Driving revenue growth management through gross-to-net optimization

Background

Our client, a leading healthy snacks manufacturer, is on a mission to create a world where people can enjoy snacking without compromising on flavor. With a strong presence in the US and Canada, the company distributes its products through major supermarkets, catering to the growing demand for healthier consumable alternatives. However, as the market for healthy snacks expanded, the company faced challenges in optimizing its product offerings and sales planning processes to sustain revenue growth in the long run.

Challenge

The company’s existing sales planning and forecasting processes were manual, time-consuming, and prone to errors. The lack of standardized pricing forecasts and version control led to inefficiencies, while the absence of detailed profitability analysis at the customer and product level hindered informed decision-making. To address these challenges, the company partnered with Keyrus, a global consulting firm specializing in data and digital transformation, to implement Anaplan, a cloud-based planning and analysis platform designed to optimize decision-making.

Approach

Keyrus embarked on a transformative journey with the healthy snacks manufacturer, focusing on optimizing gross-to-net planning, sales forecasting, profitability analysis. The journey was divided into four key phases, each designed to address specific pain points and deliver measurable benefits. Phase 1: Gross-to-Net Planning. The previous approach led to inconsistent and inaccurate pricing forecasts. The new solution enables the sales team to forecast final sales prices for each product-customer combination, factoring in all off-invoice adjustments. Standardized reporting consolidates pricing data into a single-page summary for easy reconciliation and executive insights across Finance, Sales, and Marketing. It isolates pricing differences, flags outliers, and enhances data transparency. The final output—a rate sheet—provides visibility into typical net sales prices, enables pricing comparisons, contrasts actuals against corporate guidance, and tracks gross-to-net adjustments (e.g., spoils, deal volume), while maintaining key assumptions and notes across teams. Phase 2: Sales Forecasting. The previous manual forecasting process, coupled with a lack of version control, led to inefficiencies. The new solution introduced a standardized, centralized template that enables sales representatives to forecast weekly sales volumes for their assigned accounts, at the Stock Keeping Unit (SKU) or master case level, for every product. Hierarchical allocation, based on historical distribution and business rules, facilitates higher-level planning. The solution also accounts for product lifecycle changes (e.g., new or discontinued products) when forecasting. Version control supports target setting, variance analysis, and rolling forecasts, improving accuracy and enabling better strategic decision-making. Automation of data flows streamlined the forecasting process, reducing manual effort and ensuring seamless updates. Phase 3: Customer-level and Product-level Profit & Loss (P&L). Keyrus replaced a manual cost allocation tool with an automated, fully allocated customer and product P&L, systematically distributing overhead, freight, and warehousing costs down to the SKU and customer level. This enabled precise profitability analysis, providing clear visibility into margins at every level. The solution improved accuracy with automated cost allocation, built-in controls, and error flagging, enhancing trust in financial data. By integrating data flows across four systems and standardizing allocation logic, it delivered a single, reliable view of profitability while eliminating manual inefficiencies. Phase 4: Volume, Rate, and Mix (VRM) Analysis. This phase enabled the company to systematically attribute revenue changes across all customer and product combinations to volume, rate, and mix effects. Replacing manual Excel-based analysis, the solution introduced robust reporting with intuitive visualizations, such as waterfall charts, for clearer insights and communication. It integrates all customer and SKU data from the allocated P&L, allowing users to compare revenue changes across selected time periods and versions. Variances in every P&L line are systematically broken down into volume, rate, customer mix, product mix, and SKU mix. Analysis can be performed at any level of the customer or product hierarchy, with top and bottom contributors to each factor automatically highlighted.

Key results

Benefits

• Enhanced Forecasting Accuracy: Standardized pricing and sales forecasting with set rules, version controls, and automated data flows to improve accuracy, eliminate manual intervention, and enable easy comparison of actuals against forecasts. • Increased Efficiency: Automated and streamlined processes across Gross-to-Net, Sales Forecasting, and P&L allocation, saving hundreds of hours per planning cycle and eliminating the need for IT intervention. • Improved Data Transparency and Trust: Implemented accuracy controls, error flagging, and secure data hubs, ensuring over 99% data allocation accuracy and increasing trust in the results. • Centralized, Standardized Reporting: Consolidated data into single-page summaries for easy reconciliation and executive insights across all teams, providing a clear view of pricing, forecasts, and profitability. • Scalable and Flexible Solution: Enabled flexibility to add new products, customers, and assignments, while automating data flows to support seamless updates and forecasting across all levels of the organization.

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