Embedding a self-service data culture in an organisation with Kingfisher’s Steve Taberner

Nicky Rudd:

Hello, and welcome to Fibonacci, the Red Olive data podcast, where we hear from leading specialists and get their take on the industry. I'm your host, Nicky Rudd. Today, I'm joined by Steve Taberner, Head of Data Platforms at Kingfisher plc. Steve is a business intelligence and analytics leader with a track record of delivering innovation, modernization and transformation through technology, business process, and organisational change in large organisations, including Travis Perkins, Elsevier, and Vodafone.

Nicky Rudd:

Our conversation covers how the pandemic has changed people's view of data and analytics, self-service reporting, and the importance of getting the culture right in an organisation for this to really work and at scale. What are we waiting for? Let's go. So, Steve, can you tell me about your entry into the world of data? How did you get involved?

Steve Taberner:

All right. So my career has been dotted with information or data, so to speak. And I think my first entry was when it was at Vodafone and I took over a data information department there. And then subsequently through my career, I've worked with data and BI a number of times, but I think it was probably five or six years ago where I thought actually data is looking even more attractive than it was when I previously worked at it. And I made a conscious career move to actually take on a team at Travis Perkins and build a data capability within that organisation, virtually from scratch. I was virtually the first through the door. And I've never looked back since.

Steve Taberner:

I really do think it is one of the most interesting areas to work in an organisation. I often describe it as it's like watching the blood flowing through an organisation as processes change and alter and redirect data all over your organisation. And I'm extremely passionate about the fact that I believe a modern organisation has to consider data as an asset and to that end invest heavily in making sure that it's a core part of the capability organisation.

Nicky Rudd:

Do you think that's become an easier sell?

Steve Taberner:

Funny enough, actually the pandemic has had quite a positive influence there, I think. What saw during the pandemic, so I kind was working between two organisations during that time, was that actually there were no easy decisions to be made. There was no gut feel you could use because everything was different. The way the market was reacting, the way products were being shipped, distributed, whatever, all of these things were different during the pandemic. And so the rule book was kind of thrown out the window. Actually lots of organisations suddenly realised that the only way they could really get a handle on what their organisation and what their business and what their market was doing was through the utilisation of data.

Steve Taberner:

And that has continued, I think, post-pandemic in terms of actually this new insight that they have is now absolutely critical to the way they're working. Interestingly, also I think organisations that may be previously been quite traditional like DIY market and merchandising is changed because at the start of pandemic, a very small fraction of our sales were going through the web or through a digital channel. And that has massively changed during the pandemic and has continued that way. Buying behaviours have changed for the good and permanently.

Nicky Rudd:

I think retail's really interesting space anyway, because in the last three of four decades has dramatically changed. How would you say you work with this within that B2B space and the B2C space and how you come across looking at data and identifying personas and how that data would flow to them. Is that kind of a big part of your role?

Steve Taberner:

I think it's an inevitable part of our role when you're owning data and business intelligence analytics is because you really need to understand the types of individuals, both within your organisation and then also outside your organisation who might be accessing the data that you are producing. And then working out from those personas, how much do you need to serve that data up so they need to do very little or how much do you actually need to give them a lot of leeway to be able to do their own manipulation, their own analytics and finding their own discoveries within that data. So personas are really important and certainly when I was at Travis Perkins, we tried to identify about five or six key personas across the organisation and use that to help drive the strategy as to the tools and capabilities we need within the organisation, but also the level of transformation that we might need on certain data to satisfy the needs of those personas we'd already identified.

Steve Taberner:

So very important. And then outside the organisation as well I think there's a huge opportunity to monetize data within the retail space. And there are many organisations already doing this very successfully. Boots for one are particularly strong at being able to utilise their loyalty card data to actually support their supply chain in terms of how they sell products, what the customers are buying, when they're buying them, how they're buying all this sort of information, which is gold dust to manufacturers trying to work out how to sell their products through a retail chain. So, yeah, I think personas is a really good thing to focus on quite early and understand the market that you are actually pitching your data into. So yes, we found that was a very productive way of trying to understand how we set ourselves up for success as a delivery of data services to our organisation.

Nicky Rudd:

I think when you're looking at data in kind of a consumer buyer, if you like. That whole idea within retail of it being omnichannel and having the different data points and where they give information about themselves, about what they want out of a retail experience, it has been kind of changing a lot anyway, within the B2B space. Has that massively changed or has that kind of distilled much more traditional patterns if you like?

Steve Taberner:

The challenge with the B2B space is, and I've certainly seen this in the kind of DIY and loading trade is that you have a real spectrum of B2B customers, some who are incredibly sophisticated, who probably don't need you to tell them what they've sold, because they'll know it. But then there's also others in that marketplace who actually are starved of data because they don't have their own internal systems to support their data analytics. So, we were certainly being able to provide out data to our supply chain, for instance, and also looking at the same time to start providing data out to big customers.

Steve Taberner:

And a consumer pretty much knows what they're spending and they know where to spend it because they physically did themselves, but a large organisation has a real need to understand what it's buying. And so it's a big housing organisation or a large builder being able to see where they're spending their money across. You know one of the large organisations they're dealing with is really important, so they can optimise what they're doing, how they're investing and how they're making use of their supply chain to get the right products to deliver their housing needs.

Nicky Rudd:

Yeah. I was going to say with current supply chain issues, if you've done that work up front, you must be absolutely we're not seeing from the rooftops at the moment. So I'm sure it's incredibly challenging, but at least you'd know where your issues are going to come up and bite you really.

Steve Taberner:

se sort of things, [inaudible: 00:08:13

Nicky Rudd:

I mean, I think within this DIY space at the moment, that's probably one of the longest running issues just because the pandemic obviously had such an impact on people staying at home and doing, as you said, like DIY on their own homes, but also then actually where you get stuff from and actually getting it into the country.

Steve Taberner:

Absolutely. Yes. So the building supplies have done really well, particularly in the DIY space for that very reason. There's been a lot of people with some time to actually do DIY that previously maybe haven't and as a result the market has seen some really good sales numbers. But that's kind of masked the fact that actually we've also struggled getting products because demand is outstripped supply and the pandemic has impacted the manufacturer of goods across the world. So yeah, it's a really challenging conundrum to actually be able to balance the supply chain with satisfying your customers.

Nicky Rudd:

How upfront are those big DIY customers do you think looking analytic as a way of sort of shaping future business decisions?

Steve Taberner:

I'd like to think they're seeing it as critical because there's two things. There's obviously understanding your customers and understanding your customers needs. And that's absolutely the bedrock of most sort of analytical capabilities that you'd build as you sort of focus on your customer first, but I think the other massive opportunity is in and around the supply chain. You know with a lot of products coming in many cases by container ships, you have to be forecasting essentially months in advance as to what you think you're going to need to put on your shelves. And that's incredibly difficult and if you don't have the analytics to be able to help you understand seasonal differences and impacts of weather conditions or economic situations like that, you can get it incredibly wrong and have either massively overstocked or massively under-stocked.

Steve Taberner:

So analytics pays a huge part I think in being able to look back in the past, understand trends and the way stock and product have moved in your supply chain in the past, but also try to predict what you think it's going to be in the future. And I think that's kind of the holy grail, isn't it? Being able to really understand what you need on your shelf, any one moment in time and making sure the supply chain can deliver that item to that shelf.

Nicky Rudd:

Do you think it is something that's going to happen sooner rather later, where you have AI and that sort of data science, that predictive element that is just the norm for this industry?

Steve Taberner:

Well, historically the sort of building supplies has not been like the forefront. It's not the telecoms or software industry type sector, so it has tended to follow other in the past. But I think the culture is starting to change and just the sheer volume and complexity of decisions we're making are started to become almost impossible for humans to make. You need that support from an element of automated analytics and data science. But one of the challenge is going to be, people are actually getting the trust in some of those models and being able to let go of the reins and allow a computer system to make financial commitments on behalf of your company, to buying stock or making investments in one way or another. So there's a definite need there, but I think there will also be some cultural challenges to doing that.

Steve Taberner:

My experience is that most people are slightly suspicious of a black box that tells them an answer, even though you could probably explain it many times over to them, it's very difficult to allow that machine to make their decisions on your behalf, even though you can probably prove that they are infinitely more reliable than the human brain in making some of those decisions.

Nicky Rudd:

Well, let's talk a little bit about sort of culture changes. You've mentioned that there's been quite a lot of a transformation in the way that's particularly in the industry that you've worked in has been sort of changed with the pandemic. And I know that one of the things that you are very interested is self-service culture from a reporting point of view. How would you go about creating a self-service culture within this data space?

Steve Taberner:

Any sort of culture change is invariably very difficult to influence, but you know, one of the things I feel quite passionate about is that there's historically been a bit of a disconnect between the people doing the analytics with actually the people having to make the decisions. And I think what self-service to me about is kind of bringing those two worlds together so that you can enable business stakeholders who are making decisions day in, day out to be able to get that information for themselves in a really fast way. Because a lot of these decisions have for a shelf life and so therefore you need to make those decisions quickly. How do you approach it? Well, you do need a data platform to start off with, and there's no doubt about you need the capability. But I think generally my approach has been to kind of do a sort bit of a top down and a bottom up.

Steve Taberner:

I think there's invariably a lot of appetite lower down in the organisation to get better ways of finding information and spend less time moving data between spreadsheets and more time actually trying to analyse data and make some really good insights out of it. And then from the top of the organisation, you've obviously got the investment in the technology and the capability to do it, but also the investment in the people to allow them to evolve and become more data literate because it's not a given. And it's something that organisations I think have to proactively try and manage to raise the level of data literacy across the organisation, either through the way they recruit or the way they train so that people across the organisations feel more confident making decisions based on data that they may have self-sourced themselves within a data platform.

Nicky Rudd:

In the organisations that you've sort of worked in where you've put this in place, what are the biggest challenges that you've come up against?

Steve Taberner:

Oh, biggest challenges. Some of it is just about we've always done it this way and therefore why would we change? But I think the pandemic has hopefully taught a lot of us actually, you can't assume that what you did yesterday is now going to work tomorrow.

Nicky Rudd:

You mentioned about people then sort of taking responsibility. Do you think there's an issue with people thinking that's not part of their job, that they don't want to be held responsible for any of those sort of big decisions? So there's some people that lean into it, it is a very easy thing for them to do. For a lot of others they quite like having a support network. And I just wonder whether that kind of moving into a self-service reporting point of view, whether that was one of the biggest challenges?

Steve Taberner:

Not necessarily, because I think there's some challenges around the way people view analytics in terms of historically it's been a report or a spreadsheet. And I think there is a big challenge in being able to move people beyond that in terms of actually there's a whole spectrum of analytical type capabilities that could unlock all sorts benefits within the organisation. So certainly things I've seen in my career is kind of breaking that allegiance or passion to have a particular type of report and a particular type of format on their desk at a particular type of time.

Steve Taberner:

And actually start to get them to think in a different way about, well, actually, maybe we should just be looking at the exceptions here rather than just looking at report and allow you to find the exceptions. Can we not actually find those for you automatically and surface them so you can then use them to make an instant decision rather than having to do all the analytics first. So I think the temptation when you build a new data platform is that some people just see it as a way of supercharging what you do today. When actually what I would like to see is a complete change in the way you utilise data within your organisation to make those decisions faster and in some case automatically, rather than just relying on sort of fairly more traditional mechanisms for understanding and analysing data.

Nicky Rudd:

For some people they're quite happy to look at Excel Spreadsheets, but for others they need it to be visualised in a much more accessible way. So that could have importance in the growth in the market of kind of dash boarding and visualisation tools. I didn't know what your thoughts on that were. Do you think that's something that's extremely important to encourage that self-service reporting culture?

Steve Taberner:

I think if you don't, you sort of strangle the organisation because you then put sort of reporting and analytics into a small group of people centrally rather than having it distributed. And I'm a great believer that there's lots of intelligence and talent all around your organisation and by giving them the data associated with their role, you can unleash all sorts of great things and just make better, faster decisions and free people up as well, to do more analytics, to do more insight, to question what the data's saying, why are we getting a reduced sales in this region? What if we look at other regions, can that tell us something? And actually use that time rather than just moving data around, actually to understand and get great insight into the data that flows in and around them while they're actually working.

Nicky Rudd:

And I think there's probably some key things that need to be put in place apart from the actual buy-in from everybody. If you have a well-defined sort of data directory or diction, if you like of your terms, I suppose that's one of the key things. So even before you decided to go down that route, I'm thinking there's probably a piece of work that you've got those key stakeholders in to sort of define what you want to see at the outset. Is that something that you've had experience with?

Steve Taberner:

So understanding your data across the organisation, a data platform type project is a great way to actually try and capture that tribal knowledge I'll call it, or it's sometimes called where there is a lot of information across lots of individuals across the organisation about that data. And what historically happens is you have to find that person before you can then really understand the data that you're looking at. So as part I think, of any successful data platform programme or project, you need to be able to capture that tribal knowledge as you go so that when you want people to self-serve they can not only go and get access to the data, but they can understand what that data's all about and not have to go and find those individuals across the organisation. You've captured it for the benefit of all users across your organisation.

Steve Taberner:

So that whole cataloguing process is I think, a vital part of any project and programme, but I think to be successful you need to get everyone involved in it. It shouldn't be just a centrally done thing. It's quite important that the self-service users when they find data and I know what that data's about is they have the opportunity to then input into that collective knowledge gathering. And it's a kind of living ecosystem rather than just something you do once. Bit painting the Humber Bridge, really.

Nicky Rudd:

Yeah. Do you think that now there is a more of an appetite for that? Do you think sort of central BI teams are realising that actually they can spend their time being much more effective if they have that self-service reporting culture in place? And also with that, if companies deciding to go the route, how long would that sort of shift from it being done the old way to a kind of self-service model work do you think?

Steve Taberner:

I don't know. I think if you can get top down buy-in and bottom up awareness, it can happen quite quickly because if people are demanding to understand what the data is telling them before they make decisions, but you've got to have people in the organisation demanding that and asking the difficult questions, which then need to be analysed or understood. But certainly I've seen it where if a particular business unit really gets behind it, they can change that quite quickly because actually a sort centralised data platform, one of the benefits it has is being able to provide you to a certain extent, a single version of the truth and what my experience was that actually business units stopped arguing about whose data was correct, and actually started arguing about what the data was showing them because they no longer had to do all the reconciliation to work out whose report was correct. That's massively powerful because you are all singing from a single point and actually it's derived from a single platform. And that has an immense power. And again, supports that kind of self-service environment.

Nicky Rudd:

I think you were just saying there about, you know, having a department for example, that it works really well, but how would you create an environment so that, that self-service reporting works at scale and that if it's working in one bit, it can be sort of then broadened out so that the whole business can look at it. Do you think that's something that just happened organically or do you think, again, it's better to have kind of a data leader if you like, or a data driver pushing through and showing and explaining so that it's got real momentum?

Steve Taberner:

I think, and you talked earlier about the sort of centralised sort BI and data teams, you know, how they react when something happens in terms of self-service. I think their role to changes and I think that the role of that group then becomes more about supporting that sort of community of practise and actually being able to help grow that community of practise by setting up the right forums or the right training, but actually helping to foster the proliferation of different data products that you might see in one area of the organisation across multiple areas of the organisation. So I think that centralised role is still very important to help galvanise a kind of community which then actually learns and shares together without being restricted by having to just one central body actually doing it, so you sort of really do start to get different departments sharing what they've done, and actually others learning from the things that others have done within the organisation, which is incredibly powerful.

Nicky Rudd:

In your experience, have you come across where you go into an organisation and they've started a project and it's kind of a, oh, my God, we're going to have to kind of do several steps backwards to kind of get things in, or is it one of those things with the self-servicing and that's starting with the initial data project that you can just basically pick up whatever state that organisation might be in to move it forward?

Steve Taberner:

That's a very difficult one. You know, a data platform type project within organisation has the opportunity to be massively revolutionary within that organisation. And usually my experience is the appetite for data and getting access to data is so great that actually you are pushing to a certain extent on an open door because most people are data-starved and intelligence and analytics-starved. So being able to offer them a capability where you open that access is massive, but you also have to bear in mind that there are other things you need to do to underpin that like being able to provide the right sort of training, the right sort of cultural development in terms of things like being confident with utilisation of data and things like that. So there are lots of other areas you have to focus on as well, but my experiences that most organisers you go into and doing this type of thing, there is a genuine appetite to get on board. You've just got to help shepherd that appetite into right way so that actually you drive the culture in the correct way as well.

Nicky Rudd:

Obviously there's been great changes, as you mentioned with the pandemic sort of pushing things and and everybody's got this kind of thirst for wanting to know more about how a business is or how their organisation is running. What do you think will be the challenges in the next sort of 18 months and what are you most excited about with the data sphere of the future?

Steve Taberner:

What are the changes? That's a very good question. I mean, I think this has probably hit a number of different industry sectors, it's the kind of digitization that we're seeing is going to massively increase the amount of data that's available to an organisation, but actually the challenge is going to be around as you know, how do you find the wood from the trees, because there's just going to be so much. So it's going to be about how you are not en mass you start to utilise this data to drive the right decision making in your organisation and the right sort of analytics. And recognising and being able to harvest the data that's going to be useful to you from a very large pool of data that you might have access to.

Steve Taberner:

I'm sort of really excited about the opportunity of kind of the more automated analytics and being able to close that gap between the insight and the action, which at the moment has often quite a protracted journey between the two of them as people want to get involved and influence decisions. So the opportunity to take a lot of some of the more simple decisions out of the equation. So actually again, we can focus on some of the more thorny ones. So I'm really excited about what that could do in terms of how it will influence jobs and processes across organisations. I think that's going to be a really exciting journey to go on as we evolve through that sort of data maturity.

Steve Taberner:

I think data science still feels in many organisations like it's quite fledgling and quite young. And so I think there's massive opportunity for that to grow as well. But all of those will need is a really strong data platform on the centre. So I don't think it's something you can skip. I think it's really important to have that, but it's what can go on top of it with some of the capabilities that are out there already, will be really exciting.

Nicky Rudd:

So if somebody's coming into the industry now we've talked about a lot of the sort of exciting changes in culture. There's lots of different tools. There's lots of different platforms, there's technology, there's lots of different areas to get into data. What skills would you recommend somebody sort of has, or what kind of experience do you think they could volunteer to kind of get their foot in the door?

Steve Taberner:

I mean, there's kind of obvious things like data literacy and being confident around the utilisation of data and interpreting data and things like that. That's almost a sort of baseline that you need to be in. The technologies now in some ways are getting easier because they're getting more sort user-friendly and more business-friendly. So kind of the need to be a high end sort of technologist or coder I mean, there'll always be those roles, but they're probably less important in terms of getting the value out of the data. Some of it's like personal attributes, it's kind of like being inquisitive, wanting to ask questions, difficult questions, thinking out the box, being able to look at things from a different perspective. They're probably kind of the things that very difficult to recruit to, but are really, really important in terms of the sort of data individuals that we need. Because as we push the boundaries, it's going to become much more about what you can find and where you might push data and push the boundaries. And it's probably those type of individuals I'd be really keen to get involved with in my journey going forward.

Nicky Rudd:

Some really interesting insights from Steve there, join us for the next episode of Fibonacci, the Red Olive data podcast, where we'll be joined by another expert, sharing their thoughts on latest trends in AI and big data along with some great hints and tips. Make sure you subscribe to Fibonacci, the Red Olive data podcast from wherever you get your podcast to make sure you don't miss it. That's all for today. Thanks for listening. I've been your host, Nicky Rudd. See you next time.

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