Today we are joined by the analytics “man of steel,” Steve Bartos, the Manager of the Predictive Analytics team in the steel processing division at Worthington Industries. ;-) At Worthington, Steve is tasked with strategically driving impactful analytics wider and deeper across the division and, as part of this effort, helps ensure an educated, supported, and connected analytics community. In addition, Steve also serves as a co-leader of the Columbus Tableau User Group.

On today’s episode, Steve and I discuss how analytics are providing internal process improvements at Worthington. We also cover the challenges Steve faces designing effective data-rich products, the importance of the “last mile,” and how his PhD in science education shapes his work in predictive analytics.

In addition, we also talk about:

Internal tools that Steve has developed and how they help Worthington Industries.

Preplanning and its importance for creating a solution that works for the client.

Using analytics to inform daily decisions, aid in monthly meetings, and assist with Kaizen (Lean) focused decisions.

How Steve pulls out the meaningful pieces of information that can improve the division’s performance.

How Steve tries to avoid Data-Rich and Insight-Poor customer solutions

The importance of engaging the customer/user throughout the process

How Steve leverages his science education background to communicate with his peers and with executives at Worthington

Resources and Links

Twitter: @OlDirtyBarGraph

Steve Bartos LinkedIn

Quotes from Today’s Episode

“Seeing the way analytics can help facilitate better decision making, doesn't necessarily come with showing someone every single question they can possibly answer, waiting for them to applaud how much time and how much energy and effort you'd saved them.” - Steve Bartos

“It's hard to talk about the influence of different machine parameters on quality if every operator is setting it up based on their own tribal knowledge of how it runs best.” - Steve Bartos

“I think bringing the question back to the user much more frequently, much sooner and at a much more focused scale has paid dividends”. - Steve Bartos

“It's getting the people that are actually going to sit and use these interfaces involved in the creation process… they should be helping you define the goals and the problems… by getting them involved, it makes the adoption process a lot easier.” - Brian O’Neill

“It's real easy to throw up some work that you've done in Tableau around a question that a manager or an executive had. It's real easy to do that. It's really difficult to do that well and have some control of the conversation, being able to say, here's what we did, here was the question, here's the day we use, here's how we analyze it and here's a suggestion where making and now let's talk about why and do that in a way that doesn't lead to an in-the-weeds session and frustration.” - Steve Bartos

Transcript

Brian:  So excited to have Steve Bartos here. Steve, what's happening? You're the steel man.

Steve:  I am the steel man. Not a lot is happening. Actually, we're getting ready to move over to a corporate function. So, I may be the deal, pressure cylinders and engineered cabs man but for right now we'll keep it Mr. Steel analytics.

Brian:  That's awesome. So, Steve, correct me if I'm wrong, you manage the predictive analytics group at Worthington