Inventory Allocation: 10-wk implementation

Tredence Inc

Intelligent inventory allocation solution helps firms assigns scarce inventory to the appropriate customer/ market

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