Reinventing Supply Chain Analytics For A Global Pharma Giant

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    case study
    • Pharma
    • Supply Chain
    • Pharma
    Problem Statement Problem Statement

    A global pharmaceutical giant faced significant challenges in managing its complex network of distribution centers and vendors due to inefficient processes and human errors, leading to long reporting turnaround times. To drive innovation and complete its digital transformation, the company was looking for a solution to modernize its supply chain management, focusing on inventory planning, spend analytics, and vendor analytics.

    Key Challenges Key Challenges
    • Poor master data management.
    • Transactional records kept at individual distribution centers.
    • Budget vs. actual spend analytics based on intuition, not data.
    • Slow inventory insights due to lack of planning system.
    • No single version of truth for supply chain data and analytics.
    • Unproductive data collation leads to slow decision making.
    • Gap in real-time inventory and spend reporting, hindering insight.
    • Siloed decision making
    Solution Implemented Solution Implemented
    • Automated Excel reports with Qlik, NPrinting, and Power BI analytics.
    • Integrated SAP and Excel data for comprehensive SCM analysis.
    • Implemented demand forecasting, EOQ, safety stock, re-order triggers, and inventory ageing analysis.
    • Facilitated budget vs. actual spend analysis and vendor performance evaluation.
    • Established KPIs for quality, value, and predictive analytics for decision-making.
    Technology Stack
    • Power BI
    • Qlik
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    Business Impact
    • Achieved a 20% increase in forecast accuracy.
    • Reduced lead times by 10% and enhanced order accuracy by 12%.
    • Decreased stock-out incidents by 25%.
    • Enhancing overall business performance by 20%.