Data is at the heart of any eCommerce operation, and where there is data, there is also the potential for Artificial Intelligence-driven improvements.
There are endless opportunities for AI to improve efficiencies across the eCommerce sector and supply chain, from production planning and warehouse management to predictive machine maintenance and streamlining logistics through automation. AI route planning also has significant implications for reducing logistical footprints, both in terms of better planning of necessary journeys and internal logistics, but also to identify where wasteful, repeated or unnecessary journeys to move inventory are occurring.
AI systems can enable business growth. Used properly and with access to reliable, quality data, the technology has the potential to drastically improve business resilience and enable scaling. Machine learning can be used to process the vast amount of data available within supply chains and convert it into something that humans can use, for example, to identify trends and correlations to inform stock management.
The advancing technology is also enabling increasingly accurate demand forecasting. For example, AI analysis can identify that a specific type of weather or calendar event leads to increased (or decreased) sales of a product, or how a particular marketing campaign has increased customer engagement with the brand. These insights enable retailers to better manage their stock levels in preparation for expected rises and falls in demand and avoid the pitfall of volatility, which can have a serious impact on eCommerce retailers.
The complexity of stock management
Stock management decisions are crucial to get right for eCommerce businesses to survive and thrive, and a critical area in which AI-powered technology can make an immeasurable difference.
Ordering too much stock incurs higher transportation costs and ties up cash in products that are not needed. These products, in turn, take up unnecessary and costly space in a warehouse. Where perishable, seasonal or otherwise time-sensitive products are involved, mismanaging stock may also lead to high levels of unnecessary wastage and the disposal costs of this.
On the other hand, not having enough stock runs the risk of selling out and missing out on valuable sales, as well as potentially losing customers in the process. Consumers are not used to being disappointed in today's customer-centric marketplace.
Getting the stock balance right means that cash flow and costs can be kept at optimum levels. Efficiency in stock management is also likely to mean less lorry loads and, depending on the type of product, potentially less wastage, both of which are also better for the environment. In addition to being a clear win for the planet, this is also a benefit to the brand, as consumers increasingly consider environmental credentials when shopping.
When growing a customer base and product range, the complexity of stock management builds very quickly. Even with a relatively small number of products, manually keeping on top of supply levels and accurately forecasting what is needed and when soon becomes unmanageable. This is where forward-looking eCommerce operators need to lean on and invest in technology to inform better decision-making and support growth.
Where to begin?
Most eCommerce retailers are likely to be harnessing AI-driven tools in some way, from organisational tools to support streamlined workflows to a myriad of other AI-powered resources that offer support in content creation and even help with branding, creating adverts and imagery.
However, the complexity and cost of investing in this technology for the bigger projects of forecasting and stock management can be prohibitive, particularly for small to medium-sized operations. But there are potential avenues for innovative eCommerce leaders, particularly as the government seeks to grow the UK’s AI market.
For example, Knowledge Transfer Partnership (KTP) schemes, which are part-funded by Innovate UK and supported by expertise from a partner university. These initiatives aim to bring together forward-thinking businesses and expert academics to tackle strategic innovation challenges, such as developing forecasting models. Over an agreed project length, the business is allocated the required expertise and support to see it through, with access to important tools such as supercomputers for running early models. Available funding pots for projects can be significant, alongside some investment from the business itself.
The BridgeAI scheme is another potential route to funding that progressive eCommerce retailers can explore to access the support and specialist expertise they need to bring AI in-house.
A few tips on the process
Alongside the benefits of harnessing AI, there are some key considerations and factors to be aware of before applying for funding, launching and completing an AI-based project. Four top tips include:
1. Applications for funding are likely to be very detailed, but will have the best chance of success if the proper time and resources are committed to filling them out fully with as much detail as possible. You must have a clear business case for putting the innovation to work that demonstrates a clear and plausible understanding of the benefits and impacts that the project will yield for the business and the timeframe over which that will occur. For Innovate UK, for example, the organisation is looking to fund projects that will support growth in the UK economy, so a strong business case is needed to make your project plausibly impactful and therefore worth funding.
2. Before starting on a project, businesses should not underestimate the timescale. The complexity of the data will take time to organise, and the first iteration of an AI model may take several days to run, before refinements.
3. Quality data is the key that underlies any process involving AI technologies. Poor data will yield poor results in any context where AI is applied.
4. Where an external expert is engaged to implement an AI-driven project, it’s important to ensure that when work is nearing completion, there is a comprehensive handover process and sufficient knowledge and understanding in-house before the end of the project to avoid hiccups or interruptions to the use of AI once the external support has finished.
Like any large-scale project, there are likely to be hiccups in the road in the learning process, but the opportunities that AI presents for supporting the growth of eCommerce retailers, particularly in relation to key functions like stock management, are vast.
