Business Problem
Planning teams need a shared view of demand forecasting, inventory turnover, fill rate, service level, stockout risk, safety stock, and reorder point logic.
Demand Planning Case Study
Demand Forecasting & Inventory Optimization Dashboard
A supply chain analytics case study for German recruiter screening, showing how forecast accuracy, inventory turnover, fill rate, service level, stockout risk, safety stock, and reorder points can be monitored in one planning view.
Forecast Accuracy
86%
Target: 85%+
Inventory Turnover
5.8x
Quarter view
Fill Rate
94%
Customer orders fulfilled
Service Level
96%
Target: 95%
Forecast Accuracy
86%
Target: 85%+
Inventory Turnover
5.8x
Quarter view
Fill Rate
94%
Customer orders fulfilled
Service Level
96%
Target: 95%
Stockout Risk
18%
Priority SKUs
Safety Stock
12 days
Average buffer
Reorder Point
1,240 units
High-volume SKU
Forecast vs Actual Demand
JanForecast 1180 / Actual 1240
FebForecast 1320 / Actual 1280
MarForecast 1410 / Actual 1470
AprForecast 1560 / Actual 1500
MayForecast 1680 / Actual 1720
JunForecast 1740 / Actual 1810
Forecast Actual
Inventory Risk Review
SKU-A14
High riskInventory cover: 8 days
Raise safety stock by 120 units
SKU-B22
Medium riskInventory cover: 14 days
Monitor supplier lead time
SKU-C09
Low riskInventory cover: 24 days
Keep current reorder rule
SKU-D31
Medium riskInventory cover: 11 days
Review demand volatility
Solution
A dashboard concept that compares forecast versus actual demand, highlights SKU-level inventory risks, and connects reorder recommendations to service-level goals.
Planning Actions
Compare forecast versus actual demand by SKU family and month.
Use fill rate, service level, and stockout risk to identify critical inventory gaps.
Calculate safety stock and reorder points from demand variability and supplier lead-time assumptions.
Prioritize procurement and replenishment actions for high-risk SKUs before service levels drop.
Technologies Used
Power BI conceptExcelPythonDemand forecastingInventory planningKPI design
Business impact: supports better replenishment prioritization, earlier stockout prevention, and clearer planning discussions between procurement, operations, and supply chain teams.