Modeling the Dynamics of the Obese Population
Real Food Prices
Complementors, a concept introduced by Brandenburger
and Nalebuff, are players whose products or services add value
when bought together. The Value Net makes it clear that ignoring them—which happens frequently—can be a costly mistake.
For example, in the computer industry, microprocessor manufacturers and software developers are complementors: The
more powerful the microprocessor, the more sophisticated the
software, and vice versa (see Figure 6).
With an understanding of how the four types of players interact, and realizing that they do not necessarily have to battle
zero-sum games, Brandenburger and Nalebuff identify elements
that should be part of any sound strategy.
The purpose of System Dynamics is to model the evolution of
complex systems that respond to feedback loops and are subject
to cause-and-effect delays. Such systems, usually represented in
physics by sets of differential equations, depict many real-world
situations. System Dynamics has been applied to the study of
the Cold War arms race, simulation of scenarios of OPEC oil
production, forecasting the demand for life insurance, under-
standing company morale, predicting the evolution of the obese
population, etc. System Dynamics has also been used to cre-
ate Management Flight Simulators, analytical tools that help
managers improve their understanding of the environment in
which their companies operate and to practice decision making.
For a general description of this tool, including the Causal Dia-
gram shown in Figure 7, see System Dynamics in the September/
October 2011 issue of Contingencies.
One of the building blocks of System Dynamics is Causal
Diagrams, which depict cause-and-effect relationships between
relevant variables. If you can draw correctly the causal diagram,
you understand how the system operates—and you can model it.
For example, key aspects of the evolution of the obese popula-
tion can be represented as follows (see “Modeling Obesity” in the
November/December 2012 issue of Contingencies) (see Figure 7).
With the mathematical model, policymakers can test sce-
narios and answer questions such as the following:
■ ■ What would the effect of taxes on unhealthy food be—a re-
duction or an increase in the obese population? (The answers
might be surprising.)
■ ■ Will the obese population reach a point of equilibrium if no
actions are taken to curb obesity?
■ ■ If actions are taken to reduce obesity, how much time will it
take for these initiatives to yield results, and how significant
will they be?
■ ■ What is the expected increase in health care costs to society?
■ ■ What are the effects of increasing obesity on quality of life?