To Move Forward, We Need to be Clear on What We Are Automating

September 1, 2019
8:30 pm

For the past six years, I have spent my labor day weekend preparing for the Supply Chain Insights Global Summit. Next week, I will welcome over 100 participants to the annual event. The event is designed to Imagine Supply Chain 2030.
The format of the conference is different than most. There are no vendor booths or paid speaking engagements. I handpick each of the speakers and work with industry leaders to develop content. For the event, I also invite the Supply Chains to Admire award winners to present their story and give the winners awards. This year, Sleep Number will present their story of driving profitable growth in the face of complexity. The event is live cast and will be archived. The goal is to build a guiding coalition for change.
Over the six years of the analysis, the number of winners is consistent at 4.5%. Less than five percent of companies are outperforming their peer groups while driving improvement. The reason? Traditional supply chain processes are not equal to the challenge.
If you believe we have the best practices, please spend time reviewing the data. The full report is available for review. The analysis is designed to provide Industry benchmarks by peer group and to celebrate the success of 23 companies out of 28 peer groups. As can be seen in the analysis, 80% of the industries studied for the report went backward on key performance measurements like cost and inventory management over the last decade. The reason? There are many. Some would say that there are too many to count, but I believe that it includes complexity, compliance, commodity volatility, increase in demand volatility, globalization, and alignment.

Can Data Scientists Help?

The answer is maybe. However, don’t think that the addition of data scientists to the supply chain team is a panacea.
Let me explain. I am a simple gal. For me, progress starts with people. In preparation for the Global Summit, we completed a survey of employee satisfaction. The major gaps are finding employees with the right skills, training on next-generation processes and the lack of executive understanding of supply chain processes. These themes are not new. The answers are more complex.
Figure 1. Employee Challenges

The greatest gap in sourcing talent is in deep analytic skills. These are tough to find. With the supply chain programs embedded in the Department of Marketing within Business Schools, many business leaders worry that the incoming talent lacks depth in analytics skills.
Figure 2. Positions in the Greatest Demand
The shifts in analytics are exciting, but the organization’s ability to use them is questionable. In many organizations, the inclusion of data scientist into teams is like a dog chasing its tail. The reason? Automation requires clarity. Data scientists think they know the answers, and business leaders are unable to speak their language. As a result, there is an impasse.

Progress Is Slow

The data scientist focuses on the improvement of engines, but new processes need more than engines. Systemic improvement requires the redesign of workflow, rules, and the user interface along with the engines. Most business leaders lack this attention to detail, and most software providers are too busy selling today’s systems to rethink and provide a step-change in functionality. The technologists face the Innovators’ Dilemma. As a result, the greatest innovation happens in best-of-breed start-ups.
To maximize the value of a data scientist team, the organization needs to think about an organizational layer of translation to adequately communicate the requirements of workflow, rules and the user interface. Without this, I find that the data scientist will improve the engine, but the results are not able to become part of an embedded process due to the lack of holistic thinking.
Figure 3. A Need for Holistic Thinking for User Interface, Engines, Workflow, and Rule Sets

What to Do?

To drive progress, we must challenge our mental models and test our paradigms. I am excited to do this with the audience next week. I look forward to sharing the images the groups will develop on the Future of Supply Chain 2030 with our visual artist next week. I hope that you join us online for the event.

Navigating Supply Chain Economic Downturns

August 30, 2026 5:28 pm

In 2007, the average company took six months to sense market shifts and adapt its supply chain. My estimate, based on work with clients, is that if a downturn happened today, the average company would take 20-30% more time to adjust than in 2007. Here I give insights on preparedness.

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.)

Supply Chain Shaman