Retail ‘Speed Read’: Leveraging Data Analytics
The retail industry is experiencing previously unimaginable digital disruptions from online and instant shopping to immediate/rapid home deliveries. In addition – and thanks in part to the rise of social media and mobile – we can now all enjoy a radically transformed omnichannel retail experience. These changes are affecting every retail sector, from entertainment, fashion, personal care and even grocery.
In times of such significant upheaval, it is vital to understand the drivers behind these different consumer behaviours, and how each approach can affect differences in sales revenue. Retailers who use data analytics in their organisations are ahead of the curve when it comes to customer experience, customer motivations, effective marketing to customers, and market trends. These benefits have been shown to relate directly to financial performance. With an integrated tech infrastructure, retailers are driving competitive advantage by gathering, analysing, and leveraging their unique business data, and comparing it with data from their industry. Using data-driven insights goes beyond merely tracking trends; efficiencies in daily operations become apparent and these directly affect cost savings and market position. McKinsey Global Institute estimated recently that the potential annual value of artificial intelligence for the retail industry lies between $400bn to $800bn globally.
For grocery retail specifically, McKinsey saw the potential for an incremental increase in earnings before interest and taxes (EBIT) of up to 2%. Most of this value is driven by commercial use cases around assortment, pricing, promotions, and personalization. Given the sectors long history of engagement with data – from early adoption of loyalty cards to modern, complex, and analytic-reliant reward schemes – these are also some of the most mature use cases. Analytical approaches have begun to converge across the industry, meaning standard analytics solutions are available on the market.
Over the past five years, grocery retailers have moved beyond experimenting with advanced analytics and started to adopt these use cases in a systematic way. Most European grocery retailers are now embracing advanced analytics and are investing in further developments to add more value. For example, in 2020, Ahold Delhaize announced the implementation of tools for assortment, pricing, and promotions across its European brands. Players such as ICA, Migros, and REWE have well-established analytics organizations, and several retailers have hired additional data scientists, including discounters Aldi and Lidl.
Many grocers have made great progress on analytical maturity. Leaders in analytics have tackled most fundamental use cases, such as pricing, mass promotion, and assortment optimization. Now, they have increasingly turned their focus to pursuing new use cases along the value chain and improving the existing use cases. This is made possible by the growth of AI tools which have expanded the capacity and functionality of many analytics teams, allowing a granular focus, and providing real-time insights. These efforts are often driven by a strong analytics unit, but adoption of these use cases in the business varies. The best analytics solution does not help if it is not used and understood by the respective decision makers (such as category managers).
Data analytics allows retailers to lighten the load of stressful “unknowns” and remain competitive in a crowded marketplace. In order to make the most of the potential that the wealth of data – be that from customers, or along the supply chain – can offer, retailers must ensure they have an easily-understandable data analysis system in place to collect, store, and analyse their data. The effective retail organisations are turning to well-known technological leaders to make their data analysis goals achievable.
With over forty years of experience in supporting our clients developing technological solutions, and an innovative Consumer Practice interlinked with its dynamic functional hubs, Norman Broadbent is well placed to support these discussions. To find out more about how we can help you, or to talk through a people challenge or potential search assignment, please do not hesitate to contact James Peskett via firstname.lastname@example.org for an initial confidential discussion.