demand driven

One of the favorite parts of my job is teaching classes on how to take supply chain concepts to the next level to improve corporate performance.

I love helping people to see supply chain concepts differently. One of the ideas that I am researching and sharing is the concept of building Market-Driven Value Networks. The concepts of being market-driven build on the research that I have done for the last ten years on building Demand-Driven Value Networks (DDVN).

The vision is aspirational and takes the concepts of being demand driven to a next level. To ensure clarity in this post, let’s start with definitions. I define DDVN as:

Demand-Driven Value Networks: A network that senses demand with minimal latency to drive a near real-time response to improve  demand shaping and demand translation.

And, a Market-Driven Value Network as:

Market-Driven Value Networks: An adaptive network focused on the delivery of value-based outcomes. It  senses, translates, and orchestrates market changes (buy- and sell-side markets) bidirectionally with near real-time  latency to align sell, deliver, make and sourcing functions. It builds on the concepts of becoming demand driven.

These are a step change in thinking. Both move the supply chain design from inside-out to outside-in. Traditional supply chains respond, but they do not sense. The processes and architectures that we built over the last thirty years delivered inflexible processes that take too long to respond. These legacy processes amplify and distort market signals putting the supply chain on the “back foot.”  As demand and supply volatility increases, the sensing and translation of network shifts is importance to corporate performance. Nine out of ten companies are stuck. They are unable to drive growth, maximize profitability and minimize cycles. More and more, companies are realizing that effective value networks drive GROWTH. No longer should the supply chain be thought of as just a cost center to manage.

As I teach the class, I learn too. Here I share these insights and recommendations to the readers of this blog on how to get started.

My Lessons Learned:

Supply chain practices are steeped in belief statements that there are “best practices” and that the “order is the best representation of demand.”  As we build supply chain strategies in the class, I work with attendees to first answer the questions in the green box to design the strategy:

  • What are the right ways to support the business strategy?
  • What are the right trade-offs between the value drivers for each value network?

Time after time, I find that companies are left with lofty business strategies that are not translated into actionable plans for the organization. I also find that there are too few business strategy consultants that understand the need for this translation. Most companies struggle with this activity. I find most are in a quite a mess.

The next step is to answer the questions on how to define demand and supply relationships to deliver on the promise of supply chain value networks.  The activity starts at the end of the supply chain in the definition of demand and supply relationships. It cannot be effective from the inside-out.

Companies are not good at demand. The gulf between commercial and supply chain teams needs to be closed. For most, the building of demand relationships is a new concept.  It is often the first time that attendees to the class have thought about the frequency, availability and cleanliness of demand data. We then work together through activities to gain an understanding of demand synchronization, harmonization and translation. The goal is to make channel data useful by the corporation.

In parallel, the design of supplier relationships to maximize value is a ripe area for discussion. Only 22% of companies are actively managing the end-to-end value chain to deliver on corporate sustainability goals. We discuss the principles of supplier development and how companies shift from punitive practices, where costs and waste are pushed backwards in the value chain, to owning the extended supply chain to deliver on the brand promise.

Most supply chain professionals have spent their time at the center of the supply chain and have not thought about the options and the design of the ends of the supply chain enough. The center is strong and inflexible and the ends are weak.

After answering the questions in the white boxes, companies can then define the process. It should be then, and only then that the business processes can be defined. Process needs to follow strategy. When this happens, there is greater balance between metric trade-offs and resiliency in year-over-year improvements in corporate performance.

Recommendations:

Many companies do not know where to start. And, we try to be clear in the course that the starting point is in improving reliability. The Market-Driven Value Network visions need to have both “big wings” and “big feet.” The feet are grounded in reliability. When given the choice between reliability and shorter cycles, the supply chain leader needs to choose consistency and reliability. This includes consistency in manufacturing operations, order-to-cash processes, and customer service. The wings are defined in a clear year-over-year strategy to enable evolution towards a vision.  Here is how you start:

  • Stabilize ERP Investments. I believe that ERP is important to improve transactional accuracy and cycle efficiency. You simply cannot have an effective supply chain without it, but I recommend that companies do it ONCE and do it WELL Avoid ERP bells and whistles. It is important that companies do not become hostages to long, multiyear ERP rollouts.  It is too big of an opportunity cost for the organization. In addition, the promise of extended ERP is not worth the trip. The gap in capabilities between best-of-breed supply chain planning applications and those from ERP providers is growing. When given a choice, implement the base modules for ERP and do it well. Sidestep the planning and analytic offerings.
  • Actively Invest in Cloud-Based Analytics for Self-service by the Line of Business User. Today, companies cannot get to data. The multiple ERP instances, and the tieing of analytics only to ERP projects, leaves the company unable to get data from a heterogeneous IT landscape. There are advancements of in-memory, cloud-based analytics like Qlikview in combination with visualization technologies like Spotfire and Tableau.
  • Redefine Demand.  Start by recognizing that the order is a poor representation of “true demand.” Start by asking for demand data by channel partners and then build systems to synchronize and harmonize channel demand data with new forms of analytics to recognize patterns. (Technologies to synchronize and harmonize demand data are sold by vendors like Orchestro, RSI, Retail Solutions, Retail Velocity, and Teradata.) Redefine demand planning to model what the company is “going to sell” and take advantage of the new attribute-based modeling capabilities from vendors like Logility and SAS, and demand translation capabilities (e.g., replace rules-based consumption logic) with solutions from Terra Technology. After taking these steps, invest in building cognitive learning engines and implement test and learn capabilities with technologies from Applied Predictive Technologies (APT), IBM and Enterra Solutions. These learning engines allow companies to sense, learn and then act.
  • Build Strong Horizontal Processes with a Focus on Orchestration. I describe orchestration in the blog posts  Just You and Me Dude and in the second post Bait and Switch. The important horizontal processes are Revenue Management, Sales and Operations Planning, Corporate Social Responsibility and Supplier Development. Build strong what-if capabilities through systems like Kinaxis and Steelwedge.
  • Invest in Business Networks and Inter-Enterprise Systems of Record. We are on the cusp of building effective business networks. There is a strong need for inter-enterprise systems of record. I do not think that this will happen through the repurposing of indirect procurement networks (e.g., SAP’s redefinition of Ariba). Instead, I think that this will happen through the evolution of industry-specific business networks.  I am busy researching the business network evolution of GHX for Healthcare, E2Open for high-tech, Elemica for the Chemical Industry, Exostar for Aerospace and Defense, the redefinition of Covisint for the Automotive Industry, and GT Nexus for Apparel and Distribution Intensive industries. What is old is new again. I describe this in the post Emperor’s New Clothes.

What do you think? I would love to hear your voice.

We know that companies are busy, and that it is hard to go to conferences and keep track of all the changes in the technologies. In our training, we try to build it down and combine the research with experiential exercises. If you are interested in having your teams participate in the training, and learn the concepts, check out our training options.

At the end of the presentation today, it happened. At break, after sharing research on the principles of becoming market driven, I was relaxing with my coffee when I heard a person softly say, ”I am sorry to be so dumb, but I don’t think that I understand the concepts of becoming market driven … or the differences between market driven and demand driven. It is probably me, and I hate to ask it in the group, and I would certainly hate to APPEAR in your blog tomorrow, but can you explain it ONE more time?”

It is ok. It is just you and me, dude. I will not share your name publicly. Since so many people have the same question, I thought that it would make a good blog post. I have done it in the form of an open letter.

Dear Gnarly Dude:

First of all, there is no such thing as a ”dumb question.”

It takes courage to ask tough questions, and I appreciate it. These concepts are not easy.  In fact, it took me eight years of research. So, please don’t apologize. It is ok. 

Let’s start with the difference between market-driven versus marketing-driven processes. In the old-fashioned, conventional organization, functional processes are usually marketing driven. Marketing hones what they think is a brilliant message and broadcasts the message to the crowd through media tactics. The marketing group tightly controls the message to build brand. It is hard to change because the marketing organization driving a marketing-centric program has worked over the last two decades. Change is tough.

Contrast this to a market-driven company, where you are serving the customer by listening, testing and learning. It is not about control. Instead, you understand that the crowd has wisdom to share and you want to listen. You want the supply chain to be designed to drive unique assortments and to reliably respond to changes in demand. To do this, the supply chain is designed to sense, learn and then respond. Today’s conventional supply chains only respond, and the design of the systems usually gives us a “fairly dumb response” based on history.

Additionally, in a marketing-driven company, good news happens fast. When a product is selling and marketing is meeting the business objectives, everyone is quick to grab a beer and do a toast. I am sure you have a lot of T-shirts in your closet from these launches. However, when the sales are not at plan, the news travels slowly in the organization and there is often a lot of denial. As a result, organizations are usually struggling to write off SLOB (slow and obsolete inventory).  A discussion with marketing about SLOB is never a good thing.

So, what is the difference between a market-driven and a demand-driven value network? A demand-driven value network senses demand with minimal latency to drive a near real-time response for demand shaping and demand translation. In this network, the bullwhip effect is minimized using channel data.  Contrast this with a market-driven network that builds on the demand-driven concepts. It takes it one step further. Being demand-driven is a prerequisite to be market driven. In a market-driven value network, the use of market data is used to orchestrate trade-offs market-to-market ( buy- and sell-side markets or channel to supplier trade-offs) through the use of advanced analytics in horizontal processes to orchestrate demand and supply decisions based on analysis of profitability, mix and volume against the business strategy.

Why do we need to change? It comes down to good business. In most companies, growth is stalled. Traditional marketing tactics are not as effective as they used to be. Power has shifted to the shopper. Companies today are unable to drive profitability, and manage inventory cycles, while absorbing the complexity of a rapidly changing product mix. The traditional supply chain is designed to support high volume, predictable items in known markets. When things change, it cannot adapt.

So, if you buy the argument, here are some steps to take. The first step is the building of an architecture to match customer attributes to product attributes. Think about these concepts:

  • Building of Listening Posts and Actively Listening and Learning from Consumer Data. Most of this is unstructured  data—Facebook, Twitter, Ratings and Reviews, and Blogs—which requires the deployment of sentiment and text mining applications. These technologies are new, and the process evolution to support the use of the data is evolving. The first step is to set up a cross-functional team to review this data weekly and then start to use the data in conventional processes (e.g. rating and review data into forecasting as a causal factor for new product launch, discussions on true customer sentiment to drive the decision of how much to make on the second production run after launch, or market receptivity to a new promotion, etc.)
  • Design of Outside-in Processes. The use of channel data—point of sale, warehouse withdrawal, basket and retail partner perpetual inventory data—to understand channel flows and improve demand sensing. When companies are market-driven they use channel data to drive a pull-based response while actively designing push/pull decoupling points to maximize flexibility while minimizing costs. This channel data is archived in a system of reference, often termed a Demand Signal Repository, for reuse. Using cognitive reasoning engines and advanced optimization, unique insights radically improve the response.
  • Rethinking Planning.  This channel data is then used to drive planning. Demand planning models are based on attribute logic. So, as items change, the new item is forecasted based on profiles of the history of products with like attributes.
  • Embrace Test-and-Learn. Actively design in vitro test-and-learn scenarios based on carefully designed testing based on market data. Use test and control markets to adopt assortment and demand shaping activities. Use new forms of analytics to learn from channel sales. Build a supply chain to support this type of agile response.
  • Use New Forms of Analytics to Drive Demand and Supply Orchestration. Traditional supply chains respond to volume-based pulls based on orders and shipments. The data are stored as an item sold, at a location, based on volume. In market-driven value networks, companies actively use optimization and predictive analytics to match price and demand shaping activities market-to-market. In horizontal processes, like revenue management and Sales and Operations planning (S&OP), new forms of analytics are actively used to make trade-offs of mix, profitability and volume. Commodity markets are too volatile for this to be a passive process. For example, if a product has a high commodity cost, or is difficult to manufacture with unsure reliability, the company would question if this is the right product to promote or market. The orchestration of demand to supply evaluates the price elasticity of market pricing against the commodity risk in sourcing and the reliability of processes to deliver. Let me give you an example. During the recession, there were two competing breakfast cereal companies. Each had the option to promote either cereals with corn or wheat. It was proven that consumer sentiment was equally disposed to either product. Corn was skyrocketing in cost and one cereal company orchestrated demand and supply and decided to promote a line of wheat products. The other company promoted corn-based products based on history. The company that promoted wheat-based products gained market share and managed profitability. The other company reported a serious decline in earnings.
  • Alignment of Functional to Corporate Metrics. Focus on the Use of New Forms of Analytics in Horizontal Processes. Market-driven companies understand that the most efficient supply chain is not the most effective. They actively design the supply chain based on the probability of demand and the uncertainty of supply. It is clear that the complex trade-offs of the supply chain cannot be made in spreadsheets. As a result, they model the potential of the supply chain by analyzing the trade-offs of growth, profit, cycles and complexity in new forms of analytics that support the horizontal processes of revenue management, Sales and Operations Planning (S&OP), supplier development and corporate social responsibility.

So, gnarly dude, I put you at the head of the class. You listened intently in this morning’s session, and you asked wonderful questions. I wish you well in your market-driven journey. I cannot wait to write your case study.

Sincerely yours,

The Shaman