In the background of all of our discussions of design thinking,
there's a shift going on that's even more
fundamental than the one behind democratizing design.
In fact, it's the driver of the need to democratize design.
It's a change in the very way we think about organizations themselves.
At its heart, it's about the shift from what
academics call a mechanistic view of organizations.
That is thinking of an organization as though it was a machine that you could control.
To one that sees them as complex social systems,
living organisms that don't always behave the way you want them to.
That sounds abstract, I know,
but let's look at what that really means and all of the important implications for
how we get things done in the reality rather than the theory of organizational life.
So traditionally, we've treated organizations kind of like we treat our cars.
Things that their leaders,
drivers in this case, operate and steer.
They do what we tell them to do unless they have a breakdown.
In this view, they can be controlled and managed and decisions get
made based on logic and the careful evaluation of consequences.
What academics might call the rational actor model.
Today we know that this is just not true.
And we increasingly acknowledge the reality that organizations are
collections of human beings who are motivated by different logic and perspective,
who sometimes react based on emotions and politics and bureaucracy,
rather than by careful comprehensive decision making
that optimizes choice the way the rational actor model pretends they do.
You know at best, organizations are more like riding a horse than driving a car.
They have a will of their own and they're not
always predictable in the choices they make.
These complex human social systems are inherently almost impossible to control.
They are unmanageable and often chaotic.
This is especially true of organizations in the social sector where
controlling them is nearly impossible in many cases.
We can shape and influence their operations but only if we have the right kinds of tools.
And the ones traditionally used in our customary approaches to strategy and policy,
well, they're tools based on assumptions of top down control and predictable outcome.
And so, they don't work very well.
But design thinking does.
It can help innovators deal with the complexity in
modern social systems by giving them
tools that the rational actor approach never thought about.
That's because design focuses instead on innovation as a social process,
intimately tied to human emotions and reliant on human communication and collaboration.
Let's look at how it does this in more detail.
In design thinking, the traditional notion of a single optimal solution
selected from among the set of alternatives identified in advance is rejected.
We replace it instead by a search for
multiple possible solutions with the most promising ideas emerging during the process,
shaped by the conversation among all of the players involved.
In complex social systems,
it is almost impossible to optimize in the usual sense.
We lack both the alignment around objectives and the data to assess cause and effect.
In fact, the emergence of solutions throughout the process,
their diversity and their continuous evolution in change forms one of
the most characteristic themes in
our research on successful innovation in the social sector.
Networks also play a much more critical role in complex social systems.
Increasingly, it is the network that matters.
And design thinking has a unique ability to bring the members of an ecosystem from across
diverse areas of the network into productive conversation with each other.
Equally important, efficiency, the dominant criteria in
stable simple systems must be balanced against
the need for adaptability in complex unstable systems.
Including a diverse set of voices takes time and it takes patience.
It can often feel chaotic,
but out of that chaos we will see better solutions emerge.
One of the things that we see in our research is the avoidance of
top down standardization always a favorite when efficiency is the goal,
in favor of locally determined customized solutions and processes.
Standardization, again, may seem efficient in the short run but in
a complex world it's
adaptability that favor solutions that pay attention to local conditions.
It also favors an emphasis on identifying design criteria, that is,
the qualities of desired solutions in general
rather than on the specific solutions themselves.
Design criteria have more inherent resilience, that is,
they're useful in telling us how to pivot when an initial situation fails.
Diversity plays a very important role here.
Simple stable systems favor
homogeneity and they usually see diversity of input as a nuisance.
They try hard to get rid of it.
In complex social systems,
heterogeneity is more valuable.
Why? Because it increases the range of both the current input we have to
work with as well as the breadth of the solutions we can generate.
The introduction of new and diverse voices helps an organization see more opportunities.
Ones that are not necessarily path dependent on previous choices.
That understanding also produces the possibility for
more intelligent and adaptable coordination.
All of this means that local,
rather than global decision making,
is likely to be more successful in complex social systems.
This is because local intelligence and local action truly matters.
Although the larger system is very complex and difficult to predict,
researchers have found that it's sub-units are less so.
Academics who study social systems have learned that sub-units
tend to operate on what they call replicator dynamics.
These make simple central guidelines established globally but then applied locally.
Often, the most promising method for bringing order and accomplishing change.
These rules generally specify the larger purpose and leave
decisions about the specific content of problems and their solutions to local people.
So, you can think of design thinking as just a set of
simple rules that allow us to coordinate and encourage innovation in
complex social systems and to bring local voices into
the innovation conversation to identify and to solve their own problems.
Jeanne M. LiedtkaUnited Technologies Corporation Professor of Business Administration
