Supply Chain Analytics: The Times They Are A-Changin’

February 5, 2015
7:17 pm

The Times They Are A-Changin’
Come gather ’round people
Wherever you roam
And admit that the waters
Around you have grown
And accept it that soon
You’ll be drenched to the bone
If your time to you
Is worth savin’
Then you better start swimmin’
Or you’ll sink like a stone
For the times they are a-changing

Bob Dylan, 1963

Remember this song? I sang it with a tambourine in my hand in the ’60s while swaying back and forth wearing frayed bell-bottom jeans, well-worn sandals and a flowered t-shirt. As a child of the ’60s I joined the chorus to usher in change. Now in my sixties, I want to do it again. My focus in this post is to highlight changes in supply chain analytics, and what this can mean for your business.
Today, if you ask a supply chain leader about analytics their response is all about reporting. If you ask an IT professional about analytics, their response is also usually centered in reporting. The terms supply chain and analytics mean very different things to different constituents within the organization, but my point of view is that investment in analytics can make the difference in supply chain performance. I think that it will define leaders. I also believe supply chain analytics is defined too narrowly by most IT and supply chain professionals. We are at an inflection point: a tipping point of change that I think is significant.
When I use the term analytics, I am using it broadly to define technologies that can sense and drive an intelligent response. I see it as the systematic computational analysis of data. For me it is about much more than traditional statistics and reporting. In my world view, it includes processes like data discovery, test and learn, cognitive learning, visualization and listening through unstructured text mining. While we have built traditional technologies on relational databases and asked smart industrial engineering students to build algorithms using structured data to improve decisions, I think that these times are over. In Table 1, I chart what I see as important market shifts.
Table 1. The Changing World of Supply Chain Analytics

Take time to think about the implications of these shifts. Write a list of the unstructured data that surrounds you that is not used –maps, weather, ratings/reviews, quality data, pictures, customer sentiment data, email, documents–and think of the power of combining structured and unstructured data to drive new outcomes. These impacts are profound.
My predictions:
1) Redefinition of the Market and Business Applications. Today’s software taxonomies of SCM, CRM, PLM and SRM are dead. It is no longer about the automation of traditional silos within the organization. Instead, it is about powering digital business outside-in from the customer back. With the traditional software taxonomies in chaos, a new set of innovative vendors is emerging. I find this exciting.
Take-away: Throw away your traditional definitions of software. Define architectures outside-in, from the customer back, and don’t limit your thinking using traditional paradigms.
2) Shift in Strategic Partners. In this new world, I think that SAP fails and then succeeds. (I think that this will take 4-5 years.) I also believe that Oracle and IBM fail and move into new business models.
Note that this week SAP announced a major shift in IT architecture; however, I think that it is too little, too late. SAP lacks business visionaries that can apply new technologies to business problems. Hasso and Bill have many of the right words in the launch of SAP Business Suite 4 SAP HANA, but the announcement is about the automation of a more traditional architecture that is dependent on ERP. Because of the gap in functionality, and the failure of the Ariba acquisition and SAP APO to deliver on the business promise for supply chain, supply chain leaders have lost patience.
Companies need solutions that work quickly and are easy to use. This new world is no longer about selling to the CIO. It is about cloud-based deployments to business leaders. I believe that the SAP, Oracle, and IBM of today will become legendary case studies taught in business schools in the books with those of Xerox, Kodak, and Polaroid. A portfolio of stories of failed innovation… I think that the stalwart IT providers from the last decade will struggle to make the shift to embrace digital business. I think the heart of digital business will be decision support cloud-based solutions to sense and adapt value networks. I think this is the new world of supply chain analytics.
Take-away: The belief in a strategic software partner is no longer viable. The traditional strategic vendors have not moved at the speed of technologies or the requirements of the business. The dream of effective decision support as an extension of ERP has failed. I predict in the next five years that Amazon will emerge in strategic importance and SAP will decrease in importance. Traditional maintenance costs are holding many companies hostage.
3) We Are Five Years Away from Supply Chains That Can Learn and Adapt While We Sleep. Decision support technologies are changing. It is a combination of optimization and artificial intelligence. I feel that it will redefine master data management, supply chain visibility, and value chain workflows. It will also help us to close the gap on finding and training supply chain talent.
Take-away: Build a team to invest time in learning the new approaches outlined in Table 1. Spend time to learn about Hadoop, rules-based ontologies, and listening engines. The good news is that these technologies are small, iterative deployments that can easily be handled by cross-functional teams in the supply chain center of excellence. Set aside funds in the 2015 budget for line-of-business investment to test and trial new technologies. Build a team of naturally curious business leaders to harness insights from new approaches.
Want to know more? Join us for our big data and analytics webinar next week on February 12th at 11:00 a.m. to hear a panel of experts–Dave Shuman from Cloudera to discuss Hadoop and non-relational architectures; Steve De’Angelis from Enterra Solutions to discuss combinatorial math and cognitive learning; and Sean Riley from Software AG to speak about streaming data and platforms to support the Internet of Things. We also look forward to seeing you at the Supply Chain Insights Global Summit where we will showcase case studies to help companies internalize these shifts and power new results.
What do you think? I would love to hear from you.

Is your Supply Chain AI Ready?

June 11, 2026 2:39 pm

A simple quiz to assess an organization’s AI readiness.

The pace of change is fast and furious. Every day, technology advances faster than we can digest. A great challenge to have.

Determining whether a supply chain is “AI-ready” is less about technology and more about the gray matter between the ears of supply chain leaders. Leadership, alignment, and clarity of goals matter.

Too few companies are clear on the definition of supply chain excellence. Measuring and rewarding functional metrics reduces the firm’s value. Putting agentics on top of today’s processes can make bad practices run faster, reducing value.

The toughest job for the supply chain leader is challenging existing supply chain paradigms that were defined by the limitations of decades of supply chain technologies. As the curtain lifts on the potential of new forms of technology, process redefinition is our opportunity, but only if we are clear on what drives value. (Here, I link to the Supply Chains to Admire reports to help you define value. The next report will be published on June 23rd, along with my Dynamic Benchmarking Product, to help you define value in the face of your AI readiness. More information about the launch is at the bottom of this blog.)

Case Study: A Scrappy Demand Management Approach

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This study of Franklin Sports shines a light on the work that needs to be done at the sales account level to challenge a retail forecast, and also highlights the importance of a new technique for a forecast engine — reinforcement learning.

Artificial intelligence comes in many forms — large language models, generative AI, machine learning, unstructured text mining, deep learning, neural networks, reinforcement learning, agents, and agentics. While the industry is wigging out about agentics, I think reinforcement learning is a great step forward in the journey of Artificial Intelligence.

Can We Side-Step the AI Spin Cycle?

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When it comes to combining tech, 1+1+1 should equal more than 1. The impact should be exponential. Unfortunately, today, the answer is 0.

What do I mean? Let me explain.

I find that the supply chain technology market moves slowly along traditional technology lines. Conferences are usually focused on the use of technology, not on redefining work. This bothers me. I want it to bother you as well.

Here I share some insights to drive change.

Supply Chain Health Check: The Power of an Orbit Chart

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An orbit chart is a powerful tool for understanding the “health” of a supply chain and its potential for improvement. The supply chain is a complex, non-linear system with limited trade-offs. The relationship between trade-offs varies by industry, region, and size. The orbit chart is a diagnostic we use in the Supply Chains to Admire work. Here I explain the use case.

Industry Solutions Should Drive Value Networks: They Don’t Today

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Today, companies require industry-specific supply chain solutions. The performance of 82% of the industries–I term this industry potential–is going backward while companies are trying to

Are You Writing a Check You Cannot Cash?

May 14, 2026 10:16 pm

Don’t let a well-intending, but ill-informed consultant or technologist set an expectation that you cannot meet. No when wins when there is a check written that cannot be cashed. In this case, the consultant will move to the next account leaving you holding the bag. Fight back with a data-driven argument. Help the organization think about inventory more holistically.

Supply Chain Shaman