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Mike Gilliland: The BFD

Mike Gilliland AKA: The BFD

At last weeks IBF Supply Chain Forecasting & Planning Conference in Scottsdale, AZ, I had the somber responsibility of facilitating three round table sessions on “Worst Practices in Business Forecasting.”  Thirty-eight of the biggest sinners in the forecasting/demand planning profession confessed to a variety of irresponsible and embarrassing behaviors that we can all learn from:

  • Believing Marketing / Believing Sales / Believing the Customer

Faith-based forecasting is not the way to go. Participants in the forecasting process have their own little biases and personal agendas, so when we solicit their input we must stay on guard. Many of these agendas favor an increase in inventory  which is wonderful if you aren’t responsible for overstocks or obsolescence.

  • Failing to Account for Cannibalization by New Products

New products are great … for creating a lot of forecasting and supply chain headaches. New product forecasts are very often very terribly wrong, which is bad enough. But we usually fail to account for the impact of new product sales on existing products as well. Will I really continue to buy the same amount of fresh mint dental floss, once I’ve switched to the new cinnamon flavor?

  • Over Touching the Forecast

If forecasts could speak Latin, they would probably scream out “noli me tangere!” (Don’t’ touch me!)   There is plenty of evidence that we touch our forecasts too much, and with little beneficial impact. Sure an elaborate forecasting process with lots of participants and collaborative steps sounds like a good idea, but too often these human touch points just add opportunity to contaminate what should be an objective and dispassionate process.

  • Confusing the Financial Plan with The Demand Forecast

There are lots of numbers floating around an organization. We usually start the year with an operating plan and financial forecast projecting monthly revenues and costs. But even the best laid plans will need to evolve with the realities of the marketplace. This isn’t such a bad thing when we recognize that the forecast is diverging from the original plan. Recognizing the gap allows us to address the gap by shaping demand patterns to bring us back on plan, or else changing the plan to match the new demand forecast.  The only bad practice is continuing to believe (and execute) a plan that is based on wishes, not reality.

  • No Appreciation of the Range of Uncertainty

We’re used to seeing our forecasts as point estimates or a specific number of units (or dollars) for a specific product and location, in a specific time bucket. But wouldn’t it be helpful to know the range of uncertainty in that number? Knowing  that the forecast is 100 +/- 10 units can lead to drastically different actions than a forecast of 100 +/- 100 units. Before making major downstream supply decisions, be sure you understand the likely range of outcomes and not just the point forecast.

  • Failing to Address Data Issues

Analysis and modeling need data that is clean, complete, and relevant. While we may do a good job tracking the basics like orders, shipments, and sales revenue, we must take care to not ignore elements that can dramatically impact our forecast. Rigorous tracking of pricing, promotional activity, competitor activities, or other factors influencing demand, allows us to incorporate those factors into our statistical forecasting models. The more work that can be done automatically by the models, the less manual work we need to do when reviewing and overriding those models.

These are just six of many sins confessed during the round tables. Have you confessed yours?