Data-based asset validation for a Retail & Logistics firm

Challenge

As reusable packaging and transport containers gain RFID, GPS, and other sensor capabilities, retail and logistics companies are sitting on an increasingly rich data asset. Our client wanted to turn this newly available, granular data into real operational leverage — optimizing global and local processes, shortening cycle times, and cutting losses. However, the rollout quickly revealed a fundamental barrier: the data was neither mature nor clean enough to produce reliable estimates — let alone meet future audit requirements. Without understanding the hidden biases and distortions in the data, every strategic decision rested on uncertain ground.

Approach

STAT-UP combined big data analytics, expert workshops, and statistical modeling to map the full landscape of data structures, process logic, and potential sources of error. We tested the sensitivity of our statistical estimates under different assumptions. This included holding selected effects such as seasonality or business growth constant, and varying operational assumptions like shipment volumes or container mix to isolate their impact. The result: a validated, audit-ready framework for calculating the business-critical KPIs — robust enough for operations, transparent enough for auditors.

Impact

STAT-UP provided the board and top management with a trusted, intuitive decision-making framework they could act on with confidence. The KPIs enabled real-time diagnostic control of data quality and process stability, empowering the client to steer targeted investments, optimize operations, and spot emerging issues directly in the raw data. Beyond that, external auditors fully endorsed the methodology — and the company ultimately turned its sensor ecosystem into a monetizable competitive edge.