5 tips for creating a data-driven retail organization

You’ve come to the point where you are assembling a lot of valuable and potentially actionable data. But how do you make sure that it will be acted upon and everyone in the organization sees value? How do you get to a situation where it’s not just you or your BI team that’s excited about retail analytics, but the entire organization? Today we’ll share 5 tips with you.

1. Data literacy and access to data

If you truly want to create a data-driven culture and organization, you must get everyone on board. At the same time, not everyone has the same type of background or education and thus data literacy might vary across the organization. From talking to many people we’ve learned that, for instance, a matrix that in our eyes made immediate sense actually didn’t for everyone. If you’re a BI manager and your goal is to have sales assistants use data as well, then talk to them often to discover their needs and test whether what you think is easy actually is. If it isn’t, make it simpler or teach people in your organization. Also, make sure that they actually have access to the pieces of data that are relevant.

2. Visualize your data

We’ve seen some examples at different retailers where instead of visualizing the data, BI teams used 20 different Excel sheets. Especially in retail many people are visually oriented, so don’t underestimate the power of visualizations. And from our experience, for some people a heatmap, a real picture, is much more telling than a chart. If you are the VP of retail, a heatmap alone certainly won’t give you enough information, but keep in mind that for some people in your organization it will be enough and thus make sure to think about the different needs and preferences of every team.

Moreover, make sure that the data and visualizations get noticed. If you can, put up a screen in your office that shows the key pieces of your dashboard that gets updated in real-time or often, so everyone will be able to see what happens and there are no excuses not to look at the data.

3. Culture change *and losing the fear of transparency*

What we have heard from many retailers is that a huge fear of data exists in the industry. And this goes beyond retail, in any sector there are people that have worked in that industry for a long time and are used to making decisions based on intuition or authority. They are afraid to see the ‘truth’ and feel it might invalidate their experience. The easiest way to win over skeptics is to convince them that data-driven companies will beat the competition and that it’s simply essential. Think carefully about quick wins; first focus on those experiments where it’s potentially easier to have a big impact before looking into optimizing the last 1%. Moreover, show people the value in how much time it’ll save them. It’s often easier and cheaper to test two different setups, than to have hour-long meetings about it and weigh all pros and cons.

4. Incentives to encourage data usage

To make your dashboard and data usage stick, it’s important to reward staff in some way. This could be by showing appreciation either with financial or non-financial means. If your staff knows they are being assessed by what the numbers tell, they’ll look at them and be motivated to improve the numbers. For some departments in retail in-store analytics and retail analytics have actually provided a way to assess part of their goals objectively for the first time. Especially for store designers or visual merchandisers for whom one of the goals is to engage people, make them stay in the store and touch the products, new metrics can certainly be useful for measuring success. Do make sure to focus on rewards rather than penalties, as it might otherwise scare people off while that’s the opposite of what you’re trying to accomplish. Especially in the beginning, you’re aiming to get people on board and empower them to test out their ideas.

5. Take action, create success and share

At the end of the day, most people in your organization will care about results and profits. While data can be useful for reporting, it can add more value if you can derive actions from it. Use data to set your baseline and detect patterns and outliers. Clearly think of actions to change the outliers, underperforming categories, into successful ones and after that make sure to share your success story within the organization. Taking action does require good collaboration and getting everyone on board in the data-driven decision making; as a BI specialist you might detect an interesting outlier, but sometimes it’s caused by VM, other times by store layout and at other times by staff.

To give an example of detecting an outlier and creating success: what we’ve seen a lot is that folded items don’t get touched often. At one retailer where we detected that pattern, we suggested to change the VM and partly fold and partly hang the clothes. Not only did touches increase massively, sales for that category also increase by 10%, a big success story that will convince the skeptics of the usefulness of data.

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