Automate Warehouse Execution With Decision Intelligence

If you manage or operate a distribution center (DC) for an e-commerce retailer, the following scenario might sound familiar.

At the beginning of the day, your order queue is filled with a combination of direct-to-consumer and store replenishment orders, with new ones coming in every minute. Your customers and store operators are depending on you to meet their chosen service level agreements (SLAs) — whether that’s the same day, the next day or next week.

But meeting a wide range of SLAs is complicated. You find yourself constantly juggling resources, order release plans and routing constraints in an ever-changing environment — all while material handling equipment (MHE) and labor availability are constantly in flux. Like firefighters, floor managers respond to throughput bottlenecks and process emergencies as they emerge throughout the day. And when a problem arises in one area, it often creates a domino effect of downstream consequences.

If you can relate to this scenario, then you know that these management inefficiencies can also lead to costly productivity losses, idle equipment and underutilized labor. There comes a point when the prospect of managing daily DC complexities stretches the limits of human capabilities and becomes unsustainable.

Leveraging data science to optimize fulfillment activities

At Honeywell Intelligrated, we created our Momentum warehouse execution system (WES) to address these escalating challenges. Empowered by an advanced data analytics engine that we call Decision Intelligence, Momentum WES removes the burden of manual management of warehouse execution complexities. Instead, it automates the entire fulfillment process based on the most optimum release and routing strategies for orders of varying priorities.

As next-generation execution software, Momentum WES is engineered to provide significant advancements in order fulfillment and execution capabilities. Decision Intelligence leverages artificial intelligence (AI) and optimized machine-learning (ML) algorithms to raise your warehouse execution intelligence where you need it most:

• Enabling dynamic order fulfillment optimization based on continuous and ever-changing priorities
• Driving productivity, efficiency and profitability through automated, data-driven decisions
• Monitoring real-time warehouse conditions and resource availability

Case study: Restoring fulfillment equilibrium

We were able to test these robust data science capabilities during a particularly trying time for a home improvement retail customer. Like many retailers who were subjected to near-continuous peak volume levels daily during the pandemic, they needed to quickly adapt to shorter fulfillment windows and emerging inventory replenishment challenges. Momentum WES with Decision Intelligence enabled them to meet increased order volumes and drive efficient warehouse utilization using their existing mix of MHE, automation and labor.

This journey began with order prioritization, where the DI’s smart order prioritization engine receives data from multiple decision points throughout the warehouse in real time. It then evaluates the range of customer SLAs and corresponding delivery expectations — from standard shipping windows to same-day rush orders to store replenishment — as well as the predictive processing and travel times of different types of products throughout various picking zones.

With order priority data, we were then able to program the Smart Release and Smart Routing features of the Decision Intelligence engine. Smart Release prioritizes each individual order to ensure that it is fulfilled and shipped on schedule, while Smart Routing directs products and orders to make sure they follow the most optimal paths to completion. As Decision Intelligence continues to monitor each order’s progress through the material handling system, Smart Routing evaluates conveyor status and workstation availability to determine the next best destination (or route) for each order.

Upon implementation, DC managers reported that Momentum WES has brought their operation back into equilibrium — increasing throughput and improving their ability to meet SLAs, while balancing capacity throughout inventory zones, MHE and workstations.

In our simulations of multiple e-commerce operations, we compared traditional warehouse execution methods — with no data science or automated decision-making capabilities — to data-driven optimization techniques. Our simulation results indicated the potential for substantial annual financial gains of more than $1.6 million in revenue.

To learn how Momentum WES with Decision Intelligence can remove the burdens of manual warehouse execution management, please read our recent On The Move article.

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