Kieran Towey, Head of Applied Intelligence with KPMG.

John Howe, Manager of Data Science in Brightwater is in conversation with Kieran Towey, Head of Applied Intelligence with KPMG.

JH: My name is John Howe and I’m the Manager of the Data Science & Analytics team here at Brightwater. We’re joined by Kieran Towey. Would you like to introduce yourself there please?

KT: Hi, I’m Kieran Towey. I’m the Lead for Applied Intelligence Practice here at KPMG Ireland. It’s a practice that looks after everything to do with data, from data strategy through to data engineering, cloud platforms, big data platforms through to analytics and visualisation, data science down to AI and cognitive approaches to problem solving.

JH: Super stuff. Okay, well, let’s delve into that a little bit more as well as understanding what the Applied Intelligence Practice in KPMG actually does and where the future of that is. I’d like to dig into the types of people that you’re looking for, those types of skillsets and ultimately where the future of this area is, not just for your business but for also for the domain, the industry itself in Ireland. It is an area of really fast growth, probably the fastest growing area from a recruitment perspective in IT, in Ireland now when we compare and contrast it to other areas of IT in which we recruit, it’s by far the most buoyant.

JH: Can you give us an overview of what the Applied Intelligence Practice in KPMG actually does and why it was established?

KT:  I think why it was established is exactly as you were alluding to there John, as there’s a huge  up-surge in growth in the use of data to address business problems. With the volume, the variety and the velocity, the 3 V’s of Big Data, being ever more prevalent in every organisation, the organisations are more focusing around how do we actually tackle this volume of data and extract the insights from it in order to generate business value. It’s not done for research purposes, it’s not analysis for the sake of analysis, it’s how can we find those insights that we can turn into action, that will either make us more competitive, help us look after our customers more, manage risk etc. What we’re  approach at the very least so that we can support clients in navigating a journey in what is going to be a digital future for everyone. More and more data becoming digital, more and more processes going online, more and more volumes of data external to the organisation so from an advisory and an implementation point of view, we established the Applied Intelligence Practice to be able to manage that end-to-end data life cycle from raw data down to business outcomes within our Applied Intelligence Practice. Which obviously then gives rise to a range of capabilities from data engineering and people who are adept and specialists at managing data, data processing, data supply lines, whatever we want to call them, through to those that can then process and use that data from an analytics, visualisation or an AI perspective Machine Learning to actual deliver the business value.

So the team encompasses a range of those capabilities. I think what differentiates us is that we go for deep specialists. What I can see happening around the world is that more and industry work is being commoditised but it also applies to the data science with technologies, eg most people will be familiar with Tableau and Qlik for example, have put visualisation analysis into the hands of business users. That continues apace, the more standard data science capability is being automated and is being commoditised but growth, particularly in Machine Learning and AI, is driving greater and greater need for specialisation in those kind of areas because that’s where the next generation of real values are to be realised in those organisations.

JH: That’s a really comprehensive answer, thank you for that.

JH: That brings us on to a couple of other questions that are linked into that. One, you mentioned about clients and delivering value to clients. What sort of clients or even domains or industries do you primarily work with in KPMG Ireland, specifically within your area, your practice?

KT: So we are what you would call cross industry, cross sector and cross functional so we work with all industries including health, public service, all financial services, utilities, etc. We have a range of clients from medium sized to large multinationals as clients within our Applied Intelligence Practice. The dominant functional area that analytics works in is in risk and regulatory, things like fraud, financial crime and anti-money laundering (AML) but obviously the behemoth usually in this area is customer marketing analytics for increased sales and better customer experience etc. We’re also seeing demand for what used to be called HRM analytics, as particularly organisations look to the workforce for the future and try and forecast now what are the skills that are going to be required in the future, assuming that the trends we can see in terms of automation etc , continue. Then obviously within a Covid and a Brexit environment , supply chain insights and being able to look at supply chain and suppliers. That kind of analytics is obviously top of many organisations’ agenda.

JH: Brilliant, you’ve actually answered both questions in one there, Kieran so very efficient of you.

JH: Moving onto the technologies that you would work with and I know we could probably be here for the next twenty minutes talking about all the different technologies you work with across the various different areas of the Applied Intelligence Team whether it’s strategy or business intelligence etc. Could yo u give us an overview of the technologies and tools that you use predominantly that you may look for most when you’re recruiting people into your practice?

KT: Again, I suppose it does depend on what area of the practice we’re looking to recruit people for. Data Engineers would require a range of skills from very traditional, let’s say SQL skills because there’s still some legacy systems out there up to more advanced Big Data and cloud platform engineering skills eg. Azure Data Factory, just to call out one of the cloud providers that we are cloud provider independent. The skills around manipulating large volumes & large varieties of data is obviously very strong in the engineering space. We have specialisations in visualisation, again the range of providers from the more well-known Qlik, Tableau, PowerBI. It’s the skill and the competency that’s important thing and these are just the tools that we find most of our clients will have adopted one or the other of those.

Through to the analytics, Machine Learning and AI space, what’s very strong there is Python and all their associated libraries. There are again key skills around NLP, computer vision, to extract information from the unstructured data and as I said, almost standard skills with structured data which I think is going to be heavily commoditised. This is about building classification models, prediction models, segmentation models, etc so there is a range of tools that we use there from commercial off the shelf technologies like SAAS which are extremely strong. They’ve essentially rebuilt their platform over the last while to the open source as I mentioned, the R’s,  R Shiny etc.

JH: Okay, very good, thanks for that.

JH: The team itself, the division, the Applied Intelligence Practice, how has that grown then since it was established? I think it was established in maybe 18 months ago, in and around that?

KT: Just about, yes.

JH: So how has it grown then since inception?

KT: You can say, I was the first person in, starting with a team of two, myself and a director of mine joined at the same time to establish the practice. If you now look at the bald number in the practice, we’ve over 100 between Belfast and Dublin. As you can imagine, going from single digit numbers to 100, all through Covid, an interesting experience. It was very successful, huge growth and we’re seeing a lot of demand and      we’re not stopping there. That’s just where we are today, our growth ambitions certainly would be to double within a year’s time again.

JH: Especially impressive, I know from myself, I was recruiting right through the pandemic as well and it presented some unique challenges so to scale to 100 people within 18 months and we’re still in a pandemic as well, particularly impressive so well done there.

JH: What type of people right now do you have an urgent need for? I know you’re looking for quite a wide variety of backgrounds and profiles. But where are the key areas in which you find, right, we’re really finding it difficult to find people who are specialists in these areas? It could be NLP, it could be computer vision, it could be other areas but what are the key areas in which you’re looking to recruit?

KT: So long story short, it’s across all areas but if you were to say where do I think maybe the greatest gap exists in terms of skillsets in the market, obviously there is lots of technically very adept people. As you mentioned, we have very adept NLP practitioners, very adept Python programmers for example. One of the key aspects is more on the data analytics strategy, how to marshal all of those capabilities and bind them together to create a solution starting from just the problem definition. What’s the problem we’re trying to solve? And then we try to solve it. A lot of that skill and capability derives from years of experience so it’s a hard hump we won’t be able to get over for a number of years until the volume of people that have come out of college in the last while, get multiple years of experience, get their organs, as they say.

Being able to help clients on learning how they should proceed, giving all the capability that’s at our fingertips now from a technology perspective as well as all the changing demands within the actual client themselves or within their industries. Being able to clearly see farther than others is probably the scarcest skill but actually right now what I see is that many organisations are moving away from the functional or business unit deployment of analytics where some parts of the organisation may be really quite strong in the area. Enterprise is starting to look more across the board and try and see how to make an enterprise leap forward which will always bring them back to a data conversation.  It’s actually having a cold hard look at their data, where they have that data, what’s the quality of that data and how can they best manage and utilise that data. I think where a few years ago, maybe the peak was on more data scientists and Machine Learning skillsets, I think now to start to create that foundational data layer that can provide, I suppose, the best basis for Machine Learning and AI and  analytics capabilities, we’re seeing more of a demand on the engineering side and all the skills that go with that from cloud platforms and Big Data platforms as I said down to the more traditional SQL. That’s where I think many organisations are now, because they’re focused on that area, it’s causing a lot of demand which is obviously going to pinch on our supply.

JH: yes, absolutely.

JH: For people who specialise in data science, data scientists regardless of their vertical, people like data analysts, data engineers, BI people as well, where do you see the future for them? What do you see is the future for their careers going forward? Maybe if we just take data scientists for example? Where or how do you see their careers changing or adapting to the market and to business needs in the near future.

KT: Data Scientists come from a variety of backgrounds, Computer Science, Engineering, Maths, Statistics, Physics, you know, numerous numerate backgrounds. They sort of distinguish themselves by utilising technology and data to solve problems. If I was to have a catch all one liner for them, from my years of experience of doing this, what I’ve seen, particularly over the last decade is a huge acceleration in specialist capabilities. When I started 10 / 15 years ago doing what was known as text analytics at the time, which was early days of NLP and it didn’t have any deep learning capabilities at the time, now you look at things coming up out of AI and others, they’re saying that NLP capabilities will be indistinguishable from humans in the next year or two.

JH: Wow!

KT: The passing knowledge is, let’s say of some of these specialist areas will not suffice. It will need to get deeper and deeper to follow the specialisation for each of these areas.

JH: What do you think the future looks like for the Applied Intelligence Practice in KPMG Ireland?

KT: I think we’re going to be on a continued stratospheric growth. I think the demand is out there. We’re probably working with a small customer base at the moment because as I said, we’ve only been here for 18 months. We started small and started building engagements with our clients iteratively. What I find from talking with our clients so far, is that drive towards better use of data to become more efficient, become more effective and look after customer engagement. Various marketing terms are used like digital transformation but it’s the how to!

How do you actually enable some of these capabilities? It’s always, from my point of view, built on data and built on understanding so I see, as we start to roll out clients’ successes in the market by taking this more specialist approach that we’re essentially going to build a strong reputation and be able to show that we are standing at the forefront of what’s possible with our capability. We’re opening up a new innovation centre called Platform X in the next month and a half which is going to be an environment where we can really start to work more closely with clients to really tease through their problems, their issues and work with them on solutions and then go execute. Absolutely continued growth, continued focus on business value, the technology, emerging technologies and how we can be utilised and deployed to deliver that value.

JH: Brilliant stuff. Well, I think unless you’ve got anything else to add, Kieran, we’ll leave it there. I really appreciate your time and I’m sure we’ll be chatting again there soon.

KT: Super, thanks

JH: Take care!

John Howe, Manager of Data Science in Brightwater was in conversation with Kieran Towey, Head of Applied Intelligence with KPMG Ireland. If you’re interested in a career in data science and analytics or are looking to add to your data science team, please contact John on + 353 1 592 7868 or via email on [email protected]