It is many years since Gartner started discussing demand-driven value networks. This concept is central to their ideas of an S&OP maturity model in which the most mature level, “Business Orchestration”, is all about what Gartner calls demand translation. The diagram below is from a Gartner webcast (Delivering Business Value from S&OP, Applebaum, T., Kohler, J., 29 March 2012). While this was presented on Mar 29, 2012, the earliest Gartner reference to demand-driven value networks dates from the early 2000’s.
In a public report Demand-Driven Value Network Orchestration Key Initiative Overview), Lord, P., 3 February 2012) Gartner defines demand translation as
Demand-driven value networks (DDVNs) integrate processes and data in the supply chain to enable collaboration, as well as orchestrate a response to demand that creates value and mitigates risk.
A broader definition of DDVN available on the Gartner website states that
A demand-driven value network is a business environment holistically designed to maximize value across the set of processes and technologies that senses and orchestrates demand based on a near-zero-latency signal across multiple networks of employees and trading partners.
In a recent report, (Definition: Demand-Driven Value Networks, Burkett, M. 13 July 2012) describes the required attributes of DDVN as
- End-to-end alignment and synchronization of demand, supply and pr noduct cycles across multiple enterprises
- Ability to better manage demand through sensing and shaping processes
- Ability to translate demand to deliver a profitable and sustainable supply response
- S&OP that links execution with strategy to facilitate conscious trade-offs across demand, supply and product networks
- Metrics driving joint value for customers, suppliers and shareholders
- Technology architecture enabling collaborative relationships, end-to-end visibility, responsiveness, and fact-based decision making to maximize value and mitigate risk
- Culture that develops and/or acquires talent to enable transformation and that encourages new learning, while also gaining scale by sharing standardized and proven practices
What I find fascinating is that other companies are now promoting this concept, not the least of which is Boston Consulting Group (BCG). In an article (The Demand-Driven Supply Chain: Making it Work and Delivering Results, John Budd, Claudio Krizek, and Bob Tevelson, 30 May 2012 – free registration required) they give a practical example of how DDVN can reduce the overall cycle time of responding to a demand spike.
What I find most interesting in this diagram is the manner in which they describe a different information layer that crosses organizational boundaries. In the top half of the diagram, the “traditional” supply chain we can see data flowing between systems, usually between ERPs with EDI signals, that is a cascade, starting from demand and bubbling up the supply chain to raw material. The information first has to go from the retailer’s store to the retailer’s warehouse, and then to the manufacturer’s warehouse, etc. I think we can all recognize this as the most dominant form of demand propagation in place today. The reason is that demand translation – the conversion of a demand signal into an appropriate supply signal – has to take place at each level (and node) of the supply chain before the signal can be propagated to the next node. It is difficult enough to do this with standard products at a finished goods level. Try doing this with a configurable product that is made up of 100’s of components, in an outsourced and distributed supply network.
An interesting characteristic of a DDSC described by BCG is that
A DDSC requires a scalable architecture that is flexible and robust enough to dynamically incorporate changes as they arise.
This is where the need for the “Real-Time Information” layer comes into play. Clearly this layer has to be enabled by something other than semaphore, an abacus, or Post-It notes. For far too long we have tried to enable this layer with email and Excel, a clear indication that our core transactional layer is not satisfying this need. But as I stated before, the dominant mechanism of moving data between functions and organizations is still overnight (at best) EDI between ERP systems. The use of email and Excel is merely a mechanism used to try to overcome the limitations of operating an end-to-end supply chain with cascaded EDI transfers. But even if you manage to get beyond email and excel, how do you know that the calculations performed at each level of the supply chain in the “Real-Time Information” layer are consistent with the calculations performed by the ERP at each level. It defeats the whole purpose of the “Real-Time Information” layer if at each level the MRP or planning analytics have to be invoked in the ERP system. At the very least, doing this will eliminate the real-time aspect of this layer. And yet it is necessary for this layer to translate the demand at that layer into a required supply in a manner that is consistent with the underlying ERP system. In other words a truly functional DDVN must be able to emulate the policies, bills-of-material, routings, sourcing rules, lead times, capacities, and manner other aspects of the supply chain model in order to perform the demand translation required to provide an end-to-end profitable response.
In a Supply Chain Insight’s report (Building Market-driven Value Networks – Driving Differentiation in Supply Chain Processes Market-to-Market, Cecere. L, 11 July 2012) Lora Cecere uses the following diagram to describe a similar concept.
In the report Lora defines supply chain agility as the
ability to recalibrate plans in the face of market demand and supply volatility and deliver the same or comparable cost, quality, and customer service.
More interestingly Lora states that
In the adaptive supply chain, the processes first sense and then shape demand based on revenue management practices. This is sometimes termed “a demand-driven supply chain.” Demand shaping includes the active processes of new product launch, price management, trade promotion management, marketing and advertising, and incenting sales against revenue management processes. They build processes outside-in to evaluate what “really matters to customers.” Companies that mature in this capability usually are also mature in the processes of analyzing customer profitability through cost-to-serve analysis and looking at product profitability to determine the right product portfolio. They actively manage complexity.
All of these comments have described a technology layer that far transcends what some commentators and technology vendors are portraying as “control tower” solutions. These almost never go beyond simple visibility and alerting solutions. As in many situation, visibility is a precursor, but not an adequate definition. Without a doubt the descriptions used by Gartner, BCG, and SCI all go way beyond this simplistic perspective. Even if we extend visibility to alerting we are in no way even approaching the sophistication described by Gartner, BCG, and SCI. Do we know the downstream/upstream impact of the event causing the alert to be issued? Isn’t the impact what actually determines whether the event is important or not? How does one even determine to whom the alert should go when much of the supply chain is outsourced?
Imagine the consequences if an airport control tower could only alert someone if a plane was in the wrong position but not tell that person that if the plane does not move in the next minute there will be a collision with a second plane. As importantly, imagine if the system couldn’t even detect, let alone alert the control tower, that the second plane was on a collision course. After all, in a purely event-based system, there is nothing to indicate an alert condition for the second plane because it is being viewed in isolation. This is what you will get from solutions that don’t incorporate all the capabilities described by Lora Cecere, Mike Burkett and others.
Is this really the supply chain control tower you want?
Going beyond simplistic 1990s event alerting to true risk/opportunity analysis and rapid, reasoned response is available today. This is not Star Wars or a mission to Mars, though even those idioms have lost their sense of impossibility lately. It is a journey of maturity, and as our skills, processes, and technology mature we need to both grasp the opportunity and extend the art of the possible.
I’d love to hear from people where they think they are in this journey and the steps you are taking to achieve it.