Arthrex takes work management to the next level with Domo AutoML and AWS SageMaker Autopilot

Executive Summary

Arthrex Inc., a global leader in orthopedic surgical device design, research, manufacturing, and medical education, wanted a way to optimize project management and improve delivery timelines for medical devices. Working with Domo, an Amazon Web Services (AWS) Partner, Arthrex used data science models to help product teams predict and mitigate issues that could delay the launch of a medical device. Domo AutoML, powered by Amazon SageMaker Autopilot, made it possible for Arthrex to test hundreds of machine learning (ML) models quickly, and use insights from best-fit models to reduce avoidable delays in the product launch lifecycle.

Outdated Work Management Models Fall Short

Project managers at Arthrex help product teams deliver medical devices to the field. The faster a team can get a finished product through the product launch pipeline, the sooner surgeons can use the devices to improve patient care. However, project managers using traditional methods for project management have a hard time anticipating when their teams will encounter avoidable delays and what will cause them. They must either wait for project completion to evaluate what went wrong and fix it the next time around, or they must stop when the setback occurs and rework their process to solve it. Given the already lengthy product lifecycle, Arthrex needed to find a way to use data to improve the product development process and avoid major disruptions.

Task Completion Data Begs the Question: What’s Missing?

At Arthrex, there is no shortage of data—from tools used for project planning and lifecycle management to financial reporting systems—the company can observe product development scenarios from many different angles. Building on the success of a previous project, the leadership team at Arthrex again worked with AWS Partner, Domo, to bring data science into their project management processes. “Domo helped us create a culture of data transparency, so we could really see what was going on from a product development work perspective. That led to us asking questions about how we could improve work management among our product teams,” said Dale Whitchurch, Director of Engineering Global Program Management Office for Arthrex. Using Domo AutoML, powered by Amazon Sagemaker Autopilot, Whitchurch’s team uncovered valuable insights into project management issues more quickly than they otherwise could have.

“With Domo AutoML, we garner insights faster and can more readily focus ways to add value back to the business versus going into the deep inner workings of data science.”

- Dale Whitchurch, Director of Engineering Global Program Management Office, Arthrex

Accelerate Algorithm Selection for Faster Insights

The team knew the nature of their data would heavily influence the type of insights they could extract. For example, depending on how data was ordered or stacked, the model could go in any number of directions. Testing different models manually required a lot of backing out, rerunning, and changing code, which led to analysis paralysis. “With Domo AutoML, we wanted to see how much faster we could deploy algorithms,” explained Whitchurch. “We wanted to know: Can we generate different insights faster? Can we pivot and let the platform figure it out?” Domo AutoML allowed the team to automatically apply hundreds of different ML models to different datasets in just a few hours.

Identify New Potential Causes for Project Delays

With the new system based on machine learning, project managers could quickly visualize what was going on in the launch pipeline, which has made a big difference in their ability to plan. “Domo AutoML took a lot of that middle ground out—the back and forth of analysis and code writing and then spinning off different data analysis pieces to evaluate models,” Whitchurch said. “By removing the heavy lifting of model testing, we could quickly explore dynamics we wouldn’t have been able to consider in the past, such as behavioral patterns influenced by team composition and leadership.” Today, Arthrex project managers have a much deeper understanding of how delays may or may not affect the total project outcome, including delivery date and technical debt, which allows them to change planning horizons to be more deterministic.

Prompt Invaluable Conversations among Teams

While algorithms and models cannot pinpoint what causes a problem to start, data science can help managers see scenarios more objectively. “Data science doesn't give causation, but it does reinforce gut feelings that you might not understand until you see the data. And that is at the core of what data science is doing for us,” Whitchurch explained. “It’s helping us have better conversations with leaders and individuals across the company about how to enable better work outcomes for everyone, so we can reduce avoidable delays and process rework during the product launch lifecycle.”

Arthrex plans to continue to develop its new project management paradigm, enabled by Domo AutoML, to get in front of capacity issues that could potentially delay life-saving medical devices from reaching patients who need them.


About Arthrex Inc.

Arthrex Inc., a global leader in orthopedic surgical device design, develops and releases more than 2,000 new products and procedures every year to advance minimally invasive orthopedics worldwide.

About Domo

Domo is the Business Cloud, empowering organizations of all sizes with BI leverage at cloud scale, in record time. With Domo, BI-critical processes that took weeks or months can now be done on-the-fly, in minutes or seconds, at unbelievable scale. For information about
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Published February 2021