The Big Supply Chain Analytics Failure

November 3, 2021
3:04 pm

New forms of analytics abound. Embracing them is a different story. Data abounds while insights are low. Supply chain leaders struggle with the adoption and use of new forms of analytics. Only one in two are satisfied with their success in using analytics. Here we postulate why based on recent research.

Reason #1. Knowledge

While organizations hired data scientists in the past decade, business leaders struggle to speak the language of new forms of analytics. Terms like ontology, sentiment analysis, python and nosql are unknown to 80% of business leaders. Companies lock their data into traditional relational database structures and limit their possibilities to use disparate data or understand semantics.

What to do? Spend time educating teams based on lunch and learn and open sharing between technologists and operating groups. Do not make the mistake of asking traditional consultants and technologists for insights. (They want to sell you yesterday’s solutions.) Elevate the discussions.

Reason #2. Lack of a Good Framework for Process Innovation

Companies are investing in traditional applications like supply chain planning, but the focus is usually on improving the “engines” or optimization on top of existing systems. Few are questioning the fact that the workflows and architectures are largely outdated.

While companies speak of digital transformation most are working on the digitization of existing processes. The focus is faster and hands free. Companies struggle to rethink the use of technology based on the Art of the Possible to drive process innovation

What to do? Change the dialogue. Don’t focus on making current practices faster. Push for process innovation.

Reason #3. Lack of Awareness of the Need to Unlearn

Change management is fraught with issues. Few feel that they do it well. One of the unspoken challenges is the need to unlearn or ask participants to free themselves from conventional thinking to rethink the possibilities.

What to do? Focus on helping your group to ask the right questions. Start with a focus on supply chain failure. Ask the group to brainstorm on the data available in the organization that can inform and drive new outcomes. Explore the possibilities of unstructured and streaming data.

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

June 9, 2026 5:37 pm

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?

June 7, 2026 3:44 pm

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

May 27, 2026 9:49 pm

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

May 19, 2026 10:06 pm

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