Retail moves fast. Can your data keep up?

Retailers are under pressure to deliver better customer experiences, make smarter commercial decisions and keep up with changing technology. But behind every online order, product listing and stock update is data that needs to be accurate, accessible and reliable!

And with AI creating new opportunities, getting the foundations right has never been more important.

In this episode of the Data in 10 Podcast, host Andi Jarvis is joined by James Wheeler (Former CIO of Le Creuset and CTO of Permasteelisa Group), alongside Binary10's CEO James Blake and Chief Operating Officer Steve Smales, to discuss the biggest data challenges facing the retail sector.

They talk about the importance of accurate product and inventory data, why legacy systems can make it difficult to access the information businesses need, and how retailers can prepare their data for AI. The conversation also looks at data quality, governance and why data ownership needs to be a business priority, not just an IT responsibility.

In this episode, we cover:

00:00 – Introduction: Setting the scene for the data challenges facing the retail sector.

01:28 – The data retailers rely on: Why consumer data, product information and inventory data need to be accurate, consistent and up to date.

03:11 – Customer experience and data accuracy: How incorrect stock information can frustrate customers and affect the shopping experience.

04:27 – The biggest data challenges in retail: Balancing customer expectations, commercial priorities and the limitations of legacy systems.

07:02 – Getting retail ready for AI: Why clean, accessible and secure data is essential, alongside clear use cases and measurable business benefits.

08:51 – Data quality issues in retail: The challenges of standardising product information, managing large volumes of data and ensuring AI doesn't amplify existing problems.

09:53 – Data governance and ownership: Why governance needs board-level attention and data ownership must be embedded across the business.

Why data quality is important for the customer experience?

Imagine ordering a product online because the website says it's in stock, only to discover that it isn't available when you try to complete your purchase. It's a frustrating experience and a simple example of how poor data quality can affect customer trust.

Accurate inventory data and consistent product information help retailers provide reliable stock visibility across their digital and physical channels. When that information isn't right, the impact can extend beyond an individual transaction to customer satisfaction, operational efficiency and commercial performance.

Is your retail data ready for AI?

AI is creating exciting opportunities for retailers, from improving digital experiences to using data in new ways. But adopting AI without the right foundations can create more problems than it solves!

As James Wheeler explains in the episode, businesses need to think about three important foundations:

• Clean data: Information needs to be accurate, consistent and fit for purpose.

• Data accessibility: Systems need to make the right information available when and where it's needed, supported by appropriate integrations and APIs.

• Security: Data must be protected and accessed appropriately.

Retailers also need to identify the right AI use cases and understand the benefits they want to achieve before committing significant time, money and resources. Because AI can create value, but it can't replace the work needed to get your data right.

Listen to the episode!

Listen to Episode 7 of the Data in 10 Podcast to hear James Wheeler, James Blake and Steve Smales discuss the realities of retail data and what organisations can do to get their foundations right.

Need support with your retail data challenges?

Whether you're preparing for a data migration, improving data quality, connecting systems or getting your organisation ready for AI, Binary10 can help.

We're the data people, and we help organisations make data-driven decisions they can trust.

💌 Get in touch with our team.

Questions we explore in this episode.

• What are the biggest data challenges facing the retail sector today?

• How does inaccurate stock data affect customer experience and trust?

• How can retailers balance competing business priorities when investing in data?

• What needs to be in place before retailers can get real value from AI?

• Why can AI amplify existing data quality issues?

• How can retailers create consistent product data across decentralised systems?

• Why does data governance need to be a board-level conversation?

• Who should really own data in a retail organisation?

EPISODE TRANSCRIPTION:

Disclaimer: This transcript was generated by an AI tool that did its best, but it's never met different British accents it could fully decode. Expect a few funny mistakes. Enjoy!

[00:00] - Andi J

Hello, and welcome to the "Data in 10" podcast. My name is Andi Jarvis. I'm the marketing guy here at Binary10. Today, I am joined by James Blake, CEO, Steve Smales, Chief Operating

Officer, and our special guest, James Wheeler, a retail CIO.

[00:14] - James B

Woo-hoo.

[00:15] - Andi J

Welcome to Guildford, gentlemen.

[00:16] - James B

Yeah.

[00:17] - Steve S

Thank you.

[00:18] - Andi J

Before we drag James into the conversation, where are we? Well, we said we're in Guildford, but look at this room, Jamie.

[00:23] - James B

We're in Hogwarts.

[00:24] - Steve S

Yeah, it's the Hogwarts library.

[00:26] - James B

Yeah. I'm sort of a fan of "Harry Potter," and now I'm in and around it. No, it's fantastic, isn't it, to be somewhere a little bit different? I wonder if it'll get the juices flowing in a different way maybe, and we can talk some sense today.

[00:36] - Andi J

And this is an old-fashioned data warehouse, effectively, isn't it?

[00:40] - Steve S

Well, effectively, yes, absolutely. Every single book is just packed full of data, isn't it? So, yeah.

[00:44] - Andi J

They are all ones and zeros to me. But we are here today to talk about the challenges of data in retail.

[00:52] - Andi J

Both close to your hearts. You both sort of came from a retail background, didn't you?

[00:56] - James B

Yeah. It's actually where Binary Ten started, in effect. We had a very large digital transformation program with an excellent retailer, and also where we got to meet this lovely gentleman that's with us today, that knows more about retail way more than we do, and can really sort of lift the lid a little bit on the data challenges that we face in retail.

[01:14] - Steve S

Yeah. And James, we've known each other a long time.

[01:17] - James B

We have.

[01:17] - Steve S

We've worked together for donkey's years and on several data migrations as well.

[01:22] - James B

You've probably aged as well. [all laughing]

[01:24] - Steve S

So, obviously, you've got a whole career in IT and retail. What are the specific data objects, data entities you come across in retail that's specific to that sector?

[01:36] - James W

Yeah, sure. So retail, all industries are data hungry. Retail certainly is, and particularly over the last 10 years, it has really accelerated, particularly now that consumer data is so important and with the evolution of digital platforms and where consumer behavior is now so important to a retailer.

And so I think the consumer data is crucial, and understanding buying patterns and frequency of visits is crucial. And I think also in retail, I think actually products and inventory data is now

really key

[02:13] - Steve S

Yeah

[02:13] - James W

Product attribution now, I think, is really important and making sure you've got really rich product data, particularly when you want to share it with your business partners now. So the Amazons and the other B2B partners out there are so data hungry because they want to be sharing your data on their online platforms. So making sure that data is clean and delivered on time to them is crucial. And I think, particularly for retail now, customer convenience is so important. And so where we've seen the Amazon model, but even retailers such as Argos now, right, where making sure that stock is in the right place at the right time is really, really important. So, having an up-to-date view of where your inventory is and how much you have in stock is really important. And I think, so over the last few years, the need for retail data is now so much more, but I think having it delivered and having a live view of data now is absolutely crucial.

[03:11] - Steve S

Yeah. I'd say that's spot on, particularly the accuracy of the stock and where it is, because as a consumer, there's nothing worse than looking online to see if something is in stock, going to the store, and then you can't find it because it's not actually there, even though it still says it is.

[03:25] - James W

Absolutely. And there's big sales numbers against this as well, but obviously customer satisfaction and delivering on expectations is really key. So, if you've got stock in stores, you

need to make sure it is absolutely there.

[03:38] - James B

See, I had a negative experience exactly to what you're talking about. I went to buy a wardrobe on IKEA. It was last week. Found the wardrobe. It was on sale as well, bargain. In stock for

delivery, fantastic. Added it to the basket, went to checkout, but when I was checking out, it said, "No, this isn't available. There's no stock. You can't have it delivered." And the

disappointment, that natural kind of, "What?" And I actually checked, went back, back andforth, and yet, on one page, it's in stock, and yes, you can order it, and you get to the basket,

it's not. So, absolutely proves your point about... And it always sort of, not scared me, but it just sort of astounded me, really, in retail, how data is changing. Data changes all the time in many

industries, but you really get to see it in retail, especially online. Those products, they're changing all the time. They're having sales. It's some effort, isn't it, to keep that accurate and

to keep that up to date?

[04:27] - James W

It is.

[04:27] - Andi J

And from a retail perspective, so you've outlined the challenges you've got from all different parts of the business, all wanting more and more data. And I'm sure there's a huge technical

challenge there, but in retail, maybe more than other sectors, keeping the customer right at the heart of that, the people who are going to buy the product. How do you do that practically when you're a CIO in an organization who probably doesn't meet many customers very often?

[04:51] - James W

No, and it's always an important discussion you have at the board table as well, because the objectives are to really focus on customer experience and satisfaction, but also to make sure,

effectively, it's profitable for your business and makes commercial sense to do that as well. And particularly in retail, where there are still quite a lot of archaic legacy systems, particularly for your legacy retailers as well, data accessibility and really getting hold of that data and making sure it's in the right place are clearly and very important. So it's actually a bit of a trade-off, right? You really have to go back to, well, what is it we're trying to achieve? Does it make commercial sense? And therefore, is it worth the investment of making sure that you've got the right APIs and that you've got the right integration services to be able to get to that data to deliver it in the right way?

[05:28] - Stevs S

Okay. So what would you say, James, are the biggest challenges that you're facing in retail sector for data at the moment?

[5:45] - James W

[lip smack] I think the demand from the business is significant.

We talked about the commercial expectations of the data, and when you think about digital platforms now and the data that is becoming available to you and the levels you can get to- ...

is really interesting, and people get very excited by that and see the commercial opportunity by that as well. But I think that it's not just the commercial demands. You take a subject like

sustainability, for example. It's so important at the moment, and again, that needs so much data, whether it's coming from your supply chain, whether it's coming from the materials you're

using in your products, and therefore you're having to use that now for reporting purposes and regulatory purposes as well. So, I think the biggest challenge as a CIO is trying to manage the

pipeline of work that's coming through from everyone and the demand that's coming through, because you absolutely get the importance of it.

And it's just about really, I think, being able to manage the expectations and really being clear on what are the right priorities to go after.

[06:45] - Steve S

Yeah, so juggling priorities then.

[06:46] - James W

It is, and I think that the technical challenges are still there. As I say, particularly for retailers that have been here for a long time, the very traditional high street retailers that have had to

make the move to be a digital retailer. That's not an easy journey to make.

[07:02] - James B

And so, yeah. And if we think about, naturally we're going to talk about AI. It's front and foremost at the minute everywhere. So, is AI something, as a CIO, is that something that sort of

is a bit daunting in terms of how do we get some control on this? Or are you definitely embracing it? Are you kind of looking at it and saying, "Oh, I'm so glad this is coming along.

This is going to help us out massively"?

[07:23] - James W

Yeah, look, personally, I'm really excited about it. It is a game changer. I see already the opportunities that it brings.

I'm quite patient about it. [clears throat] Excuse me. I think

there is quite a bit of foundational work you have to do to get ready for AI. I think you need to make sure that you've got clean data. I think you need to make sure that your data is

accessible, right? You've got good APIs or integration to be able to get at it. And of course, security is front of mind. Not the most exciting of topics in there, right? But you absolutely have

to be thinking about that as well. So, I think from a business point of view, you need to think hard about how you're going to get your organization ready for AI. And I think as well, it's about identifying the right use cases for it as well. It is a subject you could get very excited about and that you can go after and spend a lot of money and a lot of resources, but there is some old-fashioned IT principles for me, which goes back to, what is it you are trying to achieve? What are the benefits you're trying to get from this? And then let's focus on that. So, I think that's really important. But absolutely, and you see it in the digital space now and what's happening in areas such as SEO, for example, search engine optimization, and some of the new

technology and principles that are coming to the way that you can search and buy online. AI is going to be a

massive disruptor in that space.

[08:51] - Steve S

I think [clears throat] one of the things when we're speaking about AI, and we speak about this quite a lot, I know we do, Andy, don't we, is around AI is great if you've got good quality data. If you haven't, AI is going to amplify the issues.

[09:03] - James W

Yes.

[09:03] - Steve S

So, what do you think are the biggest data quality issues affecting the retail sector at the moment?

[09:09] - James W

Well, I think, particularly where I've worked in a decentralized business before, and you're trying to get standard views of things. So, like standard views of product, for example. You have to work hard across a business to make sure that you're aligned on what your data strategy should beand how you want to use your data, because that then drives the technical work that you have to do. And I think in retail, it's the sheer amount of data out there as well. I keep talking already in this podcast about digital platforms, but the amount of data that that generates and that the digital marketeers are greedy for as well,

I think that is a big challenge. It's just, I go back to, it's about getting the priorities right, I think.

[09:53] - James B

Yeah. And we talk a lot about, when we talk about data quality, yes, there's the technical aspect, we talk about governance as well.

[09:58] - James W

Yes.

[09:59] - James B

And how do you feel that's sort of been taken on in the retail sector? Are you seeing things like responsibilities being put into people's contracts that are clear around how they look after data

and how they behave with data? Or do you feel it's still lagging? Do you feel that there's still a long way to go to really educate organizations to make sure that data is put more towards the forefront of activity within the organization?

[10:21] - James W

I think in retail, there's still more work to be done, particularly when you talk to your peers in other industries.

[10:26] - James B

Yeah.

[10:27] - James W

The challenges in retail is that it's a very fast-moving environment, and it's very action-driven, and people want results quickly.

[10:34] - James B

Yes.

[10:25] - James W

And it's not necessarily an industry that's heavy in governance compared to financial services or something like that.

So, I think from a data governance point of view, it has to be a board discussion. You have to be talking about that, the importance of it, and you're absolutely right. It should be part of people's role. So, if we're doing a big transformation program and we're talking about, right, we're going to second product owners to the business, to the project, a big part of their role is actually data ownership and the work you do for data migration, and really thinking about how you're going to use your data is really important. We go back to data is not a technology function. They don't own it. It's the business's data.

[11:17] - James B

Right. That's key.

[11:18] - James W

The education piece that starts at the boardroom all the way down and really educating the business and the business community about how important data is, really important.

[11:29] - Andi J

We have blown through our 10-minute klaxon, so we are done for today. Again, thank you very much, James Wheeler.

[11:35] - James W

Pleasure.

[11:36] - Andi J

Thank you for bringing your insight to the "Data in 10" podcast. Jamie, Steve, thank you for your time.

[11:41] - Steve S

See you next time.

[11:42] - James B

See you next time.

FAQs:

1. How can retailers improve data quality?

Retailers can improve data quality by assessing existing data, identifying errors and duplicates, standardising information, and introducing regular validation checks. Starting with the data that has the biggest impact on business operations helps organisations prioritise improvements without trying to fix everything at once.

2. What is master data management in retail?

Master data management (MDM) is the process of creating and maintaining consistent, reliable core business data across an organisation. In retail, this often includes product details, customer records, supplier information and store data, helping different teams and systems work from consistent information.

3. How can retailers keep inventory data consistent across multiple systems?

Retailers can improve inventory consistency by integrating their stock management, warehouse, point-of-sale and e-commerce systems. They should also establish clear rules for updating stock records, validate data between systems and investigate discrepancies so that different channels rely on accurate, up-to-date information.