FMCG use case focuses on minimising OTIF loss, best promotional strategies and improved sales forecast. FMCG business owners also need data driven tools to maximise your profits via informed decision making.

Problem Statements:

  1. How to forecast OTIF losses?
  2. How to keep track of all the stockpiled for various retailers and distributors?
  3. How to understand the customer demand for all the FMCG products and be prepared in case of surge in demand?

Key Machine Learning Models:

  1. OTIF calculator/analysis
  2. Inventory tracker
  3. Customer demand prediction
  4. Sales and revenue tracker
  5. Supply chain tracker
Sample OTIF plot

Key business KPIs:

  1. Send out alerts if KPIs go above and beyond a threshold
  2. Effective sales strategies
  3. Effective marketing strategies
  4. Better preparedness for surge

Data sources:

  1. SAP
  2. Enterprise Resource Planning (ERP)
  3. Point Of Sales (POS)
  4. Excel/CSV Reports