My research shows that today, nine out of ten companies are stuck on improving supply chain performance. There are two major issues: the understanding of the supply chain as a complex system and the effective use of data.
Why are these problems? Let’s start with Supply Chain Analytics, which relates to the use of data and the complexity of today’s supply chains.
For most companies, the word analytics is synonymous with reporting. But despite thirty years of supply chain technology evolution, the most commonly used system for supply chain planning is a spreadsheet. Companies cannot effectively model the trade-offs of growth, profitability, supply chain cycles such as procure to pay and inventory turns, and business operations complexity on a spreadsheet. As that complexity increases, most companies are unable to use supply chain analytics to improve operating margin and inventory cycles.
Secondly, companies are not able to effectively balance the trade-offs in the value network. Today, only 11% of companies have the capabilities that they need to evaluate a “what-if analysis” and only 24% of companies are able to model profitability impacts of changing conditions in their complex systems.
Managing the trade-offs of inventory, customer service and costs of supply chain source, make and deliver needs to be done but the systems are not aligned to help managers to understand the inter-connectedness. While there are dashboards and reports that show the numbers about what is happening there is no why—the understanding of the inter-related nature of what is possible based on the potential of the supply chain.
Given these conditions, we asked 110 supply chain leaders to imagine the supply chain of the future at the Supply Chain Insights Global Summit in September.
We tackled the topics of talent, analytics and the many changes that are happening in the shifts of technology including the proliferation of social signals, increase in weather sensing, changes in corporate social responsibility, the shortage of talent, and the evolution of new forms of analytics.
When you get these leaders together in one room, the insights are powerful.
More Intelligent Use of Channel Data
Supply chain leaders are transforming their view of the data they collect, and how they analyze it. The work is not about inside-out and the deployment of traditional technologies. The problem is that supply chains today catch orders and shipments and assume that they are representative of the market. They do not allow for systems to manage the channel from the outside in. The analytics and traditional systems are not able to effectively use channel data.
Instead, supply chain management needs to be about outside-in processes that sense and translate market-to-market. It is about owning the entire supply chain, including the channel, and managing products from their manufacture to their end use.
In this world, the digital supply chain connects transactional data with digital images to enable new forms of connectivity and manufacturing. That means supply chain leaders can sense something in a channel and translate it through their complex organization and alert the right person at the right time to make the right next action.
How does this look? Let’s take some examples.
Logitech had an issue with complexity for their Ultimate Ear product. It is a custom ear bud based on digital images of the consumer’s ear canal. Prior to the use of 3-D printing and additive manufacturing, the ear buds were custom-made through a complex, long supply chain. The product delivery was slow and the costs were too high. Complexity reigned and product sales suffered. Through the redesign of the supply chain and the inclusion of 3-D printing, the devices can now be made locally with shorter lead time and lower cost.
These concepts are becoming more mainstream. At the conference, the use of additive manufacturing was also discussed as a means to simplify and align the medical device supply chain. Today, hip and knee implants travel to the hospital in the trunk of a sales person’s car. The manufacturer supplies multiple sizes for the replacement operation to ensure that they have the right parts. But, what if the digital image of the patient’s bone structure could be transmitted to a local lab to build implants quickly based on the patient’s digital image? And, what if this technology is also extended to 3-D cell regeneration using stem cells to manufacture kidneys and livers so that there is no longer a list for transplants? Such a use case signals the need to redesign the supply chain based on network analytics.
These were some of the discussions that we had at the summit. Attendees are still discussing how new forms of analytics, plus the use of digital conversion technologies, expand the possibilities even more. Analytics is much more than reporting. The evolution of analytics for visualization, pattern recognition, unstructured text mining and parallel processing are converging to drive a new form of supply chain. It is one that combines digital with cognitive reasoning to sense, think and act.
What if we could test and learn in-market, reading market impacts in real-time through analytics, based on matching customer attributes to product attributes to build customized products for regions around the world? This new approach allows test and learn capabilities to answer the questions that we do not know to ask to build unique insights.
And, what if we could mine unstructured data and combine it with transactional data to mitigate supplier risk?
There is some of this kind of activity already. In the aftermath of the 2011 Fukushima tsunami, Intel sent teams to Japan to rebuild infrastructure and help their suppliers. They would not have known where to go first if there had not been good information about the capabilities of suppliers in the network and early warning signals due to analytics.
But what if the capabilities went further? What if systems were more capable of analyzing the growing sets of unstructured data? What if clothing manufacturers with operations in Bangladesh had been able to sense risks related to their suppliers based on local media reports, or social media activity? Perhaps they would have provided early warnings—if supply chain experts were in position to listen.
Traditional supply chains respond, but they do not sense. Organizations do not use analytics to listen. In the world of new analytics, they will be able to sense, test and learn and orchestrate the response market to market. The world of supply chain has the opportunity to be quite different. Leaders do not have to be stuck. Instead, they only have to open up their minds and allow themselves to think about what the supply chain could be in the future and not what it is today. The changing world of supply chain analytics paves the pathway forward.
Lora Cecere, the founder of the Supply Chain Insights research firm, is the co-author, with Charles W. Chase Jr., of Bricks Matter: The Role of Supply Chains in Building Market-Driven Differentiation (Wiley, 2012). Her new book, Metrics that Matter, is due out in September 2014. You can read her blog, Supply Chain Shaman, her reports on Slideshare and follow her on Twitter: @lcecere.