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THE MS APPROACH 11

Solutions and Recommendations
Once the problem analysis is complete through the use of an appropriate MS model,
we should be in a position to offer a solution – or sometimes alternative solutions – for
the problem. However, it is important to realize that such solutions must be placed in
the wider problem context. MS is rarely able to offer a definitive solution to a manager
in the form: this is what you should do. Rather the application of MS generates addi-
tional information about the problem – and often this information is available only
through the application of MS – which the manager must evaluate alongside other
information they will have about the problem. In the case of the College, through
appropriate application of MS we may be able to offer potential solutions to the
President for consideration. However, these solutions will need to be placed in the
wider problem context – what budget is available for any changes to road layouts, for
example; what would staff and student reaction be to such changes? And so on.
Implementation

Finally, we come to implementation of the solution. Again, this is likely to be a
managerial action rather than that of the management scientist. However, the man-
agement scientist has an important role to play here. Successful implementation of
results is of critical importance to the management scientist as well as the manager. If
the results of the analysis and solution process are not correctly implemented, the
entire effort may be of no value. It doesn’t take too many unsuccessful implementa-
tions before the management scientist is out of work. Because implementation often
requires people to do things differently, it often meets with resistance. People want to
know, ‘What’s wrong with the way we’ve been doing it?’ and so on. One of the most
effective ways to ensure successful implementation is to include users throughout the
modelling process. A user who feels a part of identifying the problem and developing
the solution is much more likely to enthusiastically implement the results. The success
rate for implementing the results of a management science project is much greater for
those projects characterized by extensive user involvement.

And of course that brings us back full circle in Figure 1.1 to Problem Recognition! It
will be necessary to set up some observation system so that the solution that has
been implemented is monitored and evaluated so that we will know whether the
problem has been resolved or whether further analysis and work is needed.
It is also worth commenting that in practice the management science methodology
outlined, will not be as neat, logical or as easy as it appears in Figure 1.1. In practice
many management science problems are messy and will require an iterative approach
where we move back and forth across the different stages of the methodology. We may
develop an agreed problem structure and definition but when we move on to the
Modelling and Analysis stage we realize our problem definition was inappropriate
and needs revisiting. We may develop what we believe to be an appropriate model and
make recommendations only to find that the recommendations cannot realistically be
implemented because of factors our model did not take into account. Figure 1.2 is a
more realistic picture of the methodology we’re likely to have to follow in real life
indicating that we may have to jump around the approach a lot, go back to earlier
stages, redefine the problem and so on. It looks a mess, doesn’t it? And that’s deliberate
because a lot of MS in the real world is messy (ask any management scientist). We start
by recognizing that there’s some problem. We do some problem structuring and then
some modelling and analysis. It may be at that stage we realize we haven’t actually
structured and defined the problem properly so have to go back a step. Eventually
when we’ve got the analysis right we present recommendations to the client who tells us
they are not realistic or practical so may have to go back to the drawing board again.

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