Simon Lewis, head of growth at 7bridges, explores the long-term impacts that Covid-19 could have on the adoption of AI in the retail supply chain.
Retail is one of the main drivers behind the relatively lethargic modernisation of the logistics industry. Efficient supply chains have become essential to meeting consumers’ increasingly high expectations, with ecommerce giants like Amazon raising the bar for delivery speeds and consumer satisfaction. Even before Covid-19 hit our economies, retailers were looking for ways to separate themselves from competitors and gain consumer loyalty. AI-based solutions offer fast, efficient and flexible alternatives to ensure businesses stay ahead of the logistics curve.
Covid-19 has accelerated the need for retailers to both streamline costs and operations, and fulfil consumer demands: 72% of UK retailers have experienced supply and logistical difficulties during the pandemic. In parallel, fuelled by global lockdowns and the move to remote working and online shopping, the global logistics industry is expected to increase by $481 billion by 2021 to a value of $3,215 billion.
Yet black swan events, in which unpredictable events present severe consequences and require agile business reactions, put retailers at risk. Due to Covid-19, 7bridges observed retail-sector orders were down 80% in April, recovering to within 10% of pre-Covid volumes in July. Such unpredictable swings in the market make retail businesses vulnerable, and highlight the importance of agile supply chains. This could mean investing in platforms which allow for more accurate sales predictions, or AI which allows retailers to implement robust and nimble logistics operations.
AI enables retailers to calculate and interpret major business risks and plan for the unexpected. According to Opinium and LiveArea, the top priorities for investment following Covid-19 are digital commerce (72%) and IT infrastructure (60%).
As the repercussions of Covid-19 encourage online shopping and make room for smaller, agile businesses, smooth logistics operations and timely direct-to-consumer deliveries are essential to gaining and maintaining customer loyalty. Managing warehouse spaces, delivery expectations and consumer behaviours are three of the major challenges currently affecting retail operations; challenges which AI can help to mitigate.
The state of real estate
According to Prologis (2019), ecommerce requires over three times the logistics space of brick-and-mortar sales. This means that should the ecommerce penetration maintain gains made from lockdowns – further e-fulfilment space is needed. Regarding stock, Covid-19 has limited movement around networks or on to fulfilment centres, and a sudden drop in demand has limited the off-loading of existing stock.
This has significantly impacted retailers who don’t have an e-commerce offering, such as Primark, or decided against cancelling supplier orders, such as H&M. The closure of stores and inability to sell products to customers resulted in stock piling up. As the available storage space decreases, the cost of storage inevitably increases. In parallel, UK warehouse adoption/take-up hit record highs in Q2 of this year, at 13.3 million square feet, bolstered by ecommerce activity.
Yet, while many warehouses saw widespread disruption of the flow of goods in the wake of Covid-19 (Amazon temporarily blocked shipments to warehouses of all goods other than medical supplies and household essentials), AI adoption has enabled retailers to react quickly to redistribute stock to alternative warehouses that are open and functioning – worldwide. If, for example, centres or stores were to see reduced operations due to temporary closures or employee strikes, as in Italy and Spain, AI platforms can advise re-routing options to ship stock to or via another country. Germany, for example, saw lockdown measures lifted earlier and warehouses operating closer to normal levels before the UK.
Using AI, retailers are able to adapt the route of their goods without unnecessarily slowing down the supply chain. They can intelligently re-distribute stock across open warehouses (and stores, for those businesses able to implement a ship-from-store model), based on known and predicted demand.
Delivering on demand
As governments rolled out national lockdowns and consumers moved shopping habits online, another challenge for retailers has been to maintain timely deliveries. Limited routes, PPE requirements and safety procedures, along with increased shipment volumes going through networks, has meant retailers are having to work harder to deliver direct to consumers on time.
Since the outbreak of Covid-19, many retailers have been transparent in advising consumers to expect delays in deliveries, extending time slots and in some cases removing next-day delivery options. However, even before the uptick in e-commerce fuelled by Covid-19, 26% of online shoppers abandoned their shopping basket when the estimated delivery time was too long; in the US, their perception of speed as a top shipping priority has doubled since last year.
AI technology allows retailers to spot potential bottlenecks in the supply chain, calculate the fastest alternative route and avoid exploitative surcharges in times of disruption. Its ability to rapidly crunch through millions of permutations minimises cost to fulfil orders – saving retailers and consumers money. Combining full oversight of inventory and predicted demand, stock can be optimally distributed across warehouses and stores to be located close to the customer. This enables flexible and efficient fulfilment of orders, allowing customers to receive goods quickly.
Keeping up with the consumers
A further area ripe for adaptation is how retailers can respond to consumer behaviours. Since the outbreak of Covid-19, the physical shopping experience has fundamentally changed.
Whereas before, consumers might have happily browsed, meandering aisles and picking up, examining and trying items out in person, this ritual has been replaced by queuing, one-way systems, and the assumption that most items you touch must be bought. As such, it’s increasingly clear that the trend towards e-commerce as a familiar, hassle-free experience will continue.
While retailers that rely heavily on footfall are struggling (Burberry has seen a 75% decrease in European sales on last year’s figures), online retailers such as ASOS have reported a jump in sales. This means that intelligent logistics will feature prominently in a retailer’s stability; the entire value chain, from manufacturing hall right to consumer doorstep, relies on consumer habits and efficient operational execution.
AI can identify changing consumer behaviours in these fluctuating environments, using demand planning and predictive tools. Advanced technologies analyse large and complicated data sets to aggregate metrics such as seasonal shopping habits, highstreet sentiment and weather. In trusting AI-generated recommendations, retailers are subsequently able to understand data faster and more intelligently than humans. They can anticipate increases and decreases in demand, and adjust directives like stock levels, resourcing and logistics providers accordingly.
The AI solution
Covid-19’s upheaval of business norms has highlighted the essential need for risk planning. With the move towards e-commerce only accelerating in its wake, along with increasingly demanding and influential consumer expectations, it’s time for retailers to invest in technologies that will allow agile responses and give them a competitive edge. AI offerings can help to streamline costs and operations across the supply chain, understand and predict consumer behaviours, and anticipate and mitigate complications before they hit.
With new markets opening up to e-commerce, traditionally brick-and-mortar businesses like Poundland considering online offerings, and the inevitability of future supply chain shocks such as Brexit and natural disasters, retailers must embrace the benefits of advanced technologies in order to survive and thrive.