Let’s face it. We have not done a good job on CPFR or VMI.

October 14, 2010
2:15 am

Many tout it. Presentations expound on it; but back home at the office, customer teams are confounded. In the late 1990’s it was all the rage. Yes, CPFR (Collaborative Planning Forecasting and Replenishment) and Vendor Managed Inventory (VMI) processes, over-hyped by many, have fallen short in delivering the promise. In this article, I look at the evolution, the success and the gaps highlighting where it fits and where it does not.

Why did CPFR /VMI not delivered greater value?

The results are clear. After ten years of active projects, collaborative planning forecasting and replenishment and VMI failed to reach its promise for three reasons:

Too laborious. Just too much work for the benefit. The added costs did not measure up to the benefit.
Retail forecasts not up to the task. For CPFR to work, retail forecast accuracy needs to be high and with sufficient granularity to ensure analysis. The dirty little secret with CPFR is that for most only three retailer forecasts—Best Buy, Food Lion and Wal-Mart—were up to the task.
Lack of integration into enterprise processes. For most Advanced Planning System (APS)/Enterprise Resource Planning (ERP) deployments, there was no logical connection for the data. I predict that we will see a resurgence in the next five years based in the new Software as a Service offerings, advanced analytics based on downstream data, on tcollaborative platforms — Jive and Lithium–but, this change will not happen in the short term.

When does it make sense?

However, it would be incorrect to say that these processes never makes sense. Yes, they were over-hyped and over-promised, and applied to situations where there was not a good fit; but don’t throw out the “baby with the bath water”. So, you might be saying, where does it fit? When a company has five characteristics, companies can see benefit:

Significant channel presence. The account needs to be significant—at least 10% of the channel-for the investment to warrant the expense. The greater the channel presence, the greater potential benefit. It must matter and make a difference.
High demand volatility. CPFR makes more sense for products with short life cycles, seasonal patterns, strong dependence on weather, and in competitive categories. It makes less of an impact for products that have stable demand. Companies benefit from advance warning signals.
Strong retail partnerships. The data is clean, available and meaningful to both parties’ business objectives. Both companies have strong planning skills and a passion for forecast accuracy. It is tied and closely coupled to the business.
Direct tie to replenishment. Many companies forget the “R” in CPFR. If he advanced notification from forecast sensing can make a difference in improving replenishment and the other conditions can be satisfied, go for it! However, not all replenishment cycles can be shifted in concert with the these signals. It works best when there is high volume and unpredictable demand. What makes sense? The supply chains of products like bathing suits, suntan lotion, snow shovels, flu medication, cough syrup are good fits.
Right stuff. It makes sense when there is demand architecture to support close coupling of the collaborative demand signal from the retailer. The architecture must allow integration at the account, ship-to level.

What now?

Lately in my visits with clients, I am finding companies with 15-36 of these collaborative relationships. Lots of process, but little to show for it. When I go through the criteria, there is quick agreement that the foundation of the program was sales-driven versus adding value to the value chain. The secret is to be judicious and look for the right fit. Yes, these processes have a place in driving supply chain excellence; just not the over-hyped promise of ten years ago. The hype has listed, it is time to be more realistic.

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