Transforming Cost Forecasting for an Enterprise CPG Through Intelligent Data Automation
Solution
Delivered a fully automated purchase price variance (PPV) forecasting solution, replacing manual spreadsheets with a cloud-based, always‑on data platform. By integrating procurement, finance and commercial data, the solution enables real-time cost visibility from ingredient level through to product, brand and category outputs.
Results
The client now benefits from instant recalculation of forecasts, improved decision-making, and enhanced cross-functional alignment. The automation of a previously manual process has significantly improved accuracy, transparency, and responsiveness to market volatility.
The Challenge
The client, a large UK-based CPG enterprise, faced increasing pressure to manage cost volatility driven by macroeconomic factors such as inflation, supply chain disruption, and fluctuating commodity prices.
At the heart of the challenge was a highly manual forecasting process. Cost data was maintained across dozens of spreadsheets, requiring significant time and effort to consolidate, and introducing a high risk of error.
This approach limited the organisation’s ability to respond quickly to changing market conditions. Forecasts were not dynamic, often only updated during budgeting cycles, and lacked the granularity needed to support commercial decision-making.
Compounding the issue was the complexity of modelling cost across thousands of materials and products. The business needed to translate commodity-level price changes into meaningful product and brand-level insights—something existing tools could not achieve efficiently.
The Solution
Snap Analytics designed and delivered a fully integrated, cloud-based forecasting solution, combining data engineering, advanced modelling, and intuitive analytics interfaces.
At its core, the solution replaced spreadsheet-driven processes with a scalable data platform built on AWS Redshift, Matillion and Pyramid Analytics.
The Results
The result was a seamless, intuitive user experience that preserved familiarity while delivering significantly enhanced capability. Positive external impact including price reductions and improved customer outcomes. Strengthened digital maturity and confidence in scaling future data initiatives
The client is a large, UK-based consumer packaged goods enterprise with a diverse portfolio of products sold across retail channels. Operating in a highly competitive and cost-sensitive market, the organisation relies on accurate forecasting and pricing strategies to protect margins while remaining competitive. By transforming its approach to data and analytics, the client has strengthened its ability to respond to market volatility, optimise pricing decisions, and drive sustainable commercial growth through better use of real-time insights.
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