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Article
6 min read
Florin Pop and Matias Salmeri

The digital revolution has made data the new gold, transforming industries and reinventing the way business functions. Giant marketplaces and small disruptive start-ups alike have begun to appreciate the inherent value of data, recognising that, given the appropriate context and capacity, information holds the potential to unleash unprecedented progress and innovation.

 

Companies no longer collect and store data as a by-product of running their businesses. They are transforming into data-driven entities, which means they are collecting, transforming and compiling data to power their strategies. One can argue that modern enterprises’ income will be inherently linked to their data assets. This means proactively leveraging data for insights, innovation and competitive advantage, the opposite of the traditional, reactive approach where data management is not prioritised or strategically used within the organisation.

 

In this era of transformation, every business has two primary methods to achieve better outcomes: cutting expenses and growing sales. Data is one of the key factors that makes this possible. Whether it concerns efficient company operations, better customer service or understanding and capturing unidentified market niches, data is the secret to unlocking value and ensuring sustainable returns that will facilitate becoming a data-driven organisation.

 

The businesses of tomorrow, which value data as their most significant asset, will lead the way in this golden age. By embracing proactive approaches, accelerating data lineage and harnessing the transformative power of the cloud, they can seize new opportunities, navigate complex challenges and chart a course towards enduring success in an increasingly data-driven world.

 

How automation is used in retail

 

Retail organisations look to improve everyday processes by deploying automated tools. Whether brick-and-mortar, e-commerce or both, retail businesses that lack an online presence are at a significant disadvantage compared to those that do. Through a compendium of innovative solutions and technologies, they are more effective than ever before.

 

Not only online retailers can benefit from automation; physical retailers are leveraging the latest innovations in artificial intelligence (AI) and machine learning (ML), too. For instance, large retail chains use self-checkout to automate the checkout process and reduce the need for human intervention. The 2024 Digital Commerce Index found that 43% of consumers favour self-checkout when shopping in a grocery store. By age range, that preference is even more interesting, with 55% of 18-29-year-olds favouring it, 30-44 at 51%, 45-60 at 40%, and those aged 60+ at only 26%.

 

Going one step further, this kind of checkout is now possible using the customer’s personal device, like a smartphone, which can increase the flow in stores – no more crowded stores and queues that drive customers away. A ‘trapped’ customer who waits in line for checkout is not desired by anyone; there have been cases of abandoned carts because the queue time was too long. Thus, analysing customer behaviour in real time, forecasting inventory levels and in-store traffic management can lead to a better customer experience that will eventually lead to a returning customer.

 

Furthermore, the general practice is to offer ‘free’ wi-fi, which makes customers spend more time in the store and attracts new ones, thus augmenting foot traffic. Retailers can gather valuable data from customers who log into the store’s wi-fi network, such as demographic information, browsing behaviour and visit frequency. A free wi-fi network offers the possibility for targeted marketing campaigns and enhances customers’ shopping experience.

 

Machine learning, combined with high-resolution cameras, aids in-store traffic forecasting by capturing detailed data on customer movement and behaviour, tracking interactions with goods and staff, for instance. Through image processing and pattern recognition, ML algorithms analyse this data to predict future traffic patterns. Retailers can then optimise operations, such as staffing and layout, based on these predictions for improved efficiency and customer experiences.

 

In e-commerce, the possibilities are even greater than for in-store retailers. Automation can be implemented across every facet of operations, spanning from the supply chain to sales, shipping, inventory management and returns processing. The workforce size is contingent upon the extent of automation deployed within each aspect of the chain. A well-automated e-commerce business can have automated supply, sales and collection, returns and, of course, bookkeeping.

 

The only area that is a step behind is delivery, the part where automation is not yet implemented in such a way that no direct human intervention is needed. Technological and economic challenges, as well as a legislative void, currently prevent us from going all the way. While some ventures may have encountered challenges, there are notable success stories among those who persevere and remain committed to ongoing innovation.

 

The logistics industry implemented parcel identification through barcode scanners a long time ago, goods inside the warehouse are moved with automatic conveyors, but packaging and delivery are a little behind. The end goal is that once customer payment is approved, the order goes to the warehouse, where a system of robots will prepare the order, pack it into the right container and send it to a delivery point via drone. From there, it is taken to your doorstep by last-mile-delivery robots.

 

The COVID-19 pandemic has shifted customer behaviour towards home delivery and online shopping. People have discovered that they can do a lot remotely, driving an increased demand for household items. Although we have overcome that phase, it’s hard to reverse a trend, so the industry adapted and embraced the demand for specialised hardware and software.

 

Benefits of using data

 

In the retail chain, data is produced and holds value at every stage, whether in its raw form or after being curated and interconnected. Extracting insights, identifying trends, uncovering patterns and exploring new opportunities are some of the ways this value is realised.

 

Sometimes, data is information without any processing. In the warehouse example, the system must know information like inventory, location, size, weight and distance to travel to act as input for the system, but this is just one small part of the picture. Just collecting and using data is not sufficient though – the key differentiator for success and innovation is to be the very first. Velocity is crucial to be able to harness large volumes of data, transform them, make sense of diverse types of data and use the insights.

 

The end of an online purchase is not when the payment transaction is completed – it’s when the customer leaves a review. That is when all the value from that acquisition is extracted. That review can drive future sales, so the target is to shorten the time from checkout to review. This new model needs to integrate the latest ‘knowledge’ and be an iterative model that adjusts according to changing market behaviour. A regular revision of operations can help identify areas and processes that may need fine-tuning or even make those changes seamless. If an organisation is data-driven, it can save time and effort, while increasing revenue.

 

Finally, let’s look at a frequent feature when customers browse a shop online: a chatbot window popping out at them. This is a major development in user experience and has a tremendous effect on a company’s image. If implemented correctly, it’s a factor that can increase customer satisfaction tremendously. The quality of a good chatbot is to be like what we’d expect from a human assistant. That means to be to the point, concise and not to loop. Using large language models, we can implement chatbots that are better than ever before and can be enhanced with business-specific data, thus lifting the load from employees, consolidating your brand and increasing customer satisfaction.

 

Using a data-driven approach in retail translates but is not limited to improved productivity, cost savings, greater revenue, less human error, improved inventory and supply chain management and, ultimately, better customer experiences.

 

The human factor

 

Automation plays a pivotal role in driving human-centric transformation, empowering employees and enhancing productivity.

 

According to a recent IDC report, 58% of participating businesses have an automation strategy centred on removing mundane employee tasks. This way, automation has the potential to liberate valuable time for true value creation, boosting both employee satisfaction and customer experience.

 

Therefore, in the era of constant change, viewing technology as a collaborator is key to success and thriving.

 

At Endava, we are working together with our customers to find better solutions for their targets. We help organisations transform into data-driven businesses, providing them with a key differentiator and bringing them a competitive advantage. We're here to help your business thrive.

 

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