Case Study: Elevating Warehouse Operations with NexStride
Background
A major food storage company wanted to assess their 200,000 sq. ft. California warehouse. The facility supported both raw materials for manufacturing and finished goods for distribution. While operations met current demands, leadership recognized inefficiencies that were limiting growth, reducing throughput, and adding unnecessary costs.
Assessment Process
At NexStride, we don’t stop at diagnosing problems; we provide a clear, actionable path to success. Our assessment combined detailed observations, leadership interviews, and real-time data analysis to understand the current state and design a roadmap for improvement.
Key Findings
Process Inefficiencies
Picking operations required manual decisions for SKUs, leading to delays and errors. Each new SKU added significant time to the process, accounting for over 25% of total picking time.
Staging areas were chaotic, with operators often choosing inefficient docking points for shipments.
Underutilized Storage Capacity
Vertical space was significantly underused. Products were stacked to only 16.5 feet, despite the warehouse’s capability to accommodate up to 40 feet.
Mixed-pallet assembly areas experienced traffic jams, reducing overall productivity.
Technology and Metrics Gaps
The Warehouse Management System (WMS) lacked features for directed picking and put-away, forcing operators to rely on experience and calculators.
Productivity metrics and cost tracking were anecdotal, making it difficult for leadership to reward high-performing employees or address inefficiencies systematically.
Labor Challenges
Workforce scheduling was based on manual forecasts rather than real-time demand, leading to overstaffing during slow periods and understaffing at peaks.
Our Approach: Beyond Solutions—Building a Roadmap
Rather than simply handing over a list of recommendations, we developed a comprehensive roadmap that prioritized initiatives based on impact, cost, and feasibility. Each phase of the roadmap included actionable steps, required resources, and measurable outcomes.
Understanding needs and priorities, we crafted a phased roadmap. While we presented all possible improvements, we also advised against implementing certain advanced options immediately, as their payback periods did not align with the up-front goals. Instead, we prioritized initiatives based on impact, cost, and feasibility, backed by detailed ROI calculations.
The Roadmap
Phase 1: Quick Wins (1-3 Months)
Directed Picking and Put-away: Upgraded the WMS to guide operators on optimal SKU locations, reducing errors and improving picking efficiency by 25%.
Reorganizing High-Turnover SKUs: Placed high-demand items closer to staging areas, cutting travel time and picking delays.
Clear Staging Guidelines: Introduced visual aids and assigned docking points for shipments to reduce congestion.
ROI: Achieved within 11 months through a 25% boost in picking efficiency
Phase 2: Mid-Term Investments (3-12 Months)
Vertical Storage Optimization: Installed high-density racking to double storage capacity without increasing the warehouse footprint, reducing storage costs by 30%.
Labor Management System: Deployed a dynamic scheduling tool to align staffing levels with real-time demand, improving efficiency and cutting overtime costs.
Enhanced Metrics and Visibility: Implemented tools to track productivity and costs, enabling data-driven decisions and performance incentives for employees.
ROI: Realized within 18.6 months including a 30% reduction in storage costs and optimized labor usage.
Phase 3: Long-Term Automation (12-24 Months)
Automated Mixed-Pallet Assembly: Introduced cube-building software and robotic systems to streamline pallet creation, projected to save over 3,000 labor hours annually.
Advanced Routing Algorithms: Leveraged AI-driven tools to optimize picking and put-away paths, reducing operator fatigue and increasing throughput.
Robotics Integration: Designed a scalable plan for future automation, including autonomous forklifts and robotic loaders to further reduce manual labor.
ROI: Payback was projected at 19.5 years.
We recommended this phase for later consideration, as the upfront costs and long payback period didn’t align with immediate financial goals.
Presenting the Full Picture
While providing a comprehensive view of potential improvements, we emphasized that not all options were necessary or financially viable right away. By showing the math behind each phase—projected costs, savings, and payback periods—we empowered leadership to make informed decisions.
For example, while advanced robotics would save 3,000 labor hours annually, the associated costs of $850,000 made it a lower-priority investment compared to vertical storage expansion and directed picking. However, we mapped out the potential ROI for these projects to revisit them when operational needs grew.
Results Delivered
This structured approach ensured we didn’t just fix immediate issues but laid the groundwork for long-term operational excellence. Within six months, the company achieved:
Increased Efficiency: Picking and staging times improved by 20%, enabling faster order fulfillment.
Cost Savings: Labor costs dropped by 12%, and storage cost-per-pallet decreased by 26%.
Expanded Capacity: High-density racking boosted storage from 8,000 to over 10,000 pallets.
Actionable Insights: New metrics enabled leadership to track performance and incentivize top employees, boosting morale and retention.
Why NexStride?
At NexStride Consulting, we’re not just about identifying problems; we empower businesses with the tools, guidance, and support they need to implement changes. For this company, this meant creating a roadmap that balanced quick wins with strategic investments, ensuring tangible improvements at every step.
Ready to transform your warehouse operations? Let NexStride guide you. Schedule a consultation today.