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Virtually every manufacturing or service company needs to generate forecasts of their short to medium term sales. Being able to forecast demand more accurately has major commercial advantages, whether the forecast is used:
Yet within real world markets, many factors conspire to make accurate forecasting difficult to achieve.
In the first place, sales forecasts are frequently used for all the purposes suggested above. This leads to conflicts between optimism and pessimism and potentially introduces 'political' influences into the process. Examples are the different role of the profit forecast (probably conservative) and the sales plan (probably optimistic), or where marketing expenditure is closely associated with the turnover of brands (and therefore leads to defensive forecasting to protect planned marketing spends). There are also conflicts in terms of which units should be forecasted - orders-based for production forecasting and invoice-based for financial forecasting.
Similarly, forecasts by week by sku (stock keeping unit) for the next 12 weeks may be required by production planning. But, this time horizon is far too short and this level of detail is potentially much too great for marketing and sales planning purposes.
The important point is to have a clear vision of who the primary Customer or Customers of the forecasts are. Select the appropriate level of detail and time horizon accordingly and accept that secondary customers will probably have to accept sub-optimal forecasts. In many situations it is helpful for both Marketing and Sales to generate sales forecasts. Sales are often more likely to possess the detailed short term knowledge whilst Marketing need to 'own' the forecasts as a result of their role as brand profit 'custodians', and possibly have a clearer knowledge of longer term influences. It is vital here that each area is clear about the role and purpose of the forecasts they produce, and that issuance schedules optimise the currency of the data used as inputs, and given as outputs, by each forecaster.
The second major difficulty of forecasting in real world markets is the very nature of these markets. They frequently exhibit some or all of the following characteristics:
This makes it hard for traditional forecasting approaches such as statistical methods to provide acceptable results over a short to medium time horizon.
Peter Boulton was a full time sales forecaster for 10 years, prior to moving into software design and development. His company, Data Perceptions, specializes in the development of Sales Forecasting, Planning and Budgeting software. Contact Peter at http://www.DataPerceptions.co.uk or email firstname.lastname@example.org
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