3
min read

3 AI Baby Steps Any Retailer Can Take to Begin Supply Chain Automation

Artificial Intelligence (AI)
Supply Chain
3
min read

3 AI Baby Steps Any Retailer Can Take to Begin Supply Chain Automation

Artificial Intelligence (AI)
Supply Chain

In today's fast-paced retail landscape, staying ahead of the competition requires embracing innovative technologies. Supply chain automation powered by Artificial Intelligence (AI) has emerged as a game-changer for retailers aiming to streamline operations, reduce costs, and enhance customer satisfaction. For those just starting on their automation journey, taking a few initial steps can yield remarkable results. In this blog post, we'll explore three AI-driven baby steps that any retailer can take to initiate their supply chain automation process.

Step 1: Ensure accurate inventory counts 

Whether your goal is to create an AI algorithm for an accurate demand forecast, reduce your inventory carrying costs or simply to reduce product waste, you must look at the incoming data. If these data points are not accurate, retailers will struggle to make any impact with their desired supply chain upgrades. 

Accurate data is crucial for automating a supply chain as it forms the foundation for informed decision-making and optimized processes. Reliable data ensures precise demand forecasting, inventory management, and resource allocation. Inaccurate data can lead to disruptions, overstocking, stockouts, and increased costs. Automation relies on algorithms that depend on accurate historical and real-time data to enhance efficiency and responsiveness. Ultimately, accurate data empowers operators to streamline operations, reduce wastage, and meet customer demands effectively in a dynamic business environment. 

Step 2: Capture more frequent inventory counts

Inventory counts are traditionally slow and inaccurate. As a result, many retailers have decided to reduce the number of counts and the items counted. Frequent data updates are vital for supply chain automation as they provide real-time insights into dynamic market conditions, demand fluctuations, and inventory levels. Data refreshes enable swift adaptations to fluid scenarios, enhancing decision-making precision. 

In a rapidly evolving supply chain landscape, more frequent data empowers operators to fine-tune processes, reduce response times, and maintain a competitive edge in meeting customer expectations.

Step 3: Capture data across a network

Having comprehensive data from an entire network of locations or restaurants within a brand is crucial for effective supply chain automation. A centralized data repository provides real-time insights into the variability and captures any edge cases when it comes to inventory levels, consumption patterns, and demand fluctuations. Ultimately, leveraging data from all brand restaurants empowers data-driven decision-making, enhancing operational efficiency, and maintaining consistent service levels throughout the brand's network.

Conclusion

When evaluating technologies be sure the solution checks the basics.  At a bare minimum, the inventory solution should be accurate, fast enough where it enables you to count inventory more frequently and can easily be scaled across all your locations. While the prospect of supply chain automation might seem overwhelming, retailers can start with these three AI-driven baby steps to gradually transform their operations.

By implementing AI-enabled demand forecasting, intelligent inventory management, and automated supplier collaboration, retailers can optimize their supply chain, reduce costs, and improve customer satisfaction. As the retail landscape continues to evolve, embracing AI automation is no longer an option but a necessity. So, take these steps and embark on your journey towards a more efficient and competitive retail supply chain.

Check out a recent article where we dig into inventory counting solutions, What Solutions Are Foodservice Operators Using to Automate Inventory Counts. Or better yet, learn more about what Nomad Go is doing with their automated count platform in METAshelf.

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