Bluemercury operated a separate retail technology estate and relied heavily on manual replenishment calculations. The engineering challenge was to connect that environment to an enterprise forecasting platform without flattening important business differences.
What made it hard
The source model covered many operational domains and did not use the same hierarchy, identifiers, eligibility rules, or planning semantics as the enterprise forecasting system. The integration also required both inbound data movement and an outbound purchase-order path.
How I approached it
The work combined secure source access, defensive normalization, semantic translation, history construction, a dedicated forecasting environment, daily and weekly orchestration, audit controls, and purchase-order interfaces. The mapping evidence documented more than 500 selected source fields, illustrating the depth of source interpretation required.
Selected impact
The result replaced a largely manual replenishment process with repeatable data feeds, forecast and suggested-order generation, reconciliation controls, and an operational ordering interface. It supported multiple location types—including stores, e-commerce, warehouse, and shared-stock contexts—without presenting them as one uniform business model.
Lesson I still use
Integration quality depends less on moving fields than on preserving meaning, timing, and control across organizational boundaries.