Roar Baby Roar

May 5, 2021
5:03 pm

Lateral thinking is a manner of solving problems using an indirect and creative approach via reasoning that is not immediately obvious. It involves ideas that may not be obtainable using only traditional step-by-step logic.
Wikipedia

History teaches that political unrest and jubilation follow a pandemic. Our future is defined by extreme local patterns. Conjure thoughts of the roaring 20s following the Spanish Flu. Then imagine rebuilding a society following extreme Covid-19 spikes. Both situations are extreme.

For the supply chain, expect extreme variability. Erratic demand coupled with unprecedented logistics constraints translates to the need for improved visibility. I think the answer lies in lateral thinking. Traditional step-by-step logic leads companies down dead-end streets. (I am a big fan of rules-based ontologies to fuel learning engines in nosql applications.)

In recent research, we captured the top issues of business leaders. We share this in Figure 1. Visibility and variability go hand in hand. As variability increases, there is a greater need for visibility.

Figure 1. Top Issues of Business Pain for Supply Chain Leaders During the Pandemic

Research findings of top levels of business pain during the pandemic.

In large organizations moving forward is a struggle. Post pandemic supply chains offer the chance to build better, but I find that it is hard for an organization to make a decision, especially when everyone wants a voice. In discussions, the word visibility is bandied about but without definition confusing the issue.

Tradition logistics applications assumed availability and focused on price optimization. Today, logistics is constrained, lead times are more variable, and manufacturers struggle. Supply reliability issues are unprecedented.

On calls, companies ask how to build a Control Tower. When I hear these words, I shutter. Readers of this blog know about my feelings on control towers. I am convinced that we don’t move forward without lateral thinking. Supply chain leaders love to chase shiny objects. Most are slaves to linear thinking–functional optimization or single signal processing (telematics, unstructured data, or consumption information).

Here are some guidelines for your journey:

Design for Regional Supply. Prepare for fast and furious business cycles. Don’t argue if the demand spikes will be a U, a V, or W, just get ready. Design the supply chain for reliability and improve marketing sensing capabilities. Traditional supply chain planning is not sufficient. The reason? Order and shipment data latency puts traditional supply chain planning approaches out of sync with the market.
Visibility is not Visibility. In many organizations, there are multiple visibility initiatives without linkage. Start by listing all of the current initiatives improving visibility and ask the question, “How do we build with the goal in mind?”
Build Visibility Capabilities with a Goal In Mind. Tie the signal to outcomes. Visibility for visibility sake is limited. Map processes to a goal like on-time delivery, accurate allocation or improve Available to Promise (ATP). Then actively measure progressive improvements.
Reduce Noise and Amplify Signals. An issue for many companies is discerning noise from the signal. In one company I am working with, each role gets over 2000 alerts daily based on some great work in mining disparate analytics. I am convinced that the work has great insights. I am also sure that they are not used because there are just too many. So, start with the business role and get clarity on the most important exceptions. Then, and only then, build learning engines around these.
Bots Need Supervision. Software robots offer great promise, but effectiveness requires adult supervision. The bots need to be connected to learning engines that can adapt and change to guide the Bot’s behavior. Without this support, Bots will drive a historically defined response.
Don’t Confuse Integration and Interoperability. Interoperability ensures the portability of data across technologies, entities, and companies. While traditional approaches for integration focus on the movement of data for API ingestion, interoperability ensures the use of an established taxonomy to enable data translation, harmonization, and synchronization.

These are my thoughts on a beautiful spring afternoon as I watch a bluebird settling into my backyard nesting box. I am glad to be fully vaccinated and in full swing of planning to kick off the Supply Chain Insights Global Summit on September 7th-9th in Franklin, TN.

Preparing for the Supply Chain Insights Global Summit

The Supply Chain Insights Global Summit is happening on September 7th-9th in Franklin, TN.

We are taking the risk that everyone can get COVID shots to enable an in-person event in September. We will also have a virtual feed for those unable to travel. The goal of the conference is to Imagine the Supply Chain of 2030.

In preparation, I am handpicking the speakers and finishing up the Supply Chains to Admire analysis for 2021. The agenda publishes later this month.

If you have a story you would like to share at the conference; please drop me an email at lora.cecere@supplychaininsights.com. Mark your calendars to join us to think differently and Imagine the Supply Chain of the Future.

Our current research project is understanding the current state of analytics. Our philosophy is you share with us and we share with you. We don’t believe that research should be locked behind paywalls. If you take the study, you will be invited to a closed roundtable to discuss the output. We would love to have your input on the study. We hope to close this quickly. Would love your help!

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.

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 Shaman