Data is everything in modern businesses wishing to establish or optimize their demand planning, forecasting, sales and operation planning (S&OP), and/or integrated business planning (IBP) efforts. And although having access to more data can help teams and platforms develop more accurate, relevant planning strategies, more isn’t necessarily always better. It’s useful to weigh all relevant data and influencing factors in planning, but some strategies and types of data can prove more valuable than others for a particular business or situation.
For companies dealing in wholesale or retail goods, particularly F&B businesses, using depletion data as one primary indicator, combined with relevant shipment information and the appropriate contextual signals, can provide a more accurate view of true demand and aid in accurate forecasting, particularly when inventory moves through distributors, wholesalers, retailers, or other intermediaries. In this article, we’ll explain both the benefits of depletion-based forecasting and the limitations of relying on depletion data alone.
Depletion-based forecasting is a method that helps predict future inventory impacts and needs (sales through to end customers or lower-tier channels) rather than just tracking top-level factory shipments to distributors or warehouse orders. Let’s look at the core concepts:
As a theoretical example, consider this example showing the difference between shipment data and true demand: Imagine a company ships 10,000 units to a distributor in Q1. Obviously, that does not mean consumers demanded or purchased 10,000 units during the same period. This is particularly applicable in F&B businesses dealing in goods like wine, beer, liquor, or other products with a lengthy shelf life. Inventory may sit at a distributor for months or even years in some cases. On the other hand, if depletion data available via retailers or other downstream outlets shows 9,200 units sold during the same period, planners have a more accurate picture of actual consumer demand. It’s not perfect, but it’s closer to reality. Let’s go over some of the pros and cons of using depletion data for planning and forecasting.
No strategy is perfect or universally applicable. However, depletion-based forecasting is useful in many businesses including F&B for the following reasons.
Relying only on shipment data can trick a business into thinking demand is high when inventory is actually just piling up in distributor warehouses. Depletion data shows (closer to) what is actually being sold or consumed downstream, rather than simply what was shipped into a distributor or retailer. This can reduce distortions caused by inventory building, forward buying, or changes in ordering patterns.
When depletion data is combined with channel inventory and shipment information, planners can better distinguish genuine demand growth from inventory movements. This can support more informed production, replenishment, capacity, and inventory decisions.
By looking at actual depletion velocity, supply chains can better react before local shelves or downstream partners run completely dry. Additionally, depletions can reveal shifts in consumer or end-market demand before those changes fully appear in shipment data. This can give planners an earlier signal of acceleration, deceleration, or changing product preferences, and they can make appropriate adjustments in production, marketing, and shipping during their normal S&OP cadence.
Connecting actual market depletion with manufacturing schedules and other data inputs helps sales, finance, and operations work from a single, realistic version of demand.
An effective S&OP strategy should involve as many types of inputs, data sources, scenarios, and forecasting metrics as possible, and each has its pros and cons. Let’s briefly look at some of the potential downsides of using depletion data in forecasting.
Depletion data often comes from downstream partners, retailers, distributors, or point-of-sale systems. It may be incomplete, delayed, inconsistent, or unavailable at the desired level of product, customer, or geography. As a further note, utilizing depletion data often introduces greater complexity and data requirements generally. Effective depletion-based forecasting may require more effort or resources than using another dataset. Organizations need to reconcile shipments, depletions, channel inventory, promotions, pricing, distribution, and other factors. This creates additional integration, governance, and analytical requirements compared with a simpler (but more limited-view) shipment-based forecast.
A decline in depletions does not necessarily mean demand has fallen. And stockouts, distribution changes, supply constraints, or limited shelf availability can suppress observed sales. Without this context, a forecast can interpret constrained sales as generally weaker demand.
We mentioned above the need for context when utilizing depletion data. Caveats or factors to consider when forecasting based on depletions include the potential for:
The bottom line for depletion-based forecasting is this: Its biggest advantage is better visibility into actual downstream demand. The biggest challenge is that depletion data is harder to obtain, may be incomplete, and still requires context and significant understanding to interpret correctly. The strongest approach is to combine depletion data with available shipment, inventory, and all other forecasting signals when undergoing S&OP, rather than replacing shipment-based forecasting altogether.
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