Automation of Root Cause Analysis (RCA) for Demand Planning at AB InBev
Company: Anheuser-Busch InBev (Global Brewing Company)
Duration: 3 months (2023)
Tools & Technologies: Microsoft Excel (VBA), Data Integration, Process Design & Automation
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Project Overview
Project Overview
Context
Academic internship within AB InBev’s BNFL Demand Planning team (Belgium, Netherlands, France, Luxembourg)
Key Result
Reduced root cause analysis time by ~90% (20 → <2 minutes) through Excel & VBA automation, enabling standardized, scalable inventory decision-making across multiple countries.
Tools
Excel · VBA · Process Design · Data Structuring · Supply Chain Analytics
The Problem
The Problem
AB InBev’s demand planners performed root cause analyses for obsolete and slow-moving inventory using a fully manual Excel workflow.
Each analysis required:
Manual data extraction and cleaning
Planner-specific interpretation and logic
Non-standardized outputs
Resulting issues:
~20–25 minutes per analysis
Inconsistent conclusions across planners and markets
High error risk
Poor scalability as inventory volumes increased
This process had become a structural bottleneck in demand planning operations.
The Solution
The Solution
I designed and built a VBA-driven Excel tool that transformed a manual, interpretation-heavy task into a repeatable, automated workflow.
Key elements:
Standardized input template for raw demand & inventory data
Embedded RCA decision logic replacing manual judgment
Automated classification of root causes (logistics, FEFO, overproduction, underselling)
Clean, structured output ready for reporting and review
The solution was designed to be usable by non-technical planners and scalable across markets.
Process Overview
Process Overview
Input standardization
Planners paste raw inventory and demand data into a predefined template.
Automated logic execution
VBA processes the data and applies standardized RCA rules.
Instant output generation
Results are produced in a consistent, report-ready format within seconds.
Impact
Impact
~90% reduction in analysis time from ~20 minutes to under 2 minutes per SKU
Consistent RCA logic across countries, eliminating planner-specific interpretations
Reduced manual errors, due to less data handling, fewer mistakes
Designed for multi-country rollout and scaled across Europe
Direct financial impact by faster intervention helping to avoid obsolete inventory costs, supporting cost avoidance in the tens of thousands of euros
Why this Project Matters
Why this Project Matters
This project demonstrates my ability to:
Translate complex supply chain problems into structured logic
Design automation that fits real business users
Combine analytical thinking with hands-on implementation
Deliver measurable operational and financial impact
Build solutions that scale beyond a single team
It is a strong example of how well-designed process automation creates disproportionate business value.
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