Why Is Blockchain Not Hotter?

August 22, 2017
8:14 pm

I was sitting with a representative from the United Nations on my way back from Colombia. As we took off from Bogota, we discussed the potential of blockchain to help her with feeding children in the highlands of the Colombian-Venezuelan border. I was surprised that she knew enough about blockchain to have a discussion, and I think that she was surprised to find someone who could help her to have a deeper discussion. Today I connected her to some technology providers to start a pilot.
This morning I read a Wall Street Journal article on blockchain asking “Why Is Blockchain Not Hotter?” I smiled as I read the article, thinking about the random-chance of meeting a United Nations representative on a Delta flight who hungered to test blockchain. Through my work with the Network of Networks group, several things are becoming apparent. I think I know why blockchain is not hotter. Here are my thoughts:
1) A Lot to Figure Out. For Example, What Is a Node? Blockchain is a piece of a larger technology platform. It is critical to define the publish/subscribe mechanisms, the data architecture, and think through the nodes. Blockchain is a decentralized system based on nodes. The nodes enable replication and authentication of the data. We are not clear on which companies should be a node and how to architect public data sharing across the supply chain.
2) Security in Many-to-Many Architectures. Most of the blockchain work today is one-to-many, not many-parties-to-many-parties. Supply Chain Operating Networks like Elemica, GT Nexus (now Infor), and SAP Ariba are many-parties-to-many-parties. The complexity of many-to-many networks, as compared to one-to-many operating networks, is different by an order of magnitude. Security and data management in many-to-many architectures, and the management within blockchain, is still experimental.
3) Organizational Readiness. We are not set up to test. People with a deep understanding of EDI are in different organizations than the business teams. In most organizations they do not know each other. Companies want definitive ROIs. Power brokers–companies with significant buying power–are not stepping up to the plate (with the exception of Maersk and Walmart).
4) We Have More Sticks than Carrots. While supply chain leaders talk about collaboration, over the last decade processes steadily pushed cost and waste backwards in the supply chain. The cost of doing business is much more expensive for companies four and five layers back in the value network. For example, receivables and payables steadily increased in the chemical industry.

These are my thoughts. I welcome yours!
We will be discussing these topics, and many more, at the upcoming Supply Chain Insights Global Summit on September 5-8, 2017. We hope to see you there!

Warning: Sidestep the Narrative of the Misguided Goldiggers

August 10, 2026 4:58 pm

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.

The Myth of End-to-End Planning

July 31, 2026 9:14 pm

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.

Do You Need a Supply Chain Coach?

July 9, 2026 5:27 pm

Supply chain is where the rubber hits the road. For a public company, over 40% of market capitalization is tied to the trade-offs between growth, operating margin, inventory management, and Return on Capital Employed.

The road for supply chain improvement is fraught with issues. Here we share some and offer some advice.

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.

Supply Chain Shaman