Forecasting is usually easier when you break your forecast down into components. As an example, consider a forecast that simply projects $1,000 in sales for the month, compared to one that projects 100 units at $10 each for the month. In the second case, when the forecast is price x units, as soon as you know the price is going up, you know that the resulting sales should also increase. Thinking of the forecast in components is easier.
The first illustration for this article shows a units-based sales forecast. It takes assumptions for sales in units, then the assumed average prices, and multiplies them to calculate sales dollar values. Then it takes assumptions for unit costs and uses them, along with unit sales assumptions above, to calculate direct cost of sales.
The units-based sales forecast illustration
Graphics as forecasting tools
Business charts are much more than just pretty pictures; they are an excellent tool for understanding and estimating numbers. You should always create charts to illustrate your sales forecast, then use them to evaluate the projected numbers. When you view your forecast on a business chart, does it look real? Does it make sense? It turns out that most humans sense the relative size of shapes better than they sense numbers, so we see a sales forecast differently when it shows up in a chart. Use the power of the computer to help you visualize your numbers.
For example, consider the monthly sales chart shown in the next illustration. You can look at this chart and immediately see the ebbs and flows of sales during the year. Sales go up from January into April, then down from spring into summer, then up again in the autumn. When you look at a chart like that, you should ask yourself whether that pattern is correct. Is that the way your sales go?
The next chart, Annual sales forecast, shows a comparison of three years of annual sales. Here again, you can sense the relative size of the numbers in the chart. If you knew the company involved, you’d be able to evaluate and discuss this sales forecast just by looking at the chart. Of course you’d probably want to know more detail about the assumptions behind the forecast, but you’d have a very good initial sense of the numbers already.
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