108 HIGH-INVOLVEMENT INNOVATION
Once the nature of the problem has been analysed, the next stage is to explore
ways of solving it. There may be a single correct answer, as in crossword puzzles
or simple arithmetic—but it is much more likely to be an open-ended problem
for which there may be a number of possible solutions. The challenge at this stage
is to explore as widely as possible—perhaps through the use of brainstorming or
other group tools—to generate as many potential solutions as possible.
Next comes the selection of the most promising solutions to try out—essentially
the reverse of the previous stage, since this involves trying to close down and focus
from a wide range of options. The selectedoptionisthenputintopractice—and
the results, successful or otherwise, reviewed. On the basis of this evaluation, the
problem may be solved, or it may need another trip around the loop. It may even
be the case that solving one problem brings another to light.
In terms of learning, this is essentially a model for experimenting and evaluating.
We gain knowledge at various steps in the process—for example, about the
boundaries of the problem in defining it, or about potential solutions, in exploring
it or about what works and what does not work in implementing it. The point is
that, if we capture this learning, it puts us in a much better position to meet the
next problem; if it is a repeat, we already know how to solve it. If it is similar, we
have a set of possible solutions that would be worth trying. And if it is completely
new, we still have the experience of a structured approach to problem solving.
Why use a structured approach? In theory, the model looks pretty useful for
ensuring that we find and solve the right problems, and that we learn from the
experience. In practice, things are often less successful—mainly because the cycle
is not always followed in quite the way described. For example, we often jump over
the stages in the cycle and, in taking short-cuts, miss out on alternative solutions,
which might be better. We often fail to define the problem and instead assume
that the initial ‘presenting’ problem is the one to be solved; a bit more analysis
may reveal that this is a symptom or a by-product of the real one. Alternatively,
it may be that defining the problem reveals that it is too big to be solved, or that
it is owned by others who have good reasons for not wanting to solve it, or have
already tried, and so on.
Table 6.4 lists some common limitations to effective problem solving, which
restrict the learning possibilities.
For these reasons training and practice in using such a cycle are critical to
building firm foundations for high-involvement innovation.
This process of problem finding and solving has been applied to many different
types of problems and improvement opportunity—for example, reducing the set-
up time on machinery, reducing defects in a particular area and reducing the time
taken to respond to customer enquiries (Shingo 1983; 1986). It is often embedded
in broader methodologies—for example, much training in TQM is based on what
has come to be termed the ‘Deming Wheel’—a simple version of the above model
with four stages—Plan, Do, Check, Act.
Lack of Suitable Vehicles for Driving Forward High-Involvement Innovation
The issue here is how to mobilize the creativity of everyone in the organization
and channel it into finding and solving problems and identifying improvement
opportunities. A few ideas popping up at random are unlikely to have much of