From the course: Financial Modeling and Forecasting Financial Statements

Combine historical trends with current plans to forecast

From the course: Financial Modeling and Forecasting Financial Statements

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Combine historical trends with current plans to forecast

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Creating an accurate sales forecast is a topic all on its own. This requires a good market and economic analysis, a good understanding of the expected impact of the marketing plan, intelligence about what the competitors are expected to do, and familiarity with time series statistical forecasting models. Hey, I'm a simple accountant, so the best I can do for you in this course is to make you aware of a few factors that should be remembered when creating a sales forecast. Those three factors are, first, the historical trend, second, the impact of current plans, and third, changes in the competitive environment. Let's illustrate this with a simple numerical example. Spencer Company had sales last year of $1,000. For the past five years, Spencer has done business out of 10 store locations. The average overall sales growth rate has been 8% per year. This is very good performance because this means that the same store locations have been generating more and more sales each year. When announcing their financial results, retail companies often report the growth rate in same store sales. This year, in addition to continuing to operate these same 10 store locations, Spencer has decided to open one new store. Now to keep things simple, let's say that Spencer plans to open this store on January 1st, and that the store will be fully functional and ready for business on that first day of the new year. Okay, so what's your forecast of Spencer's sales for the coming year? If you just put Spencer's historical numbers into a spreadsheet and do a quick growth rate extension, you will get forecasted sales for next year of 1,080, continuing the 8% annual growth rate seen over the past five years. But this myopically focused historical extrapolation completely ignores the existing expansion plan. That new store will add more sales, beyond the increase in same-store sales. If we use last year's value of $100 in sales per store, that's $1,000 in sales divided by 10 stores, then the addition of the new store will bump the forecast up from 1080, that's from only same store sales increases, to 1180, that's 10,080 same store sales plus $100 from the new store. In addition, the historical extrapolation ignores any changes in the competitive environment in the broader economy or in customer tastes. For example, let's say that near the end of last year, Spencer was caught up in a scandal involving dumping of company waste on environmentally sensitive wetlands. Preliminary analysis indicates that 40% of Spencer's customer base will now refuse to buy Spencer's products. Yikes! This reduces the sales forecast from 1180 down to 708. Now we can now have a vigorous and fun discussion about how exactly to handle the interactions among the three factors here. The historical growth, the addition of the new store and the environmental scandal. But you see the general process. The historical trend is the starting point for a forecast of future sales. These historical data should be augmented with as much detail as possible about expansion plans or contraction plans. In addition, some attempts should be made to quantify the impact of changes in the competitive environment.

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