Digitisation began to reshape the traditional retail industry through the rise of online shopping and the increasingly important role played by data, even before the pandemic. COVID-19 has only accelerated this transformation, though massively. Customers had become accustomed to the ease and convenience of online shopping and having everything a click away. Though we now live in a post-pandemic world, the public has carried that expectation forward with them, and the retail industry has had to adapt accordingly. For the retail industry, an integral part of that shift has been the growing importance of e-commerce. 

This shift is best epitomised by the enormous amount of data that is generated by e-commerce. Every action and decision results in data; when properly harnessed, this data can prove enormously helpful to a business. Data accumulated in this manner can optimise operational efficiency, enhance the customer experience, and drive employee efficiency, and each of these effects has a substantial impact on the bottom line. While many traditional retailers have acknowledged the critical role data will play in the coming years, there are still those reluctant to fully adopt a data-driven model.

As the retail sector has evolved and online models have risen to prominence, the number of touchpoints to keep track of have multiplied. Each of these touchpoints acts as a source of data which, when properly utilised, can have a multiplier effect on a company’s success. Where most businesses stumble, however, is in the effective implementation of these touchpoints. In most instances, this occurs due to siloed data from different sources. For example, data generated during a sale is not automatically sent to the customer relationship management (CRM) system or the inventory management system. Instead, this data would have to be manually tracked and inputted into the relevant systems, resulting in duplicated effort and wasted time. 

This also results in key decision-makers lacking the necessary facts to choose a course of action. Over time, the compounded effects of these ill-informed decisions can have a drastic impact on operational efficiency. Traditionally, retailers have addressed this problem by storing all of their data in a single location, whether it be a data warehouse, a data lake, or more recently, a cloud environment. But as the amount of data generated only increases – driven by the Internet of Things (IoT), social media, and connected devices – this strategy has proven impractical and impossible to effectively implement. No single data storage facility can cope with the sheer volume of information being generated. 

Modern data architectures have emerged as solutions to this problem, data fabric being foremost among them. Championed by leading analysts such as Gartner and Forrester, data fabric automates the design, integration, and deployment of data, regardless of its source or storage locations. This is achieved through an overarching access layer that connects every individual data silo and source. Through technologies such as artificial intelligence (AI) and machine learning (ML), data fabric pulls this disparate information together and offers retailers a comprehensive overview of all available information – which is far beyond the capabilities of legacy systems. 

Another technology that is poised to radically transform the retail industry is data virtualization, which enables real-time access to data from varied sources, without having to physically copy and paste data from one location to another. When used in conjunction with data fabric, data virtualization empowers retailers to combine both past and present data nodules and provide an overall set of business insights. The advantage of this method is that live data remains untouched at its origin point, saving systems from having to transfer and replicate data and boosting their overall speed and efficiency.  Data virtualization is a huge step forward for the ecosystem, offering a glimpse of a future free from the drawbacks of legacy IT systems. 

Experience has taught modern retailers that attempting to gather all of their data into one centralised location is unfeasible. To successfully operate in a digital world, it is therefore vital to implement modern data architectures and designs, led by data fabric and data virtualization. A business that decides against updating legacy systems risks being left behind in this hyper-competitive online landscape. By adopting these measures, both individual retailers and the sector at large stand to massively benefit and ultimately improve the retail landscape for years to come.