CASE STUDY

Predict Procurement Lead Time To Manage Disruptions
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Industry

CPG 

Ecosystem

Oracle Fusion SCM Cloud | Oracle Fusion Cloud Procurement | Oracle Cloud WMS

Metrics

  • 30% of the purchase orders were processed through an alternate sourcing strategy.
  • Manufacturing delays attributed to procurement delays decreased by 10%.

    Problem Statement

    Customer sources raw materials from various vendors worldwide. Over the past few years, they have encountered numerous challenges, including plant shutdowns, transportation delays, capacity shortages, demand spikes, geopolitical conflicts, pandemic-related disruptions, and other unforeseen circumstances.

    They seek:

    • A predictive system capable of forecasting lead times for all approved vendor raw materials, considering various causal factors, vendor origins, and destinations.
    • A predictive system to forecast lead times for raw materials required by the facility from preferred suppliers, along with recommendations for optimal sourcing origins.
    • A predictive system to anticipate lead times for new purchase orders, accounting for potential disruptions and including forecasts for future purchase orders.

    Solution Provided

    • AI models were employed to predict Procurement Lead Time across diverse scenarios.
    • An execution workflow was implemented, enabling one-click operations for both real-time and forecasted demand.
    • Deep analytics were utilized for comprehensive assessment and actionable insights.
    • Business orchestration capabilities were integrated to dynamically adjust estimated lead times within ERP systems for effective planning.

    Outcome

    • Ensure seamless data integration, preparation, treatment, analysis, and modeling.
    • Enable real-time business decisions based on predicted values.
    • Address marketing, business plan, make-to-stock, and made-to-order demands with efficient procurement planning.
    • Proactively manage anomalies and disruptions.

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