10 steps to making data-driven decisions in retail

[fa icon="calendar'] October 19, 2017 / by Alex Ball

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Too often, retailers – especially those who have been in the business for a while – continue operating in the same way they have for years. But in today’s retail landscape, “the way things have always been done” just doesn’t hold up.

 

Neither does going with your gut, even if that’s what worked a decade ago. The fact is, your competitors – especially those that operate heavily (or exclusively) online – are already utilizing big data across their organizations. If you don’t join them, you’re going to miss chances to engage with your customers, reduce shrink and improve profits across the board.

 

Bernard Marr, an expert on big data, analytics, metrics and improving business performance, recently published a piece on Forbes.com, Data-Driven Decision Making: 10 Simple Steps for Any Business, that outlines a 10-step process for making decisions regarding your business based on data. Marr’s advice can be a great resource for retailers who are struggling to harness all their data, particularly in currency management.

 

While 23.9% of retailers use data analytics platforms to provide better customer service, far fewer utilize data to make other decisions about their business – and that’s a major lost opportunity. When your data is easy to understand and act on, you can apply Marr’s 10 steps to almost any scenario. Here’s one example:

  1. Start with strategy. Marr suggests not getting caught up in the idea of too much data and instead thinking about what your business is looking to achieve. Let’s say you want to increase profitability by 15 percent in 2018.

  2. Hone in on the business area. This could be anything from customer service to back-office operations. In this exercise, let’s focus on loss prevention – reducing shrink.

  3. Identify your unanswered business questions. So, where is most of your shrink coming from? Is it lost product? Is it missing cash? Without automated corporate reporting, these questions would be tough to answer, at least quickly.

  4. Find the data to answer your questions. Marr advises to identify “the data that could help you answer your most pressing questions and deliver on your strategic objectives.” Do you need information from the POS? Cash recyclers? The general ledger? Security cameras?

  5. Identify what data you already have. It’s probably a reasonable feat to get your hands on historical data showing inventory and cash loss throughout your stores, but it might mean manually interacting with multiple systems or painstakingly aggregating reports. This is a great time to look at the reports you get from your stores – are they asking for information you really need? Do you have to manually combine and interpret the data they contain? Identifying the specific data that will solve your problem will keep you from getting sidetracked.

  6. Work out if the costs and effort are justified. In this example, it’s easy to see the direct savings you’d see from reducing loss. But also look beyond that to intangible savings. If you had better access to information about what’s happening in your stores, in what other ways could you improve your business? If your store employees spent less time working with various systems and devices to provide you data, what other, more productive tasks could they be doing?

  7. Collect the data. If you’re doing this manually, you might need a few weeks to gather proof points from multiple sources and measure them against each other. If you have an automated system in place, though, data reporting is in real time.

  8. Analyze the data. Again, if you’re trying to make sense of data you’ve pulled together from disparate sources, it may be difficult to draw any meaningful conclusions from it. If you have real-time reporting across your locations, it’s much easier to quickly pinpoint the causes of your shrink, down to the store or even the register.

  9. Present and distribute the insights. Present the results to the right people at the right time, in a meaningful way, Marr says. When you have a single source of analytics that multiple teams use collaboratively to manage concerns like shrink, you can work faster together to improve the business as a whole.

  10. Incorporate the learning into the business. Without action, data doesn’t mean much. When you identify where cash loss is coming from, you can take steps to correct the problem, helping you toward your Step 1 goal of increased profitability.


It’s easy to get overwhelmed by all the data available within your business today. Taking a step back to think about how to use that data effectively is a useful exercise for any retailer.
Integration of your systems and devices, paired with automated analysis of their data, will help you make sense of it all and turn it into better decisions, improved stores and increased profits.

 

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Image: iStock

Alex Ball
Alex Ball

Alex works feverishly as part of the Balance Innovations marketing team to make sure everyone hears how we can help solve the challenges of retail currency management.