Legacy SCM and ERP solutions were never intended for real-time decision-making; they primarily answer known questions using historical data. And that won’t give you the visibility or the agility you need to manage complex and ever-changing operations.
It’s now possible to establish in-the-moment awareness of your supply chain through real-time information. The best supply chain analytics tools can continuously funnel real-time information such as inventory flow or shipping performance from suppliers, partners, warehouses, and stores to analytics for instant insights that enable immediate, informed action.
The concept, sometimes called “active intelligence”, begins with data integration to bring all your disparate sources together. The raw data is then transformed as it moves through the pipeline to deliver up-to-date information. Real-time alerting then brings actionable insights or triggers automatic, immediate actions in other applications.
Automation, artificial intelligence and machine learning eliminate painstaking human analysis, provide the ability to highlight potential issues before they happen, and raise pertinent questions (and answers) that haven’t yet been considered. The data is executed moment to moment and embedded directly into supply chain and machine-driven processes. Not only do your teams know what is happening right now, they can understand what is likely to happen and they are alerted to take action when specific conditions are met.
Use Case Example: Supply Chain Disruptions
Here’s an example of how you would use real-time supply chain analytics to anticipate and solve for a lack of raw materials due to supply chain disruptions:
- Bring together data from SAP (sales orders), CRM (customer data), and Oracle WMS (inventory) and land it into Azure.
- Explore data profiles and lineage to help reconcile customer data between SAP and CRM, establishing trust in the CRM data.
- Develop a machine-learning model to forecast the order fulfillment rate using demand data from CRM and supply data from SAP and WMS.
- Query the data with natural language questions, such as: “Sales orders by month” and “Sales orders by top 10 customers.”
- Monitor charts in the hub in real time and set up alerts for the largest orders and top customers.
- Alert the Customer Service and Customer Accounts teams on Microsoft Teams so they can take proactive steps with customers.