Lora's Latest Post

Change the Conversation

It is Monday morning. As the sun rises, I find myself on the 6:00 AM train drinking coffee. I am giving thanks that I am able to do what I do.
There is nothing like a cup of coffee at this time of morning. As I hold the warm ceramic mug in my hands, the horizon rolls forward with the rhythmic sounds of the train on the track.  I love the sounds of the train.  I am lost in thought about the client that I am going to spend the day with.  It is the end of a long project, and I am excited to share their data. There is such power in being able to pull together quantitative data with financial benchmarking analysis and qualitative interviews to help them see new insights. It is great to pull back the covers and help companies see the new trends and insights on supply chain excellence through research methods.
In work with clients, I find that they have good intentions and they want to be more outside-in and demand driven, but they get caught in a traps, because they have not changed the conversation.  This will be a primary focus of my session today.
Volatility is rising, supply chains are becoming more important and complexity is making resiliency tougher. All are good reasons to have the conversation….
Here are the sticking points that I see:

  1. Focus Less on Perfect Numbers. Embrace Demand Error. Demand volatility is increasing and the technologies to manage demand are maturing. In this transition, it is more critical to learn to use demand data than to make the demand number perfect. As a result, the discussion needs to be less about the “demand forecast number” and more about the probability of demand. Companies need to try to reduce demand error to the extent possible, but realize that demand error is a reality of managing a supply chain. As a result, leaders need to drive the effort to embrace demand error and design the network to drive the same cost, quality and customer service levels given the level of demand error. This requires using new forms of analytics for inventory optimization and network design and doing less on spreadsheets.
  2. Help others to Understand the Impact of Complexity. Nine out of ten companies are stuck in their ability to make progress on operating margin and inventory turns. To understand this, a good place to start is the measurement of the forecastability of the products in the demand plan and understand how this is changing. Track the impact of rising complexity on forecastability and the impact on the inventory plan.
  3. Reduce Bias and Error. If only companies could sell what they forecast. Most companies have a large, and positive bias. To counteract this, actively use Forecast Value Add techniques (FVA) to reduce bias and error.. Communicate progress on a monthly basis. Push to help leaders understand the impact of demand bias on customer service, safety stock and slow and obsolete inventory.
  4. Help others to see the Options. Actively Design the Network.  As you do, focus less on the levels of inventory and more on the trends and right sizing of the forms and function of inventory. (The form of inventory is the state of inventory and includes decisions for raw, semi-finished goods and finished goods. The function of inventory is the role that the inventory plays in driving the right supply chain response. The function of inventory includes cycle stock, in-transit stock, promotional stock, safety stock, seasonal stock, etc.) Actively model and help peers to understand the impact of rising complexity on the form and function of inventory. As you design the network, build push/pull decoupling points and buffers.
  5. Focus Forward. Finance and accounting use largely backward measurements. Push the executive team to focus forward in the design of measurement systemsLead teams to focus on forward-looking business flows through the channel. Align the flows to maximize customer service taking ownership for sell through the channel not just sell-into the channel. Don’t stumble and get hung up on only measuring backward-looking measures.

Any others that you would put on the list?
This week, I am at the Consumer Goods Technology (CGT) conference.  I hope to see you in my travels.

Search the Archives
Search
Share this Post
Email
Twitter
LinkedIn
Facebook
Pinterest
WhatsApp
Featured Image
Recent Posts

Is your Supply Chain AI Ready?

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.)

Read More »

Case Study: A Scrappy Demand Management Approach

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.

Read More »

Can We Side-Step the AI Spin Cycle?

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.

Read More »

Supply Chain Health Check: The Power of an Orbit Chart

An orbit chart is a powerful tool for understanding the “health” of a supply chain and its potential for improvement. The supply chain is a complex, non-linear system with limited trade-offs. The relationship between trade-offs varies by industry, region, and size. The orbit chart is a diagnostic we use in the Supply Chains to Admire work. Here I explain the use case.

Read More »

Are You Writing a Check You Cannot Cash?

Don’t let a well-intending, but ill-informed consultant or technologist set an expectation that you cannot meet. No when wins when there is a check written that cannot be cashed. In this case, the consultant will move to the next account leaving you holding the bag. Fight back with a data-driven argument. Help the organization think about inventory more holistically.

Read More »