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Supply chain management

Leveraging AI to Improve the Supply Chain Efficiency for Grocery Retailers

Leveraging AI to Improve the Supply Chain Efficiency for Grocery Retailers

Food companies are increasingly prioritizing supply chain transparency and efficiency. IBM expanded its food supply chain network, IBM Food Trust, with Carrefour rolling out the solution to all of its brands worldwide by 2022 and Topco Associates, Wakefern, and suppliers Beefchain, Dennick Fruit Source, Scoular and Smithfield joining the blockchain traceability program.

Half of U.S. grocery retailers are turning to artificial intelligence to improve supply chain efficiency. Nearly two thirds of the 50 retailers surveyed, most of which were grocery executives and managers, struggle with a disconnect between systems, and 48% rate their forecasting technology as average to very poor. While they would prefer that each supply chain component work together, few retailers have established a unified process.

The challenge for grocery retailers is that they lack connected systems, with consumers indicating they have separate demand planning, replenishment, allocation and order management systems for store and e-commerce orders. Combined with the fact that a small portion of consumers indicating they don’t manage each of their modules on the same platform, disparate demand replenishment systems appear to be a significant burden to efficiency.

Retailers are being pressured to push past barriers and produce more accurate demand forecasts. The pace of innovation is a significant issue, with 43% of grocery retailers saying their technology can’t keep up with business demands. Forty-two percent describe less-than-optimal synchronization between their inventory and channels, and nearly as many worry about fulfilment complexities, stocking inefficiencies and high product lead time.

When they do invest in needed technology, grocery stores are most inclined to spend on supply chain systems that increase stock availability and decrease stock holding, as 44% invest in new technology because their existing systems are unable to sustain new growth.

In an effort to keep reasonable service levels, food retailers often tend to overstock, but then over course-correct and understock instead. While 43% say they’re challenged by lack of real-time visibility of overall supply chain inventory, six in 10 say they are actively taking steps to address this hurdle and increase inventory visibility.

AI and machine learning hold a lot of potential to improve supply chain efficiency, and forward-looking retailers are already investing in these technologies. Grocery retailers say AI’s greatest potential to improve supply chain management relates to quality and speed of planning insights, while nearly 50% identified demand management as one of the top three areas for AI in the next five years.

One in three food retailers incorporate AI capabilities into their supply chain management processes, and one in four are working toward that goal. Artificial intelligence has the possibility to provide faster, more reliable demand insights, quality management capabilities and real-time updates along the way, the study noted.

woman buying groceries from a stall

Revolutionizing grocery retail with artificial intelligence

Revolutionizing grocery retail with artificial intelligence

While there is a lot of chatter around artificial intelligence and the potential it has to transform retail, it has the capability to impact the most fundamental shopping experiences: the grocery store. Most retailers are moving towards building a better grocery store experience, with the rise of subscription meal kits and competition from pure-play grocery delivery services. With the abundance of customer data and product information available, grocers today are in a special position to apply machine learning and AI in other areas of the business as well.

The grocery industry has a heavy reliance on the movement of perishable goods and with supermarkets struggling to plan, promote and sell goods in a short period of time, it is not efficient. Furthermore, there is a lot of food wastage that happens in this industry - while some of that waste happens in consumers’ homes, a good amount is also lost in the supply chain - anywhere between the farm and the store shelf. And with the various options for when, where and how to buy groceries, grocers compete on prices that are most likely to be profitable.

While grocers are faced with these challenges, they have a fairly good idea of their customer base, who they are and what they want to buy at what price point. With the data available, there is a lot of opportunities utilizing the data in the right manner. This is where AI comes in. Using machine learning capabilities and analytics, more grocers are leaning towards adopting this technology to strengthen the relationship with customers, as well as address some of the biggest challenges they are faced with today.

Leveraging the abundance of customer data

The grocery industry was one of the first industries to collect shopper buying data through programs such as loyalty programs and in-store promotional offers. These methods helped grocers gather information about their key shopper demographic as well as brand preferences. This information is already leveraged to provide discounts and special promotions, the new technology can help enhance the relationship between the grocer and shopper even further.

AI helps grocers to provide a deeper understanding of context and intent by answering the questions behind customers' shopping decisions. It also enables the grocers to parse the customer data and automate the ability to offer targeted promotions to each customer.

Enhanced inventory management

AI can change the entire way of managing inventory. AI can help stock shelves with the right mix of products and ensure that the supply chain is aligned to avoid out of stock products using point-of-sale information and inventory visibility.

Machine learning can build on grocers' rich customer data and combine that with contextual data such as weather, climate, holidays and events - providing a more accurate forecast compared to traditional methods.

Reducing waste

With better inventory management and data analytics, AI can provide better visibility on produce and perishables. Automation can help stores dynamically re-adjust orders based on demand or automate product promotions for the items that are not performing well or selling fast, and helping stores to protect margins, and reducing the amount of food that goes into landfills.

As AI and machine learning advances, grocers should begin to position their systems for a seamless transition towards a highly automated future.

AI must integrate into the commerce platforms and connect across systems to maximize its effectiveness throughout the business. While AI is a valuable tool for customer service, the impact of it will come through its ability to reward loyalty, understand consumer behavior, ensure reduced wastage and increase revenue for the retailers.

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