Louis’s Learnings – Llamacon 2020

I attended the Llamacon conference (#LLamaCon) this past week (June 16 to 18). This is a yearly event held by Llamasoft that brings together the world community of Supply Chain Design (SCD). 

Like most, if not all conferences nowadays, it was held virtually with the help of pre-recorded talks and some live discussions. The format definitely lacks the appeal and benefits of an in-person event in terms of networking and sidebar discussions, but there was nevertheless a lot to be learned! One benefit is that much of the content will be made available for later viewing if that is of interest to you.

Day 1

The first day was for plenary sessions on Llamasoft, its direction, its software and broader more generic topics. I caught the first talk but other priorities made me miss the other ones.

Day 2

I spent the second day focusing on digital twins and risk management.

In terms of the former topic, I had a basic understanding of the concept and appreciated deepening my knowledge. Essentially a digital twin is a virtual model/software representation of a real product, process, asset or service. In this context, it would be of a supply chain. The model is dynamic and paired with AI to continuously monitor and update operations. It is a useful technology that is gaining in popularity. Many leading companies have already embraced it.

Joe Beck, Vice President, Global Logistics & Distribution, and Allison Fowler, Director, Global Network Strategy, from Medtronic, gave some very informative use cases and insight.

Risk management is a particularly hot topic with this raging pandemic. Many helpful examples of using Supply Chain Design to manage risk were shared including identifying critical suppliers and potential manufacturing/warehousing bottlenecks.

Day 3

For the third day, I concentrated on Artificial Intelligence (AI). Those who know me or have been reading my blogs probably realize by now that I am somewhat cynical when it comes to new technology. 

Candidly, I prefer to think of myself as cautiously optimistic (e.g., see my blog on blockchains). However, when it comes to AI, I consider myself downright bullish and so relished the opportunity to learn about new applications of AI in the field of supply chain.

Derek Nelson of Llamasoft provided some very interesting examples from forecasting, to contingency planning, to employee retention modeling to contract bid pricing for commodities. 

When it comes to the first topic, I think that any serious organization doing forecasting/demand sensing should be considering applying AI to their models if they haven’t already done so. The ability of the technology to sift through extremely large data sets to find repeatable patterns and insights is a boon for improving forecast accuracies. That’s all I’m going to say about that!

As for the other examples, they were niche applications with limited opportunity for dissemination. And therein lays my biggest beef (those who attended Derek’s session may appreciate the play on words) with AI in general. 

Unlike, supply chain design, inventory optimization and vehicle routing that are applicable to most supply chains and where it is possible to use readymade software to build models and quickly run what-if analysis, AI solutions typically have limited applicability and require not only building the model, but the underlying data schema, solving algorithm and user interface. 

For this reason, and others, it is understandable that AI adoption has been flat in the past couple of years as reported by another presenter.

Data Quality

I’m singling out this particular topic because it was discussed in multiple sessions covering multiple subject tracks and because I would like to do something about it!

To summarize, many presenters broached the topic of data quality. One opined that it was the biggest hurdle to more widespread AI adoption. Another stated that it was a fact of life and that we simply had to deal with it. While another rightfully affirmed that data will never be perfect and suggested using cost savings from AI initiatives as a justification to implement data quality initiatives.

“My goal is to convert the Supply Chain function from a support organization to a competitive advantage.”

Guru Pundoor, VP – Supply Chain Strategy, Planning and Execution at American Eagle Outfitters Inc.

I would like to continue the discussion by recommending that Data Quality for Supply Chain have its own tract at next year’s Llamacon, CSCMP or other related conference. 

As users of TMS, WMS, Demand Planning, etc. software, we are uniquely positioned to contribute to the quality of the data we need.


I will leave you with the inspiring words of my former colleague and friend Guru Pundoor, VP – Supply Chain Strategy, Planning and Execution at American Eagle Outfitters Inc.: “My goal is to convert the Supply Chain function from a support organization to a competitive advantage.”

As a Principal at JBF Consulting, this is the frame of mind I bring when working with all of my clients.

Louis Bourassa is the Analytics & Optimization Practice Head at JBF Consulting. He provides analytical and optimization support to JBF clients. Louis has a diverse background with a mix of industry, consulting and software roles that allowed him to develop a strong business acumen and expert knowledge of supply chain analysis and design.

Founded in 2003, JBF Consulting is a supply chain execution strategy and systems integrator to logistics-intensive companies of every size and any industry. Our background and deep experience in the field of packaged logistics technology implementation positions us as industry leaders whose craftsmanship exceeds our client expectations. We expedite the transformation of supply chains through logistics & technology strategy, packaged & bespoke software implementation, and analytics & optimization. For more information, visit us at www.jbf-consulting.com