Forecast Error Benchmarking across various industry – survey results

August 22nd, 2012 by Rohan Asardohkar

Our Newsletter readers and forum participants ask very frequently:

· Which metrics should I use to measure my forecast performance – WMAPE, MAPE, Bias or something else?

· Is there any benchmark available for forecast error, particularly within my industry?

With this in mind, this past Spring we started conducting the survey across supply chain and demand planning professionals from various industries. This survey was meant to compile information about their pain points, forecast error metrics they use, industry they work for, and who owns the demand planning function. We are publishing the first installment of the results from this survey in this newsletter.

As expected one of the metrics used by 52% of the respondents is WMAPE or volume weighted MAPE, calculated as Sum of Absolute errors divided by sum of actual demand.

We have good informative data for Chemical, Consumer Goods (CPG) industries with a good sample size and participation from a broad range of companies.  CPG in our study included Food and Beverages as well.  For CPG industries average of forecast error is 39%.

One of the common pain point for CPG folks is number of variables such as price fluctuations, promotion timings, and new items. For Chemicals industry the average of forecast error is 36%.  Promotions are not formally planned or executed in Chemicals as in CPG, however there may be price incentives etc.

Please share your views and pain points as comments on this blog or on our linked-in forum.

We welcome you to participate on this survey.  If you fill out the survey you will get PDF copy of Dr. Mark Chockalingam’s presentation on “Is S&OP for you?” that will be presented in the Fall.

Here is the link to survey – https://docs.google.com/spreadsheet/viewform?formkey=dHg0ZVZWel9PZXctWnVWV3ZlS0xwcmc6MQ#gid=0

Welcome to Fall!

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One Response to “Forecast Error Benchmarking across various industry – survey results”

  1. Hi Mark / Rohan, thanks for sharing your survey results — this is an interesting topic. I had a question on your computation of the Average Forecast Error by Industry: Given the various error metrics the different companies use, how do you combine them into an industry average?

    For example, one company has MAPE of 40%, another has WMAPE of 30%, and another has Forecast Attainment of 80%. What would be the “industry average” for these three?