Change has been the one constant in the job of Veera Gordijevski, Fortaco Estonia’s production director. Over the last two years the factory has added 200 workers, several welding robots and CNC machines, and introduced tens of new products.

Coping with dramatic growth requires change, and in a modern production environment change isn’t most effective when it’s dictated. Shop floor personnel need to buy in to change and be convinced there is a better way. To make a convincing case, Gordijevski doesn’t consider herself a “person of words.” Data is her tool of choice.

Study the processes
Gordijevski’s approach has been to study processes and understand deviations, employing data analysis to isolate the root cause of a problem.

When Fortaco’s Narva factory found itself in the situation of actual orders exceeding customer forecasts, Gordijevsky and her team froze forecasts for two months in order to analyze the lines and verify capacity. “We studied the workflow of every line, balanced resources, rotated people, and eventually optimized the processes. We built a dashboard tool which gave us a global view of production so we didn’t lose information.” It may sound simple when expressed in a few sentences, but implementing change in a period of heavy growth required a large amount of discipline.

“When I started as production director in 2017 I made the decision that I would take the time to investigate processes myself. I didn’t want to take anyone’s word for how something worked, and I learned that employees themselves don’t always have an accurate view.”

‘Is it possible we’re not right?’
Middle management had worked with the processes for many years and were accustomed to doing things in a particular way. Gordijevski views it as her job to pose the tough question: Is there a possibility that you are not right?

“Sometimes a problem gets identified,” she says, “but that problem represents only a small part of the root cause. In order to convince middle management that change is needed, you’ve got to have the numbers.”

A good example was with pre-fabrication in small machining centers. “There was the belief that we had 400 hours of delays, and we needed to add labor and produce 24/7,” says Gordijevski. “But when we carefully analyzed delays and associated hours, we saw that 300 of those hours were due to other mistakes in the process. There were only 100 hours of real delays. We used data to prove it wasn’t a backlog and we did not add an additional shift.”

“I’m not a person of words,” says Gordijevski. “I am confident when what I say is based on figures. I dislike long meetings where lots of time is spent speculating about what might be the problem. Meetings can only give you a hint of where the problem might be and help you figure out ways to gather data.”

Sowing doubt
Gordijevski is the first to admit that she can’t be an expert on everything. “I once thought that as production director I should understand all detailed technical elements. But I’ve realized it’s more important to lead.”

“I have great experts on my team. My role as a leader is to rely on these experts. I can use data to sow a bit of doubt, to make them question the way we’re doing things. Should it really work like this? How else might it work? If you can raise doubt in the mind of those doing the work, get them to consider that the way we’re currently doing it may not be the best, then they will find a way to improve it!”