Data, Strategy and a Little Rock and Roll

 In this episode, Lucy Lynch speaks with Aju Alexander, CEO of The Data Company, about the real foundations of transformation. 

Transcript

SPEAKER_00 0:17

Welcome back to the show. I'm Lucy Lynch, Chief of Staff at Omni Digital, and I'm delighted to announce that we have got uh a new business partner to add to our seller ecosystem, which is Dana, the data company. So now I met our guest today, the wonderful Aju Alexander, through a mutual connection. And once we met in person, the stars were aligned, and I kind of knew we would just end up working together. Fast forward a few months later, and bang, here we are, fully inaugurated. So welcome today, Aju.

SPEAKER_02 0:51

Thank you, Lucy, for that uh very warm welcome uh as an individual and and as data company. But um uh yeah, it's been it's been wonderful knowing you and Matt and uh the great work Omni is doing, and uh we are uh really honored to be a part of the um the um partner profile that you you're building.

SPEAKER_00 1:12

Thank you so much. And I remember that when you said that you were a numbers guy, and I knew that you would totally get along with Matt Small, our CEO, and that's certainly been the case. And actually, you've had a really interesting, fascinating journey into data and and automation, uh automation. And what was the moment that we that you realized that this was the work that you were supposed to do? You know, some people grow up and think they're gonna be a fireman or they're gonna be a rocket scientist or you know, something else. What was it? What was it that kind of struck you?

SPEAKER_02 1:48

It's an interesting interesting journey for us as a company. Um, we um started our journey in 2007 as a um digital transformation consulting firm. Um, so we were helping companies to look at manual processes that can be automated uh through workflows um uh and simple, simple work workflows or or app bringing new applications, mobile or web applications and things like that. So that's how we we um we developed as a business. Uh we we we um sort of worked within multiple industries within that space, and uh uh uh we also brought in uh um our own framework which um helped us deliver um these sort of process automations consistently to our customer base as well. So so I think you know that's where we started. But around 20 um 16 to 2018 timeframe, there's um while we were engaging with our enterprise clients, we um realized that there were two pillars that we didn't focus on in the as a part of the digital transformation. So when I say pillars, um so we were focusing on the application pillar, but to make the digital transformation um work for the organization, you're right, you're also looking at the uh the the data as one other pillar, um, because you need to have the right sort of data coming through and the data flows, and uh, you know, that's quite important. And um, and the third pillar was the uh cloud infrastructure. So a lot of the enterprises were moving from on premise um sort of hardware to cloud, and you know, that gives the opportunity for the enterprises to um scale their operations and scale the automations they were trying to achieve. So so those elements uh uh uh were sort of brought into the data company. Um we were in in fact at that time um known as Tech Finium, um, which is a different um brand we were running at that time for the process automation side. But we uh we brought in the cloud data and application all together around 2016. And as the um the services developed, we realized that everything revolved around data and any transformation they need anything. So so the the the foundations that an organization needs to have for these sort of large enterprise level transformations was um around data. And we are talking about 2018. We had you know, you know, people were not uh hyped about uh AI or anything like that. People are still looking at you know conventional data warehouses, the master data management, the golden record, and all that type of good stuff, right? Uh, but what we did at that point in time from a uh uh from uh a strategy session we ran internally, we decided to pivot the business as the data company. We rebranded um our company around 2018 uh as the data company, and and we started to um evolve our own services um uh you know uh around the data uh space. Um, but as we all know, um COVID hit hit the market around 2020, and the whole um sort of strategy piece was put on a hold for almost um uh 18 months. Um and then we when when when everybody came back, uh then it it was fairly um obvious to everybody in the industry that I think the data was the the foundation and you know uh and and um uh applications were more moving into SaaS-based applications or uh uh point solutions that could be um uh sort of consumed as microservices architecture and things like that. So people people were uh and enterprises were able to achieve their application goals through um uh through sort of uh implementing um point best of breed solutions through microservices architecture. Whereas if they don't have the the data architecture in place or if they don't have the um the automation around the uh DevOps or data, um uh you know that they they they they've start they started to struggle to scale, you know, those operations. Um as the as the market moved on um around 2022-23, we saw the advent of the you know the um the machine learning models coming uh uh uh a bit more into the markets and the first stages of the AI, you know, um trying to to come into the market as well. So and and and as you can imagine, I think last 18 to 24 months, the the adoption of AI, the acceleration of the um the AI-driven automations have also started to um to um to become very to the front rather than you know anything else. And and that that's disrupting the way you know the industry itself is is is looking at some of these problems.

SPEAKER_00 6:56

But saying that as uh from a data company point of view, we always believe that to make that happen to happen, we still need to look at the data and the orchestration and the real-time uh you know, sort of uh yeah, yeah, and that kind of leads me on to a question that because I know that whenever I talk to you, you're like, oh, I'm speaking to this CEO or this CTO or CIO, whatever. So you spend a lot of your day, you know, talking to leaders all around the world, right? And what's one thing that you wished every lead understood about their data uh estate?

SPEAKER_02 7:35

Uh that's an interesting question. Um, I would probably take a step back. I mean, I think um a lot of the enterprises and at the C level or the board level, I think one of the fundamental things people um forget is the is the is the strategy definition, right? So, you know, the vision, where what's the business outcome for that enterprise you are trying to achieve, maybe the top three, and what's the strategy to get to that. You know, I I think a lot of the um a lot of the uh you know organizations actually miss that step, or you know, there's no clarity within that, you know, the the strategy definition. So that's quite important. Um, you know, and and and um that's where I think a lot of the CIOs or CTOs actually say, okay, fine, we need it technology is just an enabler, right? I mean we all talk about technology process and people uh all the time to to get the best outcome. But um it's the um it it the the level of transmission we are talking about now in terms of using data and the technology piece is is it has to be driven down by strategy, um and the business strategy that can uh that can uh lead to those implementations and executions. So I think that's where I think if we if I if I think back on my conversations with my with the CEOs or CIOs um or even CFOs, I think it's that joined up strategy for the organization, you know, uh within the various you know uh outcomes they are looking for. It can be profitability, it can be operational efficiencies, it can be you know risks, um, you know, compliance mitigation, you know, type of um scenarios. So whatever the whatever the uh uh enterprises um you know the the the the vision is to to become more more um competitive in the market. I think that's quite important for us to even even uh before even looking at data or you know any of those technology pieces. I think that that's quite key in my mind. That that comes out over and over again. So so yeah, that's that's my view.

SPEAKER_00 9:44

Yeah. And I think it's you know fair to say, you know, that you know, we've been around the block a bit, right? We've we've we've we've done a few marathons with these, with these sprints, with these transformations, with these long, like wheel, unwieldy projects. And I think, you know, like it for me it's always going back, like like you said, you know, going back to you know, twinning it with the business goals, the objectives, right? Making sure that it's always about driving the value, right, for the customer, um, and and twinning all of that together. And where do you see that organizations usually get stuck? Is there a kind of is there a is there a thing where you know they might get stuck in you know the technology adoption or the culture or the process or something else entirely where you know some organizations might get stuck when they're going through a you know a big long project?

SPEAKER_02 10:39

Certainly, I think the I think technology is not the barrier. I wouldn't I wouldn't consider that. I mean, uh you know, technology these days um are quite sophisticated. You have different tools, different technologies that can be adopted. Um it's a question of you know how you uh pick the right ones and how uh which partner you work with to sort of go through that journey in terms of technology piece. But I think the biggest piece within those um within the implementation or execution is the culture and the people element. I think that's where I think you know it it it it it um um it's sort of it's a mix of um uh you know uh resistance to change. Um, you know, when there's these sort of transformations come in. Um there the I think a lot of the organizations as they grow, the communication between departments, communication between uh regions, you know, that gets um sort of um blurred or misaligned. Um and and that that leads to siloed decision making. So you you know you know a department might become highly efficient, you know, in in their journey aligned to the strategy, whereas the organization may not, because you know you still have to deal with so so that that siloed decision making can be a um uh a problem. Uh and I think that's I think that's more the issue than a technology or or even the process, because uh the you know the the uh more mature, lar larger enterprises we work with, the tier ones or the tier twos, I think they they do have fairly strong um uh enterprise program um change program processes, but the people involved, you know, uh I think you need to handhold them. It's a journey, people people need to be skilled up. You know, there may be skills issues that can, you know, that can be um things, and uh it's that whole cultural piece is is is I think which I feel that's my opinion, but uh I think I'm uh feel free to uh I I agree with you, right?

SPEAKER_00 12:43

Those pesty people, right? You know, so it's like can you can you think of any kind of lessons learned when we're thinking about transformation? About when we think about anything that needs to be in place before the technology can actually land, because you because you guys are very, you know, sort of like expert in you know implementing you know new technology, tools, etc. implementation. I know you're very skilled at that, but you know, what needs to be in your ideal world kind of scenario, what what could it look like, the enterprise business look like that that could things that could be put in place before that technology actually lands?

SPEAKER_02 13:27

In my mind, I think there are two or three key elements that comes to uh to my mind. One is uh the business architecture itself. I think you know the the uh we talked about the business outcomes and the value creation, what the resources is looking at, you know, for that's more a strategic um intent. Um so that business architecture you know is is is agreed, signed off, and everybody buys into it at all levels, right? So so that that's one key element I see uh to be there. The second is the the sponsorship in terms of um budgets, people, resources, any sort of, you know, so it's it's because everybody has a day job to do, and this this becomes uh a pain in you know uh in their minds to to execute, right? So um so I think that that sponsorship and you know, probably so there the you know if there are leaders that can take that or drive that forward, you know, uh that that leadership around um you know uh around that uh that can be um another good point in doing it. So I think there uh you know the the um people do create business case and business value and you know they do minimum viable um products and or or or or um proof of values and proof of concepts and things like that. But most cases in these sort of transformations, because these are enterprises take a lot of time to go through these things with committees and this, that, and the other, by the time you start executing the technology element, one technology would have moved, um, you know, two, you know, the the parameters you defined your business case would have been not relevant. Um and and and in these times, um uh there are a lot of unknowns as well. So, for example, a lot of people get excited about this world of AI and agentic AI and in automations and things like that, but the cost of ownership of an agentic AI um automation can be quite high uh and and and destroy the business case you created because I think you know you don't know some of those things in terms of how the consumption is going to be. Um so the lot so so there are enterprises who have started very well with those automations on AI, have had to almost roll back, yeah, and and go back to drawing board to see, okay, fine, you know, how can we optimize it? Can we re-architect it, or can we do it in a different way so that no, we can um uh we can we can still achieve the business objectives and the and the value. I think that that's where I think the technology is maybe in two years' time, three years time, you know, like we have seen with cloud adoption, or you know, uh maybe those price points or the storage, for example, the security elements, you know, those price points may drop um uh you know in terms of consumption. But at this moment in time, there's quite a lot of uncertainty all time. So there are those two, three things which are sort of I would say hurdles for the um for those, you know, uh for those transformation projects to be successful at this stage. And again, again, it's it's from where where I see or where I have those conversations with um our clients.

SPEAKER_00 16:55

Yeah. Okay. And then, you know, we've been working behind the scenes, you know, for a while now. You know, uh what made this partnership with Omni Digital for you like feel like it was gonna be the right fit for the data company? I mean, other than working uh with me, obviously, but you are the magic, yeah.

SPEAKER_02 17:19

Um so I I think for what attracted us as data company to Omnia is actually the synergy in terms of the uh uh of the philosophy of the two organizations are very similar in terms of you know, we are both trying to achieve the best value or or or or the best business outcome for our clients. And that's our sole objective. So, you know, we bring the right people, uh, we bring the bright technologies, we bring the methodologies to make that happen. I think both the organizations, that's what actually excited me from an alignment point of view, saying that okay, fine, uh, you know, I think um Omnia Digital Undermat has been delivering uh successful transformation programs and data programs, you know, uh exactly the way we do for our customers. The second attraction for us was Omnia's focus and delivery capabilities have come from industries that that we don't sort of overlap. I mean, the the you know, in terms of you know, whether it's public sector or charity or or retail, manufacturing, you know, we don't come from that background. We come from financial services, healthcare, you know, manufacturing and engineering. Yes, there'll be an overlap somewhere, but the collective experience, data is data across the piece, right? Yeah, um, but the the collective experience of of both the teams pulled together and the wider associate network actually adds value to what we are offering to our customers as we have seen. We operate both in UK and South Africa. And and we are able to extend that capability, you know, the the the profiles of consultants from both sides, you know, uh to enhance the the type of work we we both are doing. So I think that that in my in my view uh was a no-brainer for for when we had the first discussion and said, you know, okay, fine, you know, here is omni-digital, here is data company, and there was that synergy. Um uh we we we do um a lot of the engineering work very well um in terms of data and AI engineering piece and and the auto process automation piece. And we could add that uh element of you know the the governance and the culture and the you know the um uh the strategy uh uh around some of these um architectures and things like that. I think that's where I think you know we can work together as exactly it's like parts of the pie, isn't it? Like parts of the pie, absolutely yeah, lovely.

SPEAKER_00 20:05

And what excites you, you know, about the sort of next, you know, we said like we we had a bit of a hiatus, didn't we? Like the last two years, the market was pretty, pretty like static and you know, well, there are lots of choice words we could say about the market, but it does seem to have picked up, and you know, hopefully it's a brave new world out there. But kind of like if you're thinking sort of 12 to 18 months, you know, CEO, we always have to think ahead, right? What's next, what's coming. What excites you though, about the kind of next 12, 18 months do you think in sort of in in our world that we're living in? What what what do you think is is exciting?

SPEAKER_02 20:47

So, in my mind, the way we as the data company has strategized for the next you know um uh three to five years, we see the AI adoption as going to be um accelerating, you know, from that world. And and and and for us in the space of automation, um, you know, uh this becomes quite an exciting period because you need to to to deal with the data. So we always say the data, you know, uh there's a whole exercise we can help the customers with where we can go through a process where we understand the data the customer has and is being used. We can also pull out all of the data that customer is collecting but not using, you know, and also there's a whole world of data sets, which is internal and external, that could be used for optimizing or excited uh you know, sort of uh bringing the best of the uh the the outputs of analytics or uh uh you know AI automations and things like that. You know, that that I think is uh is is is is going to be exciting because now the technology with the uh uh the the the the the space we are moving in allows you to bring structured unstructured data all into one place you know rather than a uh fixed silo of a data warehouse where you had to you know look at different views etc etc whereas now with the ability of small language or large language models you can query the right you know sort of lake houses and the date the data uh in a way and and and then anybody can do it you don't you don't need to be a super analyst or super yes exactly that's the power of AI now you know it's coming into people like us who are embracing that technology you know for making better efficiencies operational efficiencies in whatever we are doing you know it can be software development it can be you know creating a PowerPoint presentation it can be any anything that we do embracing that AI is going to be the success of each of each of the organizations you know uh going forward and we ourselves have done looked at all of our internal processes and we have adopted um ai to deliver um you know uh some of our services for example uh we are looking at ai to create use cases that could be almost like data products that could be repeated for our customers because then then then it it it's it's that standardization of the of that use case which will um um almost bring in the governance and the security element of such or such such use cases we do a lot of work within the uh fraud investigation um financial reconciliation you know those sort of use cases where we can actually create data products which can be then consumed by the the customers for example so those are exciting times for us you know creating those um data products which which which the customers uh can immediately see value from you know i think that that's that's that's really exciting for us um you know and we are creating those in our in our strategy your energy right with that so I can see that you're definitely excited now do you think that customers like other organizations are are on that same page with you or do you think that or or what do you think that some organizations are underestimating right now is it about how how fast it's gonna happen or something else so so um I have two views on it if I if I right so one is you know the the danger around ai and looks like everybody is an expert in AI in these days right you can create a piece of code you can create a piece of you know uh report you know everybody's an expert in here's my company here's this here's that doesn't matter if it's true or it's an avatar or you know it's a hallucination doesn't matter it's up it's there right exactly but but but uh that's the danger bit to it right so you are uh you know you are allowing the power of AI you know whether it's the co-pilots within an organization and or or from people using chat GPT you know but the the danger if it's not governed and and and architected properly within an organization I think you know it's it's going to expose and and bring in a lot more different types of risks that that that um uh that organizations are not even thought about at this moment in time right so so that's one side of that story you know uh so whereas the other other side is you know there are companies like Omnia Digital the data company who are helping customers with this journey for example so so I always um um discuss with customers as well uh you know this is a journey this is not a project you know we will help handhold we will help walk you through that process with a view to training the team and making sure that the organizations are self-sufficient within these these these it's not like we are there um uh and and they have to depend or class customers have to depend forever yeah you get your point and then you leave you know yeah yeah yeah you know you know we're going to probably hand hold it train the team up and and and and and do it so so that that that's sort of uh a view so the customers are at different maturity levels at the moment you know you know uh especially the tier two ones are still figuring out what needs to be done whereas tier ones have a bit more budget in terms of playing around with some of these uh structured um architectured solutions um so so I uh the the the point is I think we can help customers to to go through that journey whichever maturity stage you're at um I think that that that that's important and and and there's no harm in shout shouting out for help right yeah uh you know you know but but internal teams tend to sort of try and um um sort of try and do some some stuff but they're moving from an extremely legacy skill set to a new skill set which is completely different way of thinking different way of doing it I'm not saying that it's not possible but that's it has to be skilled up it has to be done properly at an enterprise level because I've heard um horror stories around departments um uh you know HR department or procurement department or finance department creating their own little applications and little I mean they're all moving from the age old Excel sheet and now they've got a a fancy you know application which you know an agent which does certain things and creating some fancy report but the problem is because they're not doing it as a as jointed as the organization we talked about it around the organizational objective it it it um uh it it becomes disjointed so the IT team doesn't know what they're doing it's not on their security framework it's not on their cloud framework it's not on you know so it it becomes highly disjointed you know and and that's where companies like us consultants like us can actually almost um orchestrate that that transformation journey rather than you know we will help we will bring the right guys you know through that through that process um uh yeah I I uh I don't know whether I answered your question but I I I think yeah I just uh I was just sharing my my experiences yeah yeah no thank you and I think you know I know that you're such a lovely guy now this is a maybe slightly cheeky question but what's one thing as you that people might be surprised to learn about you are listening that's an interesting one I don't know whether whether I told you this or not um I am in a band and I do like that yeah so I'm in a band uh we it's a four uh four people band um three guitarists three singers one and one drum you know so so we we no no i'm I'm I'm the lead guitarist for you know for Orienter Price yeah uh yeah so we do a lot of um um slow rock and you know 70s and 80s uh you know oh my god so so so yeah yeah yeah yeah I I I could do a couple of numbers you know when when we do the next barbecue I didn't I didn't know that I was not expecting you to say that that is amazing well I'm very surprised and I love it absolutely love it I play the piano and I just think um you know anything to do with the arts or anything like that when you've got a really sort of heavy head with loads of stuff and if you can just go and do something else that unlocks another part of your brain it it actually makes everything else make a bit more sense so I love that so thank you so much for sharing that I'm gonna yeah that is so cool.

SPEAKER_00 30:26

And that kind of brings us to the the end of today's conversation as you and so thank you for bringing such sort of clarity and honesty and depth to this world um and you know I think it's genuinely enabling for organisations that that need it most so you know I think I think that's great that we're going to be working together. So if you're listening out there today and someone something in today's conversation sparked a thought or a challenge or a possibility please reach out to me. This is the kind of work that moves organizations forward. Matt and I are delighted to to have you guys on board and we look forward to uh working with you in the very near future so thank you Adju thank you so much Lucy thanks for the podcast and and and and allowing me to share my thoughts yeah thank you