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Forecasting research project ideas

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There are some things every company should know about the nature of its business. Yet many organizations don't know these fundamentals -- either because they are short on resources, or their resources don't have the analytical skills to do the work.

Lancaster Centre for ForecastingThe summer research projects offered by the Lancaster Centre for Forecasting, offer a cost-effective way to get yourself some answers.

Project Ideas

If you haven't done these things already, here are a few of my personal favorite projects to get started:

  • Compare your last year of forecasting performance to a naïve model.

This is the start of any forecasting improvement endeavor -- find out how you are doing today. Don't compare your performance to industry benchmarks, those are irrelevant. Find out whether your process performs at least as well as a simple method, such as a random walk or moving average forecast. (And don't be surprised to learn you are forecasting worse!)

  • Evaluate the volatility of demand for your products or services.

The Coefficient of Variation is a crude and imperfect, yet still useful indicator of the "forecastability" of your demand patterns. Low CV implies that you should be able to forecast fairly accurately with simple methods. High CV implies that you probably can't expect to forecast as accurately -- although some high CV patterns (e.g. something with lots of seasonality but stable, repeating patterns) can be forecast well.

  • Create the "comet chart" relating volatility to forecast accuracy.

Get a visual summary of your forecasting challenges by seeing how volatility and forecast accuracy are related. Use this as motivation to find ways to reduce the volatility of demand patterns.

Map out your forecasting process, and review the last year of forecasts at each step of the process (e.g. statistical forecast, analyst override, consensus override, executive approved forecast). If, like many companies, you aren't recording the data at each step, then start doing so. Use FVA to determine which steps and participants in the forecasting process are tending to make it better. And eliminate those process steps that are just making it worse. (For more information, view the Foresight/SAS Webinar, "FVA: A Reality Check on Forecasting Practices."

  • Replicate Steve Morlidge's analyses of forecast quality.

In a series of articles published in Foresight, Morlidge defined the "avoidability" of forecast error, and illustrated the value of a RAE (relative absolute error) metric for evaluating performance. Read the Foresight articles, find discussion of Morlidge's methodology in  several earlier BFD posts (such as this one), and view his recording from the Foresight/SAS Webinar series, "Avoidability of Forecast Error".

Doing these will give you a good foundation on which to do further research...

Tags Coefficient of Variation comet chart Foresight FVA Lancaster Centre for Forecasting naive model Steve Morlidge
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About Author

Mike Gilliland

Product Marketing Manager

Michael Gilliland is a longtime business forecasting practitioner and formerly a Product Marketing Manager for SAS Forecasting. He is on the Board of Directors of the International Institute of Forecasters, and is Associate Editor of their practitioner journal Foresight: The International Journal of Applied Forecasting. Mike is author of The Business Forecasting Deal (Wiley, 2010) and former editor of the free e-book Forecasting with SAS: Special Collection (SAS Press, 2020). He is principal editor of Business Forecasting: Practical Problems and Solutions (Wiley, 2015) and Business Forecasting: The Emerging Role of Artificial Intelligence and Machine Learning (Wiley, 2021). In 2017 Mike received the Institute of Business Forecasting's Lifetime Achievement Award. In 2021 his paper "FVA: A Reality Check on Forecasting Practices" was inducted into the Foresight Hall of Fame. Mike initiated The Business Forecasting Deal blog in 2009 to help expose the seamy underbelly of forecasting practice, and to provide practical solutions to its most vexing problems.

2 Comments

  1. Mark Chockalingam on

    Mike,

    Great to see many project ideas for new aspiring forecasters.

    What do you think about all the forecast bashing that is going on in a variety of discussion forums? I know many are self-serving to promote their own interests and consulting services. But as the saying goes, you keep singing the same song many a time, it becomes a super hit!

    Happy New Year!

    Mark

    • Mike Gilliland
      Mike Gilliland on

      Mark,

      I think I've been guilty of some forecast bashing in my time. For example, bashing the dirty tricks of selling forecasting software or services ( #1, #2, #3 ), and bashing some of the really bad practices that are often propagated (as you point out) for self-serving reasons.

      The Business Forecasting Deal's cover art (by Jessica Crews) was meant to caricature the snake-oil-selling nature of our profession. I see it as our duty to expose the false forecasting prophets, and properly represent the capabilities (and limits!) of business forecasting.

      Thanks for the comment.

      --Mike

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