So now we've looked at four questions and how these were used to
produce some positive outcomes in The Good Kitchen story, as well as, I know,
many other stories that I could have told you about.
But design thinking is not a kind of one size fits all solution.
Design thinking works best on particular kinds of problems.
How do I identify the kinds of problems that design thinking is really suited for
versus those that our traditional analytic tool kit is better suited for.
Well earlier Jeremy talked about the differences between mysteries and
puzzles as one way to understand the difference between the kinds of
problems design-thinking solves.
Relative to the more ordered even if more complex problems that
traditional analytics work well for.
Another way that designers have talked about this distinction between different
types of problems and which I have always found particularly helpful
is the difference between problems that are wicked versus problems that are tame.
With tame problems we start with good agreement about the definition of what
the problem is.
We often have fairly relevant data and we can determine cause and effect.
And so we can successfully use linear processes and
existing data to come up with an answer.
None of these conditions apply to wicked problems.
In wicked problems, the stakeholders involved can't even agree on
a definition of what the problem is, much less agree on a solution.
There may be a lot of data, but it's not clear whether any of it is relevent or
how, and the situation is often sufficiently complex and fluid, so
that we can't really confidently predict cause and effect.
And the only way to see if something works is to try it.
Those of us living in the US will recognize, for
instance, that health care is clearly a wicked problem that we've been trying to
solve as though it was a tame one for many decades here.
Here are a few questions to ask yourself as you consider whether the problems you
have might be wicked or tame, and so lend themselves to design thinking or not.
Well, the first question to ask is, is this problem human centered?
Design thinking is appropriate if a deep understanding of the actual people or
users involved is essential.
Linear analytic methods may be better if there are few human beings involved in
the problem or the solution.
A second question to ask is how clearly do you understand the problem itself.
If we need to explore and
perhaps build agreement even around the definition of the problem.
Design thinking, is an appropriate method?
On the other hand if we understand the problem clearly and
are sure that we're solving the right one.
Linear methods may work better.
What's the level of uncertainty,
is another important question to ask yourself.
If there are many unknowns, both large and small, and
past data is unlikely to help us, design thinking is appropriate.
If, on the other hand, the day that you've got on the past is a pretty good
predictor of the future analysis works.
Finally, I'd encourage you to think about what data is already available to you.
If there's very little relevant existing data, then design thinking is appropriate.
If, on the other hand, there are several clear sources of analogous data,
linear analytic methods may work better.
So once you're sure you have the right kind of problems and
opportunities for design thinking to address.
You're ready to roll up your sleeves and get started.
In our upcoming sessions,
we will explore a 15 step model that will walk you through the four questions and
help you think about the kinds of design tools best suited to each stage.
We've talked today about what the first few of these important steps looked like.
Steps like identifying the right kinds of problems for design thinking.
And steps like then scoping the problems correctly and keep in mind how
the good kitchen started out with too narrow a definition, and fix the menu.
We'll learn more about these tools as we go through the class.
You can always learn more about the tools and
process by turning to our book, Designing for Growth.