Optimising e-commerce business for the new normal

This article is brought to you by Retail Technology Review: Optimising e-commerce business for the new normal.

By Wayne Snyder, VP Retail Industry Strategy EMEA at Blue Yonder.

The global COVID-19 pandemic has undoubtedly disrupted the retail sector significantly. With many stores forced to close their doors over lockdown, there has been a sudden and rapid rise in online shopping.

Recent ONS figures show one-third of all shopping transactions were carried out online in May 2020, up from less than 20 per cent in 2019. This also doesn’t appear to just be a short-term trend, as research has shown almost two-thirds of European shoppers who have shopped online more during the crisis plan to continue to do so in the future. 

Ongoing social distancing challenges mean that nearly all retail growth over the next year is anticipated to be online. Because of this, the digitalisation of the store and the provision of a seamless and harmonised retail experience will be imperative, as will having the right foundations for a successful e-commerce business. 

The disruption brought about by COVID-19 has shone a light on retail supply chains in particular and in many cases, has uncovered inefficiencies. A recent study from WMG, University of Warwick revealed more than half of retailers had to manually intervene to effectively respond to the fluctuation in demand and supply in recent months. The same study also highlighted the extent of the workforce issues faced by retailers, with 59 percent of warehouse and 48 percent of store operatives affected by quarantine or illness. This often resulted in the closure of online operations and the need to recruit temporary staff.

Retailers now need to start prioritising investment so they can create supply chains with greater flexibility, visibility and automation. “Fail to plan, plan to fail” is a tried and tested mantra, but for retailers, it is proving increasingly difficult to follow in volatile times. Whether it’s constant changes in tastes and associated assortment needs, or forecasting warehousing capacity or workforce requirements, it has never been more important for retailers to respond quickly and appropriately and have a connected, end-to-end supply chain plan in place to meet their customers’ needs.

Overcoming supply chain complexity with machine learning and artificial intelligence

Harnessing technology such as machine learning (ML) and artificial intelligence (AI) can play a key role in enabling retailers to quickly respond to changes in consumer behaviour and make intelligent decisions. By ingesting external factors such weather and local events, AI and ML powered systems do not simply look to the past to try and predict the future, but also evaluate the true drivers of demand to create accurate forecasts by item, location and day. By dynamically understanding the interrelationships between many complex factors, retailers can then turn the data into actionable insights and respond and react accordingly. 

Running a successful e-commerce business can be a challenge given the complexity of supply routes. Inventory can reside in many different locations, from centralised or micro-fulfilment centres through to dark stores. On top of this, in-store picking only adds to the challenge, meaning that retailers need to have full visibility across their supply chain to make online fulfilment decisions efficiently. Through aligning demand to supply, retailers can better evaluate the optimum stock requirements at every location on a risk and reward basis. Furthermore, by understanding the variability of demand, AI and ML can be applied to maximise sales and margin while minimising returns and costs. If retailers can create an automated, digital view of their network they will be in a much better position to ensure they have the right level of inventory in all locations.   

Optimising price 

Managing margin is another crucial element in creating a profitable online business. However, setting the right price has always been a complex question for retailers. On the one hand, a high price could risk losing customers – according to McKinsey, customers will not return to a retailer if prices are over 30% higher than competitors – whereas a low price leaves them with little-to-no profit. Promotions have been a common tactic over the past few years to drive more sales, but retailers need to find the right time to do this. With so many factors in play, retailers can struggle to know when to set the right price. Using AI and ML can help retailers to make the right pricing decision quickly and automatically. By understanding true price elasticity, the right pricing decision can be made, whether it be everyday pricing, promotions, or markdown. 

Efficient operations to meet real-time challenges

Whether it’s operating a large omni-channel distribution centre, a dedicated online warehouse or a micro-fulfilment centre, speed and efficiency will be imperative to retailers as they scale their online businesses. Technologies such as IoT and robotics will undoubtedly play a growing role in meeting customers’ ever-increasing demand for fast delivery, from automated robot pickers in the warehouse, to driverless vehicles on the road. However, the human workforce will still be hugely important. During the COVID-19 pandemic, online businesses have needed to quickly onboard warehouse and delivery staff, and therefore task prioritisation will become key as employees juggle multiple activities. Ultimately, the harmonisation between humans and technology will be what enables online retail operations to become more efficient. 

It’s hard to predict what will happen in the next 12 months. However, what is clear is that recent events have accelerated digitisation in the retail industry. If retailers have any chance of remaining competitive, they must ensure their supply chains are flexible and robust enough to cope. With the right supply chain platform and technological foundations, retailers can grow their e-commerce operations and most importantly, meet customers’ expectations.