SCAS Control Tower monitors the Strategic Insights depicting various performance aspects of the supply chain in the form of distinct metrics that are continuously fed to the Control Tower AI Engine. Building on the Strategic Insights layer, the Control Tower AI Engine continuously detects anomalies that may take place at the metrics, either in the near past or in the future.
The concept of a Supply Chain Control Tower has been bouncing around for a while. A Supply Chain Control Tower would provide tools for a supply chain organization to monitor and manage its resources (i.e., visibility to & control over its inventory, shipment lead-time, product availability, expirations, etc.). Traditionally, supply chain control towers have been implemented using data analytics tools, without much intelligence, to provide after-the-fact data analysis for reactive decision making.
SCAS Control Tower monitors the Strategic Insights depicting various performance aspects of the supply chain in the form of distinct metrics that are continuously fed to the Control Tower Al Engine.
This Cross-Supply-Chain Visibility is leveraged by the Al Engine to develop solid forecasts of the future performance for each of the respective metrics. Building on the Strategic Insights layer, the Control Tower Al Engine continuously detects anomalies that may take place at the metrics, either in the near past or in the future. A performance anomaly is defined as an irregularity that contradicts with the forecasted value for the metric (regardless of whether the deviation is positive or negative).
Empowered with state-of-the-art Reinforcement Learning and Big Data technologies, SCAS Supply Chain Control Tower is capable of effectively analyzing complex supply chain networks composed of tens to hundreds of thousands of unique products (SKUS), hundreds to thousands of storage locations and thousands of alternative suppliers. This allows supply chain decision makers detect irregularities in any performance angle (i.e., metric), drill down across the time, location and product granularities to detect the finest granularity causing the anomaly within the affected metric and correlate the metric at the finest problematic granularity to all other potential metrics that could be either causes or consequences to the anomaly to help the business user understand the effect of the anomaly across the supply chain.
In essence, SCAS Supply Chain Control Tower is a layer of smartness sitting on top of the supply chain applications allowing respective business users to proactively address performance problems before they arise (or at least immediately once arising) and successfully solve them. The idea of having Actionable insights empowering supply chain operators to efficiently drive day-to-day business activities seemed to be an unachievable dream for a long time. But now, it’s finally a reality!