AI in Retail: 5 Practical Uses for Supply Chain Resilience

Every supply chain manager strives for efficiency, cost reduction and visibility. And while the last couple of years raised particular challenges, the push towards efficiency in the pre-pandemic years shaped supply chain management, and not always for the better. In an effort to reduce redundancies and increase efficiencies, there was a noticeable casualty that compounded the immediate- and short-term effect of the pandemic on supply chains: flexibility.

For retail supply chains to be resilient in 2022 and beyond, they must be flexible. The pressure to fulfil fast is felt in the retail industry like no other. Consumer expectations have drastically impacted business-as-usual in the short-term and are a major influencer in longer-term strategic planning. Technology has played a large role in balancing the efficiency-flexibility tradeoff, especially in the areas of Machine Learning and Artificial Intelligence where data analytics drives decisions.

Why focus on resilience?

Simply put, resilient companies win. The ability to shift quickly and make fast decisions means companies can withstand stress and recover from external shocks faster and stronger than competitors. Here are five key optimisation areas which can impact supply chain resilience for the better.

 

Demand planning

ai-in-retail-demand-planning

The pandemic’s impact on the supply chain highlighted the need for better predictive tools. Demand forecasting and planning is pegged as one of the top ten areas of technological investment for 2022. A recent study by IDC highlights that by 2023, 50% of all supply chain forecasts will be automated using AI, which is expected to improve accuracy by five percentage points.

Companies know that investing in this area helps them become more agile in response to demand changes, allowing them to analyse data that they previously couldn’t because of the complexity or volume of it. This contributes to better and faster decision making, and overall retail resilience.

In practical terms, AI-powered demand planning allows companies to:

  • Cut storage and handling costs by only holding the stock needed at the time and reduce handling expenses
  • Prevent missed sales and increase revenue due to stock-outs by ensuring on-demand access to goods
  • Boost customer experience and retention rates with consistent and reliable deliveries by placing stock in locations where demand is forecast
  • Reduce risk and increase resilience, rapidly adapting to changes in demand and avoiding potential bottlenecks with dynamic and predictive inventory optimisation

 

Dynamic carrier switching

ai-in-retail-dynamic-switchingAnother impact of the pursuit of efficiency in recent years, like opting for “just-in-time” models, was that companies became over-reliant on sole suppliers and carriers. Supply chains suffered because companies, at the mercy of carrier disruptions and tariffs, had no spare capacity and inventory buffers.

Unlike single-sourcing, a multi-provider carrier strategy spreads logistics activities across multiple providers. Instead of relying on one provider to fulfil all orders, organisations work with 3-5 providers to find the best value route taking into account the relevant criteria like cost, delivery service, appropriate delivery date, performance reliability, special handling requirements, and customer communications.

Resilience comes in the form of savings on shipping costs (up to 30% according to our market study), avoiding potential surcharges, the ability to switch to another carrier if one experiences stress, and improved delivery and return metrics.

 

Drop-shipping to capitalise on trends

Drop shipping is a retail fulfilment method where a business doesn't physically stock the products it sells. Instead, they work with third-parties to ship directly from manufacturer to customer. The benefits of this method include reducing costs on overheads and warehouse storage, expanding on or switching offerings due to seasonal or unexpected demand changes, and eliminating the need of inventory management.

Of course it’s not an option for every retailer, as it is a numbers game. The volume of sales needs to be above a level to see positive ROI on individual items.

 

Improving CX with real-time delivery and returns updates

ai-in-retail-improving-cxWe all know how stretched customer service and experience teams have been over the last two years dealing with order tracking and customer complaints. Sometimes, having an answer with an exact location even if a shipment is late, is enough to de-escalate a bad CX ticket. Knowledge, as they say, is power.

Investing in a real-time monitoring delivery and return solution lets customers follow their order in real-time via a fully white-labelled tracking link. It removes uncertainty, and puts an end to the frustration of tracking goods via third-party sites. It can also lower indirect costs and employee stress levels, by reducing the burden of order tracking internally.

 

Intelligent dispatch and routing

Of course, the book doesn’t stop at shipment. For full-cycle retail resilience, companies need to have visibility into what’s happening in dispatch and routing. Tools that utilise AI to process and analyse the vast amounts of structured and unstructured data within the logistic networks can identify trends, and make optimised decisions on where, when and how to route each order to ensure delivery is efficient, on time, and at the right price. This will be a real area of resilience in 2022 and beyond.

Investing in AI tools that enable better visibility and decision making is key to resilience. And it’s only going one way: an Accenture study found that in 2022, 79% of executives want increased use of automation, AI and robotics to create full supply chain visibility.

 


 

Want to learn more? We're running a webinar at 12:00 (GMT) on 2nd March, 2022 on how to use AI for Retail Resilience. Register here.

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