Demand driven

March of the Penguins

by Lora Cecere on June 21, 2011 · 3 comments

They look alike.

Noisy and boisterous, they follow each other.  Mile after mile, through adverse conditions, they trudge.  It is a well-worn and familiar path.

When they come to the edge, they crowd together.  With extravagant gyrations they aggressively communicate, but each is afraid to take the next step.  The jump is a hard decision to make.

Last week, I felt like I was watching a re-run of a familiar movie. As I slipped into my seat at the Consumer Goods and Technology (CGT) Sales and Marketing event, I found myself in the balcony. I  looked down.  It was my seventh year of attending the CGT Sales and Marketing Conference. It was a great time to reflect back.   The event had a lot of “sameness.” It had the same themes, same people, same level of attendance, and same names of vendor  sponsors crowding the conference room foyer.  The audience looked alike –similar demographics, backgrounds and experiences–to previous years.  I value my time there and I give thanks for all the great work that CGT does for the industry, but in many ways it resembled one of the scenes in my favorite movie, “The March of the Penguins.”  Anthropomorphism in action….  <Try playing this word in scrabble.>

How so?  During the mating season, penguins gather on the ice flow and look down.  They are afraid to jump into the water due to the presence of the leopard seal. To protect themselves, they huddle together.  It is a dilemma; for, they must jump to feed and survive.  It is dangerous.  As a result, they wait for the first Penguin to jump.  They watch to see if the first into the water survives and then they all jump in mass.  Sometimes, when I am at conferences like CGT, I feel like I am watching a re-run of this movie.  These professionals know that they need to jump.  Traditional software approaches have not served them well; yet, they are afraid.  Their jobs are on the line.  They huddle to look to see who jumps.  They wait to see if the new approach works, and then they jump in mass.

Anthropomorphism in Action

Changing a ritual takes time.  The Consumer Packaged Goods (CPG) industry moves slowly.  The millions of dollars that companies have spent on multi-year projects for Enterprise Resource Planning (ERP) system Customer Relationship Management (CRM) is a painful and expensive trudge.  After studying the industry for over five years, there is no easy answer for trade promotion management, sales accounting and demand insights from these packaged solutions.  Bottomline, companies cannot build market-sensing approaches from these traditional technologies; yet, companies will not take the leap of faith to try different approaches.

I wish that the program and discussion at CGT had not been one of sameness.  The pace of change in the industry is SLOW…. Why? Product margins are high, there has been no compelling event to change, and with sales and marketing job security high, why should they take the plunge?  Why should they put their job on the line and try a new approach?  The answer is simple.  The traditional approach does not work.

Technology applications for sales and marketing are fraught with issues.  They are expensive.  As Oracle and SAP engage in hand-hand combat for trade promotion deals, the 20-40 million dollar price tag for license application deployments leaves many teams with sticker shock. The projects have a high failure rate. Based on over five years of research for CGT, three out of five TPM projects fail to meet expectations. The road to success is paved with many speed bumps that can derail even the well-intended project.

The needs of sales and marketing are also more complex.  The evolution of sales account teams and sales purchase of retail-specific applications has led to disparate applications. In interviews, even the smallest companies, have at least forty different systems distributed across the sales teams requiring maintenance, evolution and integration. The traditional Customer Relationship Management(CRM) data models are not a good fit for CPG.  As a result, Siebel (now Oracle) is a force fit and Salesforce.com has never been a player.   SAP, on its third generation, of CRM for Trade Promotion Management(TPM) is struggling to deliver a successful project.  Accrual accounting continues to be the Achilles heel.  As a result, many grassroots efforts have spawned solutions for downstream data, deduction management, retail execution, and syndicated data.  The names of the software companies are many, the companies are small, and all are competing for attention in the  hallway outside of the CGT conference.

What should we Do?

The times they are a changing….  The manufacturer’s product margins are smaller now. Commodity’s are scarce.  Retailers have stronger brands.  They are better at analytics.  Power is shifting to the shopper.   The IT’s organizational stronghold on the organization to buy only from a standard vendor has lessened.  Software as a Service (SaaS) is a more viable alternative.  Managed services are emerging.  New approaches through social technologies now allow companies to be more customer-centric.  Yet, the scene at the CGT conference has not changed much.  The topics are the same, the people are the same, the approaches are the same, and the It is the SAMENESS that harkens the visions of the penguins standing on the iceberg flapping their wings.  I want to SAY, “JUMP Damn it!”  Spread your wings, consider new approaches.  Let’s move this STALE agenda forward.  The threat of the leopard seal in the water is far less than the market risks that are gathering on the horizon. I think that these are the new paths that we should be trudging:

How do we Sense?  Test and Learn?  Build processes from the outside-in? Last week, I had the chance to catch-up with Jim Manzi, Applied Predictive Technologies to discuss how the building of test and learn scenarios. <He is such a smart guy!> APT applies deep statistics to help companies know the true difference between correlation and causality. I feel that we would be well served to view go-to-market approaches as experiments to be tested, with rapid test and learn approaches. Recognized leaders include Family Dollar, Meijer, and WaWa.   There are also many retailers that will remain nameless–mum is the word– especially in the hills of Arkansas.  This is a major shift.  How do we build value networks to test and learn?  Today, we just respond.  Companies have fixed plans.  As markets change, they do not.  How do we use social networks like Twitter to listen better to the customer in many to many customer service networks.  I feel that this is a new path to trudge with great promise.

How do we become customer-centric?  To listen?  To Learn? To Engage in a Meaningful Dialogue, to drive Continuous Improvement? Now is the time for sentiment analysis and the use of social networks for direct dialogue with the shopper through social networks.  These approaches allow us to reduce latency on decisions, to better sense true customer sentiment and make rapid market changes.  I also think that it is time for us to directly couple downstream data with demand orchestration processes to build a horizontal platform that connects buy-side decisions (which commodities to buy when) with sell-side decisions (what to promote and how to price when) through a combination of applications like Sentiment Analysis + Price Optimization+ Downstream Data + Pattern Recognition+Risk Management to orchestrate demand.  I was excited to have my beliefs confirmed this week in the discussion with IBM Consumer Products team.  They are currently working with Relational Solutions and Signal Demand on a Software as a Service (SaaS) solution.  There will be more strategic vendors added to this road map in the future.  I believe that these are winning combinations to leapfrog the current dilemma. I also believe that there will be more SaaS combinations and managed services to emerge that combine vendor solutions that are built to help scale the current problem.d

How do we best manage global markets?  Where is the right balance of power between central planning and regional decision making? CPG companies are becoming more global.  Retailers will remain regional  Consumer products companies can now use Social Commerce platforms to disintermediate the channel.  How do companies trudge this new path and build new processes? I feel that this would have been a great discussion. For example,  Infosys has a new solution to help companies build effective demand networks with distributors in emerging economies. In my opinion, this would have been a great audience to share techniques on sharing data with distributors in emerging economies.

New ways to reach the consumer.  Tags.  Mobile applications? Exploring new channels. New technologies for retail execution.  What are the strategies for big-data value networks? Direct communication in the buying moment directly with the consumer is the new reality.  What are the strategies and how do we design these big data value networks? How do we unleash the power of mobile applications, tags, social couponing, and visualization to change the shopping experience in the store?   These are all new concepts, but do not have pat answers in the form of standard license software. Instead it requires leadership to build the path for the future.  How are others doing it?  What is the path of the future?  How are companies funding these new approaches to know the shopper?  What do the cross-functional teams look like?

Power of Reviews. Technologies that aggregate and federate review information–Bazzarvoice and PowerReviews are examples–deserve mention.  How about video reviews like Expo TV? Too few CPG companies are discussing the power of customer reviews and the strategies to federate review information with retailers to improve purchasing decisions.  Increasingly, shoppers want to hear from voices like theirs. They are tired of brands yelling the same messages.  How do we best use these new technologies to reach the new consumer.

OK.  I know it.  I have been in the industry a long time.  I am tired of standing on the ice flows talking about yesterday’s solutions.  Please, can we jump?  Can we talk about new approaches?

What do you think? Are there new approaches to solving sales and marketing problems that you think are worth mentioning?  Are you ready to jump? Please share.  Until then, I will continue to trudge–begrudgingly–with the penguins.

 


User in the Era: Big Data Supply Chains

by Lora Cecere on June 1, 2011 · 6 comments

The time is near.  The time has come.

As I return from my trip last week, I give thanks, that it is not the end of the world that we need to prepare for….  Yes, thankfully, as the Rapture witching hour approached last week, I was holding my grandson in my arms with a glass of wine and having a great discussion with my daughter.  (This is something that I hope never ends….)  With false predictions behind us, and I wing my way back from San Diego, I am thinking about the world of Big Data Supply Chains.  I think that it is time for us, as supply chain leaders, to prepare for a new era:  the big data supply chain.  Here I share the what, the so what and the now what with a focus on why you should care.

What is Big Data?

The concept is simple.  The answer is complex.

Big data is a term used to describe data sets that grow so large, and so fast that conventional reporting and analytics are insufficient.  Can you feel it?  It is coming at us like a Tsunami.  It takes different forms, but what is common is the new world of big data. Let’s examine some trends:

1) You see it in new tagging systems for safe and secure supply chains.

2) It is ever-present in demand sensing and the design of listening posts from social networks.  These technologies us the ante on the use of unstructured text and building supply chain systems that can sense just not respond.  It is one that starts from the outside-in to define the enterprise response.

3) It takes the form of mobile devices that are redefining the workplace. Mobile data has grown 8 fold in five years.

4) It is a new world of convergence of visualization, geolocation, and digital media.

5) Partner data is growing exponentially.  What we once thought was just a simple downstream data repository is now being used as the data translator and harmonizer at both ends of the supply chain. It is redefining the world of business-to-business relationships.  Trading partners are starting to share daily data daily.

This is far different than the world of five years ago when data was shared less often; and when it was, it was usually monthly data monthly or weekly data weekly. Each relationship in the global supply chain has unique requirements for revenue management, contract compliance, shipping documentation, and licensing. As we enter the world, where data is more available from trading partners, we can navigate across the supply chain into customer’s customers and supplier’s suppliers.

In this world of big data, relational databases and desktop applications – spreadsheets, statistical packages and reporting—are insufficient. Instead, it requires the use of parallel software running on tens, hundreds or even thousands of servers.  It is the world of terabytes, exabytes and zettabytes of data.

What is a Big Data Supply Chain?  Value Network?

Bear with me.  I am an old gal.  I remember the early discussions with my boss on what we could do with our supply chain when we rolled the IBM 360, down the halls of the manufacturing plant were I was the Plant Engineering Manager.  The machine was huge, but it allowed us to have localized computer capabilities that were upward compatible to future models.  A local computer and a specialized team for reporting drove step-change improvements for our organization.  We could see trends and drive continuous improvement programs that we previously only talked about.
Today’s era of big data supply chains is an even bigger step change opportunity, but to take advantage of the opportunity, we must re-wire our thoughts to see new possibilities.  It is not just about supply, it is about making tradeoffs to improve value.  It is not just about linear relationships or a chain reaction, it is about sensing networks.  It is not just about right product, right place, at the right time.  Instead, it is about the redesign of value networks that use information to reduce latency, streamline cash flow and drive profitability.

Today’s supply chain systems are not designed for the world of big data. It is coming.  The data will be colossal.  The use of data in the supply chain will differentiate.  Have I convinced you that we are facing a new world?  One that ups the ante to sense and respond?  If so, read more…..

My Magic Ball

I was a Gartner analyst for many years. In fact, if I had not jumped ship with the AMR Research purchase of AMR Research, I would be a Gartner analyst today.  So, using my past training, I share my predictions for the supply chain of big data:

#1 A One Vendor World is not the Answer. The big data supply chain will not be a one vendor world (.9 probability). Yes, I know that it was the promise.  I was also told that there was a Santa
Claus.  Supply chain leaders need to grow up.  Gaining competitive advantage from the big data supply chain will not be a “one throat to choke” scenario.  You cannot afford to tie your apron strings to the innovation of ERP vendors.  If you do, you will move too slowly.

However, I find the evolution of the SAP HANA platform interesting.  I think that it will redefine supply chain execution capabilities.  If nothing changes, SAP will outflank Oracle in defining supply chain capabilities.  We have defined supply chain execution too narrowly.  It is more than order to cash.  There are new opportunities in S&OP execution, demand and supply visibility and demand orchestration.  I am also excited by the focus and energy of Manhattan and Red Prairie to tackle this opportunity more holistic.

#2.  Line of Business (LOB) Meet Data. In companies where the line of business leader steps up to own the big data supply chain, there will be a 3X increase in the ROI of IT investments (.8 probability). I have done research studies over the past five years on IT investments of BI in the supply chain.  One factor is clear to me.  When projects are owned by the Line of Business Leaders, and those LOBs are knowledgeable and capable team players, there is a dramatic difference in the impact and ROI on the project. In the face of the great recession, companies that were better at demand sensing changed their supply chains five times faster.  The issue is finding leaders that are both knowledgeable and capable.

#3.  Not a Project. It cannot be solved one project at a time. Companies that approach this evolution as a program, not a project will increase speed to value by 70%. As I study the evolution of Business Intelligence (BI) in supply chain, it is clear to me.  Project-based evolution absent a program and a strategy is problematic.  Companies that have multiple projects that do not build on a consistent data model, with clear data governance, and definition of the meta-data structures, have built a bridge to nowhere.  Most supply chain leaders, as a consequence, are what were described in the 1960’s song, “I am a real nowhere man.”

#4. We must part with Tradition. It will require taking a leap of faith.   It is not the case of something new, something borrowed, and something blue.  It will require a RETHINKING of supply chains to abstract the supply chain into sensing attributes that can sense market changes quickly, easily translate these changes into the world of supply and transmit them in a meaningful way to the supplier. The design is outside-in, not inside out.  It is not longer the world of the language of SKU (item at a location.) This language gets co-opted by the language of attributes. We will have to remap supply chains, rebuild demand and supply hierarchies, and redefine BI –portals, scorecards, dashboards, and predictive analytics—to think in the world of attributes. (What do I mean by attributes?  The company that I was visiting on Friday asked me the same thing. And, then they started to talk about their new world where they have defined customers and suppliers by four attributes:  capabilities, size and importance, power position, and cultural alignment.  Each of their trading partners has been defined on a continuum on these four dimensions.  So, I said, “Now let’s define your supply chain systems to use the data.”  They nodded in agreement. They got it.)

Think about it.  How does this type of prioritization change how you manage demand shaping programs, contracts, available to promise, order management, new product launch programs, assortment and special programs, allocation, network design, etc.  My client got the message.  It is no longer about a blind SKU moving on a blind order to a customer without any definition.  Just as the body has multiple senses, the supply chain will evolve with multiple sensing mechanisms based on attributes.  This evolution will make current Enterprise Resource Planning (ERP), Customer Relationship Management (CRM) and Advanced Planning Solutions (APS) solutions obsolete over the next five years (.9 probability). Because current analyst models are funded by these late stage technology solutions, you will find little from analysts on the rise of big data supply chains.  The reason? The shift is discontinuous.

#5 MDM will not take us to the Pearly Gates. As companies enter into the world of big data, Master Data Management (MDM) concepts that we know– and never loved– will fall by the wayside.  They will be scrapped.  New technologies will evolve to better handle MDM.  There are three technologies that I am watching closely that I think offer promise, both singularly, and together.

  • Search Engine Optimization(SEO) : Endeca is using their SEO tools to improve flexibility in parts management in the automotive industry.  The use of tagging and attributes improves flexibility.
  • Artificial Intelligence:  Enterra Solutions redefinition of security data for the Iraq war was applied successfully to Conair and Newell Rubbermaid supply chains in 2011 to sense supply issues and redefine the response.
  • Intelligent Workflow for Governance:  Kalido has introduced intelligent governance workflow for line of business users.

Within five years, the landscape of master data solutions will be redefined (.9 probability).

So, what do you do?

  1. Stabilize.Take a look at your product portfolio and stabilize traditional approaches, especially ERP projects. Focus on the use of ERP for seamless movement of transactions. Throw away the enterprise application lexicon that you have learned and get ready for a new world.
  2. Define. Map the supply chain from the outside-in focused on how customer attributes translate to service and product attributes.  Think about how and why you sense and what a decrease in information latency can mean for your supply chain.
  3. Build.Focus on building an inter-enterprise data model.  Focus on the ends of the supply chain….  Realize that there was never “R”– or relationship– in CRM or SRM applications. Think about what you could accomplish through the building of business-to-business relationships through a combination of social, sensing/listening technologies and predictive analytics to transform B2B.
  4. Will require a Team.  Invest in a BI team of excellence to look at how companies can drive insights from data. Staff it cross-functionally, but align the reporting relationships to a line-of-business thought leader that has cross-functional responsibilities.  Experiment with new master data management systems.  Develop a holistic BI strategy for your value networks.
  5. Get good at data.  Train teams on the evolving world of business intelligence and the use of trading partner data in data-driven decisions.  Reward innovation through the use of predictive analytics.  Focus on data reuse, meta-data definitions, and data enrichment strategies.  Overlay the BI team of excellence on top of sales and supplier relationships to build data-driven sensing to drive supply chain requirements.

What do you think?

Have you thought about big data supply chains?  Data for value networks?  Let me know your thoughts.

For additional articles on supply chain business intelligence
topics, reference these blog posts:

Ring in the New Year: http://www.supplychainshaman.com/altimeter-group/ring-in-the-new-year/

Three Things that I have Learned about Downstream Data: http://www.supplychainshaman.com/downstreamdata/three-things-i-have-learned-about-using-downstream-data/

A Leap of Faith?  http://www.supplychainshaman.com/demanddriven/a-leap-of-faith/

http://www.supplychainshaman.com/demanddriven/start-a-new-conversation-free-the-data-to-answer-the-questions-that-you-dont-know-to-ask/

http://www.supplychainshaman.com/new-technologies/is-this-the-future-of-downstream-data/

http://www.supplychainshaman.com/supply-chain-excellence/crossing-the-great-divide/