We're Definitely Not Talking About Data

Brendan Ellis: Welcome back. Well if this is your first time, hello! My name is Brendan, and this is definitely not a data podcast. Today, as ever, I'm going to be joined by my co host Leno, who is a chief data officer with 25 years experience. Over the season, we're going to talk about the tech hype, the failed rollouts, and the conversations nobody wants to have on stage. In this episode, we're going to get into why data keeps throwing up the same problems and what AI is actually doing to the way that we think. We're also going to touch on why the people question still matters more.

Bren: Marvelous, hello and welcome. This is the first of, you know, it's gonna be a worldwide series and ⁓ I'm hoping that we're gonna get mobbed for autographs in the not too distant future, but my name is Brendan. I've got a very good friend of mine, with me and this is not a data podcast. You'll probably see what we've done there, but Leno, great to see you. How you doing?

Brendan Ellis: If you liked what you heard please do share, like and subscribe. It means a lot to us and if you have time please do leave a five-star review. It will help other people find the show. But we will be back soon and as always this is definitely not a data podcast.

Lenno: Yeah, I'm doing well. I'm doing well. I'm s super excited about getting this going. ⁓ as you as as you rightfully indicated, this is the the first and foremost ⁓ well the first moment that we're actually trying to do this. ⁓ so not sure what what I'm stepping into.

Brendan Ellis: than any technology. So let's get into it.

Bren: Yeah. Thanks. I think that there's a little bit of background just for everybody listening that, let, let, let, I've been to a number of conferences and I basically pitched and I said, can we do a podcast called the world according to Leno? And anyway, it was a good line, but, ⁓ we, mean, thankfully you said, yes, let's have a chat, but you vetoed the name, which is, which is disappointing, but understandable.

Lenno: Yeah. Yeah. No, so I think I think ⁓ putting this as ⁓ the world according to Leno would be ⁓ embarrassing ⁓ to say the least. and ⁓ but going into several ⁓ several topics that ⁓ we've covered ⁓ over the course of the conferences, I do see as ⁓ very, very valuable. ⁓ speaking with you ha always has been ⁓ well a please.

Bren: If

Lenno: And ⁓ easy going, so let's see where we are getting into. Yeah.

Bren: this is it. And I think, you we've talked about it, but one of the real strengths and certainly from the conversations we've had is, in the world of the... So we both come from a data background and I've worked in the data space and it'd be nice to tell people a little bit around what we do in a moment. But actually, with the world going crazy over AI and everything moving so quickly, the number of conversations we've had is actually... There's a people element.

Lenno: Clear.

Bren: to this. There's so many other facets to actually what Invertecom is doing AI means and how it all fits together. And that's what we want to dive into. I'm conscious we've just literally jumped into it. But you've got a bit of a data background, haven't you, Leno? Is that right? Or have got that wrong?

Lenno: J just a little bit. No, no, I think ⁓ indeed it's it's a little bit ⁓ of data background. I actually come from a ⁓ mechanical engineering and business administrations background. And ⁓ I've seen ⁓ manufacturing companies, ⁓ I've been working in finance, I've been working in sales, I've been working in ⁓ operations. But everything that I've done ⁓ and every conversation that ⁓ I'm having with functional leaders ⁓ across ⁓ across many of the companies that I've worked with. somehow have its connection with data. How data is being used, how data is being generated, how we have differences of ⁓ perception on definitions, quality and so on so forth, ⁓ or where the data even is coming from.

Bren: Mm. Mm.

Lenno: And ⁓ somehow and probably somewhere in a previous life I've lost a bet and therefore now I am indeed for the last twenty-five years. ⁓ unfortunately that tells also something about my age, ⁓ have been working in in data. And so data for me has been my forte throughout my career.

Bren: 21, 21, no, no, that's all the users need to hear. ⁓

Lenno: My career I've been ⁓ operationally ⁓ executing, ⁓ I've been populating data, I've been ⁓ manipulating spreadsheets, ⁓ doing all kind of data loads, transformations, ⁓ and so on and so forth. And now my official job title is the of a chief data officer. Now that's a nice little title, which basically means everything related to data, people come to you with the expectation you need to fix it.

Bren: Yes. You Is it fair to say, is it a you touched it last, you deal with it scenario?

Lenno: Yeah. Yeah, yeah, this is this is this is the the ⁓ the typical scenario. ⁓ like everything with a wall plug, that's IT. Yeah. Regardless whether or not that's true, yeah, if your air fryer is d is is is broken, you're not going to the company IT department, right?

Bren: Hmm.

Lenno: So if you want to have a ⁓ a record of your customer or your customer ⁓ sales ⁓ invoice or whatever, you know it's it's not necessarily a problem that anyone that is responsible for data is going to fix it for you. yeah, so data indeed ⁓ has been ⁓ a bit of my ⁓ forte for the last ⁓ couple of years.

Bren: Yeah. Yeah. Brilliant, brilliant. And actually, I'll give a bit of an intro in a second. you made a comment that I think we've touched on a lot of times is the influence of everybody coming to you because they've got a data problem, when in actual fact, if you have been really harsh, you'd say a lot of the time, it's not your responsibility, is it? Is that still the case? Because we were talking about this probably 10 years ago. Is it still true?

Lenno: Yeah. No, it's still. And it's it's c what what I find very funny that ⁓ you're mentioning that, because that indeed was the case ten years ago. I'd like to rewind the clock even further. So my father who I value very much, ⁓ he's been in consultancy basically all of all of his ⁓ working years. So when

Bren: Yeah. Yep.

Lenno: In the start of my career, I was telling him about the transformations that we were doing, the complexity there, getting people corralled on ⁓ delivering and preparing on the data, getting that ⁓ into ⁓ the new ERP systems, because ⁓ the relevancy of ⁓ standardizing that across the company was massively high and we were hitting certain stumbling blocks. He then on a number of occasions he was telling me that yeah, but let out. We did that 40 years ago already. And this to me, we keep on spinning on the same the same cycles. It ultimately comes down to, and and this is why I think you and I are connecting quite well, it comes down to the human element of it. It's not about the technology, it's not about the steps that we need to go through in the process. It is about our people learning ability. of indeed genuinely looking back what worked, what didn't work, how should we actually ⁓ adjust and then adjust that in our behavior.

Bren: Yeah. Absolutely.

Lenno: And that I believe is at least limited happening.

Bren: Hmm. I think you're, I mean, you're a, your father was a very wise man. And, ⁓ it's funny when you say sort of 40 years ago, we're still, still doing it because, and this is the bit that I've, I've found a bit baffling because I trained as an accountant sort of with EY long time ago. I've kind of ventured into this data space and sort of the latter part of my career so far. And having spent a lot of the time on the end users.

Lenno: Mm-hmm.

Bren: understanding what people want and how they want to use it is key. But more and more, and you're absolutely right, we connected on this, that the people aspect is what matters because... You know, and people still buy into people, know, technology is great. But if you don't understand what somebody's trying to achieve, it's really difficult to find a solution or bring the data together or whatever it might be. And I think we've forgotten that. And at times we've ignored the people side and just focused on building a lake house or creating a new dashboard or having a process. Whereas actually the reality is if you sit down with somebody and I'm sure you see it in your everyday life is sitting down and understanding what somebody wants is so much more powerful than just saying here's a dashboard that you're not going to use again but it looks pretty. Is that fair?

Lenno: I I think I think that's that's spot on. ⁓ because we are also ⁓ I believe a highly competitive delivery ⁓ focused ⁓ time. and because of that we are aiming to get a product out there with the conviction that it's great. It's a great product. You know, everybody is going to love it.

Bren: Yeah. Yeah.

Lenno: And then to your point indeed, here's a dashboard, nobody's using it. Hey, but come on, I've done a great, great thing. So how is Yeah, yeah, 100%. And then and the stit the statistics behind it in an organization, and the organization that I'm working for now is not not uncommon in that in that direction as well. Is we're going to look at the ⁓ the frequency of usage.

Bren: It looks brilliant, doesn't it? Why aren't you using it? Hmm. Okay.

Lenno: And that will give us an indication of how good the report is. You know, it's it says nothing. Now, if I if I were to to extrapolate that a little bit, understanding what people want, but to that I'd like to add also understanding the context of where an individual actually at that moment in time is.

Bren: Yes.

Lenno: I'd like to draw an example on and I'm I I'm using my kitchen table a lot. This is where we we try ⁓ this is this is where me and the family is ⁓ is is is then sitting having conversations and I've I now have ⁓ three ⁓ more or less grown-up ⁓ children who grew up growing up in a digital age.

Bren: It makes two of us. You can't see it, but I'm on my table as well. So this is a safe space, Leno. This is a safe space.

Lenno: Whereas I've grown up in ⁓ the age where the databases were just started. ⁓ I've I've worked with the early phases of ⁓ MSDOS. And I needed to ⁓ to to key in the every command into the black the black screen with the ⁓ the pinging ⁓ double dots. You know

Bren: You

Lenno: My children are working and learning on the basis of a 100% user interface. That's their frame of reference. Why am I trying to make this point is that my children are nowhere understanding where their data, their documents that they're creating for school, the documents that they will be sharing out with others, effectively are stored.

Bren: right. Yeah. Okay.

Lenno: And so whenever I am asking them where is your spreadsheet or your document, your presentation, your whatever, I'm getting frequently the response it is in my recent files. I'm always opening through my recent files. And that annoys the hell out of me. Because because to me and

Bren: Okay.

Lenno: And and I realize that that's a personal problem for me. Yeah. I know so the so so therefore I I I recognize the safe space here. We're we're both at a at the digital table. Exactly. There's no one listening into this ⁓ podcast anyway. So ⁓ I would like to know where it is stored so that I I can reproduce it, I can ⁓ share this out, and ⁓ there's there's some logic behind it.

Bren: I would feel the same by the way, but I'm not sure I could deal with that. Nobody's listening, it's fine.

Lenno: Now because they are growing up with zero notion of how anything is working in the background, they're operating on a full user interface on all of the devices, have zero idea where it is going ⁓ going into. That's the workforce that now is transitioning into the workplace. Sorry, that is the ⁓ the age group that now is transitioning into the workplace. So I'm now getting demands in the workplace in terms of, hey, guess what? I need an app. I need an application now to ease my work. Whether that is realistic or not, there is zero notion about the foundations that you need to bring in place.

Bren: Yeah.

Lenno: in order for the user interface to be functional. Now put that put that into the context of now having quote unquote artificial intelligence. Personally I'd like to ⁓ to call it ⁓ hyper automation because I'm I'm I'm having a little bit of ambiguity with the intelligence part. But hyper automation that is speeding it up

Bren: Are you fair?

Lenno: So everything needs to be available at a click of a mouse by clipping clipping your fingers, you know, it's it's it's a speed, highly volatile and dynamic ⁓ dynamic world now. But there is zero anticipation or notion about where the data actually is coming from.

Bren: Yeah. So it's so interesting you said that because... A little bit background. So I'm doing a master's in leadership and it's around Gen Z and the workplace post pandemic. And that shift into digital natives, as you say, your children didn't know what life was like pre-internet. I I found out the other day I'm a geriatric millennial, apparently. I'm one of the very oldest millennials, which I'm not quite sure how that makes me feel. But November 1980, it makes me feel special.

Lenno: Yeah. Mm-hmm. Mm-hmm.

Bren: But because we grew up and experienced what life was like pre-internet, I remember having to do a school project or university project where you'd actually have to go to the library and look at the encyclopedia and find what you were looking for. So you fast forward to now and I think it's really easy just to complain and moan that back in our day it was different and so forth. think that's a slippery slope. But the bit that I do worry about, and I think it of dovetails into what you're saying, is I think AI is making us more stupid. And the reason for saying that, it's provocative on purpose, but we're able to get to the answers quicker, but we don't necessarily know why the answers are the answers. And so the knock-on effect is, I think we're losing the ability to be curious. And that's the point, I think, that you're referring to with your children in the workforce is, why is it that way? Why is an isosceles triangle an isosceles triangle? You don't just need to know it's three equal angles or whatever it would be. Is that fair or am I just picking on the generation?

Lenno: Think no, I think I think there's the part of it I I tend to agree with. ⁓ I I have a question mark with the statement it is making us stupid. ⁓ or or more stupid. which I also realize is a provocative statement. Yeah, so so let let's put that very very clearly in the frame as well. That's a disclaimer by the way. no precisely, precisely.

Bren: Mm. Yeah, yeah, ⁓ This is about financial advice and everything else.

Lenno: I think if if if we look back to the ⁓ the the the so-called industrial revolution, ⁓ I think even then there was a ⁓ a bit of fear of like we're all going to be lazy, we will all be out of a job, etcetera, etc. I think s likewise with ⁓ with AI, we might become even more curious. Because what what what can be behind it? You know? However, I think for all of us there is a necessity to ⁓ I think there is a necessity for all of us to be very, very curious and diligent in how did I arrive to this answer?

Bren: Interesting. Okay. Yeah. Mm.

Lenno: or proposition regardless where it came from, regardless whether this was a generated answer, I still need to be curious enough or diligent enough to to do a bit of fact-checking, which is a bit of a stretched term nowadays, ⁓ anyways.

Bren: Yep.

Lenno: And and and I think that that this is where our the generation that now is growing up will have one of the biggest challenges ⁓ any generation has ever seen. Because all of the information is information between quotes is available at your fingertips. They grew up with Snapchat, Instagram, Facebook, and no Facebook is ⁓ for dinosaurs, but ⁓ TikTok.

Bren: Yes. Thanks.

Lenno: There's so much k info available. Whether it's true, fact or not, it's still information. So the amount of rubbish that sometimes at my kitchen table is expressed as fact is also extremely high. And that I think is one of the ⁓ the elements that we, our older generation, now need to take into account.

Bren: Mm. and

Lenno: while grooming and educating the new workforce that is coming in.

Bren: Yeah. Do ⁓ you think with the... because you're absolutely right. The information that's at your fingertips is now... I mean, it's almost endless, isn't it? And with information being created...

Lenno: Yeah.

Bren: I don't know what the stats are, they're probably mind-boggling. Do you think then that the real skill has been able to, actually just very quickly, there's a very good friend of mine, whenever he tells his son one of the details, the son turns around and be like, have you fact-checked that?

Lenno: Yeah.

Bren: It's like, you know, we might need to, we might need to do that. But you think kind of, is it an hour generational thing or is it actually just a skill that we need to be able to discern kind of narrow down all this noise and all this information to actually what is important or real? If that's even.

Lenno: Yeah. I think I think that that that that is indeed where where it boils down to. And and the reason why I'm I've just mentioned that I believe that that is the biggest challenge that any generation ever had, is that and especially in the space of the hyper automation, the speed is making a humongous difference. And I think

Bren: Mm. Right. OK.

Lenno: You've said it very, very well, ⁓ Brendan, is that we used to go to the library, read the books, you know, that's slow pace. We've in net taken the information in, we've then modeled it out, and then constructed it into the assignment that we needed to provide. Now, nowadays, all of these steps are going to happen in such a high pace that how you got from the library

Bren: Mm.

Lenno: Towards the end result is unknown. So it can very well be fact. The automation may very well have performed all of the steps. So I think it it may come down to, or how we can bridge it, is a bit of ⁓ what is it, ⁓ IT auditing. So trust the process to trust the outcome.

Bren: Okay. Yes.

Lenno: And then it it's in my mind I think it comes down to the combination between two factors, that is the process and that is the data ⁓ that is being used or consumed through that process. And if these two you can more or less ⁓ connect and and recognize, then I would personally have a bit more confidence in the output that ⁓ we are generating. Makes sense?

Bren: Yeah, no, it does. does. kind of challenging our own questions. And we kind of touched on it a little bit at beginning. Are we still battling the same challenges that we had 10 years ago, but just with new technology? did we have the same with big data and then with data warehouses and then with, I mean, I'm getting way over my skis now, whatever else before. Why haven't we learned? Why haven't we improved it? Or have we, and we're just not applying it?

Lenno: I think so. Yeah. ⁓ I think part part of it is we we're just not good in applying it consistently because you can say that it is ⁓ way more convenient to hold a s ⁓ a spade by the handle, but I may have a ⁓ a different view to it. And especially over here in Europe, we tend to have different views to any subject, anything. So

Bren: Okay. Yep. Okay.

Lenno: Whenever someone is coming in with a a splendid idea someone next door will say, Yeah, good idea, but I have something better. Yeah. So we will always be challenging each other, and therefore I think our self-learning and appliance ability is relatively low. And maybe I'm I'm too negative, but

Bren: Okay. Okay. Mm-hmm.

Lenno: I may also have an element of truth in it. But hey, guess what? The next the next person will s will debate it and say, Well, I have a different ⁓ opinion or an idea about it. So that's that's also okay.

Bren: Yeah. Yeah. I mean, without this is not necessarily a therapy session. We don't need to uncover some of those wounds. That's a different podcast. That's this is not a therapy podcast. do you do kind of it to kind of taking that. then when we deal with, you know, chief execs and CFOs and some of the board when we're talking about data and exactly those those points, are we?

Lenno: No. Okay, good. So childhood traumas and so we we will not go into no. Yeah.

Bren: Are we missing a trick in how best to explain it? Or is there a misconception that actually it's going to automatically just solve all our problems still? Because, and just hear me out for a second, for me AI is still a technology that needs to be implemented in the right way and find a use case and apply it and all that sort of stuff. Are we just starting at the end and then expecting it to work?

Lenno: ⁓ 100% yes. Yeah, yeah. I I think there's a misconception of how easy we can ⁓ make things happen. And all of the con ⁓ and and for me also that that is cross companies that ⁓ I've I've been working in. we basically are requested to deliver the moon with zero funding and in ⁓ record time.

Bren: Okay. Okay. Yep. Easy, right?

Lenno: Yeah, how difficult ⁓ how difficult can it be? Yeah. And so I do recognize and ⁓ there there's two elements to the equation. And you've mentioned are we ⁓ having difficulty in explaining the story or are we having a misinterpretation of the difficulty of it? I think it's both. And

Bren: Mm. Okay.

Lenno: Which is a bit of a political ⁓ political answer, ⁓ of course. Yeah, exactly. ⁓ it we all need to get a bit of an idea of what data actually is, how technology works. ⁓ I think we all need to broaden our horizons. What

Bren: Well you're get splinters if you sit on the fence any longer then.

Lenno: Well perhaps ⁓ our parents' ⁓ generation have done in companies is segmentation. ⁓ every instead of generalists, you would have specialists in every single field. Now having all of these specialists you also need to have a whole lot of handshakes between the different specialties. And perhaps along that ⁓ specialism creation

Bren: Mm.

Lenno: We've then also said, well, okay, there's ⁓ a couple of these back office functions like IT, like ⁓ finance admin, like HR function, like well, you know what? Data. Data is also one of these subjects that we need to have a a ⁓ back a back office function who is doing doing data. You know? So fine. So instead of having the appreciation that While I'm a salesperson, I also need to make sure that my customer information is correct, that the sales order needs to represent the right quantity, the right price, etc. That is being considered to be data. So someone else is going to take care of it. It's not my responsibility as a sales person, I just need to sell.

Bren: Right. Yep.

Lenno: Similarly happening on the procurement side, my vendor information, my payment terms, the payments that is happening within the frame that we've agreed upon. That's not my problem, that's a legal problem, that's a finance admin problem. That's a you know. I am 100% convinced that in every function where you're generating data, where you're using data, you are also owning that, and you need to live up to that.

Bren: Yeah. It's. No, no, no, no. I mean, I get excited and I jump in. I felt this most recently at the previous place because it was the people that input the data didn't feel the pain. So you're being flippant. If they put a name and a date column in the CRM, the data engineers could not code around that and should not code.

Lenno: So when you want sorry, go ahead. Mm.

Bren: but also the amount of effort that was needed to kind of fix it. As you say, sales data going into a CRM and to a sales platform, they put it in, they own the data. And if that's not the case, then it means if you're telling me that I own it, that means I can put anything I like in there. And they're like, whoa, whoa, whoa, whoa.

Lenno: Yeah. Precisely. Yeah.

Bren: Right?

Lenno: Yeah, exactly. And and being being an well ⁓ an an an executive in the data space, I've indeed ⁓ been on that particular point frequently. Where indeed at some point I said, Okay, you know what, then if you are not feeling any accountability or responsibility for this, that means that I can now make a decision on the structure I can make a decision on the content and I can make a decision upon the quality parameters. And then indeed to your point it's ⁓ no no no no no no no No because that's where I want to influence it. Come on, you cannot have it both ways, no?

Bren: You Yeah, yeah.

Lenno: ⁓ and and ⁓ trying to connect this back to indeed AI. AI in my mind is is kicking up the pace, it's the speed of all of the handling that is happening much more ⁓ much more quickly and therefore very difficult to reproduce.

Bren: Mm. Hmm.

Lenno: Now if that ownership is not there, the structures are not there, the quality is not there, or ⁓ or or there's questions around that, I'm putting a question around the validity of the outcome of what any hyper automation or AI is going to deliver to you.

Bren: And that I think is, I mean, it's a great way to kind of bring it together because a flippant phrase I've often used is using AI is not an excuse to bypass process. So just, if you get whatever your particular flavor of AI is, Claude, Gemini, Chachi Pati, whatever it might be, is it going to spit out an output? Doesn't mean it still shouldn't go through a review and it shouldn't be fact checked and they're very compelling. But as you say, the... For me, the real question is, what are we trying to address? What does that look like? What are the steps that we need to do that? And then ultimately, how does technology ⁓ kind of support that? Because your comment right at the beginning in terms of being sort of hyper automation is so true because it's, and I tried to explain it to my parents not so long ago, sort of this whole chat GPT thing. I was like, ⁓ gosh, here we go. It's basically just a, it's just magic, mum. That's all you need to know.

Lenno: Yeah.

Bren: ⁓ But if you, if we, the kind of way I broke it down was just saying it's taken all the information across the world and it's worked out that when you say ⁓ fire 99 times out of 100 or whatever the context is, the next word is going to be works. So it goes, you know, based on what you're doing, I think that you want the word works because you're going to talk about fireworks and so on. We need to remember that actually it's still a technology that's got to be harnessed used.

Lenno: Yeah.

Bren: But the interesting part is, and I'm going to leave with little bit of a, what I think one of the most incredible moments was with, you know, what Sam Altman did with OpenAI and, you know, the technology is cool, but the way they designed it, like the Google search, that was a genius move because everybody could use it. And I think it kind of comes back to your point around the hyper automation. How do we... just not do really bad processes quicker using cool new technology.

Lenno: One hundred percent. Yeah. Yeah. Yeah. No, but it's that's it. Yeah. And and that is exactly where ⁓ I would argue that we need us humans to be very, very curious and still being extremely smart in coming down to that assessment, that point, that indeed it is okay.

Bren: It sounds silly doesn't it when you say it out loud and you're like we wouldn't but we do Yeah, yeah. Well, I tell you what, I mean, that half an hour for the first episode of this is definitely not a data podcast. It's absolutely flown by. I can't not say it without smiling. But what I'd like to say is I think the AI topic is one that we want to dive into more and the people side of things and all the stuff that we see, all the stuff that gets.

Lenno: Yeah.

Bren: I guess talked out behind closed doors but not really talked out in public is really what we want to do. hopefully, I know I haven't sort of put you off doing this again next time. Are you you back and sit at the kitchen table and talk a bit more?

Lenno: No. I'm super happy. ⁓ actually very excited ⁓ about ⁓ continuation. Like you mentioned, ⁓ half an hour flew by already. ⁓ yeah and I hope that ⁓ people ⁓ will actually listen and maybe engage on ⁓ on on on the subject.

Bren: Yeah. I hope so. I hope so. Well, I'm desperately hoping and looking forward to the first time you get stopped for an autograph because that's definitely going to be my...

Lenno: Yeah.

Bren: ⁓ There's a story for another day that I got stopped in Tesco asking if I was Brendan from LinkedIn not so long ago. ⁓ listen, it can be done. I'm not in Hollywood yet, so it didn't really take off. But Leno, this has been an absolute pleasure. Thank you for letting me convince you to do this. And to everybody listening, we will see you next time. Thank you very much.

Lenno: We will