The Four Agreements – In Demand Planning and Forecasting

Editor’s Note: Ben YoKell is principal for the Demand Planning Intelligence Consortium (DPIC) at Chainalytics.

In the current environment of proliferating product portfolios and increasing demand volatility, there is a great deal riding on getting demand planning right. Inaccuracies in demand forecasts generate costly waves felt throughout the entire supply chain. As such, Gartner recently positioned forecast accuracy at the very top of its metrics hierarchy.

Regular analysis of detailed transactional data from many enterprises combined with process information on exactly how demand planning is performed within the enterprise(s) is needed. Individualized results from new analytical approaches have created previously unavailable insights.

With apologies to Don Miguel Ruiz, author of the widely read Four Agreements, here are four key findings from the Chainalytics Demand Planning Intelligence Consortium for supply chain owners to take to heart:

Agreement 1: Be Impeccable With Your Word

There is a ceiling to how far forecast accuracy can be improved for each business. Don’t commit to targets that are unrealistic.

The good news is that all businesses can improve demand forecast accuracy. However, the average forecast accuracy improvement potential is roughly 10% based on results to date. Double-digit gains are possible in some cases, but are unlikely in most cases. Forecast accuracy improvement targets set without the benefit of market-based data are often entirely unachievable without additional investments in planning. Realistic brand-level forecast accuracy targets can vary significantly from the overall forecast accuracy possible.

Agreement 2: Don’t Take Anything Personally

Other business units are not directly comparable to yours. Businesses in the very same vertical are often are far from comparable

Demand behavior between companies and business units can differ dramatically, even in the same industries and markets. Demand segmentation results show that no two businesses are directly comparable no matter how similar they seem on the surface. Even when they sell similar products to the same customers, differences in promotional strategies and portfolio management approaches result in demand profiles which must be planned for and managed in very different ways. Comparisons have to control for these differences to produce valid results.

Agreement #3: Don’t Make Assumptions

Conventional wisdom around what is “good” in demand planning is often flawed. Get the facts; use data to measure and quantify.

Many demand planning functions are viewed as underperforming due to lower forecast accuracy. However, in many instances, that lower forecast accuracy is entirely within an appropriate range relative to the complexity of the planning environment. If a company’s strategy were to rely heavily on new product introduction and promotions, a 60% (example only) forecast accuracy could actually be “market-leading,” even though another company selling competing products to the same customers may have a forecast accuracy of 80% if its go-to-market strategy creates less volatile demand.

Functional owners face a daunting uphill battle to explain to their peers and executive leadership how “wrong almost half the time” can possibly be good. But the data clearly illustrates that the definition of good must be viewed in light of a standard measure of demand Forecastability. Of course the reverse is true as well: some “outperforming” planning functions are not actually leading the market once Forecastability is controlled for in the analysis.

Agreement #4: Always Do Your Best

The best companies employ segmentation. Demand segmentation and differentiation leads to more accurate forecasting.

Businesses which segment their product portfolios with respect to their demand planning process achieve higher forecast accuracy than those which do not. Classification methodologies vary greatly in the marketplace, and there is still no widely-accepted single standard on how best to segment demand for the purpose of differentiated demand planning. However, companies that do any kind of formal demand segmentation for use in demand planning measurably outperform their counterparts.

The adage about understanding your demand as a prerequisite to planning rings as true as ever with demand volatility increasing and portfolio Forecastability decreasing. Market leaders have recognized that the best approach to forecast or plan demand varies according to the nature of the demand being planned.

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