The inventory planning team at a leading global CPG company held weekly planning sessions to review product performance and determine actions to improve service while reducing waste. However, the team struggled to measure the true state of their inventory during these meetings as they had to compare data across an ERP system, a supply chain planning system, and multiple reports and spreadsheets.

Because these sources were independent, aligning and analyzing them required significant manual effort. Data often existed at different levels of granularity or represented similar information in unique ways, making it difficult to establish a single, trusted view of inventory. As a result, time spent reconciling data frequently took focus away from the team’s core strengths as inventory planners.

When business priorities shifted toward a new inventory metric that did not exist in any source system, along with an increased focus on reducing aged stock, the team recognized that their existing process would not support these goals. The company set out to implement a unified solution to improve the effectiveness and efficiency of its weekly planning meetings.

The Inventory Planning Challenge

Multiple Markets and Stakeholders

The solution needed to support multiple markets that operated independently. What one market prioritized might not matter to another, requiring flexibility while still delivering consistent and streamlined outputs.

Data Sources

The company relied on multiple systems with differing levels of granularity, data representations, and ingestion methods. More than 25 tables needed to be combined into curated datasets that supported the inventory team’s objectives.

Focus on a New Metric

Leadership introduced a new KPI as a central measure of inventory performance. The team was responsible for ensuring this complex metric was calculated correctly and presented in a way that users could understand and consistently apply.

User Adoption

New views and metrics surfaced insights that users had not seen before, which initially led to skepticism. Figures tied to the new KPI were frequently challenged early on.

The Solution

A decision support tool was developed with multiple visuals, each focused on a key aspect of inventory health, including high-level KPI summaries, actuals and projections, and stock health views.

The interactive interface allowed users to analyze inventory performance across markets, products, and time at levels they had not been able to before. Where planners previously moved between systems and spreadsheets to answer questions, they could now investigate drivers, compare changes, and understand impacts within a single workflow. Information that once required extensive manual effort could now be accessed quickly.

The solution was tailored to individual market priorities, with different visuals available based on what each group valued most. The new KPI was brought to the forefront to support adoption.

To reduce aged stock, a dedicated view highlighted at-risk inventory and provided planners with a clear, prioritized list of items requiring attention. A week-over-week comparison view showed which items experienced the largest plan changes, allowing teams to assess whether prior actions were effective and identify unexpected shifts needing attention.

As a result, planning meetings became more focused and decision-oriented.

This tool also works alongside other advanced analytics efforts. Improvements driven by a safety stock optimization model are reflected within this solution, allowing the business to track how optimization decisions translated into improved inventory health over time.

Related case study: Safety Stock Optimization to Improve Inventory Health

Benefits Achieved

By automating complex inventory analysis and embedding it into the weekly planning process, the solution reduced manual effort while improving insight quality and consistency. Planners no longer needed to recreate analyses each week and could instead focus on understanding changes and taking action.

This led to measurable value, with over $14M in savings to date through avoided aged stock.

Conclusion

By bringing all relevant data into a single, consistent view, this solution improved the team’s ability to measure inventory health and analyze what was driving change.

Planners no longer needed to navigate multiple systems to answer key questions.

Instead, they had clear visibility into where issues existed, why they were happening, and which actions to prioritize, resulting in more efficient meetings and measurable reductions in inventory waste.