Why build-to-order warehouses demand smarter WMS solutions

Editor’s note: Sreekumar Somasundaram is a senior supply chain technical program manager at AWS. This article and its content was created prior to his current position with AWS.

This article examines the main complexities involved in implementing off-the-shelf warehouse management systems (WMS) in “build-to-order” environments and provides evaluation criteria for selecting appropriate WMS solutions. However, while numerous vendors offer WMS solutions and organizations have the option to develop custom systems, “build-to-order” environments present unique challenges due to variations in product dimensions, handling, and storage characteristics. Early identification of these complexities informs both WMS product selection and implementation strategies, guiding decisions between custom development and off-the-shelf solutions.

What is a WMS and why are organizations implementing WMS?

A warehouse management system (WMS) efficiently manages warehouse operations by directing work processes, optimizing travel path, eliminating manual decision-making, providing traceability, and maintaining precise control over material movements. Unlike traditional inventory management systems, a WMS functions as an execution system, dispatching tasks to operators, directing material movement, and tracking processes from warehouse equipment loading to final placement.

Some of the key distinctions between WMS and traditional inventory management systems include:

1. When receiving mixed-material pallets, a WMS enables single-scan processing through the “license plate umber” (LPN) functionality. This feature allows physical storage containers (such as pallets or cartons) or logical containers to be transacted at the LPN level without requiring individual item level scanning.
2. A WMS generates and manages all warehouse tasks. Operators log into their radio frequency scan (RF) guns running WMS software, which provides specific work assignments throughout their shift. For example, truck-loading pickers receive picking tasks through their RF scan guns, which include detailed location and inventory information for forklift or pallet jack operations, as well as instructions for drop locations.
3. A WMS provides supervisors with warehouse control boards and dashboards offering 360-degree visibility into warehouse operations, enabling real-time control over material movements and identifying potential efficiency improvements.
4. A WMS enables the creation of advanced picking and put-away rules. Put-away rules direct operators to specific storage locations, optimizing space utilization by grouping similar materials or positioning early shipping items near docks. Picking rules determine the optimal material selection for order fulfillment, ensuring that high-quality products are chosen for specific customers.
5. A WMS provides the capability to connect inbound material directly to outbound by linking outbound orders to inbound supply through planned and opportunistic cross-docking, thus eliminating the need to put-away from receiving to storage followed by picking to outbound, significantly increasing the operational efficiency through reduced touches, saved storage space and on-time order fulfillment.

The build-to-order challenge

In build-to-order environments, each manufactured item is uniquely configured for customer specifications. These products vary significantly in dimensions, storage requirements, packaging needs, and handling characteristics. Furthermore, each item is linked to an outbound order with specific shipping dates, making efficient storage location selection crucial for optimizing picking operations and ensuring on-time delivery.

The complexities of implementing WMS in build-to-order environments can be examined through four critical warehouse processes:

1. Put-away challenges
2. Location capacity determination
3. Interdependency between location capacity determination and put-away complexities
4. Outbound picking operations

Put-away challenges in build-to-order environments

Introduction to system-directed put-away:

A key advantage of WMS implementation is its “system-directed put-away” capability, which eliminates manual decision-making by automatically guiding operators to appropriate storage locations. The system uses built-in intelligence to execute pre-configured rules, optimizing travel distances and enhancing operational efficiency.

Build-to-order vs. build-to-stock: A critical comparison

To understand the complexity, consider this scenario:

• In a build-to-order environment, a manufacturing line produces 10 unique items for 10 different customer orders. When an operator loads these items onto a cart, the WMS must determine 10 distinct storage locations.
• In a build-to-stock environment, the same 10 items would be identical, requiring only one storage location.

This fundamental difference illustrates why build-to-order environments require more sophisticated WMS capabilities.

The two-step put-away process

Step 1: Location identification and rule processing

When operators scan items for put-away, the WMS must process complex rules incorporating multiple criteria. For example:

Sample put-away rule: For Customer A products: IF height < x inches AND weight < Y lbs AND ship date = current date + 6 days THEN direct to Aisle 1 lower-level locators ELSE IF height > x inches OR weight > Y lbs THEN direct to Aisle 1 oversize lower-level locators"

Key attributes processed by WMS:

• Customer association
• Material dimensions
• Associated outbound order and ship date

Additional complexity factors:

• Products with earlier shipping dates need locations closer to dock doors
• Multiple customer-specific business rules must be processed simultaneously

Step 2: Optimizing put-away drop travel sequence

Once locations are identified, the WMS must direct the put-away operator to each location to deposit the material:

• Determine the most efficient order for reaching multiple locations
• Calculate optimal travel paths. Example - Using X, Y, and Z Cartesian coordinates for distance calculation
• Minimize travel time between locations

Critical WMS capabilities required to handle the above challenges:

1. Rule modeling and execution:

• Ability to configure complex, multi-attribute rules
• Fast processing of multiple rules simultaneously
• Support for diverse product characteristics

2. Warehouse travel path optimization:

• Sophisticated warehouse location mapping capabilities
• Efficient travel path determination algorithms

Location capacity determination challenges in build-to-order environments

In build-to-order environments, product variability presents unique challenges for location capacity management. Unlike build-to-stock operations with standardized products, build-to-order warehouses must handle:

• Significant variations in product dimensions
• Wide ranges in product weights
• Diverse shape configurations
• Unpredictable space utilization patterns

Traditional WMS solutions manage location capacity through:

• Maximum unit quantity limits
• Weight capacity thresholds
• Volume capacity restrictions
• Automatic location availability status when thresholds are reached

For example, a typical location might be configured with:

• Maximum capacity: 1,000 pounds OR
• Maximum units: 5 items

Once either limit is reached, the system automatically marks the location as unavailable.

The build-to-order complexity

In build-to-order environments, standard capacity configurations often prove inadequate because:

1. Theoretical vs. actual capacity:

• A location configured for five units might be full after three items
• Unique product shapes may prevent optimal space utilization
• Configured thresholds may not reflect real space availability

2. Dynamic space requirements:

• Each product's dimensional variations affect capacity differently
• Standard capacity calculations become unreliable
• Pre-configured parameters may not reflect actual storage possibilities

Interdependency between location capacity and put-away operational challenges in build-to-order environment

In build-to-order environments, when automated capacity management often falls short due to product variability leads to manual overrides by operators, creating a complex interplay between capacity determination and put-away processes.

Consider a multi-operator conflicts example scenario:

• Operator P1 is putting away items in locations L1 to L30
• Operator P2 is assigned overlapping locations L1 to L10
• P1 finds L10 full, marking it unavailable
• P2's route, which includes L10, is now invalid

Critical WMS capabilities required:

• Real-time processing of operator capacity update and dynamic alternative location determination for all active put-away tasks originally destined to go to the location
• Real-time put-away task modification for all the impacted operators

This situation demands a WMS capable of instantly recognizing manual capacity changes and swiftly adapting all active put-away tasks to maintain efficiency.

Outbound picking operations challenges in build-to-order environments

Palletization strategy

In build-to-order warehouses, palletization—the consolidation of products sharing destinations and shipping dates—often occurs during put-away rather than picking. This approach optimizes warehouse space, expedites truck loading, and maximizes handling efficiency.

Practical application

Consider a typical build-to-order scenario:

• Five unique orders from one customer
• Same ship date, different custom products
• Single warehouse location assignment: As the orders share the same customer destination and ship date, it’s common to group all the products in the same location in the warehouse assuming capacity is available.
• Consolidated palletization during put-away

The process flow:

• Manufacturing produces custom items
• WMS directs all items to the same warehouse pallet location
• Items consolidate on a single pallet
• On shipping date, one picking task retrieves entire pallet

The build-to-order challenge:

While standard WMS solutions support basic pallet picks, complexity arises when:

• Multiple orders and SKUs share one pallet
• Items have diverse characteristics
• System must update outbound order fulfillment status for multiple orders simultaneously when the pallet is loaded onto truck

This differs significantly from build-to-stock environments, where pallets typically contain identical items tied to single orders. Therefore, WMS selection must carefully consider the system’s ability to manage these complex, multi-order pallet picks efficiently.

Conclusion

The implementation of WMS in build-to-order environments presents unique challenges that standard solutions often struggle to address. Through the examination of four critical processes—put-away operations, location capacity determination, capacity-put-away interdependencies, and outbound picking operations—we can see how build-to-order environments require sophisticated WMS capabilities beyond those needed for build-to-stock operations.

Key considerations for successful WMS implementation in build-to-order environments include:

• Complex rule processing for variable product characteristics
• Dynamic capacity management capabilities
• Real-time adaptation of location determination based on operator interventions
• Multi-order palletization support

Organizations must carefully evaluate WMS solutions against these requirements, as standard off-the-shelf systems may require significant customization to effectively manage build-to-order operations. Early identification of these complexities during the selection process is crucial for successful implementation and optimal warehouse performance.

About the author:

Sreekumar Somasundaram is a senior supply chain technical program manager at AWS, specializing in warehouse and transportation management dystems implementation. With over 18 years of experience, he has been involved in developing and implementing logistics technology solutions across complex business environments. A mechanical engineering graduate with multiple professional certifications including Project Management Professional (PMP), Java and Oracle Programming, Transportation Management, and Supply Chain certifications from MITx, he brings a unique combination of technical expertise and business acumen to his role. His extensive background encompasses logistics solutions architecture, business analysis, and software development for warehouse and transportation systems. Throughout his career, he has successfully led WMS and TMS implementations for multiple Fortune 500 companies.

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