According to the latest ONS figures, the impact of Covid-19 restrictions on the physical retail sector has been mixed. Stores…

According to the latest ONS figures, the impact of Covid-19 restrictions on the physical retail sector has been mixed. Stores selling hardware, paints and glass, for example, saw a 13% increase in the value of retail sales compared to last year. Others have been hit particularly hard – with clothes store sales down by more than a quarter (26%) in the same time frame.

The forthcoming wave of vaccinations promises to restore the UK’s economy to a more stable position. Nonetheless, we must consider the possibility that changes in consumer behaviour may linger even when lockdowns and social distancing are a thing of the past, as well as how different sub-sectors within the industry will be affected.

Let’s therefore look at two opposing, but equally possible scenarios on the road ahead.

Scenario A – Opening the floodgates

After months of being cooped up at home, customers flock to town centres, industrial parks and shopping centres to exercise their freedom to purchase goods in-person. Sales volumes increase, but supply chains become stretched due to spikes in product demand and store inventories become more difficult to effectively manage.

In addition, disruption to both the need and availability of workers in the months prior leaves stores understaffed, leading to long queues and disgruntled customers. Finally, customers who for months have been encouraged to go cashless are now making far more card and contactless payments, leaving some POS systems struggling with the uptick in data traffic and leading to more frustration for staff and customers alike.    

Scenario B – The high street ghost town

For many, shopping online during the pandemic switched from something people wanted to do to something people needed to do. As a result, those who were previously sceptical or unfamiliar with technology (or who simply preferred shopping in-person) had to familiarise themselves with the process. Of course, although many within this group may still be averse to e-commerce today, we must assume that at least some will use their newfound familiarity to continue shopping online in the post-Covid era.

In this scenario, customers new to e-commerce have been swayed by the user-friendliness, low prices and fast delivery on offer online. As a result, footfall on the high street struggles to recover to pre-pandemic levels, creating a tough environment for the small independent retailers who compete with the online giants.

Preparing for every outcome

While these two scenarios are diametrically opposed, the Internet of Things (IoT) could help address some of the issues described in both situations. Comprising a dynamic network of sensors, devices and equipment, the IoT makes it possible to view and interact with physical objects as easily as files and folders on a computer. In other words, the IoT creates a digital overlay that sits across the physical infrastructure of retail stores, effectively facilitating the agility of online shopping in a physical space.

It will require investment, but securing the future is a goal that pays dividends. Here we look at the solutions the IoT has to offer in these two scenarios.

Solution A – Unlocking efficiency at every stage of the supply chain

Preparing to mitigate the negative outcomes in this scenario requires retailers to take a hard look at the systems they have in place, identify areas in urgent need of greater efficiency, and implement new IoT tools to address them:

  • Real-time supply chain – inventory sensors and POS data are integrated into a direct communication system with supply chain partners, triggering automated manufacturing and production systems and adjusting stock delivery schedules accordingly.
  • Data-driven decisioning – capacity sensors linked to data analytics platforms not only track the number of customers in-store, but analyse seasonally-adjusted data relating to the length of time customers spend in the aisles and predict where and when staff will be needed.
  • Robotic process automation (RPA) – from processing supplier deliveries to quarterly stock counts, RPA systems automate time-consuming tasks that happen behind the scenes, freeing up staff time for better workforce scheduling and more focus on customers.

Solution B – In-store customer experience unmatched by online retailers

Innovations such as live product tracking and same day delivery have recently tipped the customer experience race in online retailers’ favour. To attract new customers and retain their business, brick-and-mortar stores must emulate the dynamic, digital and personalised experience offered by their online counterparts:

  • Interactive digital displays & kiosks – positioned at the store entry, customers can benefit from an optimised in-store journey and a highly personalised experience by viewing commonly bought items, their location within the store and in-the-moment marketing offers based on purchase history.
  • Roaming POS – queuing is eliminated as tablets carried by staff process customer payments anywhere in the store. In addition, RFID scanners built into trolleys and baskets can total large volume purchases in real-time, without needing to take a single item out to scan.
  • Customer application integration – in-store geotargeting systems can link via Bluetooth to customer-facing smartphone applications to help locate specific items and provide other useful pieces of information, such as stock levels, current offers and the location of staff.

LTE & SD-WAN branch networking: laying the foundations for the future of physical retail

Regardless of which scenario becomes a reality, any subsequent IoT strategy must begin with a reliable, secure and agile network. The first step is cutting the cord with fixed broadband connectivity and setting up a private in-store network running on LTE. Also known as wireless WAN (WWAN), this solution offers retailers greater levels of flexibility thanks to out-of-the-box connectivity and unparalleled reliability through multiple network channel management.

The second foundational requirement for retail IoT is SD-WAN. With the sheer quantity of network applications running in most branches, cloud monitoring and troubleshooting features – including automated alerts – SD-WAN enables retailers to cost-effectively manage WAN conditions at widespread locations. Crucially, SD-WAN also allows secure VPNs to be established in a matter of minutes, providing robust protection for devices and sensitive information, such as customer payment data.

Survive and thrive in the future of retail

The past year has been an uphill struggle, not least for retailers contending with limited footfall in their physical stores. Investing in new technology may not be top of mind for all retail businesses in the immediate future. But for those who are able and willing to make small adjustments to innovate may find they are able to unlock efficiencies in their supply chain, improve their in-store experience and attract and retain new customers once lockdown restrictions start to ease.

The Internet of Things (IoT) allows devices to send data to cloud storage, where it can be combined with other…

The Internet of Things (IoT) allows devices to send data to cloud storage, where it can be combined with other data, analysed and interpreted using techniques such as predictive analytics, artificial intelligence and deep learning. The resulting knowledge, including identification of patterns and trends, reveals new insights that have the potential to touch every aspect of our lives. Many of us are already using IoT devices in our homes, from smart sensors to voice activated virtual assistants.

However, I believe that to achieve the IoT’s full potential we must add visual data to create the Visual IoT (VIoT). Sight is the most important of our senses, so integrating visual information with other IoT data streams is immensely powerful. It helps a system or device better understand and interpret objects and movement as well as its surroundings based on the visual data it can ‘see’.

We now have the processing power, bandwidth, data storage capacity and computing ability to enable fast, reliable analysis of visual data to a standard that makes it commercially viable. The result, according to McKinsey, is that video analytics will see a compound annual growth rate of more than 50 percent over the next five years, contributing to a potential economic impact for the IoT of $3.9 trillion to $11.1 trillion a year by 2025.

Doing this does not require hundreds of new cameras. Huge volumes of visual data already exist, collected by the analogue and digital cameras that surround us, from traffic and numberplate recognition cameras to CCTV systems. Most of this visual data, however, is currently collected for a single purpose, and only a tiny percentage is ever viewed. Combining it with other IoT data streams and adding analytics would make it immensely valuable.

Our research suggests there are currently some 8.2 million surveillance cameras in the UK, producing 10.3 petabytes2 of visual data every hour. Consolidating this in a cloud infrastructure and combining it with other data sets, from static data such as grid references to dynamic ones such as weather data, could provide clear visual insight into what is happening, why, and what might happen next. Applications could range from speeding up the response to motorway accidents and managing city centre parking to working with people flows in transport hubs and caring for vulnerable people.

We are already seeing companies such as Vodafone integrating cloud-based CCTV with building security systems, adding visual verification to intruder alarms. Such systems can enable home security companies and the police to check properties visually when an alarm goes off and quickly ascertain whether a break-in has occurred. This can provide significant time and cost savings while enabling immediate action to be taken if appropriate.

Cameras combined with analytics can be configured to map patterns of movement in real time, helping to understand the number and flow of people in public spaces such as stations, airport terminals, tourist attractions and shopping malls. This could be used to automate the management of people flow systems, for example changing the direction of escalators and lifts as customer behaviour patterns change during the day. In many cases cameras can be used simply as a sensor with analytics to verify something, for example that the object at the barrier is a red van with a particular numberplate, and take action, such as lifting the barrier, without necessarily recording the image.

Another application is city centre parking. According to the British Parking Association, 30 percent of city centre drivers are simply looking for a parking space. Cameras could monitor roadside parking spots, letting a central system know which are unoccupied. Location data could be shared with a driver’s routing app, with visual data made accessible so they know what they are looking for. It should even be possible for the driver to book a space and authorise payment to be made automatically, with length of stay calculated and payment taken when they leave.

Another exciting possibility is to speed up the response to road traffic accidents. The VIoT offers the possibility of combining data from motorway cameras to help pinpoint the precise location of accidents and to tell first responders in real time about any hold-ups when they are en route. This information could be combined with in-vehicle routing systems to ensure their swift arrival.

Applying analytics to visual data will lead to further applications by revealing patterns and predicting future behaviours. This intelligence will help organisations optimise systems, improve safety and make better, faster, more appropriate decisions. The good news is that machines are doing the ‘watching’ – not people.

Analytics combined with AI and IoT can also play a key role in helping protect more vulnerable members of society. We are already seeing cameras used in care situations to detect pre self-harming or suicidal behaviours, and to monitor individuals to ensure they are being well treated (with appropriate permissions). In the future older people living in their own homes could benefit from cameras which record where and when they are active. Periods of inactivity might indicate a problem and could trigger alerts to family or carers. Cameras at stations could be trained using AI to spot behaviours indicative of potential suicides and issue appropriate alerts to staff.

The big issue is of course privacy, but the right analytical software enables automatic decisions to be made without human involvement, while the General Data Protection Regulation (GDPR) provides additional data protection. There are also many applications in sectors such as the environment that will not involve individuals at all.

James Wickes is cofounder and chief executive at Cloudview

Further information is available in the White Paper VISUAL IoT: WHERE THE IoT, CLOUD AND BIG DATA COME TOGETHER.