5 Myths About Forecasting in FMCG
In our experience of interaction with the market, FMCG has a paradoxical situation with forecasting. The value of a good forecast is recognized by 100% of companies. And only 10% of them use special tools for forecasting. The reason is that business incorrectly perceives and uses the information received — common myths and false ideas interfere. Let's talk about the five most "popular" myths about forecasting.
1.A forecast is a prediction
The myth arose due to confusion in terminology. The prediction speaks of a future that cannot be changed. Oedipus was predicted to kill his father — and this was inevitable, no matter how the heroes of Sophocles tragedy tried to avoid it.
The forecast tells about events that will occur under certain assumptions. The very meaning of the forecast is to change the future — to our advantage. For example, Company X was supposed to go bankrupt by 2021, but this did not happen. Was it predicted badly? No, it was management who found out about the negative scenario and prevented its development.
2.It is useless to predict
The myth is associated with a misunderstanding of the limits of predictive analytics capabilities. A poor quality forecast is always an
additional cost. For example, an underestimated sales forecast
additional cost. For example, an underestimated sales forecast
leads to missed sales, and an overestimated one leads to the write-off of goods. Faced with this, managers stop believing in the applicability of forecasting in a particular business. And in vain. Forecasts are always wrong - we will talk about this further - but this does not mean that they are useless.
3. Mathematics can be applied everywhere
This myth is associated with an overestimation of the capabilities of applied mathematics and neural networks. Qualitative data and tools alone are not enough to create an ideal forecast - an expert assessment is needed. But when we add an expert, we get a subjective assessment. Managers may distort the forecast consciously or unconsciously.
Unconscious distortions are associated with:
Unconscious distortions are associated with:
Data
perception
we handle non-linear dependencies poorly
Special
cases
we carry the characteristics of particular cases over to large populations
Social
behavior
we aim to agree the forecast with management's vision or somebody else’s opinion
High
self-esteem
we tend to overestimate our abilities
Conscious (or motivational) distortions are changes in the forecast by managers for their own purposes:
Increasing the forecast
- for the sake of achieving financial goals
- to produce more goods to meet potential demand
- for fear of displeasing management with low forecasts
Forecast reduction
- due to production constraints and other factors
- to exceed the sales plan and get bonuses
There are also cases:
- when top management manually changes the forecast due to distrust of mathematics or the forecasting process - the so-called "evangelistic" forecasting;
- when employees hide important information that affects the forecast;
- when management distorts the forecast to justify the costs of launching a new product, promo, advertising, etc.
4.The forecast is a single number
The market is used to point forecasting, in which the forecast is a single number. It was the point forecast that was discussed in myth
2, when we said that forecasts are always wrong.
There is another way of forecasting — interval one. Based on the distribution, the intervals in which the forecast will fall with a given probability are calculated. The wider the interval, the higher the probability of a hit. How to work with these values? We will explain it in the fifth myth.
There is another way of forecasting — interval one. Based on the distribution, the intervals in which the forecast will fall with a given probability are calculated. The wider the interval, the higher the probability of a hit. How to work with these values? We will explain it in the fifth myth.
5. The forecast is important in itself
When making decisions, the marginal values of the interval forecast may be more important than the most likely ones. The most obvious example is inventory management. For products with low cost, writing off the expired goods is less dangerous than under-production. It is logical to produce more goods to ensure maximum demand. And vice versa: if it is very expensive to write off the goods, it is better to produce a volume that is guaranteed to be sold.
Conclusion:
The forecast is a working tool, without which it is difficult to plan production, sales and other processes. And if you free yourself from the captivity of myths and prejudices, then you can get the maximum benefit from forecasting.
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