Beyond supply chain and inventory management, though, an accurate forecast in a unified supply chain and retail planning platform aligns sales and operations, supply planning, and raw materials replenishment. With an accurate calculation of how many items they will sell at any given time, retail and CPG companies can order, allocate, and replenish those items accordingly. Reliable demand forecasts are integral to the health of your supply chain because, simply put, they reduce uncertainty. 1.2 What Are the Benefits of Accurate Demand Forecasting? With automated and centralized assortment reviews, CPG companies can see marked benefits including more than 90% weekly forecast accuracy, a 9-pp improvement in peak season forecast accuracy, and a 10% increase in forecast accuracy when using retailer data.ĭespite the knock-on benefits of accurate demand forecasts throughout retail and CPG operations, many companies’ forecasting capabilities are unfortunately still quite limited. A forecasting system that uses machine learningcan calculate complex and variable demand drivers automatically allowing manufacturers to quickly adapt their forecasts to changes in demand patterns at the right level of granularity. The same applies to markdown optimization, workforce shift optimization, and any other planning process with a longer planning period than daily replenishment.įor CPG companies, granular forecasts allow them to leverage retail sales and assortment data automatically for more accurate short-term forecasts. While many retailers still base planograms on past sales examined in weekly or monthly time buckets, demand-driven planograms offer a much higher degree of accuracy because they take advantage of this highly granular, day-product-location level forecast data. Figure 1: The ability to flexibly aggregate granular forecasts can support a wide range of planning processes and planning horizons across retail and consumer packaged goods (CPG) operations.Ĭonsider planograms, for example, which are not adjusted daily but are generally revised every few months as part of a larger assortment review process, with smaller adjustments often made between review periods. This is why flexible aggregation across products or over different planning horizons is critical to a company’s ability to leverage the same demand forecast in all their supply chain planning. To effectively execute replenishment, capacity planning, and other business decisions, retailers and CPG companies need multiple forecasts with different levels of granularity that look at different time spans. Why, then, would slow-moving items that sell only a couple of units per location per day, if even that, require the same level of forecast granularity? Even if the day-product-location level forecast for a slow-moving item is itself somewhat inaccurate, forecasting at this level of granularity ultimately makes it easier to aggregate demand-whether for different periods of time, across products (for example, total demand per product per distribution center), or by total demand per product in a month or customer group, etc. Additionally, modeling can help optimize production capacity. Another key benefit of granular forecasting lies in its ability to allow a manufacturer to aggregate data on products that share a certain raw material and create a forecast that will reveal the true amount of materials needed to produce each product, helping them to reduce costs by optimizing bulk purchasing and reducing the number of shipments needed. The benefits of a granular forecast are obvious when thinking of fresh food products whose short shelf-lives sometimes call for intra-day forecasts at the product-location level to prevent spoilage.įor CPG companies, detailed forecasts allow planners to model the effects on demand based on sale or promotional information. Accurate demand forecasts can be leveraged throughout your supply chain to improve decision-making and outcomes in areas such as store and distribution center replenishment, capacity planning, and resource planning.ĭemand forecasts can be developed on different levels of granularity-monthly, weekly, daily, or even hourly-to support different planning processes and business decisions, but highly granular forecasts are always extremely valuable. In practice, this means analyzing the impact of a range of variables that affect demand-from historical demand patterns to internal business decisions and even external factors-to increase the accuracy of these predictions. Introduction: What Is Demand Forecasting, and How Is It Done? 1.1 What is Demand Forecasting?ĭemand forecasting is, in essence, developing the best possible understanding of future demand.
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