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The Blue Jumper: Data governance
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How can you make sure a blue jumper is always a blue jumper? Data governance.
A single version of the truth: it’s the holy grail of any retail data strategy.
Whatever your data goals – improved customer experience, increased e-commerce, more targeted marketing – you need accurate, consistent data to fuel them. Because without the right data going in, you’ll never get the results you want out.
But just as Indiana Jones knew that the flashiest gold cup on the shelf wasn’t the real grail in the Last Crusade, achieving a single version of the truth isn’t about getting your hands on an all-singing, all-dancing data management system (although it’s an important part of it). The real solution is more humble – and has as much to do with the people who engage with your data as the technology that processes it. If you really want to achieve a single version of the truth, you need data governance.
Data governance addresses the way that data flows through your business, assessing the quality of the information, how it’s processed, its relevance and, above all, how it connects with your teams. It may not be the most exciting or glitzy aspect of your data strategy, but it’s vital to its success – and no amount of technology can replace it.
Yes, a PIM or MDM system can help you corral your data, but data governance is the real lynchpin of any digital transformation. Carried out successfully, it shifts the way that every aspect of a business perceives, processes and values the data at its disposal, enabling a unified data-centric approach across the board.
So why is this so important in retail – and why can’t a data management system alone create a single version of the truth?
Let’s pick up where we left off with our blue jumper.
It’s a jumper. It’s blue. It’s a medium and it’s a cashmere blend.
We know this because the image and data tagged to the product are telling us so. But how do we know that the data we’re viewing is correct? How do we know that when we take that jumper out of a box, it is going to be what it says it was online?
The truth is, we don’t – not without data governance. A data management system can ensure that the data being extracted is the same wherever that data is accessed – online, in store, via app, etc – but it can’t guarantee that the data going in is accurate, or complete. Someone may have uploaded a blue jumper but failed to specify that it’s in the children’s range. The product then appears on search results for adult clothing and is even included in marketing collateral as an adult-size item – frustrating and inconvenient for customers and teams.
A data governance strategy prevents these errors, as it not only sets the parameters of what information is needed, it communicates why this information is important and how individuals can benefit from data accuracy. It also aligns each department’s disparate data agendas under one wider business vision, creating a unified digital goal.
For instance, a clothing retailer’s data goal for 2020 could be to have a quicker response to fashion trends and keywords. Effective data governance makes this simple to communicate and execute: every department from purchase to marketing understands that those specific keywords – cornflower blue, not light blue, for example – are a must-have data item that has to be included in all clothing products. Without it, it’s easy for certain departments or people to disregard these tags, prioritising more generic terms for convenience.
With data governance in place, you can be confident that every product has the right, relevant information attached to it, accessible from every channel: a single version of the truth for customers and internal teams alike. Although it should be one of the first steps you take in your data journey, it’s never too late to address data governance. At Comma, we’ve worked with organisations at every stage of their data strategy, helping business leaders and their teams to understand data governance and realise the benefits it brings.
In this series of blogs, we’ll be outlining the core steps to achieving that data truth, including:
Data quality: Your results can only be as good as the data you put in
Data governance: Getting everyone on the same page with data strategy
Technology assessment: What product is right for your needs – and your vision for the future?
Data migration: Making sure that data moves between systems without a hitch
What’s next?: Using data to do things differently and make your business goals a reality
