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

thank you very much uh 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 I'm happy let's see let's see if I manage that so um yeah just before I start so I've been working six years now aumo been a little bit here and there both side of the table consultant working for 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 uh you know those things happen and basically that's why I ended up in those in that situation is that because I am a person who is very interest in putting things apart and putting them back together so I like to build with my house but also like technology when I found a radio in my d garage I pulled it apart started building the 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 very intriguing and of course coming from HR I'm interested in people as well and making that work together is really really for me and 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 uh you know have to explain to them what's happening with the social media how to use that but obviously the belief in me is not that strong they are according to them they know what they're doing so that's a fight you know I do at work I do that as well so equally going but just you know bring you first quickly autoo to set the scene in I'm not going to go through the slides uh what is read there just to know because not many people know that what aumu does so just want to say that that's stainless steel right so we are not the same as steel production as many other companies are it's stainless steel there's a huge difference of course we have about 850 different grades of stainless steel we have vast wide Market we make from this thick uh stainless steel tankers chemical you know storage to the thing that you have at home in your washing machine or cutleries or pans that the thing is definest so everything in between so it's a very large application uh but why I want to bring up autumo more than just that is that we are constantly in a pressure cooker uh Auto we are the first one who notice when the market is not going well right so we are the base product so we have to be a very technology company and find out ways to do things better we have huge investments in technology uh management is behind a lot of good ideas which makes it fun to work for out the Kumo because we are brave and want to take a lot of steps inside of Technology we are encouraged to try and test and fail it's nothing wrong to fail so that's why it makes it really interesting work there uh but is a of course you know is a good culture colleagues everyone are really accepting the new technology which makes it fun really then jumping into the area what to talk about today is 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 it's because everything hangs together you have heard other speakers today talk about some of these stuff that I will bring up but I'll try to focus as much as possible on a human element all right and let's go from there um so does anyone have seen this picture before I'm sure you have many have anyone just to show where people and technology and data comes from even long ago this is the FBI fingerprint storage from 44 just fingerprints nothing else imagine trying to find something there to prompt the search I'm not so sure how long that will take but it will take long time so just illustrating we are coming with people we have been part of the data technology managing processes very long and of course long before this but let's not go too far back uh sometimes it hasn't always looked very organized right so sometimes we have had little bit hybrid situation where we have the data uh on the desk and in the desktop and this is not you know this is 30 years ago or 40 years ago so it could look like something like this and why I bring it up is because we have as people being intrigued with data and how we operate data we want to make data important it doesn't matter how you have it where you have it it's absolutely needed for what you make every day so meaning of data of course everyone knows this this I will not stay here too long you're too smart for this so really about the decision making it doesn't matter what you use what you read data is for you daily is it in work of work you study you read paper you read the weather app what shoes you will make take on next day tomorrow will be snowstorm so I will not have these shoes on tomorrow so it's about decision making same applies in work but how do we make that decision what do we need for the data to have or basically B availability where is the data many have already brought it up today where is the data how to integrate how to connect the connections very important then what else do we need we need the quality we can we trust the data can I really trust that it's snowing tomorrow or will I have very sweaty food Fe feet tomorrow at work how does this work the same applies to work in HR can I trust the process can I trust that what comes to me I know I can make a decision based on this it comes from the right sources and then uh I think this is very important how do I make HR understand the data how do I make the organization understand the data to be utilized um it was mentioned in marketing in the morning about this many times to understand the data for kpis for example what do you want to measure so just to use the data right in the company you need to know what it is um then little bit of the data where we also as as Auto combo is what path we have gone now I've not been part of the first part of the human chaos where we have data everywhere but just to you know show you we use a lot of scrap right in Auto so we have to order it we make have to make order of the data about the scrap the same about the data that you collect and and the journey dat has gone through so really where we are maybe with uh a pretty much and many companies are we are in the stage of structured data right so we know what we have we trying to make a different uh structure data categorization subcategorization trying to explain it to other utilize it the different Integrations for different purposes of the business not just HR but HR data we want to push to the business and that's why we have to make it structured and understandable but where of course we're head you have seen this uh before and and uh we're going very much with the new technology into unstructured data and of course requires change in what we do and how we operate with data in HR as well and really you know that's it looks uh like similar stuff in the last picture but it's very very important that the structure data is correct quality it has certain amount for example in our production you have to have a certain we recycle 90% of our stuff is recycle that we use for production so it has a certain amount of nickel fer Chrome and other materials inside to make stainless steel and we need to know what is in there or we cannot make the right decision of the next product that we are developing or producing at that moment so because of production you don't just change in a heartbeat you don't just go say tomorrow I will make this type of stainless deal you have to know what you do obviously because the change to change product such a big environment takes a long time the turn of the ship is long uh in nature of course we can make the turn a little bit faster than that but the echo of quality knowing what the data is what is inside of the data is very important um so little bit what it means for HR that we have gone through a situation that we already structured uh at the moment so for us it has made really that we can trust the data more we can bring up data easily we we are more compliant with it we can share it more easily explain it to business where we are and we basically have been able to get rid of quite a lot of compliance topics trust me that's a huge task uh and and and and all these funny filing namings which we have seen throughout the year when somebody leaves and we clean up during offboarding the computer is is can be funny you know it's not long ago we we we found this I'm I cannot tell you all the cases but those are existing and and and and uh you know what to do uh happy that we have passed this almost I would say I don't know if happening but at least I haven't seen for a long time this stpe of stuff but um what this has then brought us back to the picture that I talked about quite a bit and and what is behind is for HR and what really means the change for us in the data topic and where we human element comes into play in the future is really how we how we work with the data so the unstructured we don't anymore oh how would I say we are more like how can I make this data how can I make it available where can I find that data so basically we're grafting data so it's about joining data together bring it together just like nature nature have brought Evolution together and so on so on now we are in the next evolution of data we are crafting the data we have to start doing that or we will be left behind that's a fact if we don't join data with different operational stuff and we as consumers played a key role to do that AI cannot yet plug two uh things together physically luckily so we have some jobs and also we have some ownership in the content so really that will be our part is is making sure that the data is there when you search for it and we can already see I saw a demo on Friday that you know really okay probably many of you have it already but what it's really nice to see that you can actually use a reporting tool and not anymore need to figure out what should I filter and not just type in the prompt then it brings out the data that we can already start building tomorrow if we want to if we want to put the resources in there you don't have to do your your pie charts or whatever it will do it if you know how to ask it so that's another part of HR we have to teach ourself to really Trump correctly and utilize the the unstructured data there if we want to make that work um so of course the big uh enabler is is technology data collection storage cap capacity uh capability and the computer power we all know this this didn't exist 20 years ago 30 years ago but it has grown with the human EV evolution of of working with this and and uh you know this has all made it available for us so the availability for us uh to really utilize it in different parts of business before it was big platforms big Erp platforms you had to take to use but now it's small players coming in it's a tremendous amount of small players who are able to utilize today's technology and offer that to you you don't have to make big Investments you can make it small and and do it much faster and here again then people make that happen that's a change we have to adopt to how we work with this and what we do and and and this really like the people Factor as I mentioned already so back there with the data uh unstructured data about the quality so in the future you know we need to be more the content scientist we need to understand what is in there uh and and and when those technology comes available for us we need to know what we are plugging into those we need to know what the AI will use there so you can take AI using almost all of the platforms that you have today probably it's slowly trickling in uh and yeah it was available the big news some years ago but you know business is starting to see it and feel it now so when you take something you have to know how what it's plugging into can you trust the data that it will be using is it gen ni whatever it's doing the AI for you the technology where is digging in there's no value if it's not right um for HR it really internally means that we need to obsc uh capabilities to be able to be content scientist we have to change the way we are working with it we cannot continue as is that's not an option we have to upskill because the technology we manage more ourself we are using it we are updating it we are developing it quite a bit ourself because again availability it's there for us to take more control of it and this is not just for HR of course this everywhere in the business where applications and systems they can into use uh then the question is do we still need it of course we need it's it's it's a easy answer we will always need each other we just need to change how collaborate how we work together where we who's doing what the different ownerships of different things what do we do what do they do I have no idea how to write a code how to build good Integrations there's I mean I need people with better knowledge there 100% um so the we just have to be brave open up the discussion between each other and make sure both sides understand that the requires requires change or we will not make it then basically uh just a uh a statement here from or quote from U I don't know do you know have you ever read Beka a lot of good quotes you can Google uh comes up but I like this one I I I saw it in another event and I you know copy with pride uh and and uh I can be honest with that you know no harm with that if somebody does something good take it uh and and basically the turbulence and of course don't uh you know do what you did yesterday try to do it better always and if it didn't work yesterday why continue and also this doesn't just require uh we're not just talking about the turbulence inside of the company there's a lot of turbulence outside of the company as we know and that means companies like aumu where we are very cost driven companies we have to do good business cases when we do Investments what will it bring for us today tomorrow and the day after what does it mean how do we work with it it has to be a logic and have to be something that delivers value for the business and and takes us forward and that we can actually manage the turbulence that is ahead of us not what happened yesterday in the turbulence but also what is up there we don't know what's happening it's it's it's we have seen that the past years it's it's crazy uh how it goes quickly um then little bit about the people factor in the development and and basically uh I I mentioned that you know we are the key we are the key to make it happen at the moment at the moment it cannot data or AI cannot do it alone that's it we have to be part of it uh no magic will happen if we don't act on it we also have to have a change mindset that Embraces it we have to take to our ownership we have to take it into each departments not just HR but sales marketing development everyone has to take the technology into their heart marketing as well we heard in the morning it's it's key essential to really accept the change that is coming it's here uh I don't know if the data Lex is the last terminology about dat is it data meeses or whatever we call it but generate data connect the data uh analyze it for decision making aimation not just for today but also for the future um and and and and really important is is to lead with facts uh don't assume uh that you w't make it if we assume that this is happening we have to take facts into account where we do the project Pro what it will deliver and and what is the outcome and that comes also with the business case um then briefly just mind the gap it's a gap we are working currently uh HR has to change they haven't started the journey it needs to start today or we will be left behind in a we have started the journey we are of course Very in the beginning of some of the parts that I just talked about but we definitely could effort into technology and development and people and how we will be as HR in the future that's ongoing discussion at the moment full on and it's a very positive atmosphere around that and we see a lot of potential but also the Gap who we have working for us right there's a generation difference very big generation difference inside of HR outside of HR we have to understand that we are different people and people will with technology very differently so we have to take that into account when we do it and then also uh well I mentioned already that business needs to understand uh how to leverage HR data and there's a huge gap between people how they see that there's huge somebody sees that completely unnecessary and a manager told me or a director many years ago said to me HR will never never have that important role that person is not anymore working in a director role I can tell you 100% and haven't worked for some years the data is there to utilize it use it and learn and take the change management aspect very seriously to learn people to use it uh it comes slowly it won't happen very fast even if you prove it to be right they will not believe you it's funny but that's human nature people stand their ground managers are funny we we tend to believe in our own own stuff quite a bit uh uh to let go is not easy and just in the end I just want to raise some of the areas uh this is you know there are many more areas where you can utilize HR data these are some of the are that we have been looking in and we have found strong business cases in each area are we all doing at the same time no you have to prioritize you cannot do everything at the same time but there are endless of cases where HR data can be utilized and and and be a very effective uh part of the making things better then just a few tips uh in the end how I just for for people to see how I see it is is we have to inhr first of all of course believe it ourself if we don't believe in what we are offering then the business will not uh and and we really need to embrace that data and technology and bring the benefit to the business to the end users show them what it can but also don't invent that they things that they don't need do test do pilots do pox whatever it needs to show the benefit if it doesn't work don't be afraid to change direction or stop it that's the only way it's Tri trial and errors as you go forward with the projects um and and maybe the last bit um uh is is really I want to I said it already but demonstrate the value for business the numbers will not lie that's where you find the effects that's where you get the Buy in and then you can go forward uh and then have discipline in h we always been a little bit gray gray area in some of the processes but we also need to start having more discipline how we do it we cannot just fumble around with the data or the processes we have to have discipline then also the buying from the other stakeholders will be easier to get our factoring Toro so it's a big site to utilize data everywhere in a good manner uh is is is Big topic even though we are just under 9,000 people so 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 safy learnings timing in clock in clock out plant maintenance every minute counts in that millions of Euros goes if we clock 10 minutes incorrectly for plant maintenance it's up in smoke so technology will play a big part but yeah I'll stop here because I could go on forever so I'll stop right here thank you [Music] o [Music]