Medtronic’s Digital Twin Supports Their Ability To Respond In The Pandemic

Medtronic has been engaged in a digital transformation. This includes building out a digital twin of their end-to-end supply chain to make it easier for people to make better and faster supply chain decisions. The company has built a data lake to feed LLamasoft’s Supply Chain Guru Platform to create their supply chain digital twin. The solution has already been rolled out to support distribution flow path analyses, but the company poured more resources into this project to build out an application that allows them to make better decisions surrounding all the disruption caused by COVID-19.

Medtronic, whose main operational offices are in Minneapolis, is among the world’s largest medical technology companies. This public, Irish company with revenues of $30.6 billion in 2019 with over 90,000 global employees. They have four divisions: cardiac and vascular therapies, a diabetes group, a minimally invasive therapies group, and a restorative therapies group.

This article is based on presentations by employees on the Medtronic supply chain team: Joe Beck – the Head of Global Logistics and Distribution, Jeff Chaussee – Sr. Global Supply Chain Network Optimization Manager, and Lindsay Horner – a Senior Network Optimization Analyst. Mr. Beck’s webinar occurred on May 28^th. Mr. Chausee and Ms. Horner spoke at LLamasoft’s online LLamacon conference on June 17^th.

This is a big company with a big supply chain: 86 manufacturing sites, 250 contract manufacturing sites, 80 sterilization sites, 1,200 suppliers, that produce over 250,000 distinct products. What is manufactured than gets distributed to hospitals, clinics, third-party health care providers, distributors, government health care programs, and group purchasing organizations. 60,000 daily shipments flow through 11 cross docks, 70 forward stocking locations, 57 distribution centers, across multiple modes of transportation, in shipments ranging from less than a pound to full size crates, out to 182 countries. This work is done by 3,600 employees working in Medtronic’s supply chain operations.

The Digital Twin Journey

For Medtronic, a supply digital twin is a digital representation of their end-to-end supply chain that is continually updated. This digital twin allows more scenarios to be run, better decisions to be made, and these decisions to be made in a timelier manner. Before they started on the digital twin journey, this was a struggle. For example, if they want to analyze how certain products were flowing to customers, and whether node skips would make sense, a project might take 7 months. “Be then,” Mr. Chaussee lamented, “the supply chain had already changed.” For example, perhaps a sterilizer site had shut down. “We’d end up chasing a new baseline. We Needed to be faster.”

Medtronic is still in the early stages of their supply chain digital transformation. The initial focus of this implementation was centered on a distribution flow path analyses – how products flow through the global network to customers. LLamasoft helps them to run trade-offs. A slower mode of transportation would require holding more inventory to attain targeted service levels. Faster delivery paths would lead to higher transportation costs but require less inventory. They can also look at whether adding or subtracting a node – like a cross dock – would lower the total landed costs. And this analysis can be “pan-medtronic” – an analysis that crosses the end-to-end supply chain and business units. A cross dock currently used by one business unit, might provide additional benefits if other business units’ goods flow through it.

“Journey” is the right term to describe their digital initiative. Ms. Horner did not try to minimize the difficulties associated with this kind of project. “The idea of digital twin is great. But the journey can be intimidating. Several times along the way, the journey seemed impossible. But if the goals don’t scare you, they are not big enough.” 

One key challenge was the need to pull data from many systems. Often the data was not clean or complete enough. In some cases, the data just does not exist. While they understand their transportation costs at a granular stock keeping unit (SKU)/mode/origin to destination level for most shipments, that was not universally true. In some regions, for some products, they don’t understand which SKUs are in a shipping container. Understanding the landed costs at a granular level is necessary to doing the tradeoff analysis. Getting this data would become a project involving a good deal of labor.

In other cases, getting data was easier. For example, they did not understand the fixed and variable costs drivers at some warehouse and sterilizer facilities. Here they would conduct a survey with facility mangers to get this data.

The Impact of COVID-19

Mr. Beck talked about the impact of the global pandemic on Medtronic. “It has been a whirlwind, weekends and days are blending together.” The supply chain team worked to provide visibility to what was happening around the world. One part of this was standing up calls twice a day and once on the weekend – to talk about the latest developments and issues.

The supply chain impacts have been huge. The supply chain has been whipped around by the need to protect their people, unexpected demand surges and crashes, and countries shutting down and closing customs. Shipping by air became problematic. Much freight moves in the belly of passenger planes. As these planes stopped flying, air capacity vanished.

As COVID moved from a China problem to a global problem, the team responded by pulling 4-6 weeks of inventory forward into countries before inbound shipments became impossible. Discussions were had with their leading carriers where they explained what they were doing and pressed for commitments to move their goods. “The early bird gets the worm,” Mr. Beck said, was the message they delivered to their carriers. “We’ve been successful. We kept product moving.”

The LLamasoft product has been one of the tools used to respond to the pandemic. 95 percent of the data they needed to run COVID scenarios was already cleansed and validated in their digital twin model. The COVID implementation mainly consisted of tracking down the last five percent of the data points they did not have and putting it in the model. 

Mr. Beck pointed out that while demand has dropped off for many products, at some point it will bounce back. Medtronic needs to be ready for these demand spikes. These spikes will put pressure on their European warehouse capacity and make it difficult to secure enough transportation. Because Medtronic pushed inventory closer to customers in Europe in preparation for country shutdowns, warehouse capacity is stretched.

So, as one example, Medtronic ran a total landed cost scenario for how to meet potential surges in demand for their cardiovascular products. If they did nothing, the warehouses would be running at 95 percent capacity, which is dangerously high.

There were various levers to solve the warehouse capacity bottleneck: they could put inventory in overflow warehouses, they could slow down manufacturing, change where certain products were manufactured, or they could slow down shipments by using ocean carriers turning the boats – in effect – into floating warehouses. The total landed costs of all these options were examined. But it was not always strictly an optimization exercise, human impacts needed to be taken into consideration. For example, shifting too far from air to ocean could lead to them losing people with air freight expertise.

When I first got introduced to network design twenty years ago, solving this problem would have been a long, slow, highly sequential process. A planner would examine overflow warehouse scenarios, than ocean scenarios, and so forth. But today, you don’t say let’s examine a overflow warehouse scenario and see the impact. “Really,” Ms. Horner said, “you look for the best combination of all these interventions.”

Conclusion

Mr. Chaussee said that one key lesson is that they are not going to get to perfect data. If you wait until the data is perfect, the project will never get done. There will always be a need for new data. Medtronic will continue to do studies and improve their data governance processes. “You have to start where you are and take a crawl, walk, run approach to driving value.”

Medtronic’s digital twin will be an always on, constantly updated model, that will improve not just their day to day operations, but their business continuity capabilities.