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The following article
was written by Coleman Patterson and
appeared in the Business section of the Abilene Reporter-News.
analysis the way of the future, January 13, 2008, 2D.
Imagine the advantages of being able to
see into the future and accurately predict things that will happen. Students would
be able to know exactly what to study and learn for assignments and exams, parents would
know how to help their children avoid harmful situations, investors could pick rewarding
opportunities and avoid costly ones, and emergency workers could head off hazardous and
harmful situations before they arise. The ability to accurately see the future could
help people make decisions in the present that lead to things they want in the future.
Organizations and businesses of all types
could also benefit from knowledge of the future. The abilities to forecast demand
and supply, prices and profit margins, raw material and operational costs, and customer
flow and employee staffing needs could all help organizational decision makers choose the
courses of action needed to best benefit their organizations. Unfortunately, the
ability to know the future is not something that human beings possess.
The management science field has
tools and techniques that can be used to solve many types of management and organizational
problemssuch as, inventory management, production and process control, product
mixing and blending, transportation assignment and scheduling, maximization and
minimization, and employee scheduling. There are also forecasting techniques that
decision makers can use to make educated guesses about their futures. Linear
regression is one of the most popular and well known of those techniques.
Regression analysis is grounded in the
concepts of correlation. Correlation is a measure of relationship between variables.
Variables can be positively or negatively related or not related. A positive
relationship means that as one variable increases in value, its associated value does as
well. For example, a higher number of sales calls placed should result in higher
number of sales made. A negative relationship means that as one variable increases,
the other variable decreases. As the number of days missed from work increases for a
worker, the performance for that person should decrease. A zero correlation, or no
correlation, indicates that two variables are not relatedsuch as the number of soft
drinks consumed at work and the number of maintenance calls made for copy machine repairs.
When a relationship exists between two
variables, it is possible to predict one with the other. The stronger the
relationship between the variables, the better the predictive power. For example,
when fuel efficiency of a vehicle is known, it is easy to forecast fuel consumption when
distance is known. When a known relationship is not as strong, such as the effects
of an advertising campaign on the sales of an item, the ability to predict the outcome is
not as certain. Regression analysis measures the relationships between variables and
builds a mathematical model to best describe those relationshipswhich can be used to
predict an outcome variable with one or more predictor variables. With education and
training on regression techniques, which can be run in Microsoft Excel, managers can
forecast the future for their organizations.
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