Operations and Inventory Performance Analytics

Overview

Independent operations analytics project covering order cycle time, fill rate, stockouts, supplier lead time, and forecast error. Recommendations focus on service-level and inventory trade-offs without claiming unverified cost savings.

Business problem

How can the organization reduce delayed orders, stockouts, and excess inventory while maintaining service levels?

Analysis and approach

• Define service and inventory KPIs
• Map order and fulfillment process metrics
• Analyze stockout and aging risk
• Compare supplier performance and recommend monitoring follow-ups

Skills: Operational metrics · Process analysis · Forecast error review · Dashboard design

Evidence and visuals

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  Evidence placeholder — synthetic operations dashboard export pending.

Findings and outcome

• Service-level and inventory efficiency must be reviewed together.
• Supplier lead-time variability is a major stockout-risk driver.
• Forecast error should be monitored by item segment, not only in aggregate.

Outcome: A monitoring and decision framework for balancing inventory availability, fulfillment performance, and working capital using synthetic operations data.

Recommendations

1. 1

   Create a weekly exception queue for aging orders and high stockout-risk SKUs.

2. 2

   Review supplier lead-time reliability beside unit cost.

3. 3

   Simulate reorder-policy changes before broad rollout.