The Idea Engineering course is designed to provide
students with the opportunity to train and experience several
of these competencies. Most students find workshop
facilitation the most challenging of these – they quickly
discover how difficult it is to hold the attention of the
participants for up to three hours, to maintain a high level of
motivation, and to provide clear instructions for unfamiliar
tasks.
C
OOPERATION WITH AN IDEA FACTORY
Together with two former students, the author has recently
founded a company which carries out idea production projects
for a wide variety of customers from small companies to well-
known international corporations. The company uses Idea
Engineering technology and involves five to ten students in
each project. This gives the students the added opportunity of
participating in professional idea production projects and thus
enhancing their understanding of the course material.
These opportunities enhance the attractiveness of the
course, since additional benefits include the chance to earn
some money, to travel, and to gain experience in dealing with
customers. One further motivational factor for the students is
to experience first-hand the knowledge being gained in the
course being applied to solve real-world problems.
C
ONCLUSION
Idea Engineering is the name of a research project and a one-
semester course at the University of Magdeburg, Germany. Its
goal is to improve the methodology for generating ideas from
its current state to an Engineering discipline. Student teams
have access to the latest research results via weekly lectures
and are given the task of designing their own idea factories. In
doing so, they both aid companies and organizations in need
of innovative ideas and also contribute to the ongoing research
effort.
The course is unique in bringing together students from
Engineering, Economics and Social Sciences programs in
teams which work together for an entire semester. Students
from the "hard" Sciences must learn "soft" skills such as
workshop facilitation, and students from the "soft" Sciences
must learn to develop techniques according to "hard" criteria.
These properties serve to broaden the students' horizons and
enrich their study experience.
Students rank the course highly in University teaching
evaluations and regularly praise the benefits they have
received from attending. These include not only the ability to
organize idea production events but also the key competencies
such as teamwork and workshop facilitation which have been
acquired.
Due to the success of the course, preparations are being
made to extend it from one to two semesters, which will allow
the students more space – both for looking deeper into
research questions and for more thoroughly developing their
idea factories. As of the fall semester 2006, the course will
also be offered as part of an interdisciplinary Masters
program.
R
EFERENCES
[1] De Bono, E, Serious Creativity, 1992.
[2] Goldammer, A, Ein Software-Werkzeug zur Lösung wiederkehrender
Ideenfindungsaufgaben unter Berücksichtigung von Aspekten der
kognitiven Psychologie (A software tool for solving repeated idea
production problems taking aspects of cognitive psychology into
account), Masters Thesis, Computer Science Department, University of
Magdeburg, 2005.
[3] Görs, J, Entwicklung eines Werkzeugs zur computergestützten und
kollaborativen Ideengenerierung (Development of a tool for computer-
supported collaborative idea generation), Masters Thesis, Computer
Science Department, University of Magdeburg, 2005.
[4] Harris, R, A, Creative Problem Solving, 2002.
[5] Knoll, S, W, Die visuelle Unterstützung von Teilen des allgemeinen
Ideenentwicklungsprozesses durch ein Softwaretool zur strukturierten
Erstellung von Ideen (Visual support of parts of a general idea
development process by a software tool for the structured creation of
ideas), Masters Thesis, Computer Science Department, University of
Magdeburg, 2005.
[6] Osborn, A, F, Applied Imagination, 1957.
[7] Schnetzler, N, The Idea Machine, 2005.
[8] VanGundy, A, B, Techniques of Structured Problem Solving, 1988.
[9] VanGundy, A, B, 101 Activities for Teaching Creativity and Problem
Solving, 2005.
