Many firms often approach us because they have found some of their internal forecasts inaccurate, leading to sometimes confusing and contradicting data. There can be many reasons for the periodic unreliability of these forecasts. Here we examine the possible causes and recommend solutions.
Sometimes, your best resources aren’t enough to generate actionable data
Often, the forecasts generated by the planning systems on hand appear to make sense at first glance. But upon further inspection, they prove otherwise. Then there is the challenge of picking between forecasting models. A factor here is that forecasting models vary from being rather straightforward and simple (e.g., simple moving average) to rather complex (multiple linear regression models). Few companies can afford the in-house analytics capacity to analyze the constructs behind the forecasts and thus determine which forecasts are more appropriate for a given environment or the strengths and weaknesses of different forecasting methodologies.
The lack of internal capability can span both forecasting methods and familiarity with applications. Compounding this capability gap are uneven processes across departments, business units, or product groups, and this lack of alignment bolsters the sense that one is continuously operating with erratic forecasts. These unreliable forecasts lead directly to inconsistent performance and unpredictable outcomes.
Inaccurate forecasts lead to adverse service outcomes
Errors in forecasts lead to poor customer service due to the production of the wrong quantities at the wrong locations; this is the root cause of stock outs and short orders. Another unintended service outcome is the scramble of transfer orders and the resulting stock transfer transportation costs, which often exceed planned expenditures. In some cases, the issue is even more detrimental. Instead of having transfer inventory sold to a customer, the product becomes obsolete and excess—sometimes after the company has incurred the cost of moving the product from location to location, chasing a sale. Or the firm incurs restocking costs due to returns from placing a product on consignment with vendors which doesn’t sell.
The total impact of poor forecasting is widespread, including lost revenue, reduced margins, reduced market share, impaired market rankings with retailers, and the excess costs of repositioning products and scrambling to fulfill demand.
It’s no surprise then that the approach to mitigating these demand planning challenges is multi-faceted. The first step is building the capability to generate an accurate statistical forecast. With that accomplished, these more precise forecasts must then be coupled with expert-level business knowledge to increase understanding of the leading indicators that drive demand.
Planners should then be able to combine those higher-quality forecasts with the improved knowledge of demand drivers and, along with continuous communication with customers, generate new forecasts with enhanced reliability. Instituting a process that updates these forecasts with the latest information will make it possible to obtain qualitatively better data, ensuring that subsequent forecasts continue improving the standard of accuracy.
Dependable forecasts are essential, but so is a wealth of experience
The foundation of improved planning is forecasting. But generating consistently accurate forecasts is challenging for many organizations. The complexities and specialized knowledge involved is why Chainalytics offers Forecasting as a Service (FaaS). What positions Chainalytics for success as a FaaS provider? Chainalytics focuses on supply chain analytics and has for over 15 years. We have world-class career supply chain professionals – 40 percent of our inventory management practitioners have over 10,000 hours of experience. Chainalytics has a team of over 40 people dedicated solely to inventory analysis and management. They work with a library of commercial and best-of-breed open-source tools to get the job done. Our results are measurement-driven with an upfront agreement on key metrics with our customers. We use these metrics to drive for continuously improved outcomes. Our visualization-based reporting enables customers to see critical trends and opportunities quickly. With countless executed data analytics-based client engagements, Chainalytics is a leader in advancing new organizational capabilities in forecasting and planning.
Chainalytics accelerates fact-based transformation for supply chain leaders around the globe, including 18 of Gartner’s Top 25 supply chains. Our combination of top supply chain talent, proven methodologies, and proprietary market intelligence delivers actionable insights and measurable outcomes. Reach out to us and see how Chainalytics can help transform the reliability and efficiency of your supply chain.
Salman Adil is Principal of Chainalytics’ Integrated Demand & Supply Planning practice. He leads the Managed Analytics for Integrated Demand & Supply Planning and the selection and implementation of supply chain planning technology. Jonathan Whitaker is Principal of Chainalytics’ Integrated Demand and Supply Practice, where he manages the delivery and execution of advanced supply chain solutions for supply chain leaders globally.
