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    Advanced Decision Intelligence Drives Modern Warehouse Execution

    The rules of engagement are constantly changing for e-commerce retailers. Every year, consumers expect more from their favorite brands and pure play e-tailers — raising the stakes for both experienced fulfillment providers and new entrants alike. In a recent consumer survey, 75 percent of respondents said they will expect same-day delivery within the next 12 months.

    In this brave new world of great expectations, the race is on to build the infrastructures needed to fulfill these escalating service level agreements (SLAs). When you consider that fulfilling next-day (and even same-day) delivery requires a four-hour order fulfillment cycle time, distribution center (DC) operators will need new tools and strategies to shorten this window. To compete in this environment, operators need perfectly optimized fulfillment processes from the time an order is received until it’s loaded onto a truck.

    E-commerce providers face a volatile mix of challenges, including: 

    • Large volumes of uncertain demand of single-line orders with seemingly infinite varieties
    • A wide range of delivery agreements, from next-day to next-week
    • Seasonal fulfillment spikes that can potentially account for a significant portion of annual profits
    • The ongoing transition from labor- to automation-driven processes

    New Approaches to Emerging Challenges

    To prepare for the future of e-commerce fulfillment, DC operators will need to adopt new technologies that help them balance workflows, prioritize orders, and execute warehouse assignments in real time. Thriving in this environment will require innovative approaches to order fulfillment automation and significant upgrades to warehouse execution agility. Many leading retailers are increasing their investments in new automation software and technologies that will help them adapt to this new era of distribution and fulfillment (D&F).

    At the top of this list is the modern warehouse execution system (WES). Unlike its warehouse automation software predecessors, a WES delivers data-driven decision intelligence to enable:

    • Real-time visibility into order status, inventory and fulfillment operations
    • Dynamic, automated decision making based on order priorities, labor availability and automation system status
    • Accurate predictions and proactive decisions to avoid congestion and provide optimal balance of all warehouse activities impacting order fulfillment

    These advanced WES capabilities represent a giant leap forward for operations that have relied on legacy warehouse automation software. Traditional warehouse management systems (WMS) were designed to handle business transactions and mostly manual processes of large volumes, usually in batches. Because it provides static pre-planning and conventional releasing of fulfillment activities in waves, a WMS isn’t equipped to manage e-commerce fulfillment models that necessitate the ability to make continuous adjustments in real time.

    Similarly, warehouse control systems (WCS) serve a vital purpose — interfacing with material handling equipment (conveyors, sorters, carousels) — yet offer a limited range of dynamic order fulfillment capabilities. They were built to communicate with programmable logic controllers (PLCs) and perform very specific operational functions. 

    In an era of increasing automation and greater integration of man- and machine-driven processes, a WES is a holistic decision-making system built to address the complexities of e-commerce driven order fulfillment.

    Dynamic Optimization from Data and Analytics

    DCs are filled with an array of material handling equipment, automated systems, robotics and manual workstations — all of which are interdependent. A delay or malfunction in any one area can cause cascading effects. Every machine, process and person must be precisely orchestrated to maintain efficiency and productivity.

    But too often, these impacts are either not apparent or are overly complex, and put meeting customer SLAs at risk. To consistently achieve daily throughput targets and meet profitability goals, DC operators need visibility into every facet of warehouse operations. This is where a WES demonstrates its power and unique capabilities.

    A WES collects and analyzes data from every connected system and process to enable intelligent decision making within the following critical order fulfillment functions: 

    Routing — Carton, tote and item routing based on a license plate number (LPN) are the “bread and butter” of WCS capabilities. A WES impacts larger business flows by tracking the contents within the totes — not just a tote’s LPN — to inform real-time, smart routing decisions based on the next-best destination.

    Order prioritization — DCs must continually balance a variety of delivery windows and customer SLAs, as well as both store and direct-to-consumer orders. A WES weighs every factor to determine the most optimal release timing, fulfillment process and execution path.

    Order release — A WES accurately predicts order processing time, tracks system capacity, and provides optimal release sequencing to ensure on-time shipment — all while continuously balancing the load on the entire fulfillment system, from picking to shipping.

    Labor management — A WES evaluates individual picking rates and tasks in the queue to forecast labor requirements and optimize fulfillment workflows by proactively assigning resources to the areas/zones based on the workload.

    Storage optimization — Fixed storage and slotting allocations are the norm for most DCs — whether automated storage and retrieval systems (AS/RS) or other inventory locations. A WES maximizes utilization while minimizing retrieval time with dynamic storage optimization.

    Pick path optimization — A WES determines the optimal sequence of picking-related tasks to maximize picking efficiency, minimize employee travel times, and optimize automated processes based on real-time conditions.

    Empower Decision Support with Machine Learning

    A modern WES utilizes a combination of system data, optimization techniques, machine learning (ML) algorithms and artificial intelligence (AI) to empower a full spectrum of data-driven decision making. It delivers powerful insights that can be grouped into three fundamental categories.

    Descriptive/diagnostic — Through data mining and aggregation of historical and real-time data, a WES can generate summaries and present visualizations of activities, also known as business intelligence (BI). This information provides consolidated retrospective reports on which DC operators can base decisions — such as daily throughput and labor performance — but does not require ML/AI algorithms to process the data.

    Predictive — By utilizing ML/AI prediction models to generate forecasts, a WES can empower DC operators with future operational insights in real time. These could include a list of forecasts and their potential outcomes, such as the probability of congestion at a conveyor or pick station. This information allows operators to predict and prepare for various order fulfillment demands and scenarios.

    Prescriptive — Advanced optimization techniques, coupled with ML/AI algorithms, can be leveraged to create dynamic decision-making capabilities, providing operators with a menu of recommendations to achieve specific outcomes. This information then instructs automation equipment, systems and machines on how to proceed with the most optimal tasks. A WES can be configured to make these decisions autonomously or require human review and approval. This gives DCs the option to bypass the need for human intervention when making real-time optimization decisions — to reprioritize, balance operations and meet SLAs — or leave critical decisions in the hands of operators.

    Case in Point: Smart Order Release

    Let’s look at an example of smart order release and sequencing via a prescriptive type of ML algorithm. The algorithm looks at current orders in the queue and compares potential order sequences to determine which could yield the most efficient and productive results. This calculation evaluates various dynamic factors of the fulfillment ecosystem, such as: the number of orders, the time to complete tasks, picking travel and dwell times, inventory locations, conveyor status, put wall availability and more.

    By sequencing orders and releasing them based on the best-case scenario, a WES can significantly reduce unnecessary and inefficient over-processing and deliver substantial financial benefits. Since algorithms are based on exponential equations, there’s no limit to the number of orders the system is capable of calculating, and these calculations grow with the number of orders. What’s more, these self-learning algorithms can detect existing patterns to limit the amount of calculations needed.

    Simulation Results

    Based on assumptions of a typical e-commerce operation, we’ve compared a WES with no intelligence (using first-in, first-out order processing) to simulation models that automate intelligent order sequencing. The results indicate the potential for substantial financial gains, even with the most conservative estimates of KPI improvements.

    • Increase throughput by 2 percent = $832k in additional revenue
    • Improve on-time shipments by 1 percent = $499k cost savings
    • Improve utilization by 3 percent = $295k labor savings

    In this scenario, smart order sequencing delivers annual financial benefits of more than $1.6 million.

    Prepare for a More Predictable Future

    While not all WES software is created equally, Momentum™ WES from Honeywell Intelligrated is equipped with our Decision Intelligence capabilities to deliver the cutting-edge decision support companies need to address the ever-increasing demands of modern fulfillment. Our agile, state-of-the art software architecture is built with the extensibility to scale with your future needs.

    We’ve engineered Momentum to seamlessly integrate with homegrown and leading off-the-shelf WMS systems, as well as connect to advanced automation, robotics, AS/RS, and a variety of order fulfillment technologies. By combining this robust software with an array of automation equipment and systems, Honeywell Intelligrated can deliver a robust, single-vendor solution that will grow wherever your business demands take you in the future.