The article discusses the transformation of sales territory optimization from a manual, spreadsheet-based process to an automated, algorithm-driven approach using Operations Research techniques. Here's a summary of key points and concepts:
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Territory Optimization as Combinatorial Problem:
- Territory design is not just about mapping territories but involves complex combinatorial problems such as balancing capacity and aligning human expertise with territory requirements.
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Automated Capacity Planning:
- Use mathematical models to predict exact territory requirements, eliminating the need for manual headcount estimation.
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Bias-Free Boundary Drawing:
- Implement Longest Processing Time (LPT) scheduling algorithm to ensure every territory has equal earning potential, reducing subjective boundary drawing.
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Maximizing Seller ROI:
- Deploy the Hungarian Algorithm (or Bipartite Matching) to match sellers' expertise with territory requirements efficiently.
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Handling Manager Overrides:
- Develop algorithms that can instantly suggest optimal counter-swaps when managers manually override territory assignments, ensuring balance is maintained.
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Hierarchical Quota Assignment:
- Connect the optimized territories to a hierarchical quota assignment system using Directed Acyclic Graphs (DAG) for cascading sales targets
Read the full article at Towards AI - Medium
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