Forecast for capacity, execute against demand

We have already made the point that in today s volatile business environment it is much harder to achieve high levels of forecast accuracy for individual items. Whilst managers will always be seeking better forecasts, the fact is that as uncertainty increases it gets harder to run a business on the basis of forecast demand at the stock keeping unit (SKU) level. Instead the focus has to be on how the company can move from a forecast-driven to a demand-driven mentality. Basically what this means is that ways have to be found to make it possible to react to demand within the customer s order cycle. Thus if the customer s expectation is for a five-day lead time from order to delivery, the goal is to be able to respond within that lead time. 

Whilst forecasts will always be required, the argument is that what we should be forecasting is not at the individual item level but rather for aggregate volume to enable the company to plan for the capacity and the resources that will be required to produce that volume. 

Part of the reason that so many forecasts have so little accuracy is that they try to achieve the impossible, i.e. to forecast at the individual item level (SKU) too far ahead. Clearly every business needs to plan ahead in order to ensure that they have access to enough capacity and materials. Flowever, wherever possible these plans should be made on the basis of high-level aggregate volume forecasts at the product family level. As we get closer to the point of demand fulfilment then we can start to think about product mix requirements. 

Because the stage f forecast was based upon a statisticai projection using past data, it may be necessary to modify it utiiising specific inteiiigence on currenf markef conditions and events. Thus, for exampie, there may be information about a pianned competitive product iaunch that couid affect our saies, or there is a change pianned for the price of the produot which couid impact saies and so on. 

Idealiy, this stage of fhe S OP process shouid invoive key customers or accounts. Later we wiii discuss the benefits of moving towards a coiiaborative approach to forecasting and suppiy chain pianning. The benefit of a joinf suppiier/ customer process to create a forecast is that a wider array of infeiiigence can be taken into aooount. 

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