Supply Chain Forecasting: Absorbing Risk with Resilient Plans

Line Art

Demand and Supply Chain Management Consider How Plans Absorb Risk When Forecast Error is Potentially High

In today’s supply chain forecasting world, data scientists can model entire networks and predict future demand outcomes with high levels of accuracy.  Supply chains across industries have seen the return on investment into forecast accuracy.  However, there does come a point of diminishing return.

Hinging your supply chain success on exact predictions of the future is often futile. Once foundational improvements to forecast accuracy are achieved, supply chain leaders should focus on building plans that are resilient to variability, plans that cope well with uncertainty, and plans that keep laser-focused – not on accuracy – but on attaining business objectives (like Service Levels, Growth, and Profit).

Such plans can only be produced by properly marrying advanced analytics forecasting with actual corporate business objectives. A unified supply chain forecasting platform, like Vanguard’s, can easily accommodate both. With the ability to take on a number of sources of data (including historical sales and upcoming promotions) and a user-friendly interface that supports collaborative intel, the proper planning platform facilitates plans that can weather all storms.

The truth is, some forecasts simply cannot get any more accurate. Maybe demand is truly random; maybe you’re introducing a product unlike any other in history. In these cases, efforts should shift toward creating a plan that accommodates high levels of variability in demand, and potentially higher forecast error. If you have thrown the best forecasting resources at the problem and there is a high margin of error, your plan can absorb the risk.

Another way of looking at it is that supply chain forecasting informs plans, but plans are more than just forecasts. That might not be a revelation, but a key to successful business planning lies in the midst: plans can account for things that forecasts cannot. By understanding the exact nature of your forecast (including the confidence level), you can craft a plan that maximizes opportunity, mitigates risk, and works toward your overall business objectives.