Planning Without Silos: Best-in-Class Approaches for CPG Forecasting

Planning Without Silos: Best-in-Class Approaches for CPG Forecasting

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Gross-to-Net forecasting is one of the most critical and complex processes in CPG. Sales, Finance, and Operational teams depend on accurate forecasts to ensure success from production through on-shelf execution. With many stakeholders involved, it is essential that forecasts connect commercial insights with operational realities, bridging the link between consumer demand and shipment planning.

Best-in-class forecasting, particularly for growing CPG brands, begins with retail consumption, incorporating baseline velocity trends, expected distribution, and forecasted lifts from planned promotional activity. Starting with consumption keeps forecasts the most relevant to true consumer trends, which helps brands stay ahead of fast changing conditions within the business.

Since consumption data is not always available, supplemental sources can be used to fill gaps and ensure the full business is captured. The most common source is depletion reporting, which reflects shipments from distributors to retailers, and this data typically can help with accounting for small-volume accounts or any shipments that are not captured in traditional POS data.

The final step in the forecasting process is translating on-shelf demand into a realistic shipments forecast that drives effective supply planning. This step ensures the right amount of product is available to meet consumer demand while accounting for supply chain nuances such as buy-in delays between consumption and shipments, which will be explored further below.

Bringing consumption, depletions, and shipments together in one unified model creates a single source of truth that drives alignment across the organization. The following sections will outline each forecasting method and explain how they work together to deliver a holistic and reliable forecast that works for stakeholders across your organization.

Consumption Forecasting

Starting with a consumption based view is the strongest foundation for CPG forecasting, especially for brands in growth mode. This approach relies on syndicated or POS data (Nielsen, IRI, SPINs, etc.) to capture true consumer purchasing trends by SKU and retailers. By focusing on consumer demand at a granular level, brands gain the clearest signal of expected volume as distribution expands and velocities shift, making it the most scalable method for evolving retail landscapes.

Best practice is to first establish a baseline volume forecast and then layer on the incremental volume expected from planned promotions. The baseline reflects the volume that would be sold without promotional activity or merchandising support. Incremental volume represents the additional lift generated by a promotion. Together, these elements form the foundation of consumption forecasting, which can be broken into three key components:

1. Bottoms-up Baseline Forecasting: Baseline forecasting is best done using a drivers based approach, most commonly leveraging the expected units sold per store per week and a projected store count to come to a baseline units forecast
   
   • Sales or Sales Ops involvement is crucial in this step to understand potential distribution shifts that may not show up in historical data (i.e., upcoming resets at a retailer)
2. Incremental Volume Forecasting: Layering in incremental lifts from planned promotional activity at the retailer account level. This is added to the baseline projection to create a total expected volume.
   
   • The best forecasts will link specific planned promotional activity directly to the incremental volume in the forecasts, which can be streamlined by ensuring your TPM system is connected to forecasting outputs automatically
3. Additional Opportunity Planning: Strong consumption forecasting should be able to account for potential opportunities that help leaders understand the range of outcomes that are possible, even when these events are not fully confirmed.
   
   • These are often viewed in three ways in the context of a consumption forecast: ‍
     
     1. Fully Weighted: Expected volume if every opportunity is realized‍
     2. Probability Weighted: Expected volume adjusted for the likelihood of each opportunity occurring‍
     3. Opportunities Removed: Expected volume based only on the core forecast, excluding unconfirmed opportunities

Stakeholders and Avoiding Silos:

Consumption forecasting is most effective when the commercial organization plays an active role in shaping it. Sales teams hold critical insights into account level trends and opportunities that are not always evident in the data. Their review ensures that expected distribution changes and planned promotional activity are accurately reflected in the forecast. At the same time, advanced tools and analytics can provide valuable guidance on baseline velocity shifts or unexpected distribution changes, complementing sales expertise with data driven recommendations.

Consumption forecasting is the critical starting point in the process, but it cannot exist in isolation. While it captures consumer trends and commercial insights, it only becomes actionable for operational stakeholders when translated into a shipments forecast. By incorporating potential opportunities that may impact supply, consumption forecasts can also provide operations with a range of expected demand, ensuring the right capacity is in place to meet future needs.

Depletion Forecasting

Starting with syndicated or POS data is ideal, but such data is not always available for all retail accounts. When on-shelf consumption data is missing, depletion data from distribution or wholesale partners provides a reliable alternative. Depletions represent shipments from distributors to retailers and help capture volume that is important for planning, even without direct consumption data.

A common challenge is how to handle the many small accounts that appear in depletion data. Individually, these accounts may be too small to plan for, but collectively they may represent a meaningful portion of volume.

Best practice is to create an “All Other” bucket by distributor partner, aggregating these long tail accounts. Trends can then be evaluated at the aggregate level to guide shipment planning, while avoiding the complexity of planning at the individual account level.

Stakeholders and Avoiding Silos:

Depletion reporting and analysis is often handled by finance or operational stakeholders, but trends should still be discussed with sales teams to understand future distribution and commercial activity.

By integrating both an initial consumption forecast, and a depletion forecast to fill in data gaps or account of small-volume accounts in aggregate, into a single source of truth it creates one holistic forecast of expected demand to inform shipments forecasting without leaving out crucial volume that needs to be planned for.

This improves accuracy for operational stakeholders by creating one holistic view of expected demand and leads to less opportunity for errors compared to tracking down disjointed forecasts in separate systems or spreadsheets.

Shipments Forecasting

Once expected demand is established, it must be translated into a shipment forecast. This determines how much product needs to be shipped, to which distributors or retailers, and at what time to meet expected on-shelf demand. A clear understanding of the route to market for each retailer is essential, as Shipment forecasting should be done at the “Ship-To” customer level versus retail account.

Shipment forecasts are informed by consumption and depletion data but require additional nuance to be actionable. The most typical adjustment is accounting for a buy in delay. Consumption represents on-shelf demand, but shipments must occur in advance of consumption to ensure product availability. Best practice is to embed this assumption directly into the forecast.

For example, if there is an average four week lag between shipment and on-shelf availability, and consumption forecasts show 100 cases of demand in the week ending December 28, then the shipment forecast should indicate 100 cases need to be shipped for the week ending November 30.

Advanced shipment forecasting goes further by incorporating statistical modeling and flexible adjustments for shipment specific nuances that are not captured in the consumption forecast.

A shipments forecast driven by true consumer demand and expected promotional activity delivers higher accuracy as brands scale. By embedding commercial drivers and translating them into operational realities at the customer level, companies can create a unified forecast that aligns both commercial and operational stakeholders across the organization.

Stakeholders and Avoiding Silos:

Operations teams rely on the shipments forecast for demand planning. When shipment forecasting is managed in isolation and not connected to consumption data or commercial planning, it often misses critical insights such as upcoming promotions, distribution changes, or new product launches that can significantly impact expected supply needs.

A unified process and platform ensures that consumer trends and commercial inputs are embedded directly into expected demand. This integration enables operations to plan more effectively and improves forecast accuracy across the business.

Bringing It All Together

Building a forecast that brings together real market dynamics with operational requirements is a complex task. Without the right technology, managing this across spreadsheets or disconnected systems quickly becomes unmanageable. The most effective organizations address this challenge with modern technology platforms that simplify the process, freeing teams to focus on what matters most and enabling them to drive the business forward, while turning forecasting and promotion planning into a scalable and repeatable capability.

That is exactly what Confido delivers. Our platform unifies consumption, depletion, and shipment forecasting in one place, while directly linking promotional incrementality through integrated trade promotion management capabilities. This creates true end-to-end visibility across Sales, Finance, and Operations teams. With AI-powered recommendations that adapt to your data, unlimited versioning, AOP-aligned specific planning capabilities, and industry-leading TPM functionality, Confido makes forecasting more accurate, efficient, and collaborative.

Interested in learning about how Confido can help your brand most effectively forecast? Book a demo today.