“Good management was the most powerful reason [leading firms] failed to stay atop their industries. Precisely because these firms listened to their customers, invested aggressively in technologies that would provide their customers more and better products of the sort they wanted, and because they carefully studied market trends and systematically allocated investment capital to innovations that promised the best returns, they lost their positions of leadership.”—Clayton Christensen, The Innovator’s Dilemma
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On inquiry calls over the past three months, 9 out of 10 supply chain leaders state that their supply chain is growing in importance; yet, spending for 2011 will be moderate.  How so?  The reasons are many. One is that companies are digesting past implementations of Enterprise Resource Planning (ERP) and Advanced Planning Systems (APS). They need time to reflect and drive ROI.  A second reason is that post-recession spending on technology is tight.  Funds are just hard to come by. 
However, I have another thought.  Could it be that technology innovation has stalled; and due to the lack of innovation, there is no compelling reason for investment? This is my belief. I feel that it is a classic case of the Innovators Dilemma (reference quote above).  In the words of Clayton Christensen, it is being managed to death. It is a market where market leaders are not leaders; and the market is adjusting. We are experiencing the morning after the “ERP Hangover”.  The ERP technology providers are covered-up with “user enhancements” ;and funds within their organization are getting harder and harder to get as the market matures.  I believe that as a result, we will see the adoption and encouragement of Best of Breed innovation, albeit slowly.

Not your 90’s Supply Chain

 The design of Enterprise Resource Planning (ERP) and Advanced Planning Systems (APS) reflect 1990’s thinking.  They focus was on inside out not outside in.  It was about supply.  It was about the enterprise, not the network.  The goal was to enable the efficient supply chain.  The secondary goal was to minimize disruptions by recognizing planning constraints.  In these systems, supply chain execution is defined as order execution, and the transactional systems focus on improving order to cash, procure to pay and revenue recognition processes.   This was a step forward; but as leaders are learning, 1990’s thinking is not sufficient to meet today’s requirements.  Consider these points:

• The efficient supply chain is not the most effective supply chain.  Go to any supply chain conference, and you will hear at least one supply chain executive express the need for greater agility.  Supply chains need to be designed.  There are three primary designs: agile (adaptive for demand and supply variability), responsive (short cycles) and efficient (lowest cost per case).  Current deployments of technology enable the efficient supply chain that may not be the right response.  The gap happens when there is a need for an agile or responsive supply chain.  They are not enabled by current definitions for ERP and APS. (In fact, I think that it is an unreasonable expectation to ever think that ERP could or should be adaptive or drive an agile response.  Transactional systems are rigid for good reasons.  They need to be exacting.)  It requires a different design from the outside-in or from the channel-back into enterprise applications.  
• Companies have multiple supply chains.  As supply chain practices mature, they become VERY industry-specific.  It is often tough for one supply chain application to meet the need of the entire organization. The average company has five distinct supply chains.
• Effective supply chains build strong relationships.   We have automated transactions, but have not enabled relationships.  Customer Relationship Management (CRM) and Supplier Relationship Management (SRM) do not meet the need.  The supply chain needs collaborative applications to define, enrich and grow network relationships.  CRM and SRM are not the right adaptors (connectors) for the end-to-end supply chain.  To build multi-enterprise capabilities –effectively connect trading partners– needs value chain adaptors that do not exist.
• Need to balance growth with efficiency.  To accomplish this goal, demand capabilities grow in importance. There is an increased need to better sense, shape and translate demand. These processes need to extend bi-directionally from the customers’ customer to the supplier’s supplier to enable demand orchestration (the trade off of volume and profitability in go-to market strategies while considering the volatility in direct material sourcing strategies)
• Supply chain excellence requires industry-specific data models.  I know that we have all heard it before, but the industries really ARE different. The requirements to map industries to value chains will further segment the market.  This is an inherent barrier to the growth of the SCM technology market.   The market dynamics make it impossible to have a solution that has the breadth and depth required for all industries.

If I had a Magic Wand: Seven Wishes

So, if you have been shaking your head yes, you may be asking, “what now?”  If you are shaking your head “no”, I would love to talk to you directly. Shoot me an email at loracecere@gmail.com or leave me a post on this blog.
So, if I had a magic wand and crystal ball <I know scary thought>, and I could paint the future of supply chain applications, I would have seven wishes:

• We rebuild from the outside-in.   When we map processes from the customer’s customer to the enterprise, there is usually an AH-HA moment.  Conventional enterprise applications have no place for customer supply chain data.  Therefore to build a demand sensing layer, we have to define supply chain applications that cross revenue-generating teams of marketing and sales to sense and shape demand and monitor ever-changing customer supply chain policies.  Customer data is then translated through a demand visibility layer for the functional requirements.  This demand visibility layer is VERY different than traditional forecast consumption, and is evolving in concept in several supply chain leaders’ minds.  There is no clear definition yet.
• Master data projects go away.  By definition, supply chain data is dirty.  I am convinced that conventional master data techniques will never get us to where we need to be.  I would like to see us deploy the powerful Search Engine Optimization (SEO) techniques that have been defined over the last ten years –like Endeca is doing in Automotive– to dynamically configure data.
• Supply chains start and end with a collaborative layer.  The connection of the end to end supply chain vision:  this is where I believe the true power of social technologies come to life.  Today’s enterprise applications are faceless.  The ability to deploy techniques like micro-blogging (think Twitter), video, collaborative communities (think Facebook), and education (think Wikipedia) horizontally from the customer’s customer to the supplier’s supplier excites me.  Collaborative technologies are an opportunity to better anticipate needs and enrich relationships.  It could enable true collaboration beyond the sales person/purchasing agent relationship to better serve true needs(see figure 1).

• We free the data to answer the questions that we do not know to ask.  Data sources are proliferating. Disparate data sources, the mining of unstructured text, and the need for deeper ad-hoc analysis to drive insights are transforming business intelligence (BI).  The beat of the supply chain — frequency of data sent and used– is getting faster.   I believe that the company not only needs a demand-data repository (DSR), but also an enterprise-data repository and a supplier-data repository.  Predictive analytics can then access the data directly –as opposed to waiting for the data to be rendered through a transactional data model –as the information comes in to sense and respond to changes.  I like the work that I am seeing in this area with five Fortune 500 companies.  In this area, I find the work byTeradata on data reuse and governance/architecture, the work by SAS on unstructured text management and the work by Qlikview on ad-hoc analysis encouraging.
• Intelligence from more than optimization.  We need more math and adaptive rule engines.  Supply chains are unruly, and they do not follow historic patterns.  We have tried to make them more predictive through the use of if-then rules, business process automation and algorithms; but, we have not gone far enough.  Supply chains need better math that is easier to use.  In this area, I like the work that is being done by Enterra Solutions, Mu Sigma, Revolution Computing, SmartOps, and Terra Technology.
• Supply chain execution is redefined.  I struggle to understand how we ever defined supply chain execution so narrowly as order fulfillment.  In the future, I believe that supply chain execution will wrap and connect sell, deliver, make, source in a holistic way.  Manufacturing line go down?  There is an automatic connection to order allocation and fulfillment.  Inbound shipment delayed? There is a connection for rethinking outbound distribution.  The supply chain becomes more connected and intelligent through new rules engines to drive an adaptive response.
• Supply chain apps store.  I got an email this week from a client that is buying supply chain applications.  He asked a great question, “Why can I not get supply chain applications in an on-demand model through an i-store like application?” I agree.  For predictive analytics, the time has come to shorten the sales cycle and make deployment easier. 

These are my wishes.  What are yours?  How do you see the future of enterprise applications for supply chain management?  I look forward to your response. Next week, I will be speaking at the VCF conference on retail compliance in Arizona and at the GMA IS committee on the future of retail data.  I hope to see you in my travels.
Until then, I remain the supply chain shaman scouring the world to understand how new technologies can help improve supply chain management.