Events
Receipt, putaway, reservation, picking, transfer, shipment and returns.
Operations · warehouse · inventory · analytics
Data helps you
manage inventory and operations.
I help you understand what's happening with inventory and warehouse operations, why deviations occur and which decisions can be safely enhanced with analytics and AI.
Common symptoms
The system shows stock, but it's not in the right place at the right time
Book balances differ between the accounting system and physical counts.
Shortage and surplus coexist across different items.
Picking and replenishment priorities are set manually.
Delay causes are mixed: data, planning, placement and execution.
Forecasting doesn't account for procurement, storage and logistics constraints.
Analysis workflow
First the flow and quality of facts
Master data
Items, units, batches, locations, shelf life and storage constraints.
Metrics
Balance accuracy, cycle time, availability, turnover and error rates.
Causes
Separating systemic, planning and operational deviations.
Actions
Replenishment priority, investigation, relocation or process adjustment.
Where analytics helps
We pick a scenario that can be tested on your data
Demand forecasting
An expected-need range with seasonality and structural shifts.
Replenishment priority
Item ranking by availability, expiry and business impact.
Anomaly detection
Unusual movements and discrepancies as a signal to investigate, not a verdict.
Placement and picking
Operation frequency, compatibility and warehouse topology constraints.
Pilot
A limited area with measurable results
One flow or categoryclear boundaries and an owner
Event historysufficient detail and quality-checked
Baselinecurrent rules and the actual error rate
Recommendations in workexecution checked, not just the calculation
Scale decisioneconomics, stability and integration needs
Confirmed context
Processes, ERP and the operational cycle
Experience includes auditing and optimising manufacturing processes, implementing 1C:Integrated Automation and CRM, ERP TeamSystem, and managing inventory and expenses in finance-and-operations roles. This background lets me tie analytics to a real operational workflow, not just a data model.
Working-result conditions: validated master data, disciplined transaction logging and exception control before automating actions.
First step