Forecasting and demand planning: how do you benchmark?
Are your competitors’ demand forecasts more accurate than yours? We surveyed supply chain professionals from around the world, to discover how retailers and their suppliers benchmark against key metrics. Kathleen highlights three results from this survey, and the actions your business should take, covering:
- Retailers versus suppliers – whose forecasts are more accurate?
- Which category has most accurate forecasting?
- How common is forecast bias and do businesses tend to under or over-forecast?
Use the insight to compare your performance and make decisions that drive change within your organisation.
Retailers’ forecasts are more accurate than manufacturers’
Retailers lead on accuracy; 63% have forecast accuracy greater than 85%. Only 31% of manufacturers achieve the same level.
Action: there are several methods of reporting forecast accuracy. Consider the limitations of each and make sure that whatever you use works well for your data set. Remember to use a weighted method when forecast accuracy or error measures are aggregated over numerous SKUs. This will ensure that your data set isn’t disproportionately skewed by low volume lines with poor forecast accuracy.
Fresh and chilled forecasts are the most accurate
Forecast accuracy is highest in the fresh and chilled category, where half of manufacturers reported forecast accuracy greater than 90%.
Action: understand which categories and products need the most focus when it comes to forecast accuracy. One explanation for high forecast accuracy in the fresh and chilled category could be the limited shelf life on this type of product. Holding too much stock can increase the risk of write-off, so getting an accurate picture of demand is essential for efficient inventory management in this category. The risk of short shelf life write-off is lower for categories such as personal care and ambient grocery, allowing for a greater margin for error in demand forecasting of these categories.
Over-forecasting is widespread
Manufacturers tend to over-forecast. This effect is particularly strong for promotional products, for which 62% of manufacturers reported over-forecasting.
Action: firstly, understand whether forecast bias exists and then try to uncover its causes. Once you know this, you can create a plan to eliminate or reduce them.
Improve your demand planning and forecasting
This extract comes from our insight presentation entitled Industry benchmarking 2020 - part 4: forecasting and demand planning.
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