Strengthening the Empirical Base of Operations Management

Fisher: Strengthening the Empirical Base of Operations Management
374 Manufacturing & Service Operations Management 9(4), pp. 368–382, © 2007 INFORMS
would be more effective than an expert system.
Clearly, the work at Westinghouse has structured the
problem to the point where one can visualize applying
ideas like those in Ross (1971). Forexample, it is
tempting to think of the 350 identified failure conditions
as states in a Markov process and the actions
available to the expert as the actions in Ross’s model.
However, the scale of real problems is several orders
of magnitude bigger than the problems addressed in
the literature, so computational tractability could be a
majorchallenge.
5. Principles
Prescriptions derived from empirical research can be
numeric and detailed, such as the output of an algorithm,
or more qualitative principles that provide general
guidance but require some interpretation on the
part of the user. Perhaps the best example of prescriptive
principles is the Toyota Production System, which
provides guidance on how to structure a production
process and manage workers to achieve a high level
of quality and productivity.
My favorite example of principles reported in the
academic literature is the study by Jordan and Graves
(1995), which describes several principles of manufacturing
flexibility derived from empirical research
within the auto industry. They consider a company
that makes N products with uncertain demand in M
factories with fixed capacity. Because of the limited
capacity, it may not be possible to satisfy fully a particulardemand
realization. The amount of demand
that is satisfied can be increased by providing the
flexibility to make a particular product in more than
one plant. In the extreme, when every product can
be made in all plants, demand can be fully satisfied
as long as total demand forthe N products does
not exceed the total capacity of the M plants. However,
providing this maximal level of flexibility is usually
prohibitively expensive, so Jordan and Graves
(1995) ask how closely more limited flexibility would
come to achieving the demand satisfaction benefits
of full flexibility. Starting with this natural question
and drawing on insights gleaned from extensive interaction
with General Motors managers, they derive
several principles of flexibility and provide analytic
support for these principles.
Their sharpest result is stated as a property of the
product-plant assignment graph, which has a node
foreach product and foreach plant and an arc connecting
product node i with plant node j if product i
can be made in plant j. They show that when M = N ,
the ability to make each product in just two plants
provides nearly the same level of demand satisfaction
as full flexibility, provided the product-plant assignment
graph is connected.
6. Integrating Theory and Empirics
As discussed at the start of this paper, medicine,
physics, and finance have benefited from a healthy
synergy between theoretical and empirical research.
Theoreticians develop hypotheses that are verified
by empiricists, and empiricists identify interesting
phenomena in the world to be explained through
additional theories. Some examples of research that
integrates theory and empiricism are beginning to
emerge in our field.
One such example focuses on a betterunderstanding
of the relationship among the four traditional
performance measures in operations management:
cost, manufacturing conformance quality, delivery
speed, and flexibility. Traditionally, these measures
have been thought to trade off against each other.
For example, improving quality meant increasing cost
(we will use cost and quality as ourexamples in
the rest of this section, although it should be clear
that the concept is also applicable to the otherperformance
measures). More recently, Clark (1996) and
Hayes and Pisano (1996) have suggested that companies
can and do follow improvement paths that simultaneously
increase quality and reduce cost.
A little thought makes it clearthat a company
can take various actions to improve quality; some of
those actions will increase cost and some will reduce
cost. To illustrate, consider a process that produces
a product with a 10% defect rate. An inspector at
the end of the process attempts to cull out defective
units to be reworked or scrapped. But because
inspection is imperfect, the inspector only catches half
the defects, resulting in a 5% defect rate reaching
the market. Adding a second inspector who independently
detects half the remaining defects would
reduce the defect rate to 2.5% but would increase cost
because of the expense of the additional inspector,