Embracing the Magic Button: Harnessing AI for Optimized Warehouse Slotting

In a recent conversation with a well known brand, I encountered a familiar quest: the search for a "Magic Button." This brand, with over 30,000 SKUs, has been relying on intuition and gut feel to determine the optimal slotting of products within their warehouse for over 15 years. Each season, they rely on their intuition to know when to move the former season's clothing to the back and the new season's clothing to the front, a process that has become increasingly inefficient and time-consuming.

As their inventory has grown, so has the complexity of their operations. Their pickers now navigate longer and more convoluted pick paths due to suboptimal slotting. To combat this, they’ve started exporting data and running pivot tables to identify the best locations for their products—a labor-intensive practice costing tens of thousands of dollars annually.

The Dream of a Magic Button

I've often joked with clients about the elusive "Magic Button" we all wish for. Thanks to advancements in artificial intelligence (AI), this dream is closer to reality than ever before. While an all-encompassing Magic Button doesn’t yet exist, AI models can now perform specific tasks almost instantly. Imagine a button that could execute an instant slotting analysis on demand—today’s technology makes this possible.

However, the real challenge lies in the brand’s own technology infrastructure. The brand I was speaking with uses a legacy enterprise resource planning (ERP) and a warehouse management system (WMS) that lack modern data integration capabilities. While their systems can export data, they cannot import execution tasks like move and putaway tasks, limiting their efficiency.

These legacy systems were created in an age when there was limited ability, or any ability at all, to share execution tasks from one system to the other. Times have changed and digital agility is key. 

Modern Technology Stack: The Foundation of the Magic Button

This situation highlights the critical need for a modern technology stack built on contemporary architectural practices. Enter the MACH principles—Microservices, API First, Cloud Native, and Headless—which provide the backbone for scalable, flexible, and efficient systems.

I’m going to explain the benefits of these principles outside of the MACH order. While MACH is a great acronym, I think for educational purposes, it’s easier to understand in a different order. 

Cloud Native

Cloud Native is the foundation of any modern product. Many older systems were designed for being hosted locally on servers and have simply been ported to the cloud, resulting in suboptimal performance, security, and scalability. True Cloud Native systems are designed and optimized for the cloud from the ground up, ensuring optimized execution and scalability.

Headless Architecture

The term "Headless" refers to separating the backend from the frontend. This architectural approach decouples the database and backend systems from the user interface frontend system, allowing for greater flexibility and performance. For instance, a headless system can handle complex data processing tasks without slowing down the user interface on the frontend.

Microservices

Microservices take this a step further by breaking down the application into independent services that can be developed, deployed, and scaled independently. This modular approach allows for a more stable upgrade process and better performance. For example, a brand might use a separate inventory forecasting tool alongside their WMS, each operating independently but cohesively.

API First

API (Application Programming Interface) First design ensures that systems are built with integration in mind from the start. APIs act as connectors, facilitating seamless communication between different parts of the system. This approach allows companies to make changes efficiently and integrate new technologies easily.

The Road Ahead: Flexibility and Innovation

I firmly believe that the future of software will rely heavily on flexibility and connectedness. The rapid development of AI applications means that we need systems capable of integrating with these advancements without hindering innovation. Imagine the power of a software solution that offers their own take on AI and how to optimize a brands business, but also encourages and is architected in a way to allow the individual brands to connect whatever system is best suited for the job, whether that be an AI model or a microservice developed by another vendor.

The brands that embrace the modern principles of MACH and collaborative visibility will provide a whole new definition of digital agility. These are the brands that will drive innovation and gain market share over the coming years. 

Conclusion

The Magic Button is no longer a distant dream; it’s here and evolving rapidly. To fully leverage its potential, we must prioritize software solutions that not only showcase current AI capabilities but also welcome further innovation—whether that be tech-agnostic integrations or blockchain security. By embracing modern architectural practices, we can ensure that Osa Commerce develops solutions that are flexible, scalable, and ready for the future of AI-driven optimization for the future brands, retailers, and their logistics partners.

As your business continues to evolve, make sure to evaluate different products, considering not just AI abilities and future roadmap, but their capacity to integrate seamlessly with other applications, enabling continuous innovation and efficiency.

Be sure to reach out to learn more about how the Osa Collaborative Visibility Platform can help unleash innovation for your supply chain.