Information Economics Journal
Duncan McFarlane and Professor Yossi Sheffi explain how Auto ID systems will transform the supply chain.
The rise of Automated Identification (Auto ID) applications has been driven by the need to provide corporate information systems with information relating to physical items moving through the supply chain in an automated and timely manner. In the context of supply chain operations, widespread introduction of such systems represents a major opportunity to overhaul and improve tracking-and-tracing systems, process control and inventory management. In the longer term, it is possible that Auto ID systems may enable a complete re-engineering of the manufacturing supply chain by removing a number of the constraints that limit today’s supply chain structures.
In simple terms, Auto ID involves the automated extraction of the identity of an object. The real-time availability of item identity data allows other information related to the item to be drawn on in order to assess both the current state of the product and future actions required.
The management of manufacturing supply chains can be summed up in two challenges: being able to optimise entire systems, rather than subsystems; and managing the variability inherent in supply chain operations. The first challenge stems from the restricted view of managers who are constrained by corporate boundaries, limited responsibilities and lack of supply chainwide visibility. The second stems from the ever-changing nature of demand and mismatches in response capabilities of different players in a supply chain.We focus on the second challenge, that of managing variability, which is increasingly critical due to current trends in globalisation, outsourcing, and evershortening product lifecycles.
One of the most important factors in responding to variation is the ability to detect the variation, recognise its cause and act accordingly. This is the promise of a relatively new type of software tool dealing with event management. Supply chain event management (SCEM) tools evolved from process control and are an extension of supply chain visibility software tools. Visibility software flags deviations from plan so that logistics operations managers can act on it.
The Achilles’ heel of all such systems is the data acquisition - event management processes are completely dependent on the availability of accurate and timely data from suppliers and service providers as to where shipments are, what the current inventory level is and where it is located. This is where Auto ID can add crucial value. It can make sure that deviations are captured earlier and that the data is more complete and accurate - thereby giving supply chain managers more time to recognise a problem, assess its potential impact and take corrective action. This is not only an issue of human reaction time. Early detection means that more variables can be manipulated and more options are open for a systemic response. For example, early notification of a shipment delay on the railroad may mean that it can still make its deadline by trucking it, while a later detection of the problem means that a critical part may have to be air-lifted.