For many manufacturers, the equipment on the production floor has moved well beyond the traditional mechanical machines that once produced parts and components. The physics of cutting metal or forming plastic remain, but the equipment doing the work now generates thousands of data points manufacturers can use to improve their processes, productivity and, ultimately, profits.
Large manufacturers are well positioned to take advantage of all this data. But the small- to medium-sized companies prevalent in southeastern Wisconsin often face challenges. While industry experts say data will continue to grow in importance, investing in the resources to analyze and use it can be time-consuming and complex.
“It is going to take smaller companies a while to appreciate what their information can tell them,” said Mary Isbister, president of Mequon-based GenMet Corp. “Think about how long it took a lot of organizations to adopt just lean philosophies. It’s the leadership, it’s the workforce and it’s the industry as a whole kind of coming together to make this how we do business going forward.”
Isbister was one of five industry experts to participate with BizTimes in a recent roundtable discussion organized by Illinois-based advisory firm Sikich.
W. Kent Lorenz, the former chairman and chief executive officer of Pewaukee-based Acieta LLC and now a consultant to manufacturers, said he expects early adopters of more advanced data analytics and artificial intelligence will thrive.
“The fast followers will miss it and they’ll miss it because they’re not going to get the economic benefits that the early adopters got,” Lorenz said, adding that companies chasing early adopters will also be chasing customers who have integrated their operations with the companies that can utilize and act on data.
“The stakes are high, because you could go away, but doing nothing is not the right strategy,” he said.
Rob Cowen, president and CEO of Milwaukee-based Badger Alloys Inc., said the challenge is that companies already generate a high volume of data and it can be difficult to know which pieces to act on.
“They can’t make any decisions because they’re streaming through so much information that common sense and the basics have gone out the window,” he said. “You’ve got all this data, but are you chasing the right data, or do you go off on a tangent of something that really adds zero value, or actually costs you?”
Kim Erdmann, president and CEO of Waukesha-based Schaefer Brush, said investing in new technology like an erp software can leave businesses with a lot of new data, but it is important to use it to develop information someone on the shop floor can use. If you’re planning to use an erp system in your business, you might want to contact an erp consulting services firm to discuss which erp software best suits your business.
“Just because you have the data doesn’t mean it’s actionable, doesn’t mean it’s executable, it doesn’t mean it’s going to make a difference, so it is really a huge issue, especially for smaller companies, because I’ve got it and I’m still trying to figure out what to do with it,” he said.
Isbister said GenMet found success by focusing on issues where people could see the benefit of data, like maintenance. The company started by collecting information on key pieces of equipment, correlating that to maintenance events and using it to be predictive about when maintenance should take place.
“We picked areas that people could identify with, that they could draw the line between the information and what it was telling us and then actions it suggests we should do,” she said.
Lorenz said companies also stand to benefit from having access to their historical data in the future.
“Get as much data as you can and store it, because when the AI is ready to look at your data, the more data the better,” he said. “It’s going to find trends that you would never see.”
Tom Fotsch, chief operating officer of Pewaukee-based EmbedTek, said for now it is best for manufacturers to capture data and then keep things simple. They should look at metrics that connect to their business like quality, safety, market capabilities or margins and do so through easy to understand systems like green for good performance or red for poor.
“Then you filter that down to each individual area within the organization,” he said.
Advice for using your data
- Bring employees along on the journey
Clearly communicate the need for and potential benefit to employees and start with projects with clear tangible benefits. - Keep it simple
Align the data you are collecting to key business metrics and then communicate performance in an easy to understand way. - Plan for the future
Data you collect now could be analyzed in the future by AI to identify areas for improvement.
