Automated deployment of supply planning models increases demand forecast accuracy and reduces manual intervention

jacobanalyst
Sun, 09 Feb 2025 21:43:11 +0000

Change management was definitely our biggest challenge initially. We addressed analyst concerns through several approaches:

First, we implemented a comprehensive dashboard that shows exactly what parameters changed in each deployment, with before/after comparisons and impact predictions. Analysts can review proposed changes before they go live.

Second, we maintained manual override capabilities for critical scenarios. Analysts can flag specific SKUs or product families for manual review, excluding them from automated deployment.

Third, we ran parallel systems for two months - automated pipeline deploying to test environment while manual process continued in production. This built confidence as analysts could compare results.

The breakthrough came when analysts realized automation freed them from tedious deployment tasks, allowing focus on analyzing forecast exceptions and improving algorithms. Once they saw the weekly iteration capability, resistance shifted to enthusiasm. Now our planning team actively contributes to pipeline improvements.