Lora Cecere's Recent LinkedIn Posts

I look forward to a spirited discussion with Don Hicks on the role of design in future planning architectures. This dialogue will be spirited and FUN! We hope that you can join us on April 14th at noon est. https://lnkd.in/eWs-nZSs

It seems that all supply chain leaders that I am speaking to are stuck. They want to automate their planning processes and unleash the power of Artificial Intelligence, but are not making progress with investments in agents or agentics. The answer lies with rethinking architectures for AI enablement. The starting point for most is the data fabric and data mesh, which feed the semantic layer. While a focus on foundational architectures may not seem easy or sexy, you can start by carrying small stones. How so, you might ask? In the words of Confucius, “The man who moves a mountain begins by carrying away small stones.” What is the small stone you might carry? When you encounter a business problem in your supply chain, ask, "Is this an issue at the semantic layer?" Don't accept a workaround because systems cannot talk to each other. I welcome your thoughts.

Does your organization need a Supply Chain Engineering Role to Design and Implement Orchestrate Processes? I think so. Here I share insights on a job description. I would love your thoughts.

I struggle with the current hype cycle of AI for AI where technologists are selling tactically without a focus on value. They are asking users to migrate existing software to build agents on top of traditional supply chain planning architectures. In this blog, I ask business leaders to question the first principles and focus on the user experience. I strongly believe that we need to stay centered in value and first principles and side-step the hype cycle.

Oh my. This analysis is SO out of touch with reality that it is laughable. Putting Blue Yonder at the top of this list is like saying a Saturn car will win the Daytona 500. Yes, Saturn cars are still on the road, but parts are hard to find because there are no new models. It was never designed as a race car. Yes, Blue Yonder still sells software, but I have seen no innovation. The concepts are old. This list is not grounded in reality. Buyer beware.

Software SAS technologies struggled in public markets this week to defend against a popular belief that AI could easily replace enterprise applications. I like the four-box model in Geoffery's blog below. While he mentions ERP he does not mention supply chain planning. Using Geoffery Moore's model do you consider supply chain as mission critical or build? I think that it is both. I think that there is a need for planning as a system of record that is mission critical, and that supply chain master data should be mission critical (but is seldom deployed) while optimizers, engines, visibility, rules, and workflow could be built to augment the framework of the Supply Chain Planning software. A mistake many technology companies are making today is not deepening and focusing R&D teams on the mission critical core. Many are off chasing shiny objects.

How do we drive innovation in software when companies are so focused on technology re-treads, locking horns with late adopters?

I also valued the dialogue because you were curious and thoughtful listeners. The answers lie before us. The question is how to drive the right innovation to define value in a market dragged down by hype cycles and following the herd mentality. The promise looms large. I value that you took time out of your busy schedules to reflect, reset, and redefine your mission. Best of luck! And, yes, walking to get a lobster roll in 70 degree weather while Pennsylvania was freezing was appreciated. And, unforgettable key lime pie…

I look forward to the dialogue on redefining work and improving value through AI. See you there?

My answer to Jeff Metersky’s challenge. I look forward to your thoughts. Pondering if failure can springboard us to success.

A webinar on what we can learn from Digital Transformation Initiatives to apply to the promise of Artificial Intelligence. In most organizations, both sets of these terms are used without clear definitions or well-defined outcomes. In our personal lives, digital transformation and AI are valuable tools. This is not the case for the supply chain. The promise is omnipresent, but the delivery falls short. Here Matthew Spooner and Laura Koxholt share insights on the recent research. If you participated in this research, thanks. Watch for an invite for a roundtable to continue the dialogue. The main learnings are: -Digital transformation improved order-to-cash and procure-to-pay, but fell short in the transformation of supply chain planning. -The most successful implementations reported through line-of-business leaders and supported by teams that were cross-functional, including supply chain finance, and data scientists -The gap between business and IT leaders looms large. As does the gap between business buyers and technology providers. https://lnkd.in/efJ4sBFd Many thanks to Matt and Laura for the time they shared to share their perspectives. My goal is to help companies not make the same mistake twice. I look forward to hearing your thoughts. #digitaltransformation, #artificial intelligence, #supplychain

Great position

Such a great question Few define it I believe it is the combination of transform, source, and inbound logistics. It is not constant. It is a variable.

The constraints within the supply chain of automation and innovation are real and deserve more thought as we redefine potential outcomes. The concentration of semi-conductor manufacturing and the weakness of the power grid are limiting factors. Thanks Mathew

Software companies in the supply chain space are being reevaluated because the industry has followed the herd on hype cycles and not created value. Today, buyers are trying to sort through a list of bad options to answer the question of, “What is the best of the worst in a troubled market?” A great time for true thought leadership to redefine the market. AI is enabling a reset with how we write code and our relationship with data. AI techniques are an enabler, not the answer to improve value where value in all manufacturing segments has declined over the past decade, and there is no supply chain economy of scale. Smart investors will see the opportunity as the market resets. Private companies have the best chance, but must overcome the governance issues of having boards that think they know supply chain software, but don’t.

One of my FAVORITE topics for my blog is answering questions and responding to comments on blog posts. This blog is an answer to Vijay Harrell's request to outline some specific steps companies could take to close the many gaps in supply chain architectures. Enjoy. And, Vijay, let me know how I did.

I look forward to a great conversation

I look forward to it

The beat goes on. Wave-after-wave of lost opportunity because we cannot learn from the past to unlearn to rethink supply chain planning outcomes. How do we break this cycle of wasted opportunity? I welcome your thoughts.

Love the ACR story