Big Data

Welcome in the Big Data Opportunity

by Lora Cecere on July 9, 2013 · 0 comments

Big Data Outlook

Big Data Initiative

The term big data is moving up the charts as a “hot topic.” This week, we published our second quantitative study on the evolution of big data concepts, it gave us the opportunity to talk to supply chain leaders on the evolution of technologies and the use of analytics in the Race for Supply Chain 2020.  We wanted to understand where companies are at in the adoption of big data concepts and we had a good time writing the report on the research.

The study was completed by over 120 respondents in the period of June-July, 2013 and the complete study can be accessed on the Supply Chain Insights website or through slideshare.

What Did We Learn?

We believe that the adoption of new concepts for big data is a step change for supply chain teams. It is not about force-fitting new forms of data into applications based on relational databases. Is cannot be treated as an evolution.

It requires change management. It is about small and iterative projects using new forms of analytics. The projects have to be based on a business problem and the focus needs to be on continuous learning. This is quite different from the traditional waterfall project approach of mapping “as is” and ”to be” states and managing a large project against a goal. Companies have to be open to the outcome and invest in innovation through analytics.

To drive success companies have to sidestep the hype. While the powerpoints on big data concepts abound, very few technology companies and consulting partners have built solutions to harness this opportunity, and even fewer supply chain leaders are ready to have the discussion. We find the work by Aster Data (now a division of Teradata) and the work by IBM and Enterra Solutions on cognitive learning engines to be promising. We are also encouraged by SAS’s work on unstructured text mining, Bazaarvoice on the translaltion of blog and sentiment data, and the work by APT on test-and-learn strategies is exciting. We are also encouraged by the work on cold chain and serialization by a number of consultants working on sensor data and counterfeiting.

The Findings

In the study, big data was defined as volume that is at least a petabyte, working with a variety of data that goes beyond traditional structured data, and building processes that are based on an increased velocity of data that is associated with real-time flows. In the results, we see several trends:

-The biggest opportunity is not with the volume or velocity of data. Instead, it is with the management of opportunity associated with new forms of data. In the study,  76% of companies see big data as an opportunity and 12% see it as a big data problem.

-Databases are growing, but they can be managed. 15% of companies have a database today that is at least at a petabyte. The largest databases are not Enterprise Resource Planning (ERP). Instead they are in the areas of product management or channel data.

-The work is starting: 28% of companies have a Big Data Initiative today with 37% planning to implement a big data team.

-Companies that have worked on a data-driven culture have a leg-up. Organizations that have active teams on Master Data Management are more likely to have a big data cross-functional team. 54% of companies with Big Data initiatives believe that big data techniques help with MDM.

In the words of a supply chain leader, the path forward requires a disruption. It is for this reason that we have asked experts from the Department of Defense to join us to discuss these findings on our webinar this Thursday at 1:00 PM EDT. We hope to see you there.

We will also be continuing the discussion at our Supply Chain Insights Global Summit in Scottsdale, AZ on September 11th and 12th. There will be several panel discussions on the future of analytics, the evolution of new technologies for healthcare, and the evolution of digital manufacturing with real-time data.  The event will sell out at 150 participants and the cutoff date for the discounted room block at the Phoenician is August 8th. So register soon to reserve your seat. (The event is now sold-out for technology providers.)

Another Concorde?

by Lora Cecere on September 2, 2012 · 2 comments

In high school, my favorite teacher was Wanda Hughes. She taught history. Her class was both loved and feared. This was one class where there was no messing around. It was strictly business.  She made us read the Wall Street Journal and New York Times daily. We debated the potential outcome of headlines: the Vietnam War, the rise of the Beatles, and the fall of the Nixon administration. We learned that current events quickly become history. In the process, I learned that there were patterns: people make the same mistakes over and over again. It is hard to learn from history.

A Look Back

Let’s fast forward. When I was 28, I worked for General Foods (now a division of Kraft). I was a divisional engineer responsible for the purchase of $42 million of equipment for a national launch. It was a big responsibility for a young kid.

The equipment vendor was in Denmark; and I flew cross-Atlantic flights frequently to check on progress. In those days, the corporate policy was to book cross-Atlantic travel as a first class ticket. (Ah yes, sadly these days are gone forever.) So, as a young kid, I had the enviable choice to either fly SAS First Class directly to Copenhagen or book to Paris on the Concorde and take a commuter to Denmark.  The total time difference was two hours. The cost for the Concorde aircraft was slightly higher than a first class seat on SAS.  For me, the choice was easy. The Concorde was not as pleasant of a ride. The seats were smaller and the food was not as good.

Today, there are no Concorde flights. It was canceled in 2003. After 27 years of flight, it died a slow death.  The price/value equation for the average traveler to fly the Concorde was just not there.

Learning from History

Every year, computer speeds get faster and memory costs are cheaper.  Currently, I am working with several supply chain technology vendors that are attempting to place these new forms of analytics underneath traditional supply chain planning platforms. My caution is that this is analogous to the Concorde.  My question is, “Should we invest to make current supply chain planning systems faster or take advantage of new technologies to redefine them?”

I was speaking to a leader at a supply chain planning company last week, and his words hang in my mind as I write this:

“Lora, you are pulling us along. It is hard for us to do things differently. Our business users ask us for refinements not a re-write of supply chain planning. The momentum in the company is not to do things differently. There is no incentive to adopt new enabling technologies.”

In my opinion, there is just not enough value in speeding up traditional supply chain planning footprints to make it worth our time.  I want technology vendors to start over and “Paint Outside the Lines” and recreate supply chain planning. I want them to deliver more value for the supply chain leader. However, I am convinced that it will only happen if it is pushed by the supply chain leader. If supply chain leaders do not push, I fear that we will have the 1995 version of supply chain planning in-memory.  In my opinion, this would be another Concorde. Here is my logic:

The Definition of Supply Chain Planning is Inadequate. Supply chain planning applications rate lower in user satisfaction than supply chain execution (warehouse and transportation management) software systems.  In Figure 1, based on a recent supply chain survey of 60 supply chain leaders, you can see the current satisfaction levels of supply chain software.

Figure 1: User Satisfaction with Current Supply Chain Software

The traditional definitions of planning were based on computer capabilities from the 1990s. They were the best that we could do then; but they are inadequate today. There has not been a substantial redefinition of planning platforms since 1995.

Time to Paint Outside the Traditional Lines. I would love to see us put these new forms of analytics to use in building the End-to-End value network.  I would like for us to redefine versus making the old, inadequate definitions faster. I am passionate about using new technologies to redefine business outcomes.

The possibilities to improve supply chain planning are numerous–deeper optimization, in-memory processing, mobility, pattern recognition, rules-based ontologies, simulation, text mining and visualization– and offer great promise. However, the adoption of these new technologies to supply chain planning platforms has been slow. I find that most line-of-business users do not even know of some of these possibilities.

Figure 2:  Potential Supply Chain Planning Platform Using New Technologies

These new advances in business analytics can allow the Line of Business User to sense channel demand from the customer back, to test and learn in real-time, and map multiple ifs to multiple thens to orchestrate demand and supply. We are moving into the world of Big Data Supply Chains and Outside-in Processes. Here are some examples:

Digital Manufacturing. The use of mobility in manufacturing is defining digital manufacturing.  In digital manufacturing, sensing real-time equipment status and scheduling based on actual conditions, allows companies to move from a near real-time to a real-time response for manufacturing planning.  No longer does maintenance need to be based on mean-time failure. Instead it can be based on actual operating conditions of real equipment outputs–pumps, conveyor motors and filler heads–to improve the certainty of manufacturing output.

Orchestrating Demand and Supply.  We know that a customer is not a customer and an order is not an order, but there is no way to orchestrate this; and once determined, in today’s systems there is no way to manage a rule-set to ensure that the highest priority customers get the highest priority for inventory. Or for companies to manage operations to ensure that the lowest cost operations are used to fill the customer order. These new forms of analytics enable new sets of trade-offs horizontally. I would love to see supply chain planning vendors embed the combination of Enterra Solutions and Signal Demand to orchestrate demand and supply.

Channel Sensing and the Redefinition of Order Management.  Similarly, I would love to see the roll-up of demand vendors– a demand signal repository vendor like Relational Solutions, Retail Solutions, Vision Chain with a demand sensing vendor like Terra Technology to translate demand from the channel to the enterprise and drive priorities in order fulfillment.

Network Design and Supply Chain Visualization. It is good to see the Llamasoft solution for network design being applied more widely.  This more advanced capability for optimization and simulation can be used for operational and tactical decision-making.  Today’s solutions lack sufficient visibility for teams to quickly make cross-functional decisions.

Can We Avoid another Concorde?

Mrs. Hughes died in July 2010 after 42 years of teaching. The Concorde is now legacy. It is my hope that I can apply what I have learned to help supply chain leaders redefine supply chain systems.  I am excited about the potential.

What do you think? Do you agree? Do you think that we can now declare traditional supply chain systems legacy and start again?

Or, do you disagree? Do you think that there is enough value to putting new in-memory forms of business intelligence under the traditional platforms and running them faster?

I look forward to an engaging debate.