Welcome in the Big Data Opportunity

July 9, 2013
5:35 pm

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.)

My Answer to Joe. The Future of APS

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Traditional Advanced Planning Systems (APS) are unlikely to become true enterprise platforms because organizations remain functionally siloed, metrics are misaligned, and current APS architectures were designed for an environment that has fundamentally changed. Here I share how I think that APS systems can adapt to drive more value.

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Remember the story of the frog in the pot of water? If the water temperature rises slowly, the frog doesn’t recognize the danger until it is too late. Put the frog directly into boiling water, and it jumps.

I think the analogy applies to today’s supply chains.

Companies are absorbing increasing volatility and complexity without fundamentally redefining how work gets done. Companies have confused historic practices with best practices. They are now taking those same processes and attempting to automate them with agents and agentic AI—without first stopping to ask a more fundamental question: Is it time to jump? Here I give a five-step action plan.

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Ten years ago, I started writing a book titled Stories of the Misguided Gold Diggers. The book was a collection of stories from two decades of stories of technology leaders perpetuating the myth of integrated end-to-end supply chain planning.

I dusted off the manuscript on Saturday. I think that we have a new chapter. Companies focused on putting Artificial Intelligence (AI) on top of existing architectures are putting AI Stupid on steroids.

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Supply chain planning, supply management, supply chain execution, network design, and transportation/logistics management operate in silos. Not much has changed over four decades. The connections flow back through transactional systems: order-to-cash and procure-to-pay. There is a myth that companies can buy an end-to-end supply chain management solution. This is largely a myth. Here we explain.

Lead Time: A Broken Gossamer

July 16, 2026 6:38 pm

If you are struggling with supply chain planning, dancing in the light of shiny objects, and scratching your head, please read on. My goal is to help you.

Please do not AI Stupid. What do I mean? AI Stupid is putting agents and agentics on top of existing architectures believing that making them faster and hands free add value. To me, this is fools play.

I love AI. I am excited about new technologies. To this end, I want to shine a light on how new technologies can help address the black holes and inconsistencies in today’s supply chain, which largely stem from the limitations of the first generation of supply chain planning and execution technologies. In this blog, I give you three places to start.

Supply Chain Shaman