Enterprise Resource Planning

Start a New Conversation. Free the Data to Answer the Questions that you Don’t know to Ask

by Lora Cecere on September 14, 2010 · 0 comments

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?

Have we forgotten the promise?

by Lora Cecere on August 13, 2010 · 4 comments

For about eight months, on Monday morning,he would push the well-worn newspaper clippings under the door frame of my closed office door.  They were folded and stained, but the newspaper clippings were marked with telling, cryptic comments.  I miss them. I loved his insights. 

When I was an analyst at AMR Research, they were gifts from my friend Bruce Richardson.  He was helping me lighten up my writing and enjoy blogging.  I was new at it, and he always wanted to be SURE that I had plenty of material.  He did it again this week; albeit virtually, with his post reflecting on the twenty years of Enterprise Resource Planning (ERP) http://blogs.infor.com/inside/2010/08/erp-turns-20-what-happened-to-the-party.html. Yes, Bruce there is no party; but I also feel that there is also no accountability (from either analysts or software vendors).

I started this blog post originally as “one score and fifty-two days ago, an analyst group brought forth on this planet a concept named Enterprise Resource Planning(ERP) and dedicated to the proposition that all transactions are created equal.  Now we are engaged in a great civil war, testing whether the concept, or any packaged application concept, can long endure….” But, I stopped, because I love the Gettysburg address and I did not want to do it an injustice.  A decade is a score, and we find that we are embroiled in a battle within the enterprise between Information Technology (IT) groups and the line of business of the value of ERP, and the future of packaged applications.  They were purchased against the promise of lower costs, reduced IT risk and delivery of best in class operations.  I think that it is time to give the score a score. 

I only wish that the vendors would step back and self-assess and give themselves a score.  Instead, as ERP matures, the spend is on go-go marketing.  I travel a lot and find that they are everywhere.  At every corner, or hallway in the airport, you see a sign.  They tout dominance and assume that the promise of packaged applications is a given.  Company X installed application Y. Company Z has 9 out of the top 10 companies in industry QRS. However, I don’t find any company holding themselves accountable to the original promise.  There is no score. So, I thought that I would share one.

How did we do? If the question is “how did we do on recording transactions, improving revenue recognition, and accounting for assets?  I would give the effort a score of B+.  If the question is “how did we do on the delivery of supply chain management for the enterprise?” I would give the effort a C-.  If the question was “how did we do on building the end to end supply chain?” I would give the effort an F.  I fear that we are stuck.  The investments in  enterprise platforms– traditional ERP, APS, and BI– are not moving us forward in delivering the solution for the end-to-end value chain.   Here I share my thoughts and three steps to take now to accelerate progress.

The Score for the Score

  • Did we lower IT costs?  Sadly, I report that every study that I have conducted as an analyst in a manufacturing or retail industry sub-segment for the last seven years as an analyst says no.
  • Did we reduce risks?  Yes, when packaged applications were implemented correctly, the applications delivered on this promise.
  • Did we implement best practices? The answer to this question is yes and no.  Yes in accounting, yes in order management, but for evolving areas like supply chain, it was hard for a packaged application vendor to hit a moving target.

What do we do now?

The solution for the end–to-end supply chain from the customer’s customer to the suppliers’ supplier requires a rethinking of processses and a redesign.  To make this happen, we have to change our assumptions and focus on:

  • Rethink architectures.  Most companies assumed that ERP would be the backbone for the end-to-end supply chain management opportunity.  Unfortunately, it is not that easy.  The true backbone has yet to evolve, but my prediction is that it will be a combination of collaborative technologies like Jive or Lithium (at the core) surrounded by a new definition of business analytics to sense and drive an agile response. Today’s supply chains don’t sense and the architectures drive a fixed response.
  • Elevate the discussion.  It about much more than about data, but the discussions will start there.  In the implementation of packaged applications, we did not pay enough attention to data (e.g. data reuse, governance, enrichment) and the translation requirements between trading partners.  The new world of decision support supported by new data types –unstructured text, video, channel data–can be used to sense demand, listen to the customer and understand near real-time market changes, but we need to rethink how we use these new types of data in operations to drive a flexible response. 
  • Reset expectations.  Packaged applications assume that there is a supply chain established best practice. It is a moving target.  We need to admit that there is no best practice for supply chain.  It is evolving.  The belief in best practice a score ago, is vastly different than today’s belief. 
  • Feasible?  Economies of scale?  The solutions within the enterprise need to be industry-specific.  The solutions for the value chain need to be value chain specific based on value-based outcomes.  This sounds simple, but it is not.  Moving from an industry focus to a value chain focus for packaged applications vendors is a major change management issue, and there is a great unknown if it can be profitable for the software provider. 
  • Wean vendors off the maintenance drug. Software maintenance has become the drug of choice for software vendors.  Guaranteed annuity payments drives the wrong behavior. Stabilize existing projects and push for return on investment of maintenance IT spending.  In buying solutions, push for Software as a Service (SaaS) and Business Process Outsourcing (BPO) technologies to break the mold.

To cross the chasm, free yourself to invest in cloud technologies, emerging value-chain applications, new forms of business analytics/decision support and collaborative technologies.  What do you think?  What score would you give the score on delivering the promise?