Data, AI, and the Human Factor: Guiding Organizational Transformation | Jonas Wahlberg

Thank you very much. Let's see if I can intrigue that insight and find one topic. If you walk out from here with one topic in mind that hey, this was good for you, I'm happy. So, I've been working six years now at Aumo, been a little bit here and there, both sides of the table, consultant working for an international company. My background is really around HR; that's where I come from. But accidentally, almost 15 years ago, I ended up working more with IT as well, or equally IT and HR together. You know, those things happen. Basically, that's why I ended up in that situation, because I am a person who is very interested in putting things apart and putting them back together. I like to build with my house, but I also like technology. When I found a radio in my garage, I pulled it apart, started building it back together to see what it is. I'm not an engineer or technical person; this is just who I am. I just do things like this. So, this AI data is really something that I find very intriguing. Of course, coming from HR, I'm interested in people as well, and making that work together is really important for me. At home, of course, I have the next generation coming up; I have three daughters who, of course, I am not right with them. I'm always wrong, so I have to explain to them what's happening with social media and how to use that. But obviously, the belief in me is not that strong. According to them, they know what they're doing, so that's a fight I do at work as well. Just to set the scene, I'm not going to go through the slides. Not many people know what Aumo does, so I just want to say that we are stainless steel. We are not the same as steel production as many other companies are; it's stainless steel. There's a huge difference. We have about 850 different grades of stainless steel. We have a vast wide market. We make everything from thick stainless steel tankers for chemical storage to the things that you have at home, like washing machines or cutleries or pans. It's a very large application. But why I want to bring up Aumo more than just that is that we are constantly in a pressure cooker. We are the first ones who notice when the market is not going well. We have to be a very technology-driven company and find out ways to do things better. We have huge investments in technology, and management is behind a lot of good ideas, which makes it fun to work for Aumo because we are brave and want to take a lot of steps inside of technology. We are encouraged to try, test, and fail; there's nothing wrong with failing. That's why it makes it really interesting to work there. Now, jumping into the area I want to talk about today, it's really about people, data, and technology. I will go back and forth a little bit about that and mix it up. It will not follow exactly the structure you see here, but everything hangs together. You have heard other speakers today talk about some of these topics that I will bring up, but I'll try to focus as much as possible on the human element. So, does anyone have seen this picture before? I'm sure many have. This is the FBI fingerprint storage from 1944—just fingerprints, nothing else. Imagine trying to find something there to prompt the search. I'm not so sure how long that would take, but it would take a long time. This illustrates that we have been part of the data technology managing processes for a very long time, long before this. At the same time, we have to prioritize; we cannot do everything at the same time. But there are endless cases where HR data can be utilized and be a very effective part of making things better. Just a few tips in the end: we have to, in HR, first of all, believe in ourselves. If we don't believe in what we are offering, then the business will not. We really need to embrace that data and technology and bring the benefit to the business and the end users. Show them what it can do, but also don't invent things that they don't need. Do tests, do pilots, do proofs of concept—whatever it takes to show the benefit. If it doesn't work, don't be afraid to change direction or stop. That's the only way; it's trial and error as you go forward with the projects. The last bit I want to mention is to demonstrate the value for the business. The numbers will not lie; that's where you find the effects, and that's where you get the buy-in to go forward. We also need to start having more discipline in HR. We've always been a little bit gray in some of the processes, but we need to have discipline. We cannot just fumble around with the data or the processes. Then, the buy-in from other stakeholders will be easier to get. It's a big site to utilize data everywhere in a good manner. Even though we are just under 9,000 people, in terms of people, not that huge, but the facilities are huge. Here is where we need to take advantage of technology in many ways. Timing in clocking in and out, plant maintenance—every minute counts. If we clock 10 minutes incorrectly for plant maintenance, it could cost millions of Euros. Technology will play a big part. But yeah, I'll stop here because I could go on forever. Thank you.