Hi and welcome to data futurology the podcast for that Enthusiast data scientist and upcoming data science leaders to learn the skills required to take your career to the next level. We do this by hearing the stories Lessons Learned and mistakes done by today's top industry leaders out there in the field. My name is Felipe Flores. I am your host. Thank you so much for coming back tuning in. Again. Thank you for so much for sharing the podcast telling your friends about it. And for the feedback that you've been sending across we really really appreciate you both sharing and letting us know how you're enjoying the podcast. So today's episode is a different type of episode a special episode on the eve of the podcasts one-year anniversary or birthday. I sat down with Antonio goni who you would have met if you listen to episode 21 of this podcast, he is the director of global matching and analytics at seek. He is the chairperson at The Institute of analytics Professionals of Australia. He is an advisor at Pascal. He's also a board member at the center for business analytics at the University of Melbourne. He's also on the board of the Australian Alliance for data leadership a fascinating man wealth of experience. We heard his story in episode 21 and in today's episode. We actually turned the tables so he is Antony is Doing me in this episode so obviously a little bit different but this is my story and I hope you enjoy it. Let me know what you think. Welcome to the other futurology everybody. You're probably hearing a different voice than will be used to actually because the usual host can't Mike for hosting duties and also the kind of weed if you actually hosted and ask them questions that I you can see is the subject of the podcast. My name is Anthony you got any I would in the data science field here in Australia. The honor of being one of the interviewees on this podcast enough pools really important that we took the opportunity to usually both has as Rich history and experiences anybody who is interview. So with that welcome Philippe did that if you drop it. Thanks Anthony White appreciated the lazy. It's been a long time coming. I'm glad you accepted the invitation to be interviewed. Let us start at the beginning. We'll stop the personal stuff married with one child, right? Right. That's right. Yeah, that's a nice Notch to your career. Probably the most rewarding career. You'll have tell us your cultural background or listeners will have heard this exotic accent for a year now. Yeah, where are you from? I'm originally from Chile South America and grew up in the north of Chile, which is the desert. It's the driest desert in the world and it would rain about once every seven years we get about set a one centimeter of rain. Yeah, we grew up in a small town up in the mountains which had about 10,000 people. It's a That's a big change to Cosmopolitan Melman. I know right? So, how old were you when did you when did you come to the Land of Oz how is 19 but I came over and two years ago. That's right. Yeah, I wish and I came originally as a Backpacker just to see the country obviously loved it this whole to stay. Yeah, and then studied in continued on from there, but totally loved it and in last time you're not caught up. You gave me a great story about how you support of yourself first jobs. Just how vicious and what sort of work. Do you want to share that stone? Yeah, so when I first got to Australia, I didn't speak any English and the extent of my vocabulary was the jacket is black jacket is like, I don't know why I knew that but if they were green pants I was stuffed so when I got here I thought I can try and put some money together to pay for an English course or I can try and find a job where I'm forced to speak speak English to people and get get the chance to learn that way. So I did the ladder and I became a door to door salesman selling Optus home phone and internet where I would have to knock on about $120 per day six days a week and trying to convince people to change their phone and internet provider to this company commission only. So there was a lot of days of zero payments, but the interesting thing was that we got to travel a bit with the with the job. So I was based in Queens and the time and yeah, we did obviously Brisbane and Gold Coast and when up to even to North Queensland, so we went to Cannes and Port Douglas and everywhere in between like Bundaberg and yeah types of places we get to see as part of that that doing fantastic story. So you went from the jacket is blessed with the best podcast that I think The signs coming out of Australia and I am in the world. I think it's a brightest throw away another curveball at you just to lighten it up before we get into the data Sciences stuff. It's your favorite order at your favorite restaurant. I definitely go for anything with chicken is high up there for me if there's a chicken risotto then yeah. Otherwise, it'd be like a steak sandwich and I have given this question and we should have you adopted any of the indigenous. Full time. So I you still what we call a soccer supporter. Yes law still a sucker supporter. Yes. I have been to a fell gains and I do enjoy enjoy the fast pace of it. It's yeah, really nice, but with soccer there's that unspoken tension and you see that I never give the game shifts so much even when there is no score that yeah, it is beautiful. All right. Well, let's launch into so more fully by far as the details. Let's get into it. Patient is there's no hasn't been a clear pathway to Leaders with them a ton of experience behind them without the Science World. It's been an emerging field while you and I are gonna embarking on this. So hit us up with your education for us. What did you study? Yeah, so I did computer systems engineering and business as a dual degree up in Queensland. So I studied I started my studies in Chile and transfer them when I decided to stay and chose the Dual degree as I thought I could mix between the technical and trying to get some business in there. Yeah. Yeah, and then as part of it was interesting because while I was doing my degree, we had to pick a specialization on the computer system engineering piece and the specializations to pick from was Hardware software hardware and software interface web or data was one of them and I was doing a lot of I guess it would be freelancing work. So for small companies, that would be their it person and do sort of one or two days a week while I was studying and and That work since I began which is after the door-to-door sales, but it was always a building databases doing analysis building reports and helping make better decisions with Microsoft Access for example, right at the small business end, but then when I was at University think about specializations, I remember speaking to my friends and everyone was saying data that's dead as if you're going to study that so I ended up specializing in Hardware. Oh, wow, even though all of my work was in danger. Data, and then it wasn't until I went to do the my thesis that I was in a mining Richard Center and I happened to stumble into a project where we were building a essentially brain monitor or something to detect tiredness and truck drivers in the mines and that was based of brainwave activity. So as part of this research project there was an electrical engineer the project manager and myself and we built this baseball cap that had the Electrodes at the front to measure brain wave Activity 1 by the ear to be the ground zero comparison and the electrical engineer did all the research design and implementation to build these sensors and then he will amplify the signal and pass it over to an on-board computer which was my bit. So I did the embedded system the digital design for the computer and it had to be the part had to be sort of small enough and put far away enough that we had a flexible pcv13. Like a flexible motherboard essentially so it could be put into the cap. And then in that is was the first application of machine learning that I ever did which was going from the brainwave activity to a number between 1 to 5. Where number one is you're just waking up on your feeling fresh number five is a slit your asleep and when you go from number three to number four, you're no longer able to drive and the truck had to stop so as part of that project. We got thousands of Hours of brain wave activity. So EG thousands of hours of EEG and video footage from about eight Sleep Experts around the world and they had labeled this data and we had to find a way to go from that label data to a number from 1 to 5. Yeah, and I remember on my computer. It was a thousands of lines of code. That was a very archaic neural network as in like one hidden layer and obviously things that now you do it Of lines of code and yeah, yeah and then on the on-board computer and that being a linear regression ha ha ha, but that was about as much power as we could get on the on-board computer than one in the Hat little are so that data I'm getting into analytics kind of geek mode here. So, you know, I love it capturing a whole bunch of Delta. Three four. Yes. Yes. He write it down and gold sets. It doesn't change doesn't. Yeah, interesting really interesting. But then after that when I started working after a university it was all in data, but it was more around data warehousing data migrations visualizations reporting. That is the space where I cut my teeth over the next few years before sort of coming back into it don't seem really crude password people start out. You'll be neural network going to be. All right. It's a lie around so, you know to that point earlier on to date don't see a lot of common parts of the data. It's a fantastic thing. I think is people getting to a halt. Our generation is a like an old fart music illegally younger than them seem to be surrounded by a whole bunch of leaders who got here out of a passion. Yes. So it's a nice coat with the be apart of is really nice. That's so we'll put yeah, it does your education there. So most people I speak to and you've never spoken to a number quite level critical. There's always one or two influential teachers in their life if you have any of those, yeah. Yeah, I definitely had what inflation teachers and when I was in high school. So for a long time, I always thought of myself as being very bad at maths and had a like a really negative self-image in the space. But whenever as a kid whenever somebody asked me, what do you want to be when you grow up we'd always say engineer and then obviously years later looking back. I was like why why would I say engineer? And it was literally like the may be wanting to be smart. By proxy so I was almost saying if I'm an engineer people will think I'm smart and there is like, okay, how do I get my myself in there? And then sort of was as a kid having that and I had a couple of teachers early on died. So in me that there was some I guess potential for a passion and a love of maths and physics. So yeah had I'm not teacher that I remember early on so would have been maybe year nine. He would yeah, maybe I love you. I adore you know any pulled me aside and you're saying you know, you should you should really try try on this because you're not and you can do it and essentially highlighted that it was about the effort that I was putting in that was leading to my results not the fact that I was sort of like school. Yeah and having an unrealistic image of you know, that almost like if you're talented things happen easy, so he was somebody that said to break that for me. So say it's about the effort and then things get easier. So then put me down the path of starting to love maths and physics and they're going to like the methylene periods and physics Olympiad AIDS and things and yeah, which is nice and I remember like to remember in on holiday period it was either in year nine or year 10 on I remember sitting with like a I think you're nine a math textbook and then you attend physics textbook and just going through it on the holidays like end-to-end like all right, I'm gonna work my way through this and I felt like I was covering the foundations of the things that I hadn't learned before that now we're hindering me from getting to the high levels of proper understanding of obviously high levels in terms of high school math compared to any foundation before and I really felt that I did something that I kind of still carry with me now that when I'm trying to understand something I always go back to the beginning and I want to go through everything and go see the whole way through to build that foundation and build all the links in the chain of the understanding and try to make sure that I'm not having any broken links that then Catch you out later on. That's an important message from Korea. Everybody seems to walk and go straight to accomplish with you on that and I don't actually understand that this experimental design that gives you the right data to actually answer the question of the business once your hands. I'm really good on that and I'm sure you are too. Yes under measles we actually getting yes and that there's so much that you can do with those fundamentals and business setting. There's so much value to be Created with those and usually the the turnaround on those is a lot quicker. So then you get the double benefit. You will do a little while now and you will note IT industry is being really good at it. It wasn't a lot of knowledge around the silly what was well-dressed. That's why back a little bit older a lot about somebody by back but as the discipline has emerged. What do you wish you would have learned what that getting started out with a few nights that great question. What do I wish I would have known? I think that lots of things actually I've been thinking mostly of either mistakes that I made or things that took me a while to learn so around that something that I'm very passionate about now is quick delivery of value and with a view that essentially done is better than perfect. And then that usually gives us time to have another bite of the cherry and improve on what was being done. But getting to that first sort of even if The quick and dirty solution, it builds confidence. It gets people feeling successful and then you are able to get some momentum and power through tougher challenges. That might be if you sort of structure the work so digitally the tougher challenges might be coming down the track you can start with easier ones that still add value and set to gain the momentum and yeah for but I definitely didn't start out that way and I think a lot of our educational system is around programming us with a pair. A dime that says you only get to do something once and you will be judged on how accurate and perfect that one time exam or one-time assignment is and for you to do that. If it's an assignment, you might get a very clear description of what you aiming to do. And then you take away that brief that requirements document almost take away that brief you go away. You work extremely hard with out any feedback and then you come out. This one time Judgment Day and I guess like many people are going throughout you think that that's how life is and how you should approach your work and that's the way to be successful in and obviously as we've seen the things last few years that the movies away from that and towards what they see in the working life not so much an education perspective is children at school we have responsibilities. The jacket the jacket is black. That's right. Bring the name of that we can make in the tagline. That a future of energy but that kid is black so though knocking so employment history since then so door knocking for quite a few months actually and had that travel and got to start making some money and things like that and then I did lots of odd jobs as I was sort of learning the it side and the business side to a level of Anakin's I could start working on that but I was a an audio-visual technician for a while. Yeah ticking. Actors in hiding meeting rooms and in universities and and things like that obviously like waiter and things like that. And then I remember at University after I had my first SQL and database subject. I really enjoyed it. I hadn't had stats yet as part of the degree and I thought I was going to start getting a job in a nightie and started trying to find small businesses that need it like just it person. And we'll found one first which was on business sales. So they would sell somebody's restaurant. Somebody's Kebab shop things like that. So I started working there to help out with the website and I was on the phones and then I noticed that they had this database who which everyone kept cursing at because it would crash three four times a day and I saw this sort of day in day out for a few weeks and then it was a small company less than 20 people and I remember one day I had a chat with the owner and I said, yeah. Know what I think I can build your better database don't be ridiculous. There's a software company down the road. We paid them $40,000 to a team of five to build this this piece of shit. And you're a kid. You're okay. You're going to build us something and I was like I was like, well, how are you do it ago? I said, I'll I work a couple of like a few more hours over the next eight weeks. We'll see where we get to if you like it we can continue I said, I can continue building it if you don't then not really too much skin off your back sure, whatever golf. So I went to a library and I got this book that it was I think like Microsoft Access in 30 days one hour a day or something like that. And I remember sitting at my desk with the book on my lap and I would be reading the book and flick it to the page and doing what I do. Yeah, a building this database building the reports building the phones for people to enter the information doing the analysis and essentially tapping people on the shoulder to say hey when you go to sell a business or When somebody comes in wanting to sell the business, what information do you ask them for now? Like I usually do so great you start common is that o for all Industries and sort of got to know the business that way and up building the database? It was just a Microsoft Access is easy and I ended up working there one or two days a week. So so part-time all of my studies for years, and I remember you were practicing customer that innovation has even a thing. That's it. See the problem that the people in the shoulder. Yes. It's a good point because then a lot of the reports and In being able to sounds weird to say enable the business to make data-driven decisions, obviously, like, you know, 15 people whatever it was literally saying what type of businesses do you think we do better with when we go to sell it. Is it the like the cafe or the hairdresser and then my sale, you know, it's the hairdresser's. Okay. Well, it's let's look at the data and then which salesperson is better with the Kebab shops versus the fine dining or Iran and that was a type of analysis and I remember after I left prison and came down to Melbourne. And years later there was a flood in Brisbane and that business was paid by the flood and then they lost their server and this is a know maybe five or six maybe eight years ago now but years after I left Brisbane anyway, so I ended up getting a call from my old boss like that business owner to say. Hey, we lost the server. We lost the database with it about ten years after I build it. Well, is it we're still using it. Do you happen to have a copy by any chance? Obviously being a small database I ended up I think I drop boxxing him the last copy that I had. Anyway, the last time you used yeah. Yep. Definitely last time they use access as well. So I did that also worked in this mining Research Center with which I ended up doing that thesis through before that. I had a few sort of that analysis and programming jobs to do with different research projects and An end up doing that thesis and then my other job was the audiovisual technician. So I had the three jobs and was while you study while I was studying. Yeah, and then when into IBM and they'd data Consulting, so in general which at the beginning was that migrations and then it was Data warehousing and Reporting did that for some time big client? So in mostly in the Telco space and then I really wanted to get more into the analytics side. So I went to a small analytics consulting firm, which Were based out of the UK and but in Australia, there are not fear about 20 people and so the company ended up it was called Martin those analytics of the time then change to Lava storm, which is the name of their product which was a visual ETL tool that did analytics as well. Most of the work there was in Revenue Assurance. So essentially analyzing data of how different systems work in an Enterprise to find what were they bug? Is or errors in the system where it didn't worked as expected and as a result of that we were the company was losing revenue and in large corporates, there was doozies like sometimes we spend four weeks doing an analysis as an three people for four weeks and we'd literally find that we are overcharging customers something like 16 million dollars a month and then undercharging other customers about 10 million dollars a month and we like go back and present those findings. Announces. Yeah, and then I really enjoyed it. I felt that I had been doing consulting sort of for a long time in quotes obviously, like when you're young time moves at a different pace and your perceptions of it. So I felt that you know, I was doing sort of that freelancing work when I was at University and then I was worked at IBM and then this small consulting firm and I sort of so all that is as Consulting as you go into a place you're trying to help them you have defined problems and then you leave and I wanted to take on a meaty challenge like a multi-year professional Challenge and I thought oh, maybe I can do this for myself. So a colleague of mine and I decided to leave that small consulting company and set up our own and professionally it was the best and worst thing I've ever done. We were essentially two Geeks that didn't know anything about business somehow we did end up getting an investor early on who is a guy that had had a Consulting business that he started. The it space and he grew it for 12 years. You will see Yo and he grew it to 200 people and then sold it off and then was doing some business Consulting and then wanting to invest in startups and then we were we were one of them and obviously we thought we hit the jackpot when we get humanism as an investor, but my business partner and I had no idea about business. And in the first year, we almost went bankrupt about four times and you know, the think that you're after a couple times that we were sort of on the brink and not able to sleep and obviously lots of Mistakes by two kids with no contacts like nobody newest and the market we didn't really know what we were going to be trying to sell us as our services. We knew that we wanted to be in analytics. We knew that we wanted to be moving towards Advanced analytics. But what is that mean and we've been using different software. So we thought that we had the answer in terms of whether great analytics software should do and what it should look like and we set out to start building one. So we were in a tiny tiny room in a tiny office, which I reckon we've been a fist of this and six-seater meeting room. So if we put this is well, let them not say that. Yeah, and we locked ourselves in for about six months to code up this product and then we the whole time thinking that you know, when we emerge and show this to the world we'd have people lining up around the corner to buy this the software from us and Recently, you know how this story goes. We went to show prospects and people said, oh, you know like out of this product this tiny bit like that's good. Like that's okay this big piece in the middle. We don't know what that's there for and this 60% of it. Just get rid of that bit. What are you guys done? So obviously not a being a very customer driven Innovation that case. We just thought we knew best and obviously a lot of people make the mistake. So by that point we were almost That was one of the times that we were pointing towards bankruptcy and then we're like, all right, we need to do something about this. So that's when we switched on the the Consulting. Peace. And essentially we said, all right, one of us is going to go and start Consulting and then try to grow a team of consultants in that company and then tagged out and then the other one was going to go and do it another business and we're sort of the thought was to build that and so I went first and we got one of our at the beginning we had a few small some more client but in the first Year, we had mlc as one of our clients which is part of now. Yes, we're doing some data analysis their eyes that they did that they require some help as part of an acquisition that they made or when other be company and in there we will to start a team of Consultants to help with that analysis piece. And whenever we were able to place another consultant in the client side, we were able to hire a software developer to work on our software product and we went sort of one for one for a while and in That first year in the first six months that we were doing that we set up with mlc. We got folks still as a customer which is in media. And then we got a government agency South Australian government justice department and getting those who is really really really tough and it felt that after that. We had a little bit of like proven success in different Industries doing the same type of work. It was opening doors a lot easier for us after those three and then as it happened, so I stayed as leading the Consulting. Peace. He's so the analytics Consulting and then my business partner with leading the software development and we went that way and obviously still in the same company and my roles was the sales so new client acquisition and I felt that at the time I went through this face that I really embedded my self-image and my self-worth to this idea of being an entrepreneur. I was like, oh, yeah, I mean intrapreneur and this this yeah for that time. It was very important. And for me to see myself as that be perceived as that and anyway sort of bit of bullshit that I got dire stuck in and in that sort of chasing this intrapreneur life is what sort of forced me to take sales seriously in order to develop the business and it was really difficult. It was very uncomfortable for me. Not naturally being an extroverted person and is definitely way way out of my comfort zone but looking back it was a very very important skill to develop. I think in order to be able to convince people influence be able to see their point of view so you can help them see your point of view and realize that sales is built on trust and built on a human connection and that it's not about trying to do one over somebody or pull the wool over somebody's eyes and that if you go down that track here not going to get very far at all and that it was about that funding human connection and Trust I was doing a little So even though I was doing sales kind of for the wrong reasons and by that, I mean that I was like, oh I'm being this intrapreneur and I was doing it for the wrong reasons, but I have found it a really important and valuable skill in my career. And then I was doing the managing the delivery of the program of work with a different customers. So my view at that point and at the beginning it meant that I was the project manager and then I was sort of part time to go through multiple customers when we were doing multiple customers at a time. time and then I would have project managers at the client side and I had set a rule for myself to spend at least half a day a week at each client site, which was half of that time was reviewing the project and the update and half the time with meeting stakeholders and obviously that all sort of fell apart when we got up to 10 clients, and then I also had to be doing sales and and we went through some really extremely busy period and kind of traumatizing period where Iran I spend I think about five or six months where I was billing over a hundred hours a week for about six months and then obviously on top of that there's a lot of admin work and sales work and things like that and I was literally like sleeping in the office and not necessarily my office. Like I client-side doing work there. Somebody gave me this wrist rest that you put this behind your keyboard. That is it was made of gel. That was my pillow. Yeah often I would wake up my face on the keyboard if you Okay, I'm awake. Now. Let's keep let's go working. And yeah, just like unhealthy and what usual story but software development. Yeah and coming up with the solutions for the customers was definitely a big learning for me that one of the things that we did in the business was Said as a rule that the first three projects that we deliver with a new client had to be seen as part of the sales process and we got there because they were some feelings in the company that sometimes the work that we're taking on wasn't very exciting. It was boring. It was too easy or it was beneath us and I was like, well, what do you mean we're doing work in the analytic space these people have problems in our Niche and they're happy for us to help them with it. Why wouldn't we? Correct. Yeah, however business yeah, so definitely had to keep an eye on the culture from that perspective and as having the first three projects as part of the sales process in men than in the first one we did exactly what they needed very quickly in a way that builds trust and over delivering a little bit but not necessarily infusing it with all of our ideas of how advanced we could make it but really hitting targeting the need and delivering exactly what they needed building a trust the second one. As you know a little bit more infusion, but building the trust hitting the mark on what they needed and in the third one again, and then by then we'd have a good relationship of you know, having three sort of having kick three goals and and having obviously built up the relationship over that time and then we're able to start suggesting more around the programs that work the type of challenge to tackle or how to put the different projects together in order to either get more value or make things easier to build and it will reject the business. Five years clear blue water. Yeah, so well during that time is good and bad. So highs and lows some of the highs we won some award. So we were in the top 50 startups in Australia a couple years in a row that is from Smart company magazine. I was runner-up for Victoria's young entrepreneur of the year. We see a lot of people applied and then the top five had to present at this event. That was about 650 people in the So I had to do a page. I was like, I don't know say five or ten minute pitch. There's a panel of five that had to peek and the voting was split. So two people wanted one of the other guys to people voted for me. And then the last one was Ruslan kogan from coriander comb and the guy who is essentially one of my competitors is part of this Prize or competition pay had a business that where he helped people pay their bills and get out of financial hardship and he had gone on the news. But he got himself lots of press and was always going on the news saying, you know, it's getting really tough for Australians out there and he was very vocal about the cause that he was supporting people with with his business. And even though the business wasn't very big. He was able to get a lot of press out of that and when the decision was being made let you rustling goes. He said look I really like the analytic stuff that you guys are doing cool that you building your own software. But you said I wouldn't have been able for him. He said I wouldn't have been able to get here to where I am without getting good. Press and making sure that the public knows what we're about and what's in it for them. So my vote goes to Chris the the other guy anyway, but it was a it was a good lesson. So towards the end of the company in the last couple of years my business partner and I started to diverge in our view for the business. He is a person who is extremely smart and things in terms of software. He's way ahead in the future. So maybe five years in the future. Mature is where his mind naturally gravitates and he likes to work on those problems and design that type of software and try to get there quickly in that's headed to cause a rift. I was much more concerned with delivering the customer value today and doing those simple projects that might be a reporting project or a warehousing project that might lead onto the machine learning projects. But doing those really well today, even though if it's sort of seen as boring work and we started diverging like And then eventually got too bad and as in like, yeah, we're just closing out got a little conflict and I'd been sort of going through that for I think it was a year and a half. Where was it was pretty bad. I spoke with my dad one day and he was like what the hell's wrong you look like shit. And so I was telling him and and obviously he knew that whatever happened. He's like, you just need to call it and even though yeah during that time after getting sort of that first investor in between we got another investor and during those five years. There was I had made Add a few people that had expressed interest in investing in Clearwater. So I actually sat on the decision for way too long because I saw a definitely the company has my baby and even though looking back. I had not done a very good job at being a leader creating a good culture or a work good work place. A lot of things. I did pre poorly than that being able to hit that reset button was actually quite liberating even though it was emotionally very difficult So eventually what I did was I went back to some of those people that had Interesting investing in the company over the years and I sort of said, you know, there's a opportunity coming up to invest in the company. Are you serious about it? Let's have these conversations and my business partner and I from the beginning we both had 40 40 and then we had sort of 24 investors. So when I went to exit we did in a way that he got 51 percent so he could keep control the company and then the rest went to investors. We're the ones that were there grab the bit more and then there was a another one that came in and yeah probably still go Company still going now. Oh, it's This with you. This is huh. Yeah, which is good. Yeah, and now it's been rebranded to smarter which is like smart data for together. Yeah, and it's doing a lot of folk translation work in logistics and a few other fields. Yeah doing well. So at least they're yeah, they're pretty happy for me. So from there, I went into NZ so as head of data science for the institutional division of this large bank, and I didn't know anything about banking before For and I had always been a consultant essentially. I didn't understand the amount of work internally. There is required within a company in order to get a project to the starting line at the point of where the Consultants come in to deliver. That was definitely something that I learned that ANZ at this bank. I didn't know anything about banking myself. So in large Banks, you have all these different divisions that have different types of customers and what most people think of is the the retail division where an individual you and I would go into a branch and get an account a credit card. Home loan Etc. And then from there there's a wealth division to help people with the superannuation and insurances and things and then there's our big business spectrum. That is so big that it's played out between three divisions where one is a small business which is businesses about to up in terms of Revenue up to about 10 or 12 million dollars a year. And then there's a commercial division which is about 10 million dollars a year to about 400 million in terms of Revenue and then the institutional division where I was in it was from four hundred million dollars up. So the Heavy Hitters big end of town and big big players and a lot of international ones as well. And I started the division didn't have anyone in data science. There was no data science team. It was something new that they wanted to try. So I went in to start the team to a lot of it was education around what data science was and what it could do for the business. A lot of people said to me that this is from within the bank that at that level of clients. There's very few number of companies that are of that size. And that even though you might have Rich data about the company. You don't have enough data about having enough companies of that size that you could get into some really interesting analytics. So lots of challenges sort of everywhere. So in the first six months hired a couple consultants and build lots of prototypes for six months, I think we did about 40 different prototypes and it was literally throwing shit against the wall to see what stuck for different business heads. Different parts of the business different Executives trying to whet their appetite and for them to see the value it was not very successful and I was getting pretty frustrated and then we did a project with group strategy where they wanted to redefine the strategy for the division and they wanted this to be the First Data driven strategy for the bank. This bank is a hundred eighty years old and I've never had a data-driven strategy. So they went to what was the the beginnings of the data science team for that division. We build the strategy which was Good over a few weeks with a few data scientists and unfortunately at the time and obviously all this stuff is in the papers. Now what happened is that there had been a strong focus on Revenue but not on profit and there we have gone through a period of very quick expansion in the bank and in the institutional game, the margins are very thin because the customers are so big that they have so much Market power and what has happened is that the majority of the customers were unprofitable and some of them had been for years. Where's so and that's one of the things that came out of this analysis along with segmentation and where we winning with who and work we could get more of them that have a customers. So going forward the bank started exiting customers or this division of the bank started exiting customers from the least profitable moving up essentially and for us we got some recognition internally through that piece of work, but then we got to start a team and we hired 10 interns through the data science Melbourne meet up. Program that they were running at the time hired 1010 interns and all full-time and we started doing analytics focusing on the customers who were just unprofitable. So almost at the other end and what we did was we used the data assets within the bank specifically from the retail division to build a custom analyses for these large companies. So for example, we would go see McDonald's and we would say McDonald's in your stores. This is how they're performing. Forming the stores that are best performing are in suburbs of that look like this the ones that are not performing well and within suburbs that have this other composition and there's all these suburbs and look like good servers for you that you're not in yet. This is where you should move and this is where the people are and we can see their financial transactions and help them with that. So by doing that work we were able to build a pretty big team over time. So at one point we were essentially hiring so 10 people every six months building a That capability and the main aim was around new client acquisition and cross-selling financial products. We were providing analytics as a value-add and that was our first product from the team which was this freebie analysis that came along with some of the highly profitable Financial products that the company could acquire and then over time we build the additionally a web portal that customers would pay us for so then we started charging directly as well. And that was to access very similar analysis than what they go with the really but in a much more detailed level and then we also had a bunch of apis the customers would start to use and we would invoice them at the end of the month. It became a profit Center and focus on their sales, which is good. You are wanted to reach it out. Exactly but it was it was really nice having another go and there was a lot of things that I did much better than the first time especially around the culture of the team was really good very very warm very friendly very supportive. We were have highly functioning team very productive and then obviously some of the bad things is that we were running too hard all the time. So if you think of our go hundred odometer in the car or speedometer, we're always on the red and it was always late nights and always weekends and it was always so after leaving ends at that one of the things that I thought of to try and fix for the next time so I left hand dead after I got married and then I went on a six-month honeymoon. And then while I was away I was thinking about what would be the next meaty challenge because I 1.1 was can I have a business myself and did that and then the next media challenge was can I go into large organization and Effect change and in that case, I measured it by both the number of people and the type of team and culture we created and the Revenue income that we generated for the bank and then after I left and I was traveling and I have the time of those the first time that I was thinking about, you know, like how did I do with that? Multi-year may be challenged I was like, whoa, I started with yeah pretty good. Like I have these success points that I can point at and say, you know, that was really good, but then I thought of if I look at that division has arrived. 5,000 people within the the bank that division five thousand people work there. I thought if I look at what the typical work day for one of those people look like before the data science team was there when the data science team was there and then after I left the work day of those five thousand people was exactly the same literally unchanged because all our Focus was on the clients external clients and on the sales piece, so we were generating tens of millions of dollars for the bank through these deals. Because they're large deals, but the life of the people that work there. We literally touched less than a percent of all the processes less than point. One of a percent of the processes, even though we did a few projects internally and but largely untouched so I thought that the next meaty challenge that I would like to take would be somewhere where I could have a go at affecting that change essentially like a an internal transformation where there is a capability lift through data science and machine learning that the Working Day of the people they are in the company looks significantly different before during and after and then thinking along those lines I thought well for me to get that remit and to have the responsibility essentially and to have the influence for me to be able to do that and I sort of thought and I think it needs to be a mid-sized Organization for there to be the ability to have that alignment and to be sort of like that. A data person if that makes sense. Yeah, and then I got some excellent piece of advice for their podcast, which is super helpful speaking with you. I remember was really really excellent in terms of even before we started recording so much guidance that I got from you and then in the episode as well and then the other person that really helped me when I was thinking about this that's when you and I spoke and the other person that helped me during that thinking is Tony Lang who is another guest and he was head of data. That I select and compare the market and I was in Brisbane and I remember like off the back of my conversation with you. My conversation with Tony is where I got to this point that I'm describing now in terms of that transformation in a business significant capability uplift through machine learning putting it behind every nook and cranny and every business process and for it to be a mid-sized organization Etc. And then when I go back that's what I was looking for and then through some very fortunate connections and some very nice people. Our ended up coming into Liberty Financial as general manager of data science to do exactly that so it's a company that they're hungry for that change and there I've been there about six months now, we just starting the data journey and starting at let's build our warehouse. Let's get that assigns going and what can we start to understand about our customers and taking it up from there? So yeah, that's the the next meeting multi-year challenge. So let's put a rich and varied career when you look back. So your daughter is there he'll three and a half months a half months. Let's say in what we call 17 years. I'm a half months when she's I tell ya that's right here. And now what would you tell who your most fertile? So what I'm actually most proud of it's a career achievement, but not Sara Lee I think it's not something that is generally seen as something to be proud of in a career that makes sense is at least so far. What I'm most proud of is that culture that we had in the team a day and said that it was extremely supportive very open. Everyone was friends with each other and even to this day even yesterday. I was at a meet up event and so about five or six of them and big hugs as soon as soon as we saw each other and that is Being able to start and create and maintain that culture it obviously felt great to have it and being able to enjoy the relationships with the people you work with and enjoy you the work so much and that was really nice and then obviously it didn't materialize into results as well. But for me, that was a big win because I had done well because it's such a nice thing to do but also because I had done such a bad job in that Dimension or in that area it when I had my business previously our culture wasn't very good. It wasn't very friendly and wasn't very open and it was something that I definitely wanted to change but I didn't know that I could be that good and it was really nice. Yeah, it's really interesting podcasts, but also try to get ourselves. Now the organizations out there thinking for themselves. How do I get ahold of Philippe is my organization, but in the absence of being able to do that, what would you be telling them in order to get the most out of their data science practices or even just the Anna Leaves? Yeah, I think that for a lot of businesses. It's telling them that analytics or data science. It's a team sport. I think that when people seek to test the waters or get their foot in the door in this space, they want to start by hiring a data scientist or a data engineer a data person that will be doing the work and that's generally quite tough to do to be a single person. I would say that's definitely not the right way to go. Sometimes people have done that before. Sometimes they go. Go in and they try to hire an extremely competent and experienced very technical person. Somebody that has only the technical Focus little business people get frustrated with that profile because they are extremely curious people and then they want to follow their curiosity and not necessarily do what the business wants them or needs them to do and then there's that disconnect between the the technical challenges and the business challenges. One of the things that I would say is is look for people that can think about that dual set of challenges to technical in the business and is able to pull the business through and that's one of the things that I'm hoping to help people think about through the podcast is bringing those stories to the audience and to their mind to think about the settling of the two sides and then besides that it's I think it's about the data literacy and the training so in today's world and going forward definitely machine learning is everywhere and data is everywhere and it's Obviously from a biased perspective, it's everything so developing. The level understanding is going to benefit that in any organization and I think that the more people that understand it and that can start to self-service themselves in the better. The company will be because you have people throughout the organization up and down the organization being able to make data-driven decisions. And even though other people might not want to start the journey because I say, well, I can't have 10,000 data scientist. That's not the point but having a level. Like a data analyst or like a business analyst where it might all be drag and drop tools and it might be no code written and it might be maybe some basic SQL maybe not even but they're able to extract data they're able to do like group buys and pivot tables and visualizations and things that allow them to make data-driven decisions. Then the organization will be all the better for it. We'll see. So for new starters, it's about I think about understanding business and understanding or know the domain of where you work so it can be obviously I can be a not-for-profit. It can be a government organization or business. But at least I've noticed Within Myself then when I start a new job, I feel the pressure to Value quickly and to demonstrate capability and I want to make people feel like they made a good decision by hiring me and so you always have that pressure early in your career as well. And I found that in my case. I've made sometimes rash decisions by Falling being trapped by that sentiment of wanting to show something quickly and what I should have done instead is taking time to understand the domain the business the people what they're trying to achieve and then think about what is the best way That I can help along that journey and essentially start there so meet them where they are. And then what you have that understanding seek to solve their problems and their needs in a quick and easy way which means generally not the latest algorithms not the latest tools but something that might be very ad hoc, but it definitely make is progress and give people what they need. Exactly, so that in future ology. So first of all, happy birthday, thank you this recording today on door closes. She's been sent ended months 16th of May. Yeah. So today tomorrow. It's a one-year. Really going long? That's right. This way. Yes. So 52 interviews has to be shaving it on behalf of the science Community here in Australia. It's going through a lot of people who adopted the podcast and thank you. Thank you, Ron. Sometimes you don't know that there's a gap until somebody comes in and plugs it and you've done an amazing job. I've passed what was your inspiration to fold or the beginning? I never thought that I would start a podcast. So or even continue to do a podcast the seed of the idea actually came from my wife when we were planning to go on this long honeymoon last year. I was getting a bit nervous because in the last 15 years or so the longest break that I had was two weeks. The most time of I had had for heard been a very different story by the time I met her she had travelled full time for about two and a half years in you know, like six months here three months there. Pockets but overall two and a half years of full time travel so very different profiles and for her Buck you another six months or so and actually relaxing was easy, correct? Yeah. She was excited by that it meanwhile saying what am I going to do? Whatever she said? Oh, you know we'll be together. We'll see new cultures. The side was like, but what am I gonna do anyway, so obviously she was a friend of that at first, but then she lets you said she said, well you like listening to podcast so much. Why don't you do one you can People as we travel that's actually a really good idea. I've never thought about that and then in continuing to think about that what I found is that in developing my teams in the product my career. I saw that most of the coaching and the mentoring that and the development needs were not on the technical side, but we're on business on leadership on soft skills negotiation presentation that strategic thinking how to create change in an organization. That's the what I always. We saw is the development needs for in and for people in our space and having the thought of the podcast. I was thinking I was going through podcast that I listen to and I always enjoy listening to a technical ones, but then I was like, well, where's the leadership ones and then I started following that line and then what I had started to think about with my teams before starting the podcast I have this dream that end up sparking the podcast is how can we make data scientists of today the CEOs of tomorrow and the person who is CFO in 10 years 20 years time that they once were data scientist or a chief marketing officer. That was the thinking and obviously I think that that's going to be necessary and very valuable obviously to have these skills, but you need to have all the business skills or the influence of presentation negotiation Etc. The business strategy the value creation. Those are the types of skills. So that's the vision that I started that a futurology with what is the gap in people interested in data to take them too? To a point where they could be a CEO and obviously it's not going to come only from one resource. But if we can help people to stop think about that then that would be great. That's the aim. It's really pleased. Count and I by yeah, that's right. So the more ways that we can create this change the better. So I think that we have to go to video at some point soon have more. I think I would like more interaction with the audience where that might mean IQ a show or something where we might take a group of people at a similar point in their career say five years experience or just getting into leadership 10 2015 years experience. We take a group of people. There are similar and we follow their story over a period of time through something like a workshop or like a group session where we discuss talk about our challenges and to go if possible solutions and approaches to implement. So make it more interactive and start to tie in the lessons from the leaders that we've been hearing into how those are implemented in people's careers, and I won't ask you to So what are the lessons or what are the stories? What would have been had the police detective? I've always been impressed. I've been most impressed with the way that I want to say kind of our generation of leaders or like the current generation of leaders how they've had to find their make their way and that there has been nobody to learn from nobody to emulate not a single source that you can say. That's The type of leader I want to be or that's a person in this space that I really respect that we had to well not so much me, but the people that I've been interviewing that they had to create this out of nothing and for that the types of skills. You have to be so savvy so self-aware so much passion be so driven and be comfortable with Meandering through your career and being able to a keep yourself in check but be comfortable with diverging From the Path and that through Walking around in the forest. Suddenly, you're the other end and hey, I love that but then everyone is so willing to pass on the knowledge and share that with the Next Generation and say, you know almost like it was tough for me and I didn't know what I was doing, but I wanted to see if I can hopefully make it a bit easier for you and people are so eager to help the people coming up and I really love that about our industry and I love hearing those stories of how people were self-made in their careers. They Forge their own path and they are so happy to share their wisdom your last couple of questions. What's got your curiosity? Cool possibilities will I got a science has gone in front of it seems like yeah, I'm really really got into kind of like explainable AI at the moment. I've been very interested to learn about the developments on making black boxes a little bit less like boxy and said to understand how the models are making the decisions what's driving it and from a technical perspective. Yes interesting, but I think more interesting is the learnings that We can have as humans from what the machine finds and then how can that help can help us be better in our thinking be better in that decision-making be better in our obviously feature engineering as well. And then to have this virtual cycle where the machine learning systems by being more open. They increase their power in being our assistance that is going to help us move forward with our knowledge and our creation of knowledge then by having systems that are more black box that always said leads to automation but then Want to be getting the learnings and getting the insight and instead of me feeding the machine data and for the machine to do something. I want the machine to give me something, you know, give me some knowledge. Yeah, which is a YouTube video a little while ago now and it was a self-driving car that anticipated so you wouldn't results for these cars and driving the car had anticipating Next Level very heart of it and stop. Wow and two more human eye. I couldn't see what the algorithm itself and then no way an accident and my immediate response was oh that's amazing. The II is the list and I look at the comment on the life and somebody who was kind of channeling Spirit or you despite her out by the comment. Will it be great to know what they either side of the pain? We don't have the self-driving car because know that yes that is such an insightful observation. So important. It's a great core didn't feel the eyes out. What question have an I ask that you pay me tonight, but I really wanted to answer great. Great question when we covered it all I think you've done an amazing job. Yeah. It's I've learned from you my tits, and this has been an absolute pleasure. Thank you. Thank you so much for taking the time. And yeah we need to do is it's been incredible. Thank you. So thank you for letting me take over. The product for whatnot and on behalf of the listeners for joining us and we should close with the jacket is black. The jacket is black. Thanks so much out there. That brings this episode to conclusion. Thank you so much for listening. Please find us on data futurology.com or on Facebook Twitter LinkedIn or Instagram as that of each religion. Also go to data futurology.com forward slash forecast to find the show notes for this and any other episodes If you liked this episode it would mean a lot to us. If you could leave us a review wherever you listen to our podcast. I hope you enjoyed this episode and that it was helpful and valuable for you. Thanks again and see you next time.
In this episode, Anthony Ugoni, one of Australia’s more prominent leaders in analytics interviews Felipe. Felipe came to Australia as a backpacker and ended up falling in love with the place. With Spanish as his first language, the only English he could say was the jacket is black. Then, Felipe explains some of his odd jobs and working freelance IT. At university, Felipe wanted to specialize in data, but all of his friends told him it was dead. So, he ended up specializing in hardware, even though all of his work was in data. When Felipe went to do his thesis, he happened to stumble into a project involving brain wave activity. The electrical engineer did all the research and design, the signals would be passed to Felipe’s computer, where he made his first application of machine learning. Then, Felipe explains how he and a colleague of his made the decision to quit their jobs at a small consulting firm. They decided to start their own firm, despite knowing very little about business. The first year they almost went bankrupt about four times and made lots of mistakes. They wanted to be in analytics but were unsure how to sell their services. The two spent six months creating a piece of software. When they went to show prospects they found out people did not like the entire product. So they decided to focus on their consulting business. Enjoy the show! We speak about:   [02:40] Felipe’s background   [06:10] Education and specializations  [14:30] Quick delivery of value    [17:20] A series of odd jobs and IT freelancing     [24:20] Setting up his own consulting company     [33:15] Highs and lows of Clear Blue Water   [37:30] Executive Director & Head of Data Science at ANZ   [47:55] Supportive and open culture at work    [52:40] Understanding the business at a new job   [54:45] Inspiration behind Data Futurology   [62:00] Explainable AI    Resources: Felipe’s LinkedIn: https://www.linkedin.com/in/felipefloresanalytics/?originalSubdomain=au Episode #21 Antony Ugoni: https://www.datafuturology.com/podcast/21  Quotes:    “If I’m an engineer, people will think I’m smart.”   “A colleague of mine and I decided to set up our own consulting company. Professionally, it was the best and worst thing I’ve ever done.”   “Sales is built on trust and a human connection.”   “I had not done a good job of being a leader and creating a culture.”   “How can we make data scientists today, the CEOs of tomorrow?”    Now you can support Data Futurology on Patreon! https://www.patreon.com/datafuturology   Thank you to our sponsors:  UNSW Master of Data Science Online: studyonline.unsw.edu.au  Datasource Services: datasourceservices.com.au or email Will Howard on will@datasourceservices.com.au  Fyrebox - Make Your Own Quiz! Thank you so much for listening. Enjoy the show! 