The company is engaged in retail business with over 30 stores across the country representing some of the world’s best known and most respected technology and fashion brands.

Fast growth in business and store expansion brought operational challenges of inventory management. The risk of ageing inventory vs loss of sale was a typical tough choice for procurement. The entire inventory management process was manual using spreadsheets and managed by junior staff members.

There were frequent complaints by store sales team about lack of adequate inventory leading to potential loss of sale. The procurement team was struggling with the poor order fulfillments.

Key Challenges

Judgment Based Stock Management

No statistical demand forecast Merchandising plan based purely on judgment

Poor Fill Rates At Store and Warehouse

Judgment and availability based supply management. Imbalances not identified

No Tracking & Analysis Mechanism

Reports were typically data dumps. No analysis and tracking of demand and stocks


Automated Inventory Management

Cloud based low cost planning tool No capex investment. Plug & play Statistical forecast at sku level

Defined Norms To Improve Fill Rates

Automated forecast & norms based supply. Auto correction of demand due to past poor fill rates

BI Based Demand Sensing Reports

Trend, market share & promo analysis Exceptions report to review forecast ABC & forecast error bucket analysis

Key Benifits

Quick forecasting capability deployment within 2 weeks

Cloud statistical forecasting system and BI platform Resource agnostic robust process

Improved Fill Rates By 50% Within 4 Weeks

Resulting in higher sell through just on account of better stocking

Enhanced Analytics and Data Driven Process Capability

Better demand sensing resulting in quicker response times