Sales forecasting — common mistakes

In the exam, you may be required to calculate a 3-period or 4-period moving average from a set of data, plot both the original data and the moving average on a graph, and use it to identify the trend and make a forecast. Practise these calculations.

Not necessarily. A 4-period moving average will produce a 'smoother' trend line than a 3-period one, as it averages data over a longer time. This is better for identifying the long-term trend. However, a 3-period moving average is more responsive to recent changes in sales. The best choice depends on the nature of the data and the purpose of the forecast; for example, if sales are based on four distinct seasons, a 4-period average is logical.

While quantitative methods are powerful when good data exists, they should not be used exclusively. They are poor at predicting turning points or the impact of unprecedented events. Qualitative methods, which incorporate expert judgement, can anticipate changes in the market, new competitor actions, or shifts in consumer taste that historical data cannot show. The most effective forecasting often involves a combination of both quantitative and qualitative approaches to get a more rounded and robust prediction.

No, a sales forecast can never be 100% accurate. It is an educated prediction about the future, which is inherently uncertain. There are always random, unpredictable factors (e.g., a sudden change in weather, a new viral trend, a competitor's surprise product launch) that can affect sales. The goal of forecasting is not to achieve perfect accuracy, but to reduce uncertainty and provide a reasonable basis for planning. Businesses should always build flexibility into their plans to account for forecasting errors.