Supply Chain Analytics Fact, Fiction or Fantasy
Broadly what analytics leads to is superior business performance through data driven intelligence. In order to achieve the different levels of intelligence(simple to advanced predictive analytics), it requires an organizational dimension based on inputs in terms of Processes, Policies, Procedures and Practices( incidentally 4Ps).Also it requires a computational dimension fired by data. Both of these dimensions form the basis of the analytical intelligence an organization can leverage on. It is this intelligence which leads to insights for a supply chain planner or a warehouse manager for him/her to act up on in such a way that it leads to superior performance.
I would touch up on few of perspectives on Supply Chain Analytics( few prevalent already and few emerging) in this blog series.
Organizations worldwide are keen to capitalize this new way of doing business. Organizations that started with merely reporting and to an extent drill down capabilities are today looking at exploiting analytical prowess to have end to end visibility into the extended supply chain enable management by exception. This foundational capability is helping organizations monitor and manage events which are common (example tracking where is the shipment or why is it getting delayed) and rare (effect of an earth quake or a hurricane disrupting the container movement at ports). Today's Supply Chain innovators are trying to be pro- active and are clearly heading towards a notch higher than management by exception. Classical management by exception is the fundamental premise for all Supply Chain Visibility programs. This is enabled by defining events based on the business process, understanding and establishing norms which fit into the definition of an exception and generating action points (based on breaching/meeting of norms) for supply chain managers. This framework often encapsulated in most IT enabled supply chain solutions today is helping organizations to drive an end to end visibility of their supply chain. The information derived out of historical data can further be organized, sliced, diced and served on a dash board for insights into key performance indicators. That underlines the importance of consensus on the KPIs which need to be tracked on daily, monthly and quarterly basis along with accountability/ownership defined for each of those areas. The above flavor of analytics is today the one of most popular which organizations are applying in their daily operations across the phases of plan, source, make deliver and return.
Talking of returns, we recently recommended to a leading retailer that this horizontal capability layer of event management in conjunction with returns and reverse logistics processes can help track and provide visibility into shipments returned from any kind of facility being picked up by a vendor or a 3 PL partner. A centralized and standardized capability to provide visibility in to all returns happening at retailer, with analytics iced on top of it can generate sufficient insights to tweak one's return policies or take corrective action at multiple touch points in the supply chain. An example of how analytics can enable true closed loop supply chains in terms of Material, Cash and Information flow.
Few Supply Chain and collaboration heavy business like 3 PL companies are exploiting Visibility and analytics as a strategic weapon by conceptualizing a control room/tower (akin to an air traffic control room or a turbine control room of a nuclear station) which will give them round the clock visibility to the extended supply chain, help monitoring supply chain events and KPIs and help control and mitigate risks them to a large extent.
I would like to classify the above under "prevalent" in most organizations as a capability[mostly in pockets]. In a recent experience with a global customer where we did an assessment on the Supply Chain Visibility endstate capabilities across 3 continents, one of the points we observed in the process was the aspect of enterprise readiness. An enterprise wide, rather an ecosystem wide aggregation of high quality data enabled by collaboration with trading partners across the globe is a pre-requisite to make this initiative successful. Well informed supply chain leader understand the significance of this aspect before embarking an initiative like this.
Dear esteemed readers, what is your defention of Supply Chain Analytics? how are you leveraging the prowess of data residing in throughout your organization? is it a fact, fiction or still a fantacy... I would be keen to know.