A number of supply chain analysts believe that, to remain competitive, companies will eventually have to transform their supply chains from being “focused on trying to predict demand to … customer-driven chains that are organized to respond to demand with lightning speed” [“Buiding Sense and Respond Supply Chain Networks,” by Editorial Staff, Supply Chain Digest, 17 June 2010]. The article reports on the findings of a study by the magazine’s research organization — Chief Supply Chain Officer (CSCO) Insights — entitled Next Generation Supply Chain Management: The Integration of Planning and Execution. The authors believe that most supply chains are far from becoming sense and respond systems. In fact, they believe that the next step for many supply chains is implementing “the basics” required to start down the path toward sense and respond. Those basics, such as improved sales & operations planning (S&OP) and enhanced feedback loops, will help companies move to the next phase — a real-time supply chain. That’s where the article starts. It “provides a concise description of the third phase in the evolution to highly integrated planning and execution – moving to ‘Sense and Respond’ supply chain networks.” The article continues:

“Phases I (The Basics) and II (The Real-Time Supply Chain) take care of the fundamentals and move companies much closer to a state of integrated supply chain planning and execution. But getting to a true ‘sense and respond’ network, in which operational and even tactical planning blur with execution processes, is where the supply chain is ultimately headed – and faster than many may realize. What is close to available today and will become commonplace in the future is the ability to see in near-real time a complete picture of supply and demand data, across multiple levels – from supplier’s supplier to customer’s customer. The view will also not be ‘point-to-point’ but ‘many-to-many,’ requiring collaboration and synchronization around supply chain execution and tactical planning – in near real-time. But it is a lot more than just technology, of course – it is completion of the journey from a forecast-driven supply chain, in which companies build supply chains around trying to predict demand, to a customer-driven one that is organized to respond to demand with lightning speed.”

I should probably remind readers at this point of something a senior IBM consultant wrote: “Real-time planning is quite useless when you cannot obtain real-time response.” While a lot of thought seems to be going into sensing capabilities, just as much thought needs to go into responding capabilities. Creating a sensing system for the supply chain is only a worthwhile goal if a company has a way of utilizing the data it obtains. The article continues:

“While the picture will look somewhat different from industry to industry, ‘build to stock’ will ultimately give way to ‘build or customize to demand’ in virtually every one of them. Long production runs and costly changeovers will give way to much more flexible factories that can rapidly switch gears to cost effectively make short runs of product based on the latest near real-time demand data. Procter & Gamble has publicly stated its goal of being able to make every SKU every day in its plants, recognizing the cost of the weeks of inventory its pipeline still holds after years of attention and improvement in the forecast-driven model. But this model cannot be implemented by a company stand-alone. It must be built with an intense level of visibility and collaboration.”

The “intensity” of the required collaboration gives some companies pause. Collaboration means sharing sensitive, if not proprietary, information. Suppliers supply to more than one company; manufacturers offer their goods to more than one retailer; and distributors distribute goods to a wide variety of clients. Add in the truck, rail, and shipping data and you begin to understand the complexity of collaboration. At Enterra Solutions®, we have developed a Secure Information Sharing framework based on Attribute-Based Access Control (ABAC). This framework provides the greatest flexibility and scalability for a secure information sharing system. ABAC helps ensure that the right information gets to the right people, at the right time. Such information sharing will be critical in any sense and respond supply chain. The article continues:

“As Nick LaHowchic (former supply chain executive at The Limited Brands) and Dr. Don Bowersox of Michigan State University recently wrote, if information ‘was shared fluidly between participating firms in a channel, then a great deal of ‘anticipation’ would be replaced with facts. In a collaborative environment, it would not be necessary to forecast what others are planning to do or what they are planning to buy.’ This is the critical point: visibility and information sharing will allow trading partners to simply sense and respond, within defined relationship rules. Of course, this vision of the integrated supply chain has been there all along – it was many years ago that the vision of a sweater being sold in a store in the US would trigger a sheep being shorn somewhere in New Zealand. The difference is that in addition to a continuous maturing of the supply chain, the technology to make this responsiveness happen is very close to being here: web-based visibility and collaboration, sensory networks, integrated supply chain software suites, real-time analytics, mobile devices, Service Oriented Architectures, and other technologies.”

As noted above, I have had the nagging feeling that much more is being done on the sense side than on the respond side. Perhaps that is because I have paid more attention to the supply side of the supply chain rather than the manufacturing side. Those involved in supply chain management are generally more involved in getting supplies and products from here to there than they are in obtaining or manufacturing the supplies and products that need to be moved. They leave those issues to individuals on the operations side of the business. Nevertheless, most of the technologies mentioned above relate to the “sense” side of sense and respond. Fortunately, the article concludes with some of what is being done on the respond side of things.

“Those changes will be accelerated by the powerful advances in computer technology. The cost for an entry level Cray supercomputer, for example, has fallen to just $25,000 and will drop further. What this means is that companies will be able to rerun operational plans at exponentially greater speed, based on real-time data on supply and demand. Using this type of computing power, one retailer is now able to run its store replenishment plan in just 17 seconds – a computing job that that used to take 6 hours to run. Another manufacturer is reoptimizing manufacturing schedules throughout the day in a way that was never possible with less computer horse power. There will be different models of sense and respond networks. An increasing number of companies will eventually use true build-to-order models, but others will use hybrid models that include postponement and related strategies. But most will see their supply chain velocity continue to increase, rely far less on forecasts and much more on responsive, demand-based supply chains, incorporate high levels of product customization and tailoring, and embrace related supply chain process changes. These business and technology changes will beget organizational and functional changes as well. Collaboration externally must be supported by collaboration internally, as the concept of ‘teams’ supplants the concept of ‘functions.’ In other words, at the end of this road is a substantially different and incredibly more powerful supply chain world. In many cases it will require a ‘supply chain transformation’ that will dramatically improve cost and customer service and bring the supply chain in much closer contact to end customers. That will be a very good place to be.”

There are likely to be a few cultural conflicts along the way as companies try to break down barriers to collaboration and shatter internal company silos that have defined industrial age corporate structures for more than a century. They are, however, battles worth fighting. As Lora Cecere has commented, corporate executives are going to have to learn how to make trade-offs. You can’t “reward sales on volume, marketing on market share, finance on minimal budget variance, manufacturing on asset utilization, and sourcing on the lowest cost of materials” Lora writes and ever hope to “achieve the lowest total cost.” Collaboration and trade-offs are complementary traits and both are empowered by improved data sharing. Lora says that the problem is not finding the right technology to share data, but determining what data needs to be shared [“Start a New Conversation. Free the Data to Answer the Questions that you Don’t know to Ask,” Supply Chain Shaman, 14 September 2010]. She explains:

“IT says to line of business leaders, ‘Tell me what you need for Business Intelligence (BI), and I will go find the right technologies.’ The issue is that we don’t know, and we will not know soon. We only know that applications are changing and that the data is growing exponentially. The answer to the question of: ‘What is the right data architecture for demand-driven value networks?’ The answer is ‘It is evolving. We don’t know.’ All we know is that it will get even bigger and more complex. We are facing a redefinition of applications for consumer products and retail. It will require a rethinking of business intelligence strategies.”

The question you might be asking yourself is: “Why don’t we know what data we need to collect and share?” Lora says it’s because we are asking the wrong questions about the data. She writes, “The analogy that I would like to apply is ‘that it is like a discussion of which window pane will be best for the view, when we should really be talking about the design of the house.'” She continues:

“I think that we need to create conversations that don’t exist. We need to free the data to answer the questions that we don’t know to ask. Sensing technologies to support the evolution of pattern recognition technologies, advanced optimization and rules-based ontologies. We also need flexible information architectures that will support changing application infrastructures. Let’s take a closer look at six drivers:

• Geo-spatial Data. Maps enable new ways to engage the shopper. The list is endless but includes geo-mapping for gaming, new technologies to track shopping to drive in-store insights, and searches across banners to understand in-stock positions, pricing strategies and offers. Mapping has grown in importance and generates a new type of data.
• Sentiment Analysis/Listening Posts: I was speaking to a customer last week that is trying to syndicate data from 800 review sites, and another that was listening to customer sentiment at 500 listening sites. This is unstructured data that needs to be cleansed, syndicated, and managed. A new source of data that will be critical to the evolution of the future of demand-drive value networks. It will allow us to better plan demand, execute assortment and run-out programs, and adjust new product launch programs.
• Loyalty Programs. Traditionally, loyalty programs have been household level data. As social/mobile/ecommerce programs converge, loyalty programs move from household to individual loyalty data sets. The data explodes as we add shopper attributes to individual data to drive market insights.
• Engage[ment]. Before we have loyalty data we have the tracking of engagement behavior. How do I engage with fans like me? In programs that make sense in my community? The result is social behavior data. Look for a convergence of social and shopping insights data as we try to merge information across the proliferation of channels. The apparel retailer will soon have at least five channels: social, mobile, ecommerce, direct store purchases and purchases within other retail outlets. The term cross-channel will take on a WHOLE new meaning.
• Point of Sale (POS)/Enrichment. As we move from broad-brushing markets to localized assortments driven by crowd sourcing/social fan engagement, retailers will add enrichment data to POS data. Recently, I attended a Retail Connections conference. … [at which] three retailers mentioned that they have over 100 attributes to add to their retail POS data. Just think about the possibilities of how we can use this enriched data to sense, shape and respond to demand.
• Data Enrichment/Syndicated Data. Despite the investment in downstream data, syndicated data is not going away. Instead, it will become deeper and we will see a coalescence of social, consumer and shopper insight data.

“…It is time to stop picking out window panes. We need to build a new foundation—a data foundation—for the new enterprise architecture that is coming. Yes, we do not know exactly what it looks like, but we do know that it will need to:

• Manage large quantities of data
• Most of the data is EXTERNAL
• Unstructured data will open up new frontiers for sensing true customer service
• Be built using a data strategy where data reuse will be key
• Be flexible to support changing applications as the vendor landscape rises, wanes and falls. There will be a lot of change.
• Support line of business sandboxes that will become prevalent to run specialized analytics
• Have advanced master data management (MDM) tools for data maintenance”

I was obviously pleased that Lora included “rules-based ontologies” in her description of technologies that will be needed to support sense and respond supply chains since that is an area of specialization for Enterra Solutions. Although the Editorial Staff at Supply Chain Digest believes that sense and respond supply chains may be achieved more quickly than many people imagine, Lora offers us a sobering reminder that a number of challenges remain along the road to that vision.