Whitepaper

Data in retail: Transforming in-store performance 

Using real-time data to improve your in-store efficiencies at speed.

About this whitepaper

In this whitepaper, we explore how data analytics can help you improve productivity, drive up sales, and make better business decisions.

Discover:

  • Why retailers struggle to get actionable insights from data
  • The benefits of an insight-driven approach to in-store efficiency
  • How automating insights can be a game changer for retail

or continue reading below

whitepaper front cover

Foreword

Brick-and-mortar grocery retailers are being squeezed from all sides. Growing e-commerce, declining customer loyalty, and the rise of discount retail are all impacting traditional retailers’ profits. There have been seismic shifts in major retail markets, too.In the UK Aldi now has a market share of 7%, overtaking Waitrose and the Co-Op. Brick-and-mortar vendors need to up their game if they are to compete in this new retail landscape.

The initial reaction to these market shifts has been to dispose of assets and reduce headcount. This is all part of the retailer’s bid to maintain margins and fund price, promotion, and multichannel investments that drive customers into physical and virtual stores. For example, retailers closed over 8,000 stores in the US in 2020. And experts predict we could see a further 10,000 closures in 2021.

Woman shopping for fresh produce

 

Extracting value from data

Data can have a big role to play if used correctly. Retailers have traditionally used data to generate excessive reporting, drowning their retail operations in data rather than insight. It is not unheard of for a store manager to receive over 100 reports each day and they will be expected to decipher what these reports mean and what the subsequent actions should be. They are data rich and insight poor, which impedes their ability to execute and compete.

Retailers are data rich and insight poor

The retailers ability to collect, store, and transmit data has grown exponentially, but their ability to manage it and create value still lags behind. Industries like manufacturing and oil and gas have actively embraced deeper analytics, artificial intelligence (AI), and the internet of things (IoT) to drive operational effectiveness. As Paul Boyle, CEO at Retail insight, asks, “retail scan data opened the door to what the world now defines as business intelligence. But has it really pushed on as far and as fast to areas such as predictive analytics?”

Woman comparing prices using her smartphone

According to John Paul McNeil, COO at Retail Insight, “Grocery retail has traditionally focused on the creation of heavy dashboards sat on top of large data warehouses. At a time when headcount is reducing every quarter, there is not the enough resource to dig into hundreds of reports. From top floor to shop floor, our clients tell us that they want to know which actions to take to deliver highest value in the quickest time and with as little resource as possible.”

Better insights, better business decisions

But as data streams grow, could the increase in information create an endless stream of backward-looking reporting hard-pressed store managers must wade through every day? Collecting more data does not mean you are getting more insights; it merely means you are getting more data. The rear-view mirror approach to business intelligence and reporting may tell you what has happened, but you then want to know how you can do something different to make a measurable change to your performance. If you can automate this, then it is a productivity game-changer for retail.

We should focus on extracting insight through intelligent automation. Machine-driven insight that can guide, or even take action, is more valuable to retailers than basic data visualisation tools. Especially for a workforce that does not have time to look at the data, much less form it into something approaching value.

John Paul McNeil

COO, Retail Insight

Global management consultancy firm McKinsey & Company believes in the benefit of an insight-driven approach to sales and in-store efficiency. They claim that this helps retailers develop “a deeper understanding of consumer and shopper behavior and embed these insights into the way they manage every product category.” Retailers in the grocery, drug, and DIY sectors that have used the insight-driven sales approach have achieved a sales uplift of 3-5% and a net margin improvement of 1-4% in 6-18 months.

If you do not up your game when it comes to data analytics, you risk falling behind those competitors who do and by quite a lot too. McKinsey Global Insight estimates that retailers who exploit data analytics at scale across their organizations could increase their operating margins by more than 60%.

 

If we can provide a positive answer when retailers ask whether this information is enabling them to do a better job in less time, or even to eliminate tasks having no value to the business, then we are on the right track to significant productivity gains.

Paul Boyle

CEO, Retail Insight

There is a large prize for automating this insight and the pressure in the market means retailers have no time to waste. Retailers that want to drive sales and productivity quickly should look to employ a trusted partner that specialize in operationalizing retail insight. This will ensure that you get the most from your data in the shortest time possible, which, in turn, allows you to concentrate on executing an optimized retail plan.

Written by Paul Boyle

Paul, a Masters graduate in Engineering, became CEO of RI in 2011 having previously served as COO since RI’s founding in 2005. He enjoys everything about RI; our people, products and partners. Prior to RI, Paul worked at P&G and HJ Heinz in Commercial and Strategy.

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