Enterprise Resource Planning

Which Boat Do You Sail to Cross the Blue Ocean?

by Lora Cecere on August 6, 2012 · 2 comments

In a recent post, Time to Paint Outside the Lines , I advocated that we needed to expand our current concepts of supply chain management.  I challenged readers to rethink conventional processes and to think outside the lines; to redefine them using the new capabilities of mobile, social, cloud-based computing and more advanced analytics.  The post was about the “what.” In a discussion with a client, I was challenged to write about a third dimension. The client asked me to write about the delivery of the services or the “who.” Here I share my insights.

When we start to paint outside the lines, we begin to enter the world of blue oceans.  By definition, a blue ocean is a new market that is uncontested. For the deliverer of services, it is a vast opportunity. Full of hope and promise, the deliverer of services is bullish and aggressive on how they will cross the blue ocean. For the user of technology, it is a situation fraught with indecision, risk and uncertainty.

Blurring of Lines

The lines are blurring on packaged application delivery. (When I use the term ‘supply chain management,’ I am using the broad definition of defining cash, inventory, information and product flows from the customer’s customer to the supplier’s supplier.) My goal is to help clients build the end-to-end supply chain (E2E).

Mobility, advanced analytics, cloud-based computing, advanced predictive analytics, and the Internet of Things offers us the ability to deliver new and improved solutions. By definition, Software as a Service (SaaS) applications open the door to enable this innovation. It allows us new opportunities to deliver value in the areas of pervasive computing and analytics. The traditional software licensing model–always held back by the delivery of user-based enhancements–can now be untethered and cast free to deliver new applications through SaaS delivery. Market requirements are driving it. The processes need to be designed outside-in and there is a need for horizontal business processes to enable a level of agility that is not possible in today’s organization.

As I attend conference after conference, for me, it seems that everyone is talking the talk, but they have one foot in the first phase and one foot in the next phase trying to figure it all out.  While Silicon Valley is still in a love-fest with social applications,  I see companies slowly realizing that social for the sake of social is too limiting. It is about SO MUCH more than digital marketing.  Likewise, it is not mobile for the sake of mobile. It is about pervasive computing and real-time information.  There is also a growing recognition that it will not happen through the sticking of mobile and social data in the outdated models of CRM and SRM. These applications were defined too narrowly to sense and translate market signals into enterprise workflows. The delivery of services and products in these new more pervasive models requires the redefinition of enterprise applications. The traditional definitions of Enterprise Resource Planning (ERP) and Advanced Planning Systems (APS) are slowly becoming legacy.

After the first and second decades of digital marketing, companies are now starting to ask questions about digital business.  They want to know how to transform their very “transactionally-focused enterprise applications” into solutions that can sense and deliver a more agile response.  They want to turn to Oracle and SAP, but these very sales-driven solution organizations are well-tuned to deliver traditional solutions, not to help users cross these blue oceans. They would like to turn to the traditional supply chain planning vendors like JDA and INFOR, but they find that these organizations are busy trying to harmonize and rationalize many acquisitions and that they have lost many of their thought leaders. Deep within the IT groups of organizations, companies may reach out to the conventional analytical vendors like Teradata and SAS, but they quickly find that these organizations are used to selling servers and analytical tools and lack the deeper understanding of enterprise application processes.

The Phases

As we progress, I feel that there are three phases.  While we can argue about the names, please read past the labels to understand the broader discussion, and then let’s engage in a discussion.

  • Phase I. The Efficient Organization.  The first phase of enterprise applications is ending. It is where companies have invested and know best. The focus was on transactional efficiency.  In this phase, the organization was defined from the inside-out and the order-to-cash cycle was automated. (In most cases, it was very rigid. The focus was on control.) Decision support was layered on top of the transactional systems to improve decision making using order and shipment data. This era is ending. Leaders now realize that the dream of ERP II and building the end-to-end supply chain on the back of ERP and B2B connectivity was too limiting.
  • Phase II. Digital Business.  The redefinition of processes outside-in from market to market is the phase that we are entering. It will be enabled by cloud-based computing, business-process outsourcing, and pervasive computing.  New forms of predictive analytics will enable listening (e.g., sentiment analysis and text analysis) to understand the questions that we do not know to ask, and systems will be able to adapt through horizontal process orchestration. This movement to listen, test and learn and bidirectional horizontal process management is just beginning. It is the new blue ocean. It is the era of digital business.
  • Phase III. Systems of Commerce for E2E Value Networks.  As systems evolve, companies will come to realize that there needs to be a greater focus on value-based outcomes and inter-enterprise systems of record to better manage bifurcated trade. This phase will no longer be about industry-specific applications. Instead, it will enable the process flows of end-to-end value networks.  For example, in healthcare, the shift will move from efficient sickness (checking patients in and out of the hospital and lowering the admission rate) to sensing the body and focusing on health and wellness. Likewise, in transportation, the focus will shift from selling cars to safe transport using sensors to guide vehicles with improved safety and lower carbon footprints. We are already seeing this shift in Performance-based Logistics (PBL) in the department of defense.

Users are confused. They want to know, “Which horse do they ride to cross the blue ocean?” Simply speaking, the Best-of-Breed Service Provider will be the best bet. Here are my predictions:

  • Consultants Will Stumble. As the gravy train of ERP implementations winds down, more and more consultants are attempting to build software. This includes traditional consulting partners like Accenture, IBM, Infosys and Wipro. I do not believe that they will be successful.  The client model for consulting is just too strong. While they fundamentally understand the client relationship for the delivery of services, they lack the understanding of product marketing and product development. Of the four, IBM will do the best. They have a long history of building software, but they have struggled to market and capitalize on the software’s potential.  While they will continue to have success in the areas of analytics and data mining, and retail, they will struggle in penetrating the deeper areas of enterprise applications. I believe that each will have some initial success selling SaaS solutions, but will wake up within the year and align their skills to contribute to the market in a greater ecosystem play (e.g., putting SAP solutions into cloud-based delivery systems). I think that they would be better served to combine business-process outsourcing with global centers of excellence targeting large business problems like the Race for Africa for consumer products or the Redefinition of the Cold Chain for biologic products.
  • Best-of -Breed Vendors Will Prevail. For me, the most exciting news is coming from the Best-of-Breed Providers. I am bullish about the opportunities for E2Open, Enterra Solutions, Llamasoft, Kinaxis, ModelN, Predictix, Red Prairie, Signal Demand, Steelwedge, Terra Technology, and SmartOps to bring industry-specific solutions with greater depth to the market. They will push the envelope on the delivery of industry-specific SaaS solutions. They will do it faster with support from their clients. I also believe that vendors like Arkema, Aspen Tech, John Galt, and Logility will continue to gain mind-share with mid-market companies with industry-specific solutions. These solutions are becoming mainstream, helping to fill the gaps that the extended ERP solutions cannot fill due to cost and depth of solutions.
  • Oracle and SAP Will Follow.  While Oracle and SAP will talk “blue ocean talk,” internally they will struggle to “walk the walk.” Neither has been successful at driving partnerships and each is handicapped by a very strong sales-centered (as opposed to market-driven) model. I predict that consulting companies like Converge, Neoris, and Infosys will align with SAP to deliver on many of the blue ocean opportunities that are available through the SAP acquisition of Sybase in either the area of mobility or HANA into emerging markets. I think that they will be more nimble in their realignment than Accenture, IBM or WIPRO. With market success, Oracle will follow. Salesforce.com will be relegated to improving sales efficiency and Microsoft, despite having promising software, will continue to struggle in penetrating the enterprise software market.
  • Conglomerates Will Circle the Drain. The JDA and Infor models will continue to consolidate, and the solutions will progress, but slowly. They will continue to be a good fit for software evolution of existing implementations, but they will not be the horse to ride across the blue ocean.
  • Analytic Companies Will be Best Supporting Actors. GreenPlum, SAS, Teradata and IBM will continue to help with analytic applications, but they will bring up the rear.  None of the analytic vendors really understand how to sell and market supply chain applications to line of business leaders.
  • Business Process Outsourcing Will Grow. The use of analytics and the evolution of business process outsourcing for multi-tier processing will continue to grow.  The work that CapGemini or Genpact is doing on retail deductions or Accenture on consumer insights will continue to grow.

My Take

So, as we set our sails for new places, and plan to navigate blue oceans, be sure that you are working with partners that can help you get there. Long term, it will take a village.  Short term, it will be hoisted on the back of best-of-breed providers.  Sailing in the waters of enterprise applications for supply chain management is always choppy, but it is time to look ahead.

I look forward to your thoughts. Anchors aweigh!





It happens all the time.  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 Discussion Today

When I talk to most people about BI and demand-driven value networks, the discussion quickly evolves to two topics:

  • What is the best BI solution to layer on top of Enterprise Resource Planning?
  • How do I contain and manage the volumes of data in Excel spreadsheets?

For me, these are the wrong discussion tracks.  It is like going to the wrong church with the wrong pew.  For a lady that is knee-deep in building a house, 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.”

Planning for Tomorrow

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.  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 <BTW, Marc Millstein throws a great conference>, 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 coelesceance of social, consumer and shopper insight data.

 Where to Turn….

My bet is that answers will come from a new set, and a mixture, of predictive analytics vendors that are largely Software as a Service (SaaS) suppliers – Bazaarvoice, Clarabridge, DemandTec, IRI, M-Factor, Predictix, Revionics, SAS, and Terra Technology–  in combination with vendor solutions from data analytics companies like GreenPlum, Netezza, and Teradata

In the short term, due to the large quantities of data, I am also seeing a Microstrategy resurgence and the use of Microsoft ProClarity for ad hoc reporting.   Business models for downstream data found for consumer products in solutions like Retail Solutions, Relational Solutions, Shiloh, Vision Chain and VMT will find their place within the Microsoft, Microstrategy and Teradata ecosystems. They will consolidate and mature, but the data models are needed to support retail-specific processes.  Prepare for IBM Cognos, Oracle BI, SAP BW, and SAP Business Objects approaches to be largely relegated to the world of reporting infrastructures.  When it comes to managing demand data, they have been proven to not be equal to the task.

My Take….

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

Am I missing anything?  What do you see?  Where will you turn?