Inventory Allocation: 10-wk implementation

Objective: Develop an inventory allocation tool to ensure right rationing of constrained inventory to the right locations and customers

Key Challenges Addressed: The solution provides data driven recommendations for the following challenges and issues

1. Which customer orders do I allocate inventory against?
2. How much do I allocate against each order?
3. How do I plan for future orders?

How do we address your challenges: The solution provides the optimal inventory allocation by

1. Segmenting customers based on volume, margin, recency & order frequency, relationship and industry
2. Allocating available inventory to hot regions and most profitable customers
3. Aligning with user preferences while learning from previous manual overrides

Pilot outcome: An inventory allocation tool which can map the appropriate inventory quantity against each customer order

Implementation Plan The break-up of the implementation plan is as below:

1. Week 1 to 3: Conduct data discovery and set baselines
2. Week 3 to Week 7: Develop Inventory prioritization Algorithm at DC Level and customer Prioritization Algorithm at Division – DC Level
3. Week 7 to Week 10: Develop front end and refine model findings

This implementation uses the following native Azure components:

1. Azure SQL
2. Azure Databricks