In the fast-evolving landscape of logistics and supply chain management, Warehouse Resource ProductivityStandard is a critical factor in ensuring operational efficiency and enhancing customer satisfaction. Defining Resource Productivity Standard requires a thorough understanding of various factors that differ from one warehouse to another, including warehouse size, material handling equipment(MHE), order profiles, slotting, layout, labor skill levels, and work-allocation effectiveness.
"Our approach considers these variables and breaks down each task to the activity level to calculate the standard time for completion of a task. This forms a key part of our Resource Productivity Management (RPM) module."
This guide explores the essential components of advanced warehouse resource productivity standard, including calculation methods, task classifications, and the impact of various operational levers.
Understanding warehouse productivity
While understanding the core components of warehouse productivity—Work Availability, Resource Productivity, and Value Add Rate—provides a foundational framework, it is equally important to identify the specific factors that influence these metrics. With this, we delve into the Key Performance Indicators (KPIs) and the operational levers that directly impact each component.
By examining these levers, such as layout optimization, workload balancing, and resource quality, we can uncover actionable strategies to enhance productivity and drive operational efficiency in warehouse environments
KPIs and impacting levers
WorkAvailability (A): Work Availability measures the extent to which work is available for labor to perform tasks in the warehouse. The efficiency of warehouse operations is impacted by the following factors:
Layout & Slotting
Impact : Optimized warehouse layouts and strategic product slotting minimize travel time for picking and reduce handling time, thus improving pick rates and overall productivity.Key Levers: Product categorization, proximity to high-demand items, storage density.
Impact : Minimizes travel time by optimizing the sequence in which items are picked, reducing the overall time spent on picking tasks and increasing throughput.
Key Levers : Route planning software, real-time adjustments based on item availability.
Warehouse Size
Impact : The size of the warehouse affects travel distances and storage capacity. A larger warehouse may result in longer pick-paths, while a smaller warehouse may lack sufficient space for all required inventory.
Key Levers : Space utilization techniques, vertical storage options.
Resource Productivity (P): Resource productivity evaluates how efficiently labor and equipment are used to achieve operational goals. It is influenced by:
Resource Quality:
Impact : The quality of resources, such as the experience and skills of warehouse staff, directly impacts productivity. Well-trained and skilled employees are able to perform tasks faster and with fewer errors.
Key Levers : Training programs, recruitment practices, experience-based role assignment.
Resource Experience:
Impact : Experienced workers can perform tasks more efficiently due to familiarity with the processes, leading to faster execution times and fewer mistakes.
Key Levers : On-the-job training, role rotation, mentoring.
Working Conditions:
Impact : Well-designed work environments with appropriate ergonomics, lighting, temperature control, and safety measures contribute to higher productivity and lower absenteeism.
Key Levers : Facility design, safety protocols, employee health programs.
Value Add Rate (V): The value-added rate measures the proportion of time and effort spent on activities that directly contribute to the flow of goods versus non-value-added (NVA) tasks. The levers for this metric include:
Internal Movements:
Impact : Time spent moving products internally within the warehouse (e.g., moving items to picking locations or moving them between different zones) should be minimized.
Key Levers : Automated material handling systems, inventory management systems that reduce unnecessary relocations.
Stock Consolidation:
Impact : The process of combining items from multiple locations to fulfil a single order should be efficient. Excessive time spent consolidating stock adds to NVA time.
Key Levers : Consolidation zones, order batching strategies.
Any Other NVA Activities:
Impact : Non-value-added activities, such as unnecessary inspections, repackaging, or excessive documentation, should be reduced as they take up time without directly contributing to fulfilling customer orders.
Key Levers : Process automation, Lean principles, standard operating procedures (SOPs) to reduce NVA tasks.
Productivity models and Calculation methods
Warehouse tasks are typically categorized into two primary productivity model types:
Pick & Drop Tasks: These tasks involve moving goods from onelocation to another within the warehouse.
Work Station Tasks: These encompass static tasks such as receiving,loading, quality assurance (QA), and packing.
Productivity Calculation Methods:
Time & Motion Studies: Detailed time and motion studies help establish initial productivity models by calculating standard times for various tasks.
Historical Data Regression: Analyzing historical data refines productivity benchmarks and identifies patterns for improvement.
Machine Learning and Continuous Improvement: Leveraging advanced technologies like machine learning drives continuous productivity improvements by analyzing operational data and optimizing workflows.
Detailed Productivity Standards
Pick & Drop Tasks: These tasks focus on the movement of goods within the warehouse, with productivity calculations factoring in:
Resource Type: Different resources, such as operators using Hand Operated Pallet Trucks (HOPT), Battery Operated Pallet Trucks (BOPT), or Reach Trucks (RT), have varying speeds and efficiencies.
Handling Unit: The type of unit being handled, such as palletsor cases, affects the process time.
Travel Distance: The distance between pick and drop points plays a crucial role in determining the total standard time for task completion.
Work Station Tasks: Tasks at fixed workstations like receiving and loading have distinct productivity standards. These are measured by the process time per handling unit and the overall time per work order.
Example Calculation:
Example 1: If 700 Cases to be received in a Truck. It would take…
700*10 + 180 = 7180 ResourceSecs (if there are 2 resources – it will take 3590 Secs to receive the Truck)
Example 2: If 20 Pallets to be Loaded in a Truck using Fork lift. It would take…
20*120 + 180 = 2580 ResourceSecs (if there are 2 Forklifts – it will take 1290 Secs to load the Truck)
Conclusion
Measuring and Optimizing warehouse productivity is a multifaceted challenge that demands a nuanced approach to warehouse resource productivity standard, a deep understanding of task classifications and resource efficiency. By implementing detailed productivity standard models and leveraging continuous improvement strategies, businesses can enhance warehouse operations, reduce costs, and improve service levels.
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