Improve your demand planning process with better data and resources

Many firms approach us because they’ve found some of their internal forecasts inaccurate, which sometimes leads to confusing and contradicting data. Numerous reasons are to blame for the periodic unreliability of such 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 make sense at first. But further inspection proves otherwise. Then there’s the challenge of picking between forecasting models, which vary from straightforward and simple (that is, simple moving averages) to complex (multiple linear regression models). Few companies can afford the in-house analytics capacity to analyze the constructs behind the forecasts, or determine which are more appropriate for a given environment. Not to mention coming to grips with 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. This lack of alignment bolsters the sense that you’re 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; These lapses are 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 the transfer inventory sold to a customer, the product becomes obsolete and excess stock. This outcome sometimes occurs after the company has incurred the cost of moving the product from location to location, chasing a sale. Then there are possible restocking costs due to returns of unsold product initially placed on consignment with vendors.

The total impact of poor forecasting is widespread. It includes lost revenue, reduced margins, reduced market share and impaired market rankings with retailers. There’s also 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 multifaceted. The first step is building the capability to generate accurate statistical forecasts. With that accomplished, you need to pair these more precise forecasts with expert-level business knowledge to increase your understanding of the leading indicators that guide demand.

Planners should be able to combine those higher-quality forecasts with 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. That data makes sure ensuing forecasts will 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 for many organizations, generating consistently accurate forecasts is challenging. The complexities and specialized knowledge involved is why NTT DATA offers forecasting as a service (FaaS). We’ll focus on supply chain analytics. Our team of 40-plus people — each with no less than 15 years of experience — is dedicated solely to inventory analysis and management. They work with best-of-breed commercial and open-source tools to get the job done.

Our results are measurement-driven, and we agree upfront on key metrics with our clients. We use these metrics to encourage continuously improved outcomes. Our visualization-based reporting helps clients quickly see critical trends and opportunities. With countless data analytics-based client engagements, we’re a leader in advancing new organizational capabilities in forecasting and planning.

— By Salman Adil