Importance of Statistics to Industry & Business

by Jim Woodruff - Updated June 28, 2018
Statistics are important to industry and business because they allow companies to quantify progress and potential success.
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Business managers use statistics as an aid to making decisions in the face of uncertainty. Statistics can be used for making sales projections, financial analysis of capital expenditure projects, constructing profit projections for a new product, setting up production quantities, and making a sampling analysis to determine the quality of a product. Using statistics provides real data about complex situations rather than making decisions based on unsubstantiated hunches.

Performance Measurement

A common use of statistics is as a measure of performance. For example, you might gather data about a small number of product units to make an estimate about the quality level of an entire batch of production; this is known as statistical sampling and is used to determine whether to accept or reject a batch. Another use could be the analysis of the production output of an employee to find out if the worker is meeting the desired productivity standards. If not, adjustments such as improvements in equipment, change in the work environment or better communication may be needed.

Forecasting

Managers analyze past data to find statistical trends and make predictions about the future. For example, you might analyze the previous sales of all products sold to make estimates about the volume of future sales under specific economic conditions. In turn, these projections would then be used to set up production schedules.

As an example, consider the farmer who has to decide whether to plant soybeans or corn. Of course, the farmer wants to maximize the number of bushels produced under good or bad weather conditions; each weather condition has a certain probability of occurring. An analysis of historical data will show the volume of soybeans or corn produced over a range of weather patterns in a particular geographical area. From this statistical model, the farmer can make an informed decision about which product to plant.

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Risk/Return on Investments

The objective of a new capital expenditure project is to optimize the return on the investment and minimize the risk. Use statistical methods to evaluate the project under different economic environments, changing consumer preferences and strength of the competition.

Market Research

Companies use statistics in market research and new product development. They take random surveys of consumers to gauge the market acceptance and potential for a proposed product. Managers want to know if there will be enough demand for the product. Is there enough demand to justify spending money to develop the product and, ultimately, to build a plant to produce it? From the statistical analysis, a break-even model is constructed to determine the volume of sales necessary for the product to succeed.

Limitations of Using Statistics

While using statistics to make decisions is helpful, it has limitations. For example, the size of the sample used in market research is a factor. Larger samples would produce a better quality of results, but larger samples cost more money and are sensitive to the law of diminishing returns. This is the classic trade-off between the cost of getting more precise results against budget and time constraints.

Using historical data to construct statistical models for forecasting does not take into consideration any causal changes in the marketplace. Economic environments are constantly changing and so are consumer behaviors and tastes. Managers must have an awareness of these changes and incorporate them into their decisions.

When properly used, statistical methods make the decision-making process much easier. However, the application of statistics is both an art and a science and should not be used as the sole basis for making decisions. When interpreting the results of statistical analysis, exercise judgment based on your own real-life experience and other qualitative factors that are not incorporated into the mathematical model.

About the Author

James has been a management consultant to more than 1,000 small businesses. As a senior management consultant and owner, he used his technical expertise to conduct an analysis of a company's operational, financial and business management issues. James has been writing business and finance related topics for blogs and e-commerce websites since 2007. He graduated from Georgia Tech with a Bachelor of Mechanical Engineering and received an MBA from Columbia University.

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