The Power of Data Podcast
Episode 13: The Increasing Possibilities of Data
Guest:Simon Walker, Managing Partner, Kubrick Group
Interviewer: Louise Cavanagh, Communications Director - Dun & Bradstreet
Louise Cavanagh 00:00
Welcome to the power of data podcast. We're recording live today at the Women in Data conference in London. I'm joined by Simon Walker, who's Managing Partner of data consultancy firm Kubrick, who are partnering with Women in Data today. Thanks for joining us today, Simon.
Simon Walker 00:14
Thank you very much for having me.
Louise Cavanagh 00:15
I wonder if we get started with you explaining a little bit more about how your consultancy works. And how the model works. It's a really interesting approach to skills in the data industry.
Simon Walker 00:24
Yeah, we're a data consultancy with, as you said, somewhat of a unique model. Often we describe that we bridge the gap between academia and business. So, we create our own data workforce. We specialize in two areas soon to be a third. Data engineering, data governance, and then soon to be data transformation. What we do is we hire what we call Junior professionals, the commonality with a lot of these people is they've not only got very strong logical skills, good maths base and normally from academia, but also they're compelling communicators. And we then bring them into our data labs and we train them in the very various data technologies and skills that they'll need to be able to hit the ground running on the client site. And one of the big differences with us is that after two years of some being with Kubrick, we actually allow our clients to take on our staff if they want into their permanent workforce, and about 75% of our staff transfer on to client sites permanently.
Louise Cavanagh 01:20
It's a really unique model. It's interesting and a great way to look at it actually, a great way to do things. So you talked about data governance there. Is that something with of the onset of GDPR and the increasing regulation in the industry that you're seeing more need for skilled and that sort of area in the data stewardship side of things?
Simon Walker 01:37
Yeah, that's definitely been one driver, I'd say. I kind of take it back a few steps. When we first set Kubrick up one of the things that we noticed was basically it felt like nearly everyone said, don't do data engineering, do data science. And luckily, we didn't take that step or the advice that we were given at the time. And basically, what we found was a lot of people were saying hire data scientists and their Data wasn't in the right order or structure environment to provide analysis. So then you saw the rise of data engineers, which was great for Kubrick, because that's what we were planning on. And what we've come to see in the last, I would say, 18 months in particular, not only do you have some regulatory drivers driving the need for data governance, but also actually what's happening is we've got large data engineering teams and data science teams producing data products. But often, the old adage of garbage in garbage out is really coming home to roost. It's actually you're starting to see businesses that may have invested significant sums of money in their data projects. But actually, the data quality or the actual governance of that data hasn't been set out in the beginning. So that's why we actually launched our data governance practice for that. There's definitely a maturing of the industry that's been driving that.
Louise Cavanagh 02:51
And in terms of the people that you attract, and bring in to your schemes, how do you attract underrepresented groups? Today's all about gender and women, but I think it's a wider than that in diversity and in a wider sense. And what do you think businesses can do to sort of attract more people into data careers?
Simon Walker 03:09
I'm an eternal optimist on this, not just for purely moral and ethical reasons do you have to have a balanced team, but it's great with data, because actually, it's commercially the right thing to do. You have a homogenous data team, they will have an inherent bias, you know, whether you like it or not, so you've got to have diversity. It's great that there's such an obvious driver that you actually need a diverse team to have better value from your results. There's a number of things you can do, I think, fundamentally, firstly, it has to be bought into from the top. So I'm fortunate enough that myself and my business partner, we believe very strongly in this and as I said, it's not just for altruistic reasons, it's commercially the right thing to do. So it has to have that senior level buy in, I think, then that allows you to invest and focus on the right areas. So actually being able to have an employer brand that attracts other people that could sometimes might not have the confidence to apply to you, I know that, you know, if there's a great big shining skyscraper in the city, some people might not feel confident to apply to that business because they wouldn't see themselves there. So I think it's also looking at how does your employer brand represent the type of people that you want on board? And also, what does it do maybe also to scare some people away? I think the optimistic part I said earlier is, we've got fantastic technology around us that we're able to do some really, really clever things to identify people that may have fallen in the gaps. So one of the projects we're undertaking at the moment is looking at contextualizing someone's academic performance. So for example, if you would have someone that went through a really good schooling system, went to university and they got certain grades, that's brilliant, but let's say someone went to school that was in quite an impoverished area. The Ofsted rating wasn't great, that then allowed them to go to a certain University. On paper, that person might look like they've got low results, but actually, contextually, they could have actually performed better. So we were in this fantastic moment, where we were able to get this technology, this data analytics is that able to open up people that we may have, we may have missed out on and it is definitely a tool that I'm really encouraged about. And it's beginning to be used by some of our clients now.
Louise Cavanagh 05:26
I love the idea of using data to recruit into data is brilliant. Sort of related to that topic of technology. So we're seeing that in the data space, a real move towards more automation, the use of machine learning AI, various different techniques. What's your experience of when you're dealing with your clients and the people that you're training in terms of, is it a different skill set that's now required? I mean, people may say, you know, the robots are taking over, we’re not going to need people anymore. How much is that is the human element of this data skill set still as relevant as ever?
Simon Walker 05:59
I'm probably fairly biased in this answer, but put it like this: one of the areas when we get feedback from our clients, they always give us outstanding feedback on the technical skills about consultants. The one thing that they always want us to invest in more is their softer skills, the human side, because data projects and being able to understand what data can do is nothing without that human element to it. And I suppose the second part of your question, I, I totally understand the automation element of it. But I don't know where we are in that in that kind of curve. So at the moment, you need more people to be able to do the automating. There's just this constant change in innovation, which then requires new skills. So as I said before, I'm quite an optimist on this. I think it's actually creating more jobs. It's just different.
Louise Cavanagh 06:50
Yeah. And there is research out there. I've read some stuff and we've gone out with survey results that show that actually more jobs are being created with the emergence of AI and things because it is such an unknown. Yeah, I know, we haven't got much time with you because you're out busy on the floor at the conference talking to people. But I just wanted to ask, you know, what, in your view, having been part of the industry for several years now, what's the thing that most excites you about the evolution of sort of data science? And I was quite interested when you mentioned earlier about transformation, the data transformation element.
Simon Walker 07:20
Yeah, so data transformation, I've heard it been called a number of things by clients. I think, one large Life Sciences company that we deal with calls it data translators, maybe a somewhat more traditional data business analyst, but really what I see data transformation as is someone that's actually able to drive real change in an organization to be able to get the real value out of a data project. So my earlier example of you had all these data scientists trying to produce things but the data wasn't in the right structural condition to be able to analyze data engineers came along, did that for them, but the data quality wasn't there hadn't been governed correctly. So then the rise of data governance now, where we're at the maturity of data projects is a number of clients and millions of millions on these, and they need to be able to land them and deliver them. And actually a data transformation is about someone understanding, change management, project delivery, product management, but also having the data skills to be able to do that translation element of what are one of our clients calls it and being able to deliver these large scale projects. And I think actually, what I'm most excited about going forward is data literacy increasing. So I think as we see more and more people throughout the workplace, understand what data is and become more data literate, I think the possibilities of what data can do will only increase. So I think it's, it's about being able to equip your workforce with the skills that they need, that will actually understand what data can do for them, and equally what it can't. So I'm pretty sure that people might think it can do some amazing things and it might not be quite there yet. It’s when we have we have the UK as a more data literate nation. I think it's, it's going to be it's going to be quite interesting what we're able to do with data.
Louise Cavanagh 09:07
Yeah. I love that the possibility of what data could do for us. The mind boggles. Yeah. And that's, I think that's a great point to leave on. I just wanted to thank you again for your time.
Simon Walker 09:17
Yeah, thanks very much.
Louise Cavanagh 09:18
Really interesting. And we'll see you next time on the Power of Data podcast.