Case Study: From Manual to Modern – Transforming a Spare Parts Warehouse for an Automotive Company

Christiaan Vander Kuylen | Management Consultant | January 12, 2025

Executive Summary

The following case study explores a comprehensive warehouse optimization project broken into three phases for a spare parts distribution center.

The project aimed to address inefficiencies in space utilization, inventory accuracy, and process standardization while laying the foundation for future automation and scalability. Through a structured methodology, our team transformed a reactive, manual-driven operation into a streamlined, system-led environment.

The project was executed in three strategic phases, beginning with a thorough site and best practice assessment, followed by process mapping and material flow analysis, and culminating in a comprehensive implementation plan.

Six months after implementation, the warehouse realized significant gains:

• Inventory accuracy exceeded 98%, driven by disciplined slotting and scanning protocols.

• Picking times were reduced by 20% through optimized routes and batch strategies.

• Space utilization improved by 30%, eliminating the need for facility expansion.

Beyond these measurable results, the initiative fostered a culture of data-driven decision-making and continuous improvement. Operators embraced new technologies and standardized workflows, while management gained real-time visibility into key performance indicators. By aligning process redesign, technology investments, and workforce engagement, the warehouse is now positioned for scalable growth and advanced automation.

This case study demonstrates how a holistic, evidence-based approach to warehouse optimization can deliver immediate operational benefits and lay the groundwork for long-term competitive advantage in a demanding industry.

About the Client

The spare parts warehouse of an automotive brand serves as a critical distribution hub for these parts across North and South America.

Located on the East Coast, this facility supports a network of dealerships and service centers that demand precision, speed, and reliability.

The warehouse manages thousands of SKUs, ranging from small, fast-moving components like sensors and gaskets to large, irregular items such as body panels and exhaust systems.

The complexity of this inventory profile creates unique challenges: balancing accessibility for high-demand parts with secure storage for expensive, low-turnover items, all while maintaining stringent standards for service excellence. This environment requires not only operational efficiency but also scalability to accommodate future growth and evolving customer expectations.

Establish Methodology: Building the Foundation

Before diving into design and execution, the project followed a rigorous methodology framework to ensure recommendations were grounded in best practices and tailored to operational realities. This methodology consisted of five key components:

1. Site Assessment

2. Best Practice Audit

3. Process Mapping

4. Material Flow Analysis

5. Conceptual Layouts Development

Component 1. Site Assessment

The first step was conducting a comprehensive site assessment, which involved walking the warehouse floor, observing workflows, and interviewing operators and key stakeholders. This exercise identified pain points such as:

• Excessive travel time during picking due to poor slotting and lack of guided routes.

• Underutilized vertical space, with racks capped at suboptimal heights.

• Manual processes prone to errors, including handwritten receiving logs and ad-hoc cycle counts.

• Congested aisles caused by inconsistent material flow and oversized pallets in narrow zones.

The assessment provided a baseline for improvement and highlighted constraints such as ceiling height, material handling equipment limitations, and safety regulations.

Component 2. Best Practice Audit

Next, we benchmarked current operations against industry best practices for spare parts warehousing. Key gaps included:

• Absence of location scanning and barcode-driven workflows.

• Lack of system-driven slotting logic, resulting in random storage and frequent mis-picks.

• Minimal cycle counting discipline, leading to inventory in accuracy and reactive corrections.

• Inefficient space allocation, with fast-moving SKUs stored far from dispatch zones.

This audit informed the design principles for the future state: accuracy, traceability, and space efficiency.

Component 3. Process Mapping

Detailed process maps were created for all core activities – receiving, put-away, picking, packing, and shipping. These process maps revealed redundant steps and manual interventions that slowed operations. For example:

• Receiving involved multiple handoffs and delayed system updates.

• Picking relied on operator intuition rather than guided sequences, increasing variability.

Mapping these processes allowed the team to identify opportunities for streamlined workflows and automation.

Component 4. Material Flow Analysis

Material flow studies quantified SKU movement patterns, demand velocity, and handling requirements. Insights included:

• 20% of SKUs accounted for 80% of picking activity (Pareto principle).

• High-frequency items were scattered across the warehouse, increasing travel time.

• Bulky, slow-moving items occupied prime zones near shipping.

These findings drove slotting strategies and layout redesign, ensuring high-demand items were positioned for easy-to-access.

Component 5. Conceptual Layouts Development

Finally, conceptual layouts were developed using planning factors such as total invnetory on hand, SKU dimensions, handling equipment reach, and safety clearances. The design prioritized:

• Zoning by velocity: Fast movers near dispatch, slow movers in peripheral zones.

• Vertical optimization: Multi-tier racking and VLM systems for small parts.

• Aisle rationalization: Narrow aisles enabled by Sprinter WAV pickers for high-density storage.

This methodology ensured that every recommendation was backed by data and operationally feasible.

Phased Implementation Approach

Phase 1: Foundation & Vision

Phase 1 focused on quick wins to stabilize operations and improve efficiency without major structural changes. The objective was to increase inventory accuracy, reduce travel time, and improve operator safety while leveraging the existing footprint.

Key Initiatives in Phase 1

1. Update Picking and Order Release Strategy

The existing picking process was highly inefficient – manual, no sequencing, and dependent on printed slips. To address this, several strategies were considered:

• Pick Path Sequencing: Organizing pick paths to minimize travel time. This approach reduces unnecessary backtracking and optimizes picker movement.

• Order Release Logic: Releasing orders in batches based on proximity and priority. This prevents congestion and ensures high-priority orders are fulfilled first.

• Zone Picking: Dividing the warehouse into zones and assigning pickers to each zone. This reduces walking time by up to 22%, improving productivity and reducing fatigue.

While a WMS typically supports these strategies, interim solutions were implemented using manual sequencing and visual guides until system capabilities could be upgraded.

2. Implement Scanning for Accuracy and Visibility

Scanning was introduced as a cornerstone of Phase 1. Barcode-driven workflows were applied to:

• Receiving: Items scanned upon arrival to update inventory in real time.

• Put-away: Scanning confirmed correct location assignment.

• Picking: Scanning validated SKU and quantity before moving to packing.

• Packing: Final scan ensures order completeness before sealing.

With barcode scanning in place, inventory accuracy improved dramatically, reducing mis-picks and enabling real-time visibility. Also, operators gained confidence in guided workflows, reducing reliance on memory and intuition.

3. Invest in Material Handling Equipment

Safety and efficiency were addressed through targeted investments:

• Remove Mezzanine: Leveraging full ceiling height increased storage capacity.

• Wave Pickers: Mobile platforms allow operators to reach heights safely and move faster, doubling productivity.

• Picking Carts: Enable pick-to-cart logic, consolidating multiple orders in one trip and reducing travel distance.

These changes improved ergonomics, reduced risk of injury, and enhanced throughput.

Impact of Phase 1

• Inventory Accuracy: Increased to >95% within three months.

• Picking Efficiency: Improved by 20% through sequencing and scanning.

• Safety: Incidents reduced by 40% due to better equipment and SOPs.

Phase 1 laid the foundation for system-driven processes, creating stability and operator confidence before moving to advanced automation.

Phase 2: Design & Planning

Phase 2 focused on medium-term improvements and strategic investments to extend the life of the current facility and prepare for future scalability.

Key Initiatives in Phase 2

1. Long-Term Warehouse Strategy

The analysis revealed that the current warehouse was operating over capacity, with storage needs consistently exceeding available space. Forecasted growth of 10% annually intensified the challenge. Recommendations included:

• Evaluate Relocation: Consider a greenfield site with optimal ceiling height and layout flexibility.

• Explore 3PL Partnerships: Outsourcing could reduce costs and leverage specialized expertise.

• SKU Rationalization: Eliminate D-items/obsolete items (50% of inventory) by returning them to suppliers or redistributing to dealers.

These measures would free up space and reduce congestion, improving operational flow.

2. Introduce Automation for Space Optimization

Automation was identified as a critical enabler for space efficiency:

• Automated Storage and Retrieval Systems (ASRS): Ideal for medium-sized items and slow movers, ASRS maximizes vertical space and reduces manual handling.

• Vertical Carousels: Perfect for small parts, providing dense storage and real-time inventory control.

While these solutions require significant investment, they offer long-term ROI by freeing up space and reducing labor costs.

3. Upgrade System Capabilities

Implementing a Warehouse Management System (WMS) was recommended to:

• Enable logical slotting based on velocity and dimensions.

• Support wave picking and batch order release.

• Provide real-time inventory visibility and automated replenishment triggers.

A WMS would transform the warehouse into a data-driven operation, enabling predictive planning and continuous improvement.

Impact of Phase 2

• Storage Capacity: Increased by 25% through mezzanine removal and implementation of vertical storage solutions.

• Picking Efficiency: Improved by an additional 15% with automation and updated system directive logic.

• Scalability: Facility prepared for future growth and advanced automation.

Phase 2 positioned the warehouse for sustained performance, buying time before a potential relocation or full automation investment.

Phase 3: Bringing the Vision to Life – From Design to Execution

Implementation was structured into four major initiatives:

Initiative 1. Starting Fresh: Clean Slotting and Smart Cycle Counting

With new racking installed, the team seized the opportunity to reset inventory accuracy. Instead of migrating legacy errors, a structured cycle count program was launched:

• Every SKU was verified before being slotted.

• Slotting decisions considered dimensions, demand velocity, and handling needs.

• Cycle counts were embedded into daily operations, preventing drift.

This approach established a stable baseline and reinforced accountability from day one.

Initiative 2. Smarter Tracking: Scannable Locations and Sequenced Picking

To eliminate mis-picks and optimize movement:

• Unique barcodes were assigned to every rack and bay.

• Put-away involved scanning items into system-assigned locations, creating full traceability.

• Picking leveraged sequencing logic, guiding operators through optimized routes and enabling batch picking.

These upgrades reduced travel time by over 20% and virtually eliminated mis-picks.

Initiative 3. Rethinking the Core: Redesigning All Warehouse Processes

The ideal warehouse process is system-driven, standardized, and error-proof. Here’s what that looks like:

Process 1: Receiving

• Goods scanned upon arrival.

• Labels printed instantly with SKU and location data.

• WMS suggests optimal put-away locations based on slotting logic.

Process 2: Put-away

• Operators scan items and confirm system-assigned locations.

• WMS considers ABC classification, velocity, and handling constraints.

• Real-time updates ensure inventory visibility.

Process 3: Picking

• Guided by handheld devices with sequencing logic:

  • High-priority orders are grouped for batch picking.

  • Routes are optimized to minimize travel time.

• Visual confirmations to reduce mis-picks.

Process 4: Packing

• Integrated scanning validates order accuracy before sealing.

• System flags discrepancies instantly, preventing shipping errors.

• This end-to-end process eliminates manual decision-making, reduces variability, and ensures traceability.

Initiative 4. Making Every Inch Count: Smart Space Utilization

Space optimization was a cornerstone of this project because facility expansion was not an option. The challenge was clear: maximize the existing footprint while maintaining accessibility and safety. To achieve this, we deployed a multi-pronged strategy:

Solution 1: Specialized Racking Systems

Traditional racking often fails to account for SKU diversity, leading to wasted cubic space. We introduced:

• Adjustable pallet racking for bulky items, allowing dynamic beam positioning.

• Shelving systems for small, fast-moving parts, reducing dead space between levels.

• Cantilever racks for irregular or long items, eliminating inefficient horizontal stacking.

Impact: By tailoring racking to SKU profiles, we improved cubic utilization by 15–18%, freeing up floor space for additional zones.

Solution 2: Narrow Aisles Enabled by Sprinter WAV Pickers

Standard aisles (typically 10–12 feet wide) consume significant square footage. By deploying Sprinter WAV (Work Assist Vehicle) pickers, which offer vertical reach and maneuverability, we reduced aisle width to 6–7 feet without compromising safety.

Impact: This adjustment alone reclaimed 8–10% of floor space, enabling additional storage rows.

Solution 3: Vertical Lift Modules (VLMs)

VLMs are automated storage systems that use trays to store small parts in a high-density vertical column. Operators retrieve items via a computerized interface, eliminating the need for manual searching.

Impact: Each VLM condensed up to 120 linear feet of shelving into a 10-foot footprint, increasing storage density for small parts by up to 80%.

Solution 4: Clear Dividers and Slotting Discipline

Physical dividers within racks prevent SKU mixing, which often leads to wasted space and picking errors. Maintaining slotting discipline ensures that every inch of rack space is used for its intended SKU profile.

Impact: Reduced cross-SKU contamination and improved accessibility, indirectly supporting space efficiency.

Overall, these measures improved space utilization by 30%, avoiding costly offsite storage and keeping operations centralized.

Project Management Principles

Principle 1: Change Management and Training

Change management was not treated as an afterthought – it was embedded into every phase of the project. The team recognized that introducing scanning technology, narrow aisles, and automated workflows would fundamentally alter how operators performed their tasks. To ensure smooth adoption, a three-tiered approach was implemented:

Communication Strategy

• Weekly town halls explained the rationale behind changes, linking improvements to tangible operator benefits such as reduced manual effort and fewer errors.

• Visual dashboards displayed progress against KPIs, reinforcing transparency and trust.

Training Programs

• Hands-on sessions introduced operators to new scanning devices and WMS workflows.

• Safety training addressed concerns related to narrow aisles and VLM systems.

• Peer champions were appointed to provide on-the-floor support, creating a culture of shared ownership.

Feedback Loops

• Operators were encouraged to share pain points during pilot runs.

• Suggestions were incorporated into process refinements, reinforcing that their voices mattered.

Impact: Within three months of go-live, adoption rates exceeded 95%, and error rates dropped significantly. Operators reported increased confidence in system-driven workflows, and the cultural shift from intuition-based decisions to guided processes became a cornerstone of the warehouse operation’s new identity.

Principle 2: Stakeholder Engagement Stories

Stakeholder engagement extended beyond leadership alignment – it was a collaborative transformation journey. Early workshops with senior management focused on defining success metrics and timelines, ensuring operational goals were linked to broader business objectives such as customer satisfaction and cost control.

On the warehouse floor, skepticism was addressed through pilot programs. Operators were invited to test scanning workflows and provide feedback, which was incorporated into final designs. This participatory approach transformed resistance into advocacy.

Leadership reinforced this momentum by celebrating quick wins and recognizing operator contributions during monthly performance reviews. This shared accountability model created trust and accelerated adoption.

Principle 3: Risk Mitigation Strategies

The project team identified and mitigated three critical risk items:

Risk 1: Data Integrity

• Risk: Inaccurate master data could undermine slotting logic and inventory visibility.

• Mitigation: A full data validation exercise corrected SKU dimensions, weights, and classifications before migration.

Risk 2: Operational Downtime

• Risk: Disruption during racking installation and system cutover.

• Mitigation: A phased implementation strategy maintained critical operations through temporary parallel processes.

Risk 3: Resistance to Change

• Risk: Operator pushback could delay adoption.

• Mitigation: Incentive programs, peer champions, and continuous training ensured engagement and confidence.

These measures ensured a smooth transition with zero missed service-level agreements (SLAs) during go-live.

Principle 4: ROI Analysis

The financial impact of this transformation was substantial. Key ROI drivers included:

• Space Optimization: Narrow aisles and VLM systems reclaim approximately 8,000 square feet, eliminating offsite storage costs estimated at $250,000 annually.

• Labor Efficiency: Sequenced picking and batch strategies reduced travel time by 20%, equating to 1,200 labor hours saved per quarter.

• Error Reduction: Barcode-driven workflows cut mis-picks by 90%, reducing returns and associated costs by $50,000 annually.

Overall, the project achieved payback within 18 months, with projected annual savings exceeding $400,000.

Principle 5: Cultural Transformation

Beyond operational metrics, the most profound change was cultural. The warehouse transitioned from a reactive, intuition-driven environment to a data-driven, system-led operation. Operators now rely on guided workflows rather than personal judgment, and supervisors monitor performance through real-time dashboards instead of manual logs.

This cultural shift fostered accountability and continuous improvement. Operators began suggesting enhancements to scanning sequences and slotting logic, signaling a mindset change from compliance to collaboration.

Principle 6: Governance Structure

To sustain improvements, a governance framework was established:

• Monthly Performance Reviews: KPIs such as inventory accuracy, picking speed, and space utilization are tracked and discussed.

• Continuous Improvement Committee: Cross-functional team evaluates new technologies and process refinements quarterly.

• Training Refreshers: Mandatory sessions every six months ensure operators remain proficient in system updates and safety protocols.

This governance model ensures that optimization is not a one-time event, but a continuous journey aligned with business growth and change.

Retrospect & Fast Forward

Results So Far

Six months post go-live, the impact was clear:

• Inventory accuracy: >98%, driven by clean slotting and disciplined cycle counts.

• Fulfillment speed: Picking times reduced by 20%, mis-picks nearly eliminated.

• Space utilization: Improved by 30%, avoiding costly expansion.

• Operational consistency: Standardized, scan-supported workflows across all processes.

Beyond metrics, the cultural shift was profound: operators now rely on guided workflows, and management enjoys real-time visibility. What was once reactive is now proactive – setting the stage for automation and continuous improvement.

Future Roadmap for Automation

Planned initiatives include:

• Robotic Picking: Autonomous systems for high-volume zones to reduce labor dependency.

• AI-Driven Slotting: Algorithms that dynamically adjust locations based on real-time demand patterns.

• Predictive Analytics: Leveraging historical data to forecast inventory needs and prevent stockouts.

• IoT Integration: Sensors for real-time monitoring of temperature-sensitive parts and automated replenishment triggers.

Closing Remarks

The transformation of our client’s spare parts warehouse stands as a testament to the power of a holistic, data-driven approach to operational excellence. By systematically addressing inefficiencies, embracing technology, and fostering a culture of continuous improvement, the project delivered measurable gains in accuracy, speed, and space utilization while also laying the groundwork for future automation and scalability. The collaborative spirit between operators, management, and project stakeholders ensured that change was not only implemented but embraced. As the warehouse continues its journey toward advanced automation, it is well-positioned to meet the evolving demands of the automotive market and set new standards for service and efficiency in the industry.