Building a Business Case for Improved Demand Forecasting
I’ve always maintained that improving demand forecast accuracy, as helpful as it can be, shouldn’t be the end goal itself, but simply a means to the end. A recent report from Gartner agrees, focusing specifically on the challenge of building a better business case for improved forecast accuracy.
Gartner says that you shouldn’t just pitch forecast accuracy to your executive management, but translate your plan into business metrics. “Identifying the value that can be created from an accurate forecast is what counts—not an accurate forecast," says Gartner in Win the Business Case for Investment to Improve Forecast Accuracy (Steve Steutermann, May 2017). "Many planning professionals do not take this additional step and miss the opportunity to understand and quantify the value of an improved forecast to the organization."
Gartner makes three recommendations, and I will add a fourth of my own.
- Identify and quantify the impact of an improved forecast to the organization - Most importantly, put numbers on the expected benefits. "You must be able to make a direct link between the forecasting accuracy improvement and customer service, cost, efficiency, inventory, cash flow or capability improvements,” says Gartner. “You should take the additional step and quantify the win for, or risk to, the organization if the initiative is not funded."
- Use benchmarking to identify gaps and opportunities in demand forecast capabilities -
Gartner says that you can make your business case more compelling by demonstrating the gains others have won through demand planning improvements. In its own benchmarking services, Gartner found that for every 1% forecast accuracy improvement—narrowing the gap between median and best-in-class performance—companies on average realized gains including:
- 7% reduction in finished goods inventory (days)
- 2% reduction in transportation costs (percent of sales)
- 9% reduction in inventory obsolescence (percent of inventory value)
- Build a road map of the needed improvements to bolster the business case - Understand what to prioritize for investment. Gartner recommends defining demand planning best practice, then launching initiatives to fill the gaps in your organization. They add that best practice can also include accountability for stakeholder inputs, recognizing sources of error, and measuring performance.
One example that Steutermann cites are segmentation exercises that identify specific items that could be forecast better. This helps identify causes of error, and which new forecasting techniques/technologies could correct the situation.
My final recommendation is to remember that for addressing demand volatility, improved forecast accuracy reaches a point of diminishing returns. That’s because forecast accuracy is a main driver for every day, fast-moving items. But for slow moving “long tail” items forecast accuracy becomes less and less relevant. Focusing on forecast quality will not translate into improved service level. Customer service must come from inventories.
So don’t get caught of the trap of thinking, “If only we could only do a better job of demand forecasting, our supply chain problems would go away.” It won’t, because forecast accuracy is just a part of the problem. Demand volatility is the other part and it is quite likely growing. You cannot provide service from focusing exclusively on forecast accuracy. Inventory must serve the demand by absorbing the probability and size of the order. So if you have slow or intermittent long tail demand, don’t focus exclusively on forecast accuracy, look for ways to also address demand volatility. Look for a broader supply chain planning solution that also addresses inventory.