The Foundations of Supply Chain Transformation

Stephen DeAngelis

January 19, 2016

“Supply chains are changing and evolving into something new,” writes Daniel Miller, Head of the Finance Division at The Innovation Enterprise Ltd. “Gone are the days when a supply chain was just moving a product from one place to another, today they require a considerable amount of complex movements that all need to be co-ordinated and tracked.”[1] How dramatically are supply chains changing? George Prest (@gwprest), CEO of MHI, predicts, “When 2025 rolls around, traditional supply chain models will be extinct.”[2] Amarnath Shete (@AmarnathShete), head of Internet-of-Things Advisory at Wipro Digital, agrees that supply chains are transforming rapidly and that the “chain” analogy that has been used historically is going to have to change as well. He believes a more fluid and adaptable term is required. “With the advent of the ‘Internet of Things’ (IoT),” he writes, “there is tremendous potential to change the very structure of the supply chain, from a linear, step-by-step process, into a seamless, data insight-driven stream.”[3] Shete refers to one of the technologies that will drive change — the Internet of Things — but there are other related technologies that are going to be woven together to create the fabric of the transformed supply chain — or as Shete calls it, the supply stream.

 

Big Data

As Miller explains, data is going to be at the heart of supply chain transformation because the complex movement of resources and goods need to be coordinated and tracked. “Supply chains need to be data driven,” he writes. “This means that data needs to be collected from as many sources as possible in order to create wide ranging insight that can have a positive impact on the supply chain as a whole. This could be anything from tracking where a particular product is, to the speed of movement in certain areas. These insights will allow companies to optimize their supply chains based on informed analysis rather than gut feeling of what is quicker or more efficient. It also means that the performance of any one aspect can be monitored and maintained or improved.”

 

Advanced Analytics

Data by itself is not going to transform supply chains or create value. Prest explains, “Managing and leveraging the massive amounts of information companies collect and store about operations, sales, and customers requires advanced computing power to analyze and visualize the data. Organizations no longer have to look back to reconstruct what happened; they can apply sophisticated algorithms that perform predictive analytics to anticipate and prepare for future scenarios, thereby mitigating risk.” One of the maturing technologies providing advanced computing power is cognitive computing. Cognitive computing will not only help transform supply chains but will help transform industrial age organizations into digital enterprises. John Richardson, Transportation Insight’s Vice President of Supply Chain Analytics, observes, “Ongoing breakthroughs in big data and advanced analytics are nothing short of revolutionary.”[4]

 

Internet of Things

The technology that is going to have the greatest impact on generating data is the IoT. So much data is going to be generated by the IoT that the term “Big Data” will seem quaint in the years ahead. “IoT enables more innovation, communication and an enormously improved customer experience,” Shete writes, “including more customer touch points, clearer insight into customer behavior and preventative capabilities. IoT is an ideal candidate for transforming supply chains in key areas: warehouse, inventory, logistics, shop floors and new product development.” From Shete’s description of the benefits that the IoT will foster, it’s clear that he means the combination of big data, advanced analytics, and the IoT is required for true supply chain transformation.

 

Benefits of Supply Chain Transformation

 

Improved Visibility

Almost every supply chain pundit insists that supply chain visibility is going to be absolutely essential in the years ahead. Shete notes, “IoT makes inventory visible at granular levels.” Prest adds, “The proliferation of embedded sensors that communicate in real-time via the Internet without human intervention supports the Internet of Things. Among the opportunities: sensors in manufacturing could warn of problems and offer instructions for corrective action; packages and transport containers could be continuously tracked via GPS for optimized routing and delivery.” Implied in both Shete’s and Prest’s observations is that an underlying analytics platform is in place to make automated decisions and provide actionable insights.

 

Optimized Inventory

Inventory optimization continues to be a priority for both manufacturers and retailers. Too much inventory means higher warehousing costs and too little inventory means lost sales. Miller writes, “Making sure that the stock being held is both enough to meet demand and not excessive is important to next gen supply chains, simply because it makes warehouse management more efficient and allows for stock levels to be monitored to give the shortest possible chain to the eventual end user.” Shete adds, “A typical pain point in inventory management has been the glaring discrepancy between actual physical inventory and what’s shown in records. IoT can integrate data from logistics to provide an accurate and comprehensive view of replenishment and withdrawals.” Occasionally, products have to be recalled. When that situation arises, the combination of big data, advanced analytics, and IoT can also help. Louis Columbus (@LouisColumbus), explains, “Big data has the potential to provide improved traceability performance and reduce the thousands of hours lost just trying to access, integrate and manage product databases that provide data on where products are in the field needing to be recalled or retrofitted.”[5]

 

Better Collaboration

Most supply chain analysts believe that collaboration between stakeholders must be improved. They also agree that improving collaboration can be hard because trust issues exist (which can impede data flows) and important data resides on systems that are incapable of sharing that data easily. As Prest explains, new technologies are helping with the latter challenge; but, the former challenge — trust — still needs to be addressed. “Existing technologies can significantly reduce the inherent cost associated with supply chains by leveraging the data held by each party,” he writes. “To truly reap the benefits, however, trading partners will have to establish trust in order to collaborate. For example, competitors might share trailers to eliminate empty truck miles, thereby reducing transportation costs.” By employing a third-party that can provide a cognitive computing system that renders decisions impartially and generates actionable insights to all stakeholders while keeping proprietary data safe, trust can be enhanced at the same time supply chains are made more efficient.

 

Conclusions

 

Prest notes that there are a number of trends forcing changes in the supply chain (i.e., e-commerce; omnichannel distribution; urbanization; mobile and wearable devices; robotics and automation; and sustainability pressures). The ability to adapt to these changes is going to be the difference between surviving and going out of business in the years ahead. Miller explains, “Next gen supply chains will need to be an agile operation that can adapt to changing circumstances. This is not only in terms of how things are delivered, but also in reacting to problems within the supply chain.” Columbus concludes, “Choosing to compete on accuracy, speed and quality forces supplier networks to get to a level of contextual intelligence not possible with legacy ERP and SCM systems.” Evolution has taught us that the species that survive and thrive are those that are most adaptable. In the evolving business world, the same holds true for organizations. Cognitive computing systems can help provide that adaptability.

 

Footnotes
[1] Daniel Miller, “The 7 Characteristics Of The Next Gen Supply Chain,” Innovation Enterprise, 10 December 2015.
[2] George Prest, “Traditional Supply Chain Models Will Be Extinct in 2025, Thanks to These 10 Disruptors,” Inbound Logistics, January 2015.
[3] Amarnath Shete, “How IoT Is Transforming Supply Chains Into Supply Streams,” Manufacturing.net, 15 December 2015.
[4] John Richardson, “The Next Frontier of Supply Chain Innovation: Analytics, LEAN and the Power of Big Data,” Inbound Logistics, April 2015.
[5] Louis Columbus, “10 Ways Big Data Is Revolutionizing Supply Chain Management,” Business 2 Community, 10 September 2015.