Cutthroat competition, the continuing rise of eCommerce and cost-side pressures stemming from a weak pound all point to continued challenging times ahead for retailers. When it comes to staying ahead of the curve, the data that exists within your organisation is the most valuable asset at your disposal – providing it’s put to work in the right way.

When UK home furnishings giant, DFS wanted to create a culture of data-driven decision making, Assimil8 was called upon to put the tools in place to achieve precisely that. The company now has what it needs to move from data to insight to action in a way that’s sustainable, reliable – and that matches the needs of its decision makers.

So what are your needs? Well, for a start, there’s the constant challenge of predicting and responding to changing trends and buyer behaviour. If you have a presence across multiple stores, there’s the issue of bringing everything together to inform business-wide decision making. And of course, data has little value if your people on the ground can’t make sense of it. So with all of this in mind, here’s how to really put data to work…

Staying up to date on buyer behaviour and sentiment

Sentiment can certainly move quickly: with instant access to the latest info on products, pricing, reviews and trends, you’re dealing with the most highly-informed consumers in history.

It’s no surprise that across the retail sector as a whole, the concept of a single, rigid product range per-season looks increasingly out of date. Now, the emphasis is on staying agile, on monitoring what’s happening on the ground and on adjusting your range accordingly. Store-side, of course, there’s still the perennial concern of keeping shelves stocked while not being lumbered with swathes of unsellable stock.

The so-called “fast-fashion” giants are the undisputed masters of responding to this, where speed is everything – especially when it comes to interpreting and responding to data. Take Zara, for instance: it’s not just branch-level sales data but anecdotal comments from customers that are transmitted swiftly from store to HQ. This info is constantly informing stock replenishment and design decisions alike – and explains how Zara is able to put out up to five waves of new products after each initial season launch.

Without swift and effective data analysis, then quite simply, fast fashion wouldn’t exist. It’s a principle that applies across the retail sector: to react to changing trends, you need the ability to get the data that matters from customer touch points to decision makers quickly and reliably.

Extracting data from multiple locations

In an ideal world, data from each physical branch and online platforms should combine to give you the full picture – uncovering the sales patterns, inventory and margins for each location and helping you to optimise your processes across each of your stores. It should also help you to discover hidden problems and opportunities – from under-achieving outlets, through to product lines that are performing exceptionally well in certain geographical locations.

That’s the theory, at least. But what happens when you have transactional data from 100+ stores to collate and interpret? Hollie Haeney, Head of Financial Planning & Analysis at DFS describes the problem the company was faced with prior to overhauling its data analysis processes: “Previously, if I wanted to compare the product sales performance of 50 stores, I would have to generate 50 different individual store reports and then manually collate them. Each report might take a couple of days to run, so it could literally take days to get an answer.”

Manual, spreadsheet-based reporting takes up valuable time and resources; you need the ability to pull data from multiple locations – and to do so swiftly, without compromising data integrity. For DFS, the solution came in the form of IBM Cognos Business Intelligence deployed in the cloud, along with IBM Cognos Data Manager.

The flexible, cloud-based architecture enables the company to scale up easily as the company and data user-base grows. For sales managers, it’s a case of having access to the information they need – when they need it: “We have a daily sales report that Cognos automatically generates overnight and delivers to our managers’ inboxes at 7am every morning – so they don’t need to go looking for information, it’s right there when they log in”.

Making data accessible to the people who need it

For DFS, its new system was introduced as part of a bigger objective: encouraging faster, evidence-driven decision making. The company wanted to move away from the situation where “People used to rely on whatever data they could get hold of easily – which wasn’t necessarily the data that they really wanted”. Cognos solved this problem.

For other retailers, the problem is slightly different. Execs across the organisation might be completely on board with the idea of data-driven decision making; it’s just that different individuals have their own preferred ways of getting there. Some might prefer the canned reports, and instant visualisations of the many self-service BI tools on the market. For others, the ‘user-friendly’ aspects of a BI tool might be less of a priority than security, integrity and functionality.

And what happens when stores merge? Do you force your people to standardise and give up using the tools that work for them? This is where Theia can be put to work for retailers. By consolidating multiple BI tools and assets into a single visualisation, it enables your people to continue using the tools that work best for them, while providing the C-suite with a single view of the entire data estate.

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