Online retailers have faced many challenges over the past two years. Fulfilment models remain under unprecedented pressure, owing to surging demand, supply chain disruption and now soaring prices. With governments considering environmental requirements in the wake of COP26, what are the key supply chain trends for 2022? Emma Dempsey, CEO, James and James Fulfilment takes a look at what’s likely to change in the year ahead.
Adding contingency to meet commitments
With peak season 2021 now over, we can expect to see a significant rebalancing of the supply chain. The frailties of once popular just-in-time models have been exposed over the past two years. Faced with global supply chain disruption that is expected to extend throughout the year, retailers are recognising the importance of adding contingency to ensure customer commitments can be met.
Companies will be compelled to carefully consider where best to locate resources, as the need to increase stock holdings puts further pressure on already stretched warehouse spaces. It is likely that micro-warehouses will pop up in towns and cities across the UK, while larger companies will also review their global distribution strategies to avoid disruption issues and enable products to be fulfilled closer to the customer.
Overcoming barriers to global trade
Companies’ global strategies will be further aided by the simplification and automation of charges relating to duties and taxes. As highlighted by Brexit, customs confusion often results in unnecessary friction in fulfilment services. Many businesses have been deterred from costly global operations due to the high overheads endured throughout cross-border trade, with products held up at customs and goods being returned to suppliers.
Systems to automate this process and add far more clarity will become more widespread in 2022. Not only will this overcome the barrier to global trade, it will also unlock the local fulfilment model.
Insights from Artificial Intelligence
While micro-warehouses and extending global fulfilment models to get closer to customers require additional capital investment, they also bring new opportunities to service the customer.
In order to take advantage of these opportunities, companies will need access to accurate, real-time data. Initial warehouse location strategies will be informed by data points on rates of sale and stock turnover, as well as global patterns of customer demand – insights which will then be fed into replenishment models. The role of machine learning and artificial intelligence (AI) in optimising these distributed fulfilment models will be increasingly important. Intelligent warehouse allocation rules will enable different customer offers to be made based on stock location and quantity, as well as cost and speed of shipping, and the rate of sale for stock in each area.
Environmental requirements
With COP26 prompting calls for firms to show they will hit net zero, companies cannot ignore the need to better understand their environmental footprint. Online retailers will be required to gain a better understanding of every stage of the supply chain, starting at manufacture all the way through to the last mile and returns. The rise of local fulfilment could also mean a reduction in delivery mileage and associated carbon footprint, but companies should review in depth information to understand the implications in detail.
Effective, efficient supply chains are already driven by data – the onus is now on companies, and fulfilment providers, to surface new data points that shed light on the environmental impact of their businesses. Utilising AI will also be vital in the drive towards net zero. Environmental impact metrics, such as carbon footprint, will provide companies with in-depth understanding of their environmental performance, allowing them to both meet both government requirements and fulfil consumer expectations.
Preventing returns
Retailers need to ensure that the perennial problem of returns is addressed more effectively in 2022. Not only will this counterbalance the cost of rising inflation, it will also reduce the environmental impact of additional, unnecessary journeys. Analysing the vast quantities of data collected throughout the supply chain can provide amazing insight into returns trends.
Some vendors are already recognising the value of using returns data to inform strategy. If products are being sent back repeatedly due to sizing, redescribing them on the website can prevent further returns. In addition, this information can be fed back into the manufacture process. Using AI and machine learning to analyse detailed returns data will also surface new insights, further enhancing companies’ understanding of customer behaviour and performance by SKU. By proactively exploring and using this insight over the next 12 months, businesses will gain far greater understanding of returns, enabling them to implement new policies to reduce the financial and environmental impact.
