Hi Terence,
Au contraire! It seems you (and now I) are not alone. The issues and
questions you have raised are precisely what my research investigations
into design thinking are about. To date, I have only found literature
highlighting and discussing these issues and the need for more empirical
research, but none publishing so.
To share my thoughts on your points...
*1. The practical limitations of design thinking as a human activity ( i.e.
what it cannot do)*
-- Currently investigating this issue through observational case study
research. The main problem i find is limiting the scope/defining what
design thinking is or isnt within practice. This is a really tricky point
to justify in itself (within academia) without enough evidence as you may
know.
*2. The practical limits of applicability of design thinking (i.e. where
it
does not work, and where you should not apply it)*
-- This will also be answered through investigations above (insights of
observational research into design thinking)
*3. The theoretical/ epistemological limitations of the concept of design
thinking in terms of other more established theories of human cognition.*
-- This might require another phd in itself, but theoretical limitations
are proving difficult to justify without leaving oneself open for critique
by examiners (i have been contemplating the use of grounded theory but was
warned against doing this)
*4. What needs to be done instead of 'design thinking' in for design tasks
in
which design thinking does not apply.*
*
*
-- This might also depend on how you define design thinking and what it
consists of. There are problems and circumstances where design thinking
certainly would not be applicable
5. The implications of better understanding in this area for the validity of
design theory in other areas of design practice
-- I believe this to be quite important. What prompted myself to
investigate this issue was one part skepticism (despite being a designer
and secretly enjoying its success ;) i was also dissatisfied with a) what
little information there was to justify DT and b) worry that with DT being
so broadly lathered over every industry, failings were surely due to arise
and without investigation into how/why DT works, it may cause more harm
than good. My opinion is that i will find there are certain parameters
where DT will flourish, and others where it needs to be avoided. And of
course it goes without saying that it is imperative to design theory. How
can we promote and use something we cannot justify or explain?
> * My findings so far:
>
> A) Design thinking does not work for design situations whose outcome
> behaviour is shaped by 2 or more feedback loops. It typically produces
> design solutions that fail after a short time. This failure of design
> thinking unfortunately includes most of the interesting design situations
> in
> complex problems and strategy that design thinking is claimed to apply. The
> proof is easy to do in a practical way and anyone can prove it for
> themselves with half an hour or so of effort.*
>
> -- Do you have evidence/case studies of the failures you are referring
to? As mentioned, it depends upon what context/industry. As i am focusing
on the application of DT in social innovation and policy design, i can say
that within social and community projects multiple feedback loops appear to
be of benefit for outcomes. Within policy design, it appears that
regardless of design thinking and its iterative cycle- outcomes fail due to
higher levels of management.
Furthermore, questions such as: was it DT that failed, or the individual
that failed to apply it correctly? To me, that seems to be one of the other
reasons why DT may not be as successful as it should be. DT is less of a
method and a toolkit for anyone to slap into a project, and more about
knowing (intuitively as well) when/what/how to apply it within a certain
context.
*
*
*B) The reason is a biological limitation in human thinking.*
*
*
*--* This is has long been understood. Scholars such as Herbert Simon and
Horst Rittel both commented that designers can do much more than
'satisfying'
*
*
*C) The same reasoning shows that using collaborative design thinking*
> * approaches also fail for design situations whose outcome behaviour is
> shaped
> by 2 or more feedback loops.*
-- Example? And in what context? Many human centered designers would argue
with you against that statement.
> *D) It also shows that drawings, regardless of how insightful, illustrated
> or complicated, do not explain or enable people to understand design
> situations whose outcome behaviour is shaped by 2 or more feedback loops.
> *
-- Im not sure if feedback loops is relevant to the basic understanding of
a design problem? Can you elaborate on this point?
*
*
*E) The best strategy so far that produces design outcomes that are*
> * successful, as expected, and produce outcomes that are intended, is
> to
> use mathematically-based simulation methods with the input information
> collated from collaborative multiple constituents/stakeholders. The
> simulation is then used to 'test' proposed designs by using the simulation
> to reveal the design outcomes over time. System dynamics in its various
> forms at the moment appears to be the best design tool/simulation method.
> An example of this approach (although conceptually problematic in its
> reasoning) is *:
>
> -- Simulation methods are also described by H. Simon in The Sciences of
the Artificial. Correct me if i am wrong, but a mathematically based
simulation would be of little use in socially sustainable projects, where
communities and cultural groups of individuals are involved that require
sensitivity to culture and tradition.
Furthermore, however wonderful this simulation may be, one cannot predict
the longevity of outcomes in the future. Even Simon acknowledged this,
which is why he and others settled on 'satisfying' than 'predicting'
perfect outcomes no matter how intelligent the computations and algorithms
are.
>
> F) A new direction I've developed to provide a more holistic design method
> is through 'dynamic variety space axioms'. This involves looking at the
> dynamics of the distribution of variety across multi-feedback loop design
> situations and using axioms I've identified that characterise the change
> behaviour and indicate points of leverage to change the future behaviour of
> the system in particular ways. This is early days for this approach yet.
>
-- Dynamic Variety Space Axioms. This (and much of your argument/points in
this post) seem best applied within technological design developments. But
no matter how much data you receive and how great the computational
analysis is to predict outcomes- you may be missing the simple point that
underlies design thinking: that it is a human centered endeavour. No amount
of mathematics can computate the complexity of human emotion
I hope to learn more of your insight,
Regards,
--
*Stefanie Di Russo*
PhD Student
Faculty of Design
Swinburne University
*twitter:* @stefdirusso <https://twitter.com/#!/stefdirusso>
*linkedin: public
*profile<http://www.linkedin.com/pub/stefanie-di-russo/35/16/a84>
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