A predictive monitoring of incoming supply for mitigating the risks
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
This implementation uses the following native Azure components:
1) Azure Data Factory
2) Azure App Services
3) Azure Databricks
4) Azure analysis services, etc.