Supply Risk Monitoring: 12 wk Pilot Implemenation

Objective: Develop a solution to better predict supplier outages, allowing firms to avoid production disruption by pre-ordering at-risk materials or ordering from alternative suppliers.

Key Challenges Addressed:

1. Existing manual purchase order and risk assessment processes are labor intensive resulting in slow and reactive decision making
2. Current supplier risk assessment reports are not always accurate due to manual report generation and underlying data issues 
3. External data sources such as weather forecasts and news reports are not prebuilt into the system

How do we address your challenges: The solution utilizes a dynamically updated Stock out Possibility Score (SPS) to assess the risk of purchased goods using a) Item and supplier attributes (Based on whether the item is locally sourced or not, Predicted suppliers’ performance, Suppliers’ risk score (financial, geopolitical, operational, number of suppliers, and current inventory levels) b) Dynamic market risk (Based on external data related to weather, regulatory changes, network disruption etc.) The solution will provide timely alerts and recommendations for items which are predicted to be at risk based on the predictions

Pilot outcome: An intuitive decision support system that provides a holistic view of all purchased items, suppliers and their associated risk

Implementation Plan: The break-up of the implementation plan is as below:

1. Week 1 to Week 3: Conduct data discovery and set baselines
2. Week 3 to Week 7: Develop supplier risk monitor using internal data
3. Week 8 to Week 12: Enhance supplier risk monitor using external data sources

This implementation uses the following native Azure components:

1. Azure Data Factory
2. Azure App Services
3. Azure Databricks
4. Azure analysis services