How Do I Know If I Am Ready?

March 27, 2014
8:23 pm

“How can I move the ball down the field, if I don’t have the ball?”

A Question from my Training Class this Week

“How do I know if I am ready for cool technologies? Especially demand sensing and shaping?”

A Demand Planner for a Large Multinational Pharmaceutical Company

Last week was a blur. It was a series of days on planes, trains and automobiles. Unfortunately, it was one of those weeks with pressing deadlines when nothing goes right. I rescheduled my Monday to meet with a client on a pressing deadline and worked through the night to edit and refine the reports/journals for last week’s newsletter. I also continued to work on the manuscript for the book Metrics That Matter to publish in the fall of 2014. The book is now a very worn manuscript.
At the end of the week, we hosted a networking call of the Shaman’s Circle. This is a networking group that meets by phone once a month. No technologists are invited. It is designed to be business leaders talking to business leaders. Each session has a topic. This week’s topic was cool technologies. In preparation for the call, I had given the group a list of emerging technologies that I am watching and I asked each person to come to the call ready to talk about technologies that they are working with. I wanted it to be a discussion about cool technologies, but we quickly got into the subject of adoption.
During the call I got asked a question that made me stop and think. The question was, “Lora, we are a late adopter. We are not comfortable being on the bleeding edge. How do I know if I am ready for these new technologies? Especially demand sensing?” I thought that this was an excellent question. It is frequently asked. So, I am going to focus here and share my answer:
Demand sensing is the application of analytic technologies to detect short-term patterns in channel data and translate it into distribution requirements. It replaces rules-based consumption in demand planning, and will improve short-term forecasting by 30-35%. The data can be structured or unstructured.
It makes a difference. The average client that has implemented demand sensing technologies has reduced inventory by 11%. So, you might ask, why is this not a no-brainer? The answer might surprise you. Here goes:
-Sales Wants to Manipulate the Data. When sales is incented to move product into the channel, they want to touch the forecast and expedite shipments to make bonus incentives. They are uncomfortable trusting their fate to a black box.
What do you do about it? Find an advocate within sales to help sponsor the project. Help to educate the sales force and consider modifying sales incentives for the first three quarters to let the shipments even out to a pull-based signal. The short-term impact for one to two quarters can be a reduction in shipments even though case fill and end-level consumption will rise. Make sure that this is not a surprise.
-Break Paradigms. Traditional Processes Encourage Bias and Managerial Overrides. The implementation of demand sensing puts the fate of the company in the hands of an optimization tool. It will drive a better answer than managerial overrides; but, for companies that have encouraged managerial overrides and consensus forecasting without the discipline of forecast value-add, expect for it to be a battle.
The answer? Take it slow. Prove that it works and educate the team on how the “touching of demand data” actually reduces demand accuracy. Be deliberate. Communicate often.Understand that people will be uncomfortable.
-It Is All About Influence Management. Be very clear on the goal and work to increase advocacy in finance and sales. Make the project a win-win. Yes, it may decrease short-term sales, but in the longer-term it will increase customer service, reduce inventory and improve the execution of new product launch and trade promotions. Who doesn’t want this?
The answer might surprise you. When I was asked the question this week of “How can I move the ball down the field if I don’t have the ball?” My answer was for the team to help the other teams understand the rules of the game and work to move the ball down the field together. Not everyone understands supply chain; and for many, a discussion of demand sensing will sound like gobbledygook.
The success rate is highly influenced by this pre-work. Sell the project internally and find an advocate. And, yes, many companies fail before they succeed. Does this mean the technology is bad? No. It just means that the company didn’t take the right steps to get ready. Remember, many organizations do not understand the basics of demand management. Don’t take it for granted.
Would love to hear your thoughts. I will be landing soon in Philadelphia. Spending the weekend writing and then off to New York to work with a client and then speaking later in the week at a conference. I hope to see you in my travels!

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