Returns on investment (ROI) from forecasting and planning systems range widely, based on innumerable, case-by-case variables. But of all the possible IT investments, it is safe to say that increased forecast accuracy (the benchmark of forecasting & planning) is the single biggest and surest driver of direct savings, revenue, and total return on investment.
Before we get into how that ROI scenario plays out in supply planning, let’s take a quick look at three essential components of an enterprise-class forecasting & planning system, as it should apply to any business-user case – sales, finance, operations.
Three Essentials of a Positive Net-Return System
At the core of any serious investment in a forecasting and planning system is a statistical forecast engine. This is the under layer of software that pulls in historical data (sales, demand, etc.), identifies trends and patterns, and then extrapolates an objective representation of the future. The forecast engine produces your baseline forecast, or best-possible starting point.
From there, an intuitive and collaborative user interface (UI) is essential. The user UI must set forth optimal workflow patterns and foster collaboration among sometimes diverse stakeholders. In the best cases, collaboration tools and features are the basis of the UI. That way when a baseline forecast is established, any user can (using the same system) layer that baseline forecast with knowledge or insight that is not already captured in historical data. These inputs can markedly improve the accuracy of forecasts.
The third essential component is not the software itself, but the advanced-analytic expertise and consulting savvy of the system vendor. Pulling off a successful implementation takes more than configuration and training. Optimal results (especially ROI) require expert knowledge in management consulting, operations science, and statistical forecasting methods and techniques.
Operating Efficiency & Savings
Okay, let’s get back into efficiency gains. While benefits from forecasting & planning software investments can occur across multiple functions in a business, those tied to inventory and supply chain management tend to be the easiest to measure and the quickest to provide hard returns.
Regardless, the basis of analytics-driven operating efficiency is forecast accuracy. And the basis of forecast accuracy is the quality of baseline assumptions. Are they guestimates? Or, are they products of statistical analysis of the past (plus anything known to be different about the future)? This first layer of analysis is essential to accurate forecasting, and therefore to reliably informed decisions and plans. Without it, subsequent calculations will only compound initial inaccuracies – think of a multi-division roll-up based on the untested assumptions of uncoordinated division heads.
Again, starting values drive results. Get them wrong and everything else is off. Get them right and you set the stage for simulation and optimization modules to identify and adjust for complicating factors such as seasonal demand, limited historical sales, and plenty more. The benefits are multiple: sharper insight into product demand patterns, lower safety stock, improved service level and faster response to market changes.
Let’s take an example. Winzer Corporation, a modestly-sized industrial parts supplier, cut inventory by $1 million, or about 10%, within just five months of implementing a new forecasting & supply planning system (Full Disclosure: Winzer implemented our solution, Vanguard Forecast Server). The company’s fill-rate stability meanwhile increased across all warehouses. And these gains were modest as compared to those of larger, more complex organizations.
Large inventory carriers such as distributors and make-to-stock manufacturers typically reduce finished-goods inventory by 10% to 25% within nine months of forecast implementation, according to multiple industry reports. That’s a one-time boost to the bottom line plus a lasting transfer from safety stock to working cash. These same companies meanwhile maintain or boost customer service levels. The result is goodwill and topline revenue growth, plus savings and bottom line growth from optimized inventory holding and replenishment decisions. Even manufacturers with partly or predominantly make-to-order operations can realize double-digit returns. Some start with a statistical demand forecast for finished goods and then explode that backwards into required inputs and resources. This can optimize raw-materials inventory, staffing, and equipment usage.
Additional gains come as system stakeholders share knowledge and insights, further refining these forecasts. The results include streamlined supply-chain and fulfillment processes, lower operating costs, and improved customer service, revenue, and profit.
Lastly, there are other benefits that may emerge outside of supply planning, such as the ability to redeploy high-value knowledge workers from forecast preparation to other high-value pursuits, or improved project and capital management, mostly from better informed financial planning.
In many ways, forecasting & planning software is the perfect complement to larger investments in ERP and other data-management and execution systems.
ERP systems are the operational and transactional backbones of the modern enterprise. They execute and log transactions, cut down on desktop spreadsheet management, consolidate and report financials, and provide excellent web-based computing environments and historical reporting. But, ERP systems are neither designed nor intended to transform forecast accuracy or provide comprehensive what-if analyses. These capabilities are the reason for dedicated, analytics-driven, forecasting and planning applications – again, the perfect complement to ERP, investment-wise as well as functionally.
For one, forecasting & planning software can begin delivering hard returns immediately, especially with respect to supply planning. Additionally, top-tier forecasting & planning systems integrate with ERP to create value in ways that ERP alone cannot, such as determining optimal service levels, safety stock, reorder points, and order quantities.
Both of these values provide front-end lift to the ERP investment, which by itself has a much longer, multi-year payback horizon.