A recent study by [Name Redacted] explored best-in-class practices amongst companies applying advanced analytics for strategic sourcing. The study found that amongst these companies the best-in-class have twice the amount of savings than low performers, and an on-time delivery that is 40 percent better than competition. The report ratified a trend where increasing number of companies are looking to move away from descriptive analytics alone, and towards predictive and prescriptive analytics during both the planning and the execution phase.
To break into the top echelon of companies that successfully leverage advanced analytics, an organization-wide change in mindset is required. Organizations need to move away from thinking only in terms of Key Performance Indicators (KPIs) and also start relying on Key Performance Predictors (KPPs). Rule 6.2 in David Simchi-Levi’s book, Operations Rules, states that "IT should be used not only to monitor current supply chain performance but also to predict what is likely to happen if no corrective action is taken."
While KPIs are vital, they only describe what has already happened. By the time an organization learns from the KPIs and takes any action, a lot of the business value is already lost. On the contrary, KPPs predict something that might happen, elevating us from an "event driven" supply chain to one that identifies risks and trends early, thus ensuring a healthy performance. It is akin to receiving a flu shot before the onset of the flu season, and not waiting till you come down with one!
Using KPPs does not just involve monitoring trends in KPIs, but instead encompasses identifying causal relationships between performance indicators (e.g., fill-rates, lead times, quality) and factors such as order quantities, time of the year, and relationship with supplier/customer, etc. Both KPIs and KPPs should be monitored for deviations to confirm both adverse and advantageous performance trends early. Identifying these trends early allows your supply chain to take preventive actions or lock-in quantities and prices based on the nature of these trends.
Linking supply side predictive analytics with predictive analytics on the demand side would be an impactful step towards attaining supply chain zen. A descriptive end-to-end view of not only the current supply and demand but also a predictive end-to-end view of the next cycle’s supply and demand can help in efficient procurement, effective inventory positioning and reduce the cost of lost sales or lost margins. For instance, inventory shortages or overages can be predicted by observing trends in demand and supply variability. Identifying drifts in changing transportation mode mixes will allow for improved vehicle utilization and more meaningful freight price negotiations. Monitoring KPPs around customer complaints and queries is another useful example of leveraging predictive analytics to improve overall performance.
There is no debating that advanced analytics just by itself is an exercise in futility. One example of forward looking analysis is looking at the Risk Exposure Index a method of determining the risk points in the supply chain through analysis of the ability to survive a disruption. [Name Redacted] has adopted this expanded approach and now uses REI not only for strategic risk management but also for tactical and operational risk management. This is an example of the use of prescriptive analytics to assess risks.
An effective way of making the most out of analytics is through the deployment of a Control Tower—a set of processes and technology that enables flawless execution through visibility. Visibility of incidents assures continuity of supply while visibility of performance drives corrective action. A Control Tower with various analytics capabilities enables detecting present interruptions through and predicting future disruptions. As you can see in the illustration below the short term can use descriptive analytics to determine what is happening, predictive to determine inventory needs and prescriptive to plan for capacity that will match demand and risk.
Keep a watchful eye on your organization’s KPIs along with its KPPs to forecast the inevitable storms of supply chain fluctuations, disturbances and imbalances. Deploy a Control Tower to successfully navigate even through the perfect storm.
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