Like many industries, retail is rapidly evolving as it capitalises on the disruption digitalisation has brought to the market. Whether a new entrant that has rapidly scaled, an established enterprise adapting to the new order, or a local stalwart using digital technologies to expand internationally, there are significant growth opportunities to be had. This is reflected in the results from our Data Literacy Index, where 94 percent of respondents from commercial industries (retail and wholesale) were confident both their industry and business were going in the right direction.
That might seem at odds with the retail landscape at a local level, with the acceleration of store closures in malls and on high streets. But according to Deloitte’s Global Powers of Retailing 2019, international retail is on the up, with revenue increasing for 83 percent of the world’s 250 largest retailers.
There are a huge number of factors that contribute to retail performance, from national economic health to energy prices. Yet what’s interesting to see is that in that top 250, three of the top four fastest growing businesses were exclusively Chinese-founded e-commerce operations, while Amazon leapt up to fourth overall and Walmart occupied the top spot.
Better use of data accelerates success
Why is that interesting? Because they are all prime examples of proper use of data in retail. Amazon is seen by many as the leader when it comes to using data in retail – its algorithms, suggestions and ability to introduce new features before its customers even know they want them are all evidence of what might be considered an extremely data literate business. It’s similar for those fastest growing businesses too – as e-commerce organisations, data is at the heart of everything they do.
Where does Walmart fit in to this? Right at the beginning – Walmart was the trailblazer, right back in the 1980s when it came to understand how data would help it optimise its operations and perform more effectively. It’s little wonder that it is the world’s largest retail company – as the first shop to introduce data warehousing, it has been capturing every transaction across every store in the USA for years.
It’s apparent that most large retailers and wholesalers have woken up to the value of data – 95 percent of them say data is important to their business, with 89 percent believing data literacy is important to the industry. They’re also conscious of the importance of having the right skills in place – 86 percent say their employees’ data know-how facilitates the ability to make critical decisions, with training being a huge part of that.
The gap between knowing and doing
There’s a difference, however, between knowing you need to do something and being able to do it. Despite almost universal acceptance of the power of data and the need for data literacy, the retail industry was found to be the second-worst performing industry in the Data Literacy Index.
Indeed, a significant proportion of the commercial leaders surveyed for the report don’t appear to be doing much to ensure they have the right skills in place. Just over a fifth say they provide data literacy training to employees. This does not compare well when looked at alongside financial services (47 percent), services (49 percent) and heavy industries (32 percent).
This has significant implications for talent acquisition and retainment: if data-literate workers know that they are more likely to be able to put their skills to good use and get paid well for it in other industries, why would they entertain a retail career? There are exceptions – UK retailer Marks & Spencer launched the world’s first retail data academy for employees in 2018 – but the fact remains that without investing in improving data literacy, retailers are going to struggle to get true value out of their data goldmines.
The key to unlocking the next wave of retail innovation
What does that mean? If employees cannot understand data, they cannot use it to make better decisions – no matter what their seniority. On the shop floor, for example, as a customer, there’s few things more frustrating than a sales assistant not knowing if an item is in stock or when it will next be available. If those employees have access to data, and the ability to know what it is telling them, then that experience is greatly improved.
It can also support better management of stores. Take cosmetic firm Lush: in the UK, its shop managers have access to data which shows them sales, stock levels and freshness, enabling them to make decisions to drive individual store performance. It could be grouping in closer proximity products that sell well together, or more short-term, rather than longer, promotions. By giving its employees access to key data, Lush is empowering its staff to make the decisions they see fit to increase profitability and reduce wastage. They have seen an incredible response, with 70% of staff accessing the platform every day to review sales and stocks and to manage performance. This resulted in £1 million of savings in lost stock in the first two years of having the data available to staff.
There’s also a huge opportunity around the use of data-drive technologies, including artificial intelligence (AI) and machine learning, in back-office operations. A classic example is forecasting – something that clothing retailers have always struggled with. By deploying AI, retailers have the potential to be able to rapidly process relevant data and determine the best forecast. However, it must then be the responsibility of the team to read, analyse and question AI-determined decisions to confirm that it’s the right trajectory for the company.
The big opportunity for retailers
The world is powered by data and the potential for companies that harness it is massive. The Data Literacy Index found that firms with higher levels of data literacy have a greater enterprise value of between 3-5 percent. For the survey respondents, this represented $320-$534 million of the total market value of each business.
In today’s market, retailers can’t afford not to recognize and act on the potential for data literacy to improve the productivity and profitability of their organisation. And with over-three quarters of retail workers willing to invest more time and energy into improving their data set, it is the right time to take advantage of every opportunity for data to inform their business practices and decisions.
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Paul Winsor is the Head of Customer Solutions at Sempre Analytics. He is a Data Analytics Professional with extensive skills and experience in developing and executing data-driven strategies for the largest companies globally. Prior to Sempre Analytics, Paul was the Retail AI General Manager at DataRobot and the Global Senior Director Industry Solutions at Qlik.