forecast error

Forecast error | Increase the accuracy of your demand plans

 

forecast error

Rob Crellin

Forecast error – What does your historical demand really mean? Can you explain why demand in a particular period is exceptionally higher or lower that what you had forecasted? More importantly, do you know how best to manage these exceptions?

In this article, Supply Chain expert Rob Crellin explains how historical demand data is a critical source of information for assessing both the performance of a business as well as anticipating future demand. Given that this data will be used by a broad range of departments across the business to determine everything from future purchasing requirements to production plans, it is vital that the demand history is as accurate as possible. However, even if the process for recording retrospective demand is flawless, this raw data alone may not be sufficient to base such critical demand forecasts.

After all, how can you be sure that a shift in demand is the result of “normal” business conditions? What if your sales team were incentivised to push this particular product or what if a customer decided to make a larger order than usual to save on logistics costs? Given that such factors may be totally irrelevant for the purposes of forecasting, should such data be included in the forecasting error process? If so, to what extent?

Unless you have a complete understanding of the true causes behind an exception, you cannot be sure how relevant such data will be in determining future demand. Ultimately, without working in collaboration with the wider business, you simply cannot guarantee the reliability of your demand history. Equally, unless you review demand history effectively, how can you be sure that your service levels are appropriate?

Watch the forecast error video now!

Watch our latest installment of the webinar series “forecast error – 5 steps to supply chain success” as we explore how you can work more effectively with the sales, supply chain, operations and finance team in order to gain a greater understanding of why exceptions in the demand history exist and how you can utilise insights from across the business to manage them. This short recording of the webinar will highlight the steps you can adopt within your organisation to overcome the following challenges whilst avoiding forecast errors:

  • Ensure sales related supply chain KPIs (OTIF, fulfillment rates, etc.) are achieved
  • Highlight problem areas and identify the true causes of such expectations
  • Adopting the right approach to manage demand history exceptions
  • Communicate a single “one truth” of historic demand across the business
  • Alignment of your forecast to the “real” demand

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