Organizations
are composed of managers who make decisions using both rational and intuitive
processes; but organization level decisions are not usually made by a single
manager. Many organizational decisions involve several managers. Problem
identification and problem solution involve many departments, multiple
viewpoints, and even other organizations, which are beyond the scope of an
individual manager. Research into organization level decision making has
identified four types of organizational decision making processes; the
management science approach, the Carnegie model, the incremental decision
process model, and the garbage can model.
MANAGEMENT SCIENCE APPROACH
The
management science approach to organizational decision making is the analog to
the rational approach by individual managers. Management science came into
being during World War II. At that time, mathematical and statistical
techniques were applied to urgent, large scale military problems taht were
beyond the ability of individual decision makers. Mathematicians, physicists,
and operations researchers used system analysis to develop artillery
trajectories, antisubmarine strategies, and bombing strategies such as salvoing
(discharging multiple shells simultaneously). Consider the problem of a
battleship trying to sink an enemy ship several miles away. The calculation for
aiming the battleship’s guns should consider distence, wind speed, shell size,
speed and direction of both ships, pitch and roll of the firing ship, and
curvature of the earth. Methods for performing such calculations using trial
and error and intuition are not accurate, take far too long, and may never
achieve success.
This
is where management science came in. Analysts were able to identify the
relevant variables involved in aiming a ship’s guns and could model them with
the use of mathematical equations. Distance, speed, pitch, roll, shell size,
and so on could be calculated and entered into the equations. The answer was
immediate and the guns could begin firing. Factors such as pitch and roll were
soon measured mechanically and fed directly into the targeting mechanism. Today,
the human element is completely removed from the targeting processes. Radar
picks up the target and the entire sequence is computed automatically.
Management
science yealded astonishing success for many military problems. This approach
to decision making diffused into corporations and business schools where
techniques were studied and elaborated. Today, many corporations have assigned
departments to use these techniques. The computer department develops
quantitative data for analysis. Operations research departments use
mathematical models to quantify relevant variables and develop a quantitative
representation of alternative solutions and the probability of each one solving
the problem. These departments also use devices such as linear programming,
Bayesian statistics, PERT charts, and computer simulations.
Management
science is an excellent device for organizational decision making when problems
are analyzable and when the variables can be identified and measured.
Mathematical models can contain a thousand or more variables, each one relevant
in some way to the ultimate outcome. Management science techniques have been
used to correctly solve problems as diverse as finding the right spot for a
church camp, test marketing the first of a new family of products, drilling for
oil, and radically altering the distribution of telecommucations services.
Other problems amenable to management science techniques are the efficient
scheduling of air crews for commercial flights and the training of crews, as
illustrated in the following case.
Management
science can accurately and quickly solve problems that have too many explicit
variables for human processing. This system is at its best when applied to
problems that are analyzable, and can be structured in a logical way.
Management
science has also produced many failures. Part of the reason, as discussed in
the preceding chapter, is that quantitative data are not rich. Informal cues
that indicate the existence of problems have to be sensed on a more personal
basis by managers. The most sophisticated mathematical analyses are of no value
if the important factors cannot be quantified and included in the model, such
as happened when Quaker Oats decided to acquire Gaines. Such things as
competitor reactions, consumer “tastes”, and product “warmth” are qualitative
dimensions. In these situations, the role of management science is to
supplement manager decision making. Quantitative results can be given to
managers for discussion and interpretation along with their informal opinions,
judgment, and intuition. The final decision can include qualitative factors as
well as quantitative calculations.
