Downstream data

Dreaming of Clouds, Lakes and Streams

by Lora Cecere on June 13, 2014 · 2 comments

 It is morning in Chicago. I crave coffee. The sun shines brightly out the window, but the noisy city is quiet. My mind is moving to the click-clack of my keyboard on this quiet morning.

I cannot sleep. It is hard to quiet an unquiet mind. Somewhere deep inside me is the need to write this post.

Yesterday, I spoke at the Eye for Transport conference on the Big Data opportunity in supply chain. (The slides are available on slideshare.) Before I start, let me give a preamble. I hate the term Big Data. It is overhyped and overused. As a result, it has lost meaning. I writhe in my seat when I hear it. It is even more painful when I hear others speak about it to drive commercial aspirations without a firm grounding in reality.

When I go to an analytics conference today, I feel like the dumbest person in the room. The rate of change is incredible. I firmly believe that the Supply Chains in the next decade will look vastly different from those we see today. I think that we are poised for the third act of supply chain technologies. It is a new world of Best-of-Breed Technologies. The reason? Today, we are stuck. Nine out of ten companies are not making progress at the intersection of inventory turns and operating margins.  Our supply chains are not able to meet the requirements of the business. Frustration abounds.

For the supply chain leader, the noise of change is deafening—rising complexity, demand volatility, new business models, commodity volatility, ethical supply chains, collaborative economy—yet, our processes and technologies are staid and unwielding. We are paralyzed by history that has been transcribed into a canonical myth of “best practices.”

“Rubbish!” I say.

So, in summary, today, we don’t have a big data problem. Instead, and more exciting, I believe that we have a big data OPPORTUNITY! It is not driven by data volumes. Few companies that I work with have databases larger than a petabyte. Instead, it is driven by the opportunity to use new forms of data, and to improve the speed of decision making with increased data velocity.

 

The Real World

Yesterday, Abby Mayer and I presented an update in a webinar on the two-year research project, The Supply Chain Index. As I look at the progress of the companies that I have worked with over the last decade, the stories hop off the page. They are stories that I can never tell because of NDAs. My voice is caged by my promises to my customers.

In one peer group, there are two companies. One company is outperforming the other in very volatile times. The company that is exceeding was an early adopter of in-memory analytics for self-service by business users. This company can do “what-if” analysis and on-demand reporting. They implemented ERP early and stabilized the implementation. They are now working on the adoption of new technologies that many would call “Big Data.” The other company has implemented ERP three times, and badly. In this second company, it takes five days for a business leader to get a custom report. All of the custom reporting is a service through IT.

The first company sits on one of the largest databases of channel data in the consumer products industry. They can see daily channel data daily by item. The second company reads market data through syndicated sources. They can see more aggregated data with a two-week latency. I believe that data matters. Every company that I work with that has invested in channel data sensing tells me that it is a project that pays for itself in days not weeks. Yet, the number one question that I get is, “What is the business proposition of building a demand signal repository?”

In the real world, we don’t wake every morning knowing what questions to ask. The markets are ever-changing. We see data, observe patterns and want to learn more. The business leaders at the second company are at a clear disadvantage. I can see it in their numbers. However, it is hard to package what I see into a nice, neat ROI package to delight a CFO.

Some Context

When I think about the big data opportunity, it is not the world that we have today. Instead, it is about the advantages that we can garner in this next generation of technologies. For me, it is about data lakes, clouds and streams. The financial, insurance and e-commerce industries are leading. They are paving a way for manufacturers to rethink their processes. I want to break down the barriers for adoption. What do I mean?

  • Clouds. In supply chain circles, data clouds get the most buzz. We have seen the impact and the effects are far-reaching. It enables new business models for B2B network providers, in-memory optimization and new forms of virtualization. Concurrent optimization allows us to paint outside of traditional Advanced Planning System (APS) frameworks. It is powerful; however, this is the concept that I find the least exciting when I think about the big data opportunity.
  • Data Lakes. The ability to mine data in data lakes or pools to unearth new opportunities through new forms of analytics using nonrelational techniques is exciting. The mining of structured and unstructured data together ignites my thinking.  Today, we do not have an average customer; yet, we broad-brush markets. Our abilities to sense outside-in and to listen to the market are too limiting. For example, why are we not using Google search trends as a causal factor for forecasting? Or mining sentiment data for quality insights? The market data is there. We are not using it. Why? It does not fit into our paradigm. We are frozen in our thinking on inside-out processes that are powered by relational database thinking of traditional enterprise applications. Our functional silos are struggling to get the technologies of yesteryear to work.
  • Streams. This is the concept that I find the most exciting. Streaming data is pervasive in e-commerce and also core to the future of  supply chain technologies. Why do I feel this way? Most companies are so busy recording transactions into nice, neat rows and columns that the streams are hidden. But, encased in the data, we have order streams, shipment streams, payment streams…. The list can go on and on. The evolution of big data techniques can allow us to sense changes in these streams quickly and change course. The same principle of streaming data from a temperature sensing RFID device can be applied to streaming data within the enterprise. The ability to write APIs to data streams and the possibilities for supply chain excite me.

I believe that we are attacking many business problems too narrowly. Let me give you an example to use these three concepts. Does master data management give you a headache? We are hard-coding master data into relational systems; and as we do, we lose the context. What if we could place enterprise reference data into a data lake that can be assembled through rules-based ontologies and cognitive learning?

What Are the Barriers?

The problem is us. There are three primary obstacles for the line-of-business leader:

  1. The first barrier is that we , as manufacturers and distributors, are cheap. The great minds working on big data opportunities are working in industries where investments in technologies are viewed as mandatory to drive innovation. They are not hampered by having to have a fixed ROI with a three-year payback proven by a two-year pilot.
  2. The second barrier is that we have to retool our minds to understand the opportunity. It requires a new language and embracing new concepts. It requires education. Spend time teaching your team about the new concepts. Here are some to start with: Hadoop, Yarn, MapReduce, R, Nonrelational Data, Unstructured Data, Rules-Based Ontologies, Canonical Integration and Cognitive Learning. Business leaders need to spend time learning the concepts and brainstorming the use cases. This shift will not come from the IT department. They are too constrained with fixed budgets, mountains of requests, and traditional vendor interaction. It will also not come from discussions with the traditional vendors that you find pasted all over the airports. Instead, it is found in conferences that are primarily attended by e-commerce pure plays, home entertainment companies, financial, and insurance institutions. Form a small team to go learn about the new opportunity.
  3. The third barrier is how we think about technology. We are hard-wired to think about technology as a fixed project with a set of defined deliverables. As a result, we cannot be open to the outcome of what we can learn by testing and learning with new forms of analytics and techniques to seize the big data opportunity. The companies that are doing this well have cross-functional teams that are funded with innovation seed dollars to test new technologies against a business problem. However, there is a major difference. The projects are small and iterative. They are not the massive, large consulting projects of yesteryear. I love my podcast with Fran O’Sullivan from IBM that explained this very succinctly.

I will stop now. Room service is knocking. Coffee is in my future, and soon….

This morning, I will be presenting on the opportunity for social data in the supply chain. A subject that many of you know has been top of mind for many years. Hopefully, I will sleep tonight….

How Can We Help?

If you would like to better understand the Big Data Opportunity in Supply Chains, please join us in our quest to help others think differently. Join us in our research study on Big Data and join us at our Global Summit in Scottsdale, AZ on September 10-11, 2014. It is only 89 days away…

At this conference, a number of business leaders have asked to have a private whiteboard brainstorming session. It is private. It will be a session amongst peers to rethink the opportunity in supply chain analytics. I am looking forward to it. I hope that it is standing room only. I hope to see your face in the room….

 

 

The Third Act

by Lora Cecere on May 2, 2014 · 0 comments

An antagonist (from Greek ἀνταγωνιστής – antagonistēs , “opponent, competitor, enemy, rival”, from anti- “against” + agonizesthai “to contend for a prize,”) is a character, group of characters, or institution that represents the opposition against which the protagonist , or main character, must contend. In other words, an antagonist is a person or a group of people who oppose the main character(s). 

Wikipedia

The stage is set. We are now in the third act. In the script, the supply chain leader is attempting to get value from supply chain software. The pressures are mounting, the service failures are many, and the drama is high. They reach out for answers. Technologies have advanced and they believe that there MUST be a better way. It is less about the cost of software than the delivery of value. The stakes are high. Their career rides on the decision.

If they are a gray hair, like me, they have survived the first two acts of the play. They are callous and skeptical. The stories of “consultant answers” fills their bookshelves like fairy tales stacked on my grandson’s shelf. They know that there is something better out there, and they are looking.

How does the third act end? I don’t know. Let’s look deeper at the plot of the first two acts.

The first act centered on the “birth” of supply chain planning software. The best-0f-breed (BOB) market was a cast of characters. The stories of “bad behavior” are now legend. Unfortunately, the fight became one of market share. Companies like i2 Technologies and Manugistics fought each other. As they battled for market share, the focus on innovation and serving the customer dissipated.

The second act was the promise of the “integrated supply chain.” In this act, very large systems were sold with big price tags and high expectations. The market became mired with large implementations and expensive consulting engagements. The planning systems in this era of software were inferior to the first generation, but they were sold with the belief that 80% would be sufficient. And, that one size could fit all…. Supply chain leaders now know that this was not the answer.

In the third act, companies are waking up. The business requirements have changed. Growth has stalled, and demand and supply volatility is greater. The business pain is high. The complexity of managing a global supply chain has changed everything. Uncertainty is rampant. Due to the amount of investment in supply chain technology in the second act, the CIO is dragging his feet. He does not want to talk about a new system or a different approach. The CIO believes that if he just pushes harder on the tightly integrated ERP providers, that they will step up to the plate.

The third act is very different. Supply chain matters more than ever, and the CIO plays less of a role. To succeed line of business leaders have to learn about new forms of technology and use their influence management to drive supply chain innovation. The traditional definitions of architectures disappear. Here is what I think happens:

  • Analyst Frameworks Matter Less. As the supply chain planning and execution technology landscapes get redefined, new software products, services and taxonomies are defined. As a result, the supply chain technologies of the next five years will be difficult to graph in traditional four-box models.
  • New Capabilities. While the traditional focus for planning was to take transactional data as an input and drive time-phased data as an output, leaders now know that this is not sufficient. Technology capabilities up the ante. As a result, the new solutions will focus on sensing flows and patterns, driving visualization and insights, and producing intelligent rules and policies as outputs. It will be about end-to-end orchestration of volume, mix and profitability. The inputs will be both structured and unstructured data types. It will be less about integration and more about data synchronization. New forms of visualization will make decision support easier.
  • Cloud and Non-Relational Databases Drive New Capabilities. The use of the cloud, and the evolution of Software as a Service models become mainstream.
So, how do I write the script of this act? Who are the players? Let me give it a try.
  • New Players Change the Story. The rise of the dutch software solutions and North American analytics providers changes the course of the play. The conservative, product-centric dutch, offer an alternative to the market giving the buyer a new set of choices. As the anger rises against JDA and Oracle maintenance policies, more and more companies turn to these new solution providers like AIMMS, OM Partners, Ortec and Quintiq. As a result, JDA and Oracle become less relevant.
  • New Forms of Analytics and Concurrent Planning First Confuses, and then Advances the Market. Technology providers like DecisionNext, Enterra Solutions, Llamasoft, O9 Solutions, Solvoyo, Terra Technology and Tools Group offer new capabilities and possibilities. With the confusion, business leaders have to re-skill to understand the new opportunity. As the curtain rises, the first set of demand architectures is unveiled. Supply chain analytics combine advanced optimization with cognitive learning to drive new levels of insights from the outside-in. For the first time, supply chains can test and learn in-vitro around the clock. The fights between IT and line-of-business reach fevered pitches; but dissipate when IT understands the capabilities for insights and visualization.
  • SAP Stumbles and then Recovers. SAP, the provider that has built the strongest and most capable system of record, but has failed at delivering excellence in systems of differentiation, is called onto the carpet. The company stumbles and then recovers at the end of the third act. The announcement of SAP APO re-write onto the HANA platform raises customer ire. As commissions fall for the SAP sales personnel, the company adapts and then recovers. At the end of the third act, SAP starts to copy the best-of-breed innovation that has powered new levels of corporate performance. The press releases and celebrations are served with great fanfare.
  • Logility and Kinaxis Survive and Thrive as the No-nonsense Solutions. Logility and Kinaxis continue to survive and thrive as the focused vendors. They become the partner of choice, based on industry requirements, for a system of record for companies .5M to 2B.
  • Canonical Integration Layers and Collaborative Multi-party Applications drive New Capabilities. With the rise and acceptance of B2B Supply Chain Business Network Providers, EDI VANS carry fewer messages and are less relevant. New forms of application capabilities are developed and birthed on Many-to-Many Architectures. The business value between a synchronized and a tightly integrated supply chain becomes painfully clear for the manufacturers that fail at the start of the next recession.
  • Infor Finds a Niche. The ION architecture and social collaboration with Ming.le offer new opportunities to retrofit very capable old architectures. The pragmatic buyer celebrates the new business model that does not require rip and replace.
One of the things about writing the script for the future is that you are guaranteed to be wrong. These are my thoughts; but more importantly, what do you think? Lend your voice. At our upcoming conference, Imagine on September 10th-11th, we will give supply chain planning leaders a room and a facilitator to sort this out and come up with their vision of the third act. You will not want to miss it. It is a unique opportunity for leaders to talk to leaders to figure out their version of the script. We hope to see you there!