You can use trend analysis to forecast how your business will perform, but you have to be aware of the method's limitations. When business variables, such as sales, revenue or customer complaints change over time, you can observe patterns that make up the trends, allowing you to project historical data to obtain future values. Knowing which factors influence the validity of your analysis lets you establish the pros and cons of using trend analysis for your particular situation.
Trends can increase or decrease linearly or exponentially and they may depend on cyclical or seasonal factors. You can analyze them using manual methods such as plotting graphs and matching curves or with software such as Excel spreadsheets. The overall pros and cons are influenced by how predictable the trends are, how likely it is that they have been influenced by random events and whether you have correctly identified variable factors such as weather, competitor initiatives or economic changes.
Trend analysis is often a quick method to gain insights into your business operations and obtain rough forecasts for key business variables. For example, if sales have increased 3 percent every year for the past five years, you can forecast a probable 3-percent increase for next year. If your summer season usually results in a 20 percent increase in revenue from outdoor goods, you can predict the same increase for next summer. Entering historical data into a spreadsheet lets you carry out more detailed analysis and output mathematical projections. The historical data is usually readily available and you don't need any other inputs or outside help to make the relevant forecasts.
Because trend analysis is based on historical data, both accuracy and reliability of such forecasts suffer when the business environment changes or when you mistake cyclical trends for long-term influences. For example, if a new competitor enters your market, your sales, revenue and profit may all decrease unexpectedly and your trend analysis based on past data will give forecasts that are too high. If you come to the end of a recessionary business cycle and you have analyzed the cyclical influence as a long-term trend, your forecasts are going to be too low as an expansionary cycle takes hold. When you don't know how changes might affect your business, your forecasts based on trend analysis are not reliable.
You can make the best possible use of trend analysis by examining the data and your markets to take advantage of the pros and minimize the effect of the cons. Checking your trend analysis with additional data from industry publications and the public results of competitors helps validate your results. If your business situation and competition hasn't changed, your trend analysis will be reliable. If historical data is consistent with few outliers and little data point variation, your results will be accurate. If forecasts differ for related variables, such as for sales and revenue, your trend analysis may be faulty and you will need additional methods, such as an analysis of current market conditions, to obtain reliable and accurate forecasts.
