Non-Value-Add Labour Payments
Do You Pay for “Ghost” Labour and Wasted Motion?
Idle labour results more from problematic processes than from lazy workers.
Material Shortages: Assembly workers sit idle because the warehouse team has not delivered parts
Long Setups: Frequent switching between products and having to wait for a specialised technician to calibrate machines make operators wait before they can start work
Maintenance Downtime: In the absence of modern predictive maintenance, equipment can go down any time, leaving workers unable to continue work
Approval Delays: Employees wait for approvals from managers in a bureaucratic set up with many layers
Tech Downtime: Slow software, frozen screens, poor Wi-Fi and delayed support all cause workers to sit idle
Unbalanced Teams: When outputs result from team effort, any lack of balance in human or machine workloads leads to some workers or machines waiting for work
“Looking Busy”: When managers and supervisors focus on keeping workers busy at all times rather than on ensuring value-add work, workers might stretch a ten-minute task to an hour-long routine to appear busy
Wasted motion results from:
Poor Workplace Design: When workers have to search all over for tools or other requirements to complete their tasks, work slows down. Poor design can also increase physical effort leading to fatigue or even injuries which in turn affect performance
Digital Spaghetti: When workers have to search tens of folders to find a file, or constantly switch between tens of apps to complete a task, a lot of wasted effort is built into the work
Scavenging: When workers have to search for misplaced tools or safety gear, or sift through messy inventory to get what they want, wasted time is inevitable
Poor Work Design: When work involves excessive bending, stretching, lifting, etc. workers tend to get exhausted, resulting in below-normal work speeds
Double Handling: Moving a box of parts to a temporary shelf, only to move it again to the assembly line an hour later
If you want to improve value addition and productivity, focus on the above issues rather than blaming or punishing workers.
Example of a Company Producing High-Capacity Industrial Drone Batteries
The company was a Series A Funding Startup seeking to scale up from 500 units to 5000 units per month. The problems it faced included:
A chaotic factory floor
Missing lead times
Spiralling overtime costs
Shrinking profit margins
Seeking a solution to the chaos, the company engaged a consultant to review operations and suggest remedial actions. The consultant used two main tools to analyze the issues:
Spaghetti Diagrams (to track wasted motion) and
Time Studies (to track idle time).
They uncovered massive hidden wastes:
Phantom Labor (Waiting) Issues
The QC Bottleneck: Assembly workers finished battery packs in 12 minutes. However, the Quality Control (QC) testing machine took 30 minutes per pack. Workers frequently sat idle waiting for the tester to clear.
The Component Hunt: Because parts were stored in a central cage, line workers spent 15 minutes at the start of every shift waiting in line for the inventory manager to hand out kit boxes.
Cardboard Chaos: Operators spent 10% of their day cutting open plastic wrap and unboxing raw components at their workbenches instead of assembling batteries.
Non-Value-Add Motion Issues
The 10,000-Step Factory: The soldering station was located 40 feet away from the final assembly table. Operators walked back and forth all day long carrying heavy battery trays.
Poor Ergo-Design: Part bins were stacked high above the workbenches. Workers had to stand up, stretch, and pull down bins to get specialized screws for every single build.
The Action Plan (The Lean Interventions)
The consultant pitched a low-cost, high-impact reorganization plan tailored to the startup's tight budget.
Fix 1: U-Shaped Manufacturing Cells
Before: Linear assembly line where parts traveled 120 feet in total.
After: The consultant rearranged the benches into a tight U-Shape.
The Result: Walking distance dropped by 80%. The same operator could now solder a part, pivot 90 degrees, and place it directly into the assembly fixture without taking a single step.
Fix 2: Point-of-Use Storage (POUS) & Water-Scouts
Before: Operators fetched their own materials and unboxed them at the line.
After: Central storage was eliminated. Materials were placed on gravity-fed rolling racks right behind the assembly cells. A low-cost "water-scout" (material handler) unboxed components in the back and kept the racks filled.
The Result: Operators never stopped assembly to open boxes or look for parts.
Fix 3: Balancing the Line (Smashing the QC Bottleneck)
Before: One expensive testing machine caused a huge backup.
After: Instead of buying a second $50,000 machine, the consultant split the testing process. They moved the simple visual checks to the assembly cell (done by the operator) and reserved the machine only for the final electronic calibration.
The Result: Machine cycle time dropped from 30 minutes to 8 minutes. The bottleneck vanished.
Final Results (The ROI Blueprint)
After a 4-week implementation, the startup saw dramatic shifts in its key performance indicators (KPIs):
Metric Before After Improvement
Distance Walked / Day 4.2 miles per operator 0.6 miles per operator 85% reduction
Operator Idle Time 22% of shift < 3% of shift Eliminated waiting time
Daily Production Capacity 24 units per day 58 units per day 141% increase
Cost per Unit $45 $28 37% Savings
The Remedial Framework
Find the Root Factors
Map the Value Stream:
Map every single step of the process.
Visualize where work stops and workers have to wait
Create Spaghetti Diagrams:
Trace a worker's physical path on a floor plan.
If it ends up looking like a plate of spaghetti, the layout has serious problems
Check the Following Options
Use the 5S System:
SORT: Separate needed items from unneeded items and remove what is unnecessary
SET IN ORDER / STRAIGHTEN: Neatly arrange and identify essential tools and materials for easy use
SHINE: Clean the workspace and equipment regularly to spot issues early.
STANDARDIZE: Create consistent daily rules and procedures for the first three steps.
SUSTAIN: Build a habit of following the rules and maintaining long-term improvements
Use Automation and Integration:
Use software to automate data entry and hand-offs
Connect different apps so workers do not have to click back and forth
Cellular Manufacturing:
Arranging machines and workstations in a U-shape instead of a straight line.
This allows one operator to run multiple machines and eliminates walking waste.
Single-Minute Exchange of Die (SMED):
Separate tasks done while the machine runs (external) from tasks done while stopped (internal).
Shift as many internal steps as possible into external operations. This principle is illustrated in a testing context in Fix 3 of the drone battery example above, when visual checks were moved to the assembly line
Simplify and standardize the remaining internal setup tasks
Eliminate Adjustments: Reduce trial-and-error adjustments to speed up final execution.
Point-of-Use Storage (POUS):
Store raw materials right at the workstation where they are used.
Eliminate forklift trips and central warehouse retrieval wait times.
Visual Factory (Andon Cord):
Use lights or strings that workers pull to instantly signal for help when a problem arises.
This stops the line immediately to fix the root cause, preventing long phantom delays later
Implement Through Testing and Fine-Tuning
Testing:
Run small pilot tests on the production line
Check machines for errors and safety risks
Measure output speed and product quality
Collect feedback from machine operators.
Fine-Tuning:
Adjust machine speed, heat, or pressure settings
Fix weak spots found during the test phase
Update step-by-step worker instructions
Train staff on the final adjusted process.
Conclusion
Idle time in manufacturing is more often the result of faulty processes than worker laziness. And poor workplace and work design can lead to unnecessary worker movements, and reduce productivity.
Analyses like value stream mapping and creating spaghetti diagrams can reveal the factors underlying these problems. Several options are available to remedy identified problems.
The drone battery example illustrates the problems that are common, and an approach that is appropriate in most cases. Success potential is enhanced when changes are implemented through testing and fine-tuning.