How does an operations analyst conduct a time and motion study to improve warehouse efficiency?

A time and motion study in a warehouse combines two questions:

• Time: How long does each activity actually take?
• Motion: What movements, travel, waiting, handling, and unnecessary effort are involved?

The operations analyst uses the results to establish a better standard work method, reduce waste, and improve throughput without compromising safety or quality. Standard work typically defines the work sequence and expected cycle time.

A practical 8-step approach

1. Define the problem and objective

Start with a specific process rather than studying the entire warehouse.

Examples:

• Pick rate is below target.
• Orders spend too long waiting for packing.
• Receiving has a bottleneck.
• Pickers walk excessive distances.
• Labor costs are rising.
• Loading trucks takes too long.

Define a measurable baseline, such as:

"Reduce average order-picking cycle time from 6.2 minutes to 5.0 minutes while maintaining ≥99.5% picking accuracy and no increase in safety incidents." This prevents the study from becoming simply "watching workers."

2. Map the process

Break the job into observable elements.

For an order picker, for example:

1. Receive assignment.
2. Travel to location.
3. Locate SKU.
4. Reach/bend to product.
5. Pick quantity.
6. Scan.
7. Place item in tote.
8. Travel to next location.
9. Wait for system/equipment.
10. Deliver completed tote.

Separate value-added work from activities such as walking, searching, waiting, rehandling, and correcting errors.

3. Observe and collect data

The analyst can use a stopwatch, WMS timestamps, handheld-device data, or video—with appropriate workplace policies and worker communication.

For each cycle, record:

OSHA's work-method guidance recommends observing employees, recording movements, obtaining representative production data, and using video where useful for subsequent analysis.

Important: Don't measure only the fastest employee or a single cycle. Capture enough normal cycles to account for variation—different SKUs, order sizes, locations, congestion, equipment availability, and shifts.

4. Analyze where the time goes

Calculate:

Average cycle time

Average Cycle Time=Total observed timeNumber of cycles\text{Average Cycle Time} = \frac{\text{Total observed time}}{\text{Number of cycles}}

Then classify the time.

For example:

• 35% walking
• 25% picking/handling
• 15% searching
• 10% scanning
• 10% waiting
• 5% error/rework

That immediately tells the analyst that improving the actual "pick" motion may have little impact if walking and searching account for 50% of the cycle.

Also look for:

• Excessive travel distance
• Backtracking
• Reaching or bending
• Waiting for equipment
• Waiting for system responses
• Congestion
• Duplicate scans
• Rehandling
• Poor slotting
• Bottlenecks
• Uneven workload between workers
• Frequent interruptions

5. Analyze the motions—not just the seconds

This is where a time study becomes a time-and-motion study.

For example, suppose a picker repeatedly:

Walks 20 ft → bends → searches → stands → scans → turns → places item. The analyst should ask whether the workstation or storage location can be redesigned so the worker can:

Walk 5 ft → reach at waist height → scan → place. OSHA specifically recommends reducing the distance between workers and objects, minimizing lifting range/frequency, and using conveyors or carts for horizontal movement where appropriate.

This matters because an apparent productivity improvement can create an ergonomic problem. Warehousing commonly involves repetitive motion, bending, reaching, lifting, and pushing/pulling; OSHA recommends incorporating ergonomic assessment into warehouse improvement efforts.

6. Identify root causes and redesign the process

The analyst might find:

Problem: Pickers spend 30% of their time walking.

Possible solutions:

• Re-slot high-frequency SKUs closer to packing.
• Put frequently co-picked SKUs near each other.
• Change the pick path.
• Batch or zone picking.
• Use cart/tote configurations that reduce handling.
• Optimize replenishment locations.
• Reduce unnecessary travel between workstations.

Or:

Problem: Pickers spend 12 seconds searching for each SKU.

Possible solutions:

• Improve bin labeling.
• Standardize locations.
• Improve lighting.
• Change slotting.
• Add visual identifiers.
• Improve WMS location information.

The key is to attack the cause, not simply tell employees to "work faster."

7. Establish the improved standard

After testing a new method, repeat the measurement.

Suppose the original process is:

6.2 min/order After redesign:

5.1 min/order That's a 17.7% reduction in cycle time.

You can then establish a realistic standard based on representative performance rather than simply taking the fastest observed time.

A useful standard-work document might specify:

• Work sequence
• Expected cycle time
• Required quality level
• Equipment/tools
• Standard route
• Safety requirements
• Exceptions and escalation procedures

8. Validate the improvement

Don't declare victory immediately.

Compare before vs. after on several metrics:

This is important because faster isn't necessarily better if accuracy falls, workers become fatigued, or safety risks increase. OSHA recommends worker involvement and evaluating whether implemented ergonomic solutions actually work over time.

A simple example

Imagine an analyst studies case picking and observes:

100 orders → 620 minutes of labor → 6.2 min/order. The breakdown is:

• Picking/handling: 155 min
• Walking: 280 min
• Searching: 93 min
• Waiting: 62 min
• Rework: 30 min

The analyst discovers that the biggest opportunity isn't picking speed. It's travel and searching.

They test:

1. New SKU slotting.
2. Better location labels.
3. Optimized pick paths.
4. Moving fast-moving items closer to the dispatch area.

A second study produces:

100 orders → 510 minutes → 5.1 min/order That's a 17.7% improvement, while accuracy and ergonomic measures are monitored to ensure the productivity gain isn't creating new problems.

The mindset to use

A good operations analyst asks:

"Why is this activity taking this long?"

rather than:

"How can I make the employee do it faster?"

The biggest warehouse gains often come from eliminating motion, travel, waiting, searching, rehandling, and poor layout rather than squeezing seconds out of the worker's actual picking motion. And worker input is valuable: employees often know exactly where the wasted motion and practical problems are.

A useful overall formula is:

Observe → Measure → Break down → Find waste → Redesign → Test → Standardize → Monitor.

An operations analyst conducts a time and motion study by breaking down warehouse workflows into discrete elements, measuring exact durations, and eliminating waste (muda) to boost productivity . Originally pioneered by Frederick Taylor (time study) and Frank & Lillian Gilbreth (motion study), this technique combines stopwatch timing with ergonomic and process observation.

Here is how an analyst typically executes a time and motion study in a modern warehouse setting:

• Define the objective (e.g., reduce order pick time, optimize packing station throughput).

• Select the process or workstation to analyze (e.g., high-velocity SKU picking or receiving dock put-away).

• Inform warehouse associates and operators to ensure transparency and reduce the Hawthorne effect (where workers change behavior because they are being watched).

• Observe the current state and break the job into micro-steps or elements (e.g., for a picking task: walk to location → scan bin → pick item → place in tote → scan tote).

• Document ergonomic bottlenecks, unnecessary reach distance, or excessive backtracking.

• Time each element across multiple cycles and different shifts/operators to account for variability.

• Record the observed time using a stopwatch or digital time-study app.

• Apply a performance rating factor (adjusting the observed time up or down based on the operator's pace relative to standard normal performance) to find the normal time:
  Normal Time=Observed Time×Rating Factor Normal Time equals Observed Time cross Rating Factor N o r m a l T i m e=O b s e r v e d T i m e×R a t i n g F a c t o r

• Add allowances to the normal time to account for personal needs, unavoidable delays, and worker fatigue.

• Calculate the final standard time (the time a qualified worker needs to complete the task at a sustainable pace):
  Standard Time=Normal Time×(1+Allowance Percentage)Standard Time equals Normal Time cross open paren 1 plus Allowance Percentage close paren S t a n d a r d T i m e=N o r m a l T i m e×(1+A l l o w a n c e P e r c e n t a g e)

• Identify non-value-added activities (e.g., searching for misplaced tools, redundant walking, double-handling inventory).

• Redesign the layout (e.g., implementing ABC inventory slotting to place fast-moving items closer to the packing zone).

• Standardize the new, optimized method and update Standard Operating Procedures (SOPs).

• Train warehouse staff on the revised workflows.

• Monitor key performance indicators (KPIs) like units per hour (UPH) and labor cost per order to validate improvements.

If you're working on a specific warehouse layout or bottleneck, tell me:

• What process is causing the most friction (picking, packing, receiving)?
• What kind of WMS (Warehouse Management System) or automation tools do you have in place?

I can help you tailor a data collection template or step-by-step metric plan for your operation.

An operations analyst conducts a time and motion study by systematically breaking down warehouse processes into discrete tasks, measuring their durations, and analyzing worker movements to eliminate waste, streamline workflows, and boost throughput.

• Project preparation, defining the scope, selecting the specific warehouse process to study (e.g., picking, packing, or receiving), and briefing the warehouse team to ensure transparency and cooperation.
• Process decomposition, breaking the chosen operation down into micro-steps or elements (e.g., walking to a shelf, scanning an item, picking it, and placing it in a tote).
• Observation and data collection, recording cycle times using a stopwatch or digital time-study app across multiple workers and varying shifts, while noting any delays or ergonomic friction.
• Performance rating and normalization, adjusting the recorded raw times based on the operator's observed pace relative to a standard "normal" pace (Rating × Actual Time).
• Standard time calculation, factoring in allowances for personal needs, fatigue, and unavoidable delays (PF&A allowances) to establish a reliable baseline standard time for the task.
• Motion and ergonomic analysis, evaluating the physical path of movement (spaghetti diagrams) to identify excessive walking, bending, or reaching, and redesigning the layout or tool placement.
• Implementation and continuous monitoring, introducing the optimized standard operating procedures (SOPs), training staff, and tracking performance metrics post-implementation to ensure sustained efficiency gains.

Would you like me to dive deeper into how to calculate PF&A allowances or show you how to map a spaghetti diagram for a specific warehouse workflow?

A time and motion study in a warehouse is a structured way for an operations analyst to measure how work is actually performed, how long each step takes, and where time or movement is being wasted. The goal is not simply to make employees work faster—it is to redesign the process so the same work can be done more safely, consistently, and efficiently.

1. Define the problem and objective

Start with a specific business question, such as:

• Why is picking productivity below target?
• Why are orders taking too long to ship?
• Where are forklift operators losing time?
• Can the warehouse handle 20% more volume without adding labor?
• Why does one shift consistently outperform another?

Define measurable objectives, for example:

"Reduce average pick-cycle time from 4.2 minutes to 3.5 minutes while maintaining ≥99.5% picking accuracy and without increasing injury risk." This prevents the study from becoming simply an exercise in collecting stopwatch data.

2. Select the process to study

Break the warehouse into major processes:

Receiving → Put-away → Storage → Picking → Packing → Staging → Shipping

Then select the process with the greatest potential impact.

For example, suppose an analyst discovers that picking consumes 45% of warehouse labor. That would usually be a better study target than a receiving activity that consumes only 5% of labor.

A real warehouse study has used this approach across unloading, inbound checking, put-away, picking, checking, and loading, identifying put-away and stamping as bottlenecks.

3. Break the job into work elements

Don't time "picking an order" as one giant activity. Break it into observable elements.

For example:

This is where the motion study component becomes valuable: the analyst looks at how the employee performs each step, not just the elapsed time.

4. Observe multiple employees and conditions

The analyst should collect observations across:

• Different employees
• Different shifts
• Different days
• Different order sizes
• Different SKU types
• Normal and peak periods
• Different warehouse zones

This matters because timing one highly experienced employee on a quiet Tuesday can produce a misleading "standard."

The analyst can use a stopwatch, tablet/software, video where appropriate, or work-sampling techniques.

For example, they might record 50–100 picking cycles:

5. Separate value-added work from waste

This is often where the biggest improvement opportunities appear.

The analyst looks for:

• Excess travel — walking/driving unnecessarily far
• Waiting — waiting for inventory, equipment, instructions, or another worker
• Searching — looking for products or locations
• Reaching/bending — unnecessary physical movement
• Double handling — moving the same product multiple times
• Rework — correcting errors
• Congestion — workers or equipment blocking one another
• Poor layout — frequently picked products located too far away

For example, a 90-second pick might turn out to contain:

35 sec travel + 20 sec searching + 15 sec picking + 5 sec scanning + 15 sec waiting

The obvious opportunity isn't necessarily "make the worker pick faster." It may be eliminating 20 seconds of searching and 15 seconds of waiting.

6. Analyze the motion itself

Watch the worker's physical movements carefully.

Ask questions such as:

• Does the worker repeatedly bend to floor-level locations?
• Are high-volume SKUs positioned inconveniently?
• Does the worker have to turn around repeatedly?
• Are tools or scanners within easy reach?
• Does the worker walk around an obstruction?
• Is the employee repeatedly reaching overhead?
• Could two motions be combined into one?

This has an important safety component. OSHA identifies lifting/lowering, bending, overhead reaching, pushing/pulling, awkward postures, and repetitive work as warehouse ergonomic risks.

So the fastest method isn't automatically the best method. A good analyst optimizes productivity and ergonomics.

7. Establish the baseline

Calculate metrics such as:

• Seconds per pick
• Picks per labor hour
• Lines per hour
• Cases per hour
• Travel distance per order
• Labor utilization
• Waiting percentage
• Equipment utilization
• Order accuracy
• Cost per unit/order

For example:

Current state: 80 picks/hour Target: 100 picks/hour Labor: 10 pickers Volume: 8,000 picks/day If the process can genuinely reach 100 picks/hour, the warehouse could theoretically process the same volume with fewer labor hours—or use the capacity to handle additional volume.

8. Develop improvement ideas

Now redesign the process rather than simply demanding faster performance.

Common solutions include:

Layout

Move high-frequency SKUs closer to packing/shipping.

Slotting

Put fast-moving products in the easiest-to-access locations.

Travel reduction

Change the picking route or batch multiple orders together.

Workstation redesign

Position scanners, labels, totes, and tools within easy reach.

Process changes

Eliminate redundant scans, paperwork, or duplicate handling where appropriate.

Equipment

Use carts, conveyors, lift equipment, or other material-handling equipment where economically and safely justified.

Staffing

Match labor to workload by time of day rather than keeping a fixed staffing level.

Standard work

Document the improved method so different employees perform the process consistently.

ECRS—Eliminate, Combine, Rearrange, Simplify—is one useful framework for generating these improvements. A recent warehouse case study combined ECRS with time/motion analysis to identify bottlenecks and reduce handling resources.

9. Calculate the new standard time

Once the improved method is established, determine the expected time.

A traditional time-study approach is roughly:

Observed time → performance adjustment → normal time → allowances → standard time

The allowance accounts for legitimate factors such as personal needs, fatigue, and unavoidable delays.

For example:

Average observed pick time = 60 sec Performance rating = 105% Normal time = 63 sec Allowances = 15% Standard time ≈ 72.5 sec The exact methodology depends on the organization's labor-standard system.

For highly repetitive work, an analyst may also use predetermined-motion systems such as MOST or MTM instead of—or alongside—direct stopwatch studies.

10. Pilot the improvement

Don't immediately redesign the entire warehouse.

Test the new method in one zone or with one process.

For example:

Before

• 82 picks/hour
• 2.8 miles walking/shift
• 3.1% pick errors

After

• 101 picks/hour
• 2.0 miles walking/shift
• 2.7% pick errors

Then check whether the improvement survives real operating conditions.

11. Measure the results

Compare before vs. after:

Also check safety, quality, and employee feedback. A productivity improvement that increases injuries, errors, or turnover isn't a successful warehouse improvement.

12. Standardize and continuously monitor

Once the improved method is proven:

1. Document the standard work.
2. Train employees.
3. Establish the labor standard.
4. Update WMS/task-management rules if necessary.
5. Monitor KPIs.
6. Re-study the process when volume, layout, equipment, or product mix changes.

The best time-and-motion studies therefore become part of continuous improvement, rather than a one-time stopwatch exercise.

A simple analyst's workflow

Observe → Break down → Measure → Analyze → Eliminate waste → Redesign → Pilot → Measure again → Standardize

The key mindset is: don't ask "How can I make the worker move faster?" Ask "Why does the worker have to make this movement at all?"

That distinction is often where the largest warehouse-efficiency gains come from.

Observe → Break down → Measure → Analyze → Eliminate waste → Redesign → Pilot → Measure again → Standardize

Position scanners, labels, totes, and tools within easy reach.

Process changes

Eliminate redundant scans, paperwork, or duplicate handling where appropriate.

Equipment

Use carts, conveyors, lift equipment, or other material-handling equipment where economically and safely justified.

Staffing

Match labor to workload by time of day rather than keeping a fixed staffing level.

Standard work

Document the improved method so different employees perform the process consistently.

ECRS—Eliminate, Combine, Rearrange, Simplify—is one useful framework for generating these improvements. A recent warehouse case study combined ECRS with time/motion analysis to identify bottlenecks and reduce handling resources.

9. Calculate the new standard time

Once the improved method is established, determine the expected time.

A traditional time-study approach is roughly:

Observed time → performance adjustment → normal time → allowances → standard time

The allowance accounts for legitimate factors such as personal needs, fatigue, and unavoidable delays.

For example:

Average observed pick time = 60 sec Performance rating = 105% Normal time = 63 sec Allowances = 15% Standard time ≈ 72.5 sec The exact methodology depends on the organization's labor-standard system.

For highly repetitive work, an analyst may also use predetermined-motion systems such as MOST or MTM instead of—or alongside—direct stopwatch studies.

10. Pilot the improvement

Don't immediately redesign the entire warehouse.

Test the new method in one zone or with one process.

For example:

Before

• 82 picks/hour
• 2.8 miles walking/shift
• 3.1% pick errors

After

A time-and-motion study in a warehouse is essentially a structured way to answer two questions:

1. Where is labor time actually going?
2. Which motions, delays, and process steps can be eliminated or reduced without hurting safety, quality, or service?

An operations analyst should treat it as a process-improvement exercise, not simply a way to determine how fast an employee can work. OSHA specifically notes that warehouse work can involve repetitive motion, awkward postures, lifting, reaching, and pushing/pulling, so productivity improvements should be evaluated alongside ergonomics and safety.

1. Define the objective

Start with a specific process and measurable problem.

Examples:

• Reduce order-picking labor hours by 10%.
• Increase picks per labor hour.
• Reduce average order cycle time.
• Reduce picker travel distance.
• Improve dock-to-stock time.
• Determine whether staffing matches workload.
• Identify bottlenecks in receiving, picking, packing, or shipping.

Don't start by timing everything in the warehouse. Pick a process with a clear business impact.

Example:
"Why does an average e-commerce order take 18 minutes from release to completion, and how could we get that below 15 minutes?"

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2. Map the current process

Go to the warehouse floor and document the actual sequence of work.

For an order picker, for example:

Receive task → travel to location → locate SKU → scan → pick item → verify quantity → place item in tote → travel to next location → repeat → deliver completed tote

Separate the work into individual elements that can be timed consistently.

A useful process map might look like:

This decomposition is important because the total cycle time alone doesn't tell you why the process is slow.

Lean warehouse studies similarly break activities down and look for unnecessary effort, material movement, and other forms of waste.

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3. Establish a representative sample

Don't time one employee doing one unusually easy order and call that the standard.

Sample across:

• Different employees
• Different shifts
• Different days
• Different order sizes
• Different SKU types
• Different warehouse zones
• Normal and peak-volume periods

For repetitive operations, video can be particularly useful. OSHA's work-method guidance recommends observing employees, recording movements, and using video for subsequent analysis; it suggests capturing multiple representative cycles rather than relying on a single observation.

For example, you might collect:

30 orders × 5 pickers × 3 shifts = 450 observations

You don't necessarily need that many, but the principle is to obtain enough observations to distinguish normal variation from unusual events.

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4. Capture the right data

A good time-study sheet might contain:

Also record why waiting occurs.

Instead of simply recording 30 seconds of "delay," classify it:

• Waiting for replenishment
• Congested aisle
• Scanner problem
• Waiting for equipment
• Searching for product
• Waiting for another worker
• System delay
• Supervisor interruption

That makes the data actionable.

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5. Measure motion, not just elapsed time

The "motion" component is where many warehouse opportunities emerge.

Look for:

• Walking
• Bending
• Reaching
• Turning
• Lifting
• Carrying
• Searching
• Repositioning
• Repeated scanning
• Unnecessary handling
• Empty travel

OSHA recommends examining repeated motions and worker posture, including arm, wrist, and trunk positions, rather than considering productivity in isolation.

For example:

Picker walks 40 feet → bends to retrieve SKU → walks back → discovers wrong quantity → walks back → corrects quantity.

The analyst shouldn't merely conclude "picker took 90 seconds." The better question is:

Why did the process require that much movement?

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6. Calculate the baseline

Once enough observations are collected, calculate:

Average cycle time

[ Average\ Time = \frac{\sum Cycle\ Times}{Number\ of\ Observations} ]

Labor productivity

[ Picks/Labor\ Hour = \frac{Total\ Picks}{Total\ Labor\ Hours} ]

Labor content

For example, if 1,000 orders require 250 labor hours:

[ Labor\ Content = 0.25\ hours/order ]

or 15 minutes/order.

You can then break that 15 minutes into categories:

• 6.5 min — travel
• 3.0 min — picking
• 1.5 min — scanning/verification
• 1.0 min — searching
• 1.5 min — waiting
• 1.5 min — other

Now the improvement opportunity becomes obvious: travel consumes 43% of the labor content.

Travel is often a major component of warehouse work; the Lean Enterprise Institute notes that travel can represent a substantial portion of work-assignment time.

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7. Identify the waste

Use the data to classify activities as:

Value-added:
Actually transforms or fulfills the customer's order.

Necessary but non-value-added:
Required for safety, compliance, verification, etc.

Pure waste:
Could be eliminated without affecting the customer.

Typical warehouse wastes include:

• Excessive walking
• Searching for inventory
• Double handling
• Poor slotting
• Waiting for replenishment
• Unnecessary paperwork
• Congestion
• Rework
• Equipment downtime
• Poorly organized workstations

For example:

Before

Picker walks 1.8 miles/shift → picks 90 units/hour.

Finding

38% of observed time is travel.

Potential intervention

Move high-frequency SKUs closer to the packing area and reorganize pick paths.

A real Lean warehouse case found that standardized work and process changes substantially reduced employee walking distance while improving picking performance.

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8. Develop improvements

Don't automatically conclude that employees need to "work faster."

Look first at system-level changes:

Layout

• Move fast-moving SKUs closer to demand.
• Reduce unnecessary walking.
• Improve aisle configuration.

Slotting

• Put high-frequency items in optimal locations.
• Store frequently co-picked products near one another.

Process

• Batch or wave compatible orders.
• Change picking sequence.
• Eliminate duplicate scans or handling.

Equipment

• Better carts or containers.
• Pick-to-light/voice systems where economically justified.
• Conveyors or other material-handling equipment.

Standard work

• Define the best-known sequence.
• Make it easy to follow.
• Train employees on the new method.

Lean practitioners emphasize creating standardized work with the employees who perform the job, rather than simply imposing a standard from management.

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9. Check ergonomics before implementing the "faster" method

This is critical.

A method that saves 10 seconds but increases awkward lifting or repetitive reaching may be a bad improvement.

OSHA recommends designing material-handling tasks to minimize weight, range of motion, frequency, and distance between the worker and the object.

So your analysis should capture things such as:

• Lift frequency
• Load weight
• Reaching distance
• Bending
• Twisting
• Overhead work
• Push/pull force
• Repetition
• Workstation height

The goal is:

Less waste + less risk + equal or better quality.

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10. Pilot the improvement

Don't redesign the entire warehouse based on one time study.

Run a controlled pilot.

For example:

Baseline

• 82 picks/hour
• 1.6 miles walking/shift
• 3.2% picking errors

Pilot

• New slotting
• New pick sequence
• Standard work
• Same equipment

After

• 101 picks/hour
• 1.0 mile walking/shift
• 2.1% errors

That's much stronger evidence than simply saying, "The new process seems faster."

A Lean warehouse example illustrates the same principle: measure the process before and after the change so the actual time and cost savings can be demonstrated.

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11. Convert the results into financial impact

Suppose your study finds:

• 20 warehouse employees
• $22/hour loaded labor cost
• 1 hour/day saved per employee
• 250 working days/year

Annual labor capacity released:

[ 20 \times 1 \times 250 = 5,000\ hours ]

Potential annual labor value:

[ 5,000 \times $22 = $110,000 ]

That doesn't necessarily mean you should eliminate positions. The capacity might instead allow the warehouse to:

• Process more orders
• Reduce overtime
• Avoid future hiring
• Improve service levels
• Absorb peak demand

That's an important distinction for an operations analyst.

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12. Establish the new standard and monitor it

Once the pilot works:

1. Document the new process.
2. Train employees.
3. Update standard work.
4. Establish performance metrics.
5. Continue measuring.
6. Audit periodically.
7. Re-study when volume, layout, products, or equipment change.

Useful warehouse KPIs include:

• Picks per labor hour
• Lines per labor hour
• Order cycle time
• Dock-to-stock time
• Travel distance per order
• Labor hours per order
• Picking accuracy
• Rework rate
• Overtime
• Equipment utilization
• Safety/ergonomic indicators

The important idea is that the time study isn't the improvement. It is the measurement system that helps you find and validate improvements.

A practical analyst workflow

Observe → Map → Time → Analyze → Identify waste → Improve → Pilot → Re-measure → Standardize

A strong operations analyst therefore doesn't walk into a warehouse with a stopwatch and ask, "How fast can this person pick?"

They ask:

"What does the process require the employee to do, how much time does each element consume, why does that time occur, and what can we change in the system to make the work safer, easier, faster, and more reliable?"

That mindset is what turns a basic time-and-motion study into a genuine warehouse efficiency project.

Conducting a time and motion study is a classic industrial engineering technique that helps an operations analyst break down warehouse workflows, eliminate bottlenecks, and boost overall efficiency.

Here is how an analyst typically runs the study from start to finish:

1. Preparation and Scoping

• Define the objective: Pinpoint what needs improvement—such as reducing order-picking cycle times, cutting down travel distances, or minimizing idle time during packing.
• Select the process: Focus on a discrete, measurable workflow (e.g., "case picking in Zone A" or "pallet wrapping at Station 3") rather than trying to analyze the entire warehouse at once.
• Gain worker buy-in: Communicate transparently with warehouse operators. Explain that the goal is to optimize workflows and reduce frustration, not to police or rush individuals.

2. Observation and Data Collection (The "Motion" and "Time")

• Break the process into micro-steps: Deconstruct the task into distinct, repeatable elements. For example, picking an item involves: (1) reading the pick list/scanner, (2) walking to the bin, (3) reaching and grasping the item, (4) placing it in the tote, and (5) confirming the pick on the device.
• Time the elements: Use a stopwatch or video recording to time each step across multiple cycles and different operators. This accounts for human variance and different skill levels.
• Record environmental and ergonomic factors: Note obstacles like cluttered aisles, poor lighting, heavy lifting angles, or suboptimal inventory placement (e.g., fast-moving SKUs on high shelves).
• Factor in allowances: Document necessary delays, such as operator fatigue, equipment recalibration, or personal breaks, by applying a standard allowance factor (often 10% to 15% of total time).

3. Analysis and Evaluation

• Calculate the Standard Time: Convert the observed times into normal time (adjusted for the operator's working pace) and add allowances to arrive at the standard time required to complete a task.
• Identify waste (Muda): Look for the classic lean wastes:
  • Motion waste: Unnecessary bending, reaching, or walking back and forth.
  • Waiting waste: Operators waiting for forklifts, system lagging, or replenishment.
  • Transportation waste: Excessive material handling distances.
• Compare performance: Benchmark current performance against historical data, slotting efficiency, or warehouse management system (WMS) expected rates.

4. Designing and Implementing Improvements

• Redesign the layout (Method Study): Reconfigure warehouse slotting (placing high-velocity items closer to packing stations), clear aisle obstructions, or adjust workbench heights to minimize awkward reaches.
• Standardize the process: Create clear, visual Standard Operating Procedures (SOPs) based on the most efficient methods observed during the study.
• Train and transition: Walk the team through the new optimized workflow and explain the "why" behind the changes.

5. Review and Continuous Improvement

• Measure post-implementation metrics: Monitor KPIs like units per hour (UPH), order lead time, and error rates to verify the impact of the changes.
• Iterate: Treat efficiency as a moving target; conduct follow-up spot checks as seasonal volume or SKU profiles shift.

If you'd like, I can:

Provide a template breakdown of standard allowance factors used in warehousing Show you how to calculate Normal Time vs. Standard Time with an example Discuss how WMS and labor management systems (LMS) automate this data collection

A time-and-motion study in a warehouse is essentially a structured way to answer two questions:

1. How long should each activity take under normal conditions?
2. What motions, delays, travel, or process issues are making it take longer than necessary?

The goal isn't simply to make employees move faster. It's to redesign the work so that less time is spent walking, waiting, searching, handling, and correcting errors, while maintaining safety and quality. Lean standardized work uses the same basic principle: define the work sequence, measure the time for its elements, and use that baseline for continuous improvement.

1. Define the process and objective

Start with one clearly defined warehouse activity, such as:

• Receiving
• Putaway
• Order picking
• Packing
• Replenishment
• Loading
• Returns processing

Then establish the metric you're trying to improve—for example, picks per labor hour, order cycle time, dock-to-stock time, or labor hours per 1,000 units.

Avoid trying to study the entire warehouse at once.

2. Map the current process

Go to the warehouse floor—the gemba—and document the actual sequence.

For example, an order picker might:

Receive task → walk to location → locate SKU → scan → pick item → verify quantity → place in tote → walk to next location.

Break the job into small, observable work elements. A standardized-work combination table, for example, separates manual work, walking, machine time, and waiting.

3. Measure the work

Use a stopwatch, tablet, WMS data, or video observation—with appropriate employee/privacy policies.

Record multiple cycles rather than one "best" cycle.

A simple data sheet might look like:

You want enough observations to capture normal variation—different SKUs, locations, order sizes, operators, and times of day.

4. Separate value-added work from waste

This is where the study becomes useful.

Classify observed time into categories such as:

• Value-added: physically picking, packing, labeling, etc.
• Walking/travel
• Searching
• Waiting
• Equipment interaction
• Handling/re-handling
• Error correction
• Administrative work
• Unavoidable delays

For a warehouse, you may discover that the actual pick takes only 10 seconds while the associate spends 30 seconds walking and 15 seconds searching.

That's a very different problem from "the employee is picking too slowly."

Warehouse labor studies can use these observations to distinguish value-added and non-value-added steps and establish more accurate labor standards.

5. Look at motion, not just time

A true time-and-motion study asks why the time is being consumed.

Watch for:

• Excessive walking
• Bending or reaching
• Turning around repeatedly
• Searching for inventory
• Poor slotting
• Congested aisles
• Long travel between sequential picks
• Scanner/device delays
• Waiting for replenishment
• Waiting for equipment
• Repeated handling
• Poor workstation layout

For example:

Before:
Picker walks 80 feet → bends → searches → picks → walks back 80 feet.

Potential improvement:
Move the high-frequency SKU to an ergonomic golden zone near the normal pick path.

The improvement isn't "walk faster." It's remove the unnecessary walking and searching.

6. Determine the root cause

Don't automatically eliminate every long task.

A 20-second delay might be caused by:

• Bad warehouse layout
• Poor inventory accuracy
• Missing replenishment
• Slow equipment
• Poor system design
• An unsafe workstation
• An unusual order profile

Lean standardized work is intended to expose these problems and provide a baseline for improvement—not simply force workers to conform to an arbitrary "best" time.

This is also where employee input is extremely valuable. The person doing the work often knows why the standard process doesn't work in practice.

7. Design the improved method

Once the causes are understood, test countermeasures.

Examples:

Lean warehouse implementations specifically use standard work, workload planning, and process diagrams to improve flow and labor deployment.

8. Establish the new standard

After testing the improved method, establish a standard time and documented work sequence.

For example:

Picking standard: 42 seconds/order line under defined conditions
Sequence: scan → pick → verify → place → proceed
Expected output: 85 lines/hour under the defined mix

Importantly, define the conditions behind the standard. A 42-second standard for a single-item forward pick shouldn't necessarily apply to bulky-item picking or highly variable multi-line orders.

Standardized-work documentation can show the work sequence, operator movement, walking time, machine time, and required inventory/WIP.

9. Validate the result

Run the new method for a reasonable period and compare:

Before vs. after

• Units/hour
• Labor hours/order
• Travel distance
• Cycle time
• Waiting time
• Picking/packing accuracy
• Damage
• Safety incidents/ergonomic risk
• Overtime
• Employee feedback

For example:

Before: 72 picks/hour
After: 86 picks/hour
Improvement: 19.4%

But don't declare victory solely from productivity. If productivity increases while errors or injuries increase, the process hasn't actually improved.

10. Monitor and continuously improve

The final step is to turn the study into a management system rather than a one-time stopwatch exercise.

Compare actual performance against the standard and investigate significant deviations. Modern warehouse labor-management systems can combine WMS, time-and-attendance, and other operational data to identify where work is taking longer than expected and where bottlenecks are developing.

A useful cycle is:

Observe → Measure → Analyze → Improve → Standardize → Monitor → Repeat

A practical analyst's workflow

If I were conducting one as an operations analyst, I'd structure the project like this:

Week 1 — Baseline

• Select the process
• Define KPIs
• Map the process
• Collect WMS/operational data
• Observe and time multiple cycles

Week 2 — Analysis

• Calculate average and variation
• Identify travel/search/wait time
• Create a spaghetti diagram of movement
• Identify bottlenecks
• Interview associates and supervisors
• Quantify the biggest sources of lost time

Week 3 — Improvement

• Test layout/slotting/routing changes
• Modify work sequence
• Remove unnecessary handling
• Establish a proposed standard
• Pilot with a small group

Week 4 — Validation

• Compare before/after performance
• Check quality and safety
• Validate the standard with operators
• Document the new process
• Establish ongoing KPI monitoring

The most important mindset is: don't study people to find out who is slow; study the process to find out why the work takes as long as it does. That distinction is what turns a time-and-motion study into a genuine warehouse-efficiency improvement program.

An operations analyst conducts a time and motion study to break down warehouse processes into individual tasks, measure how long they take, and eliminate inefficiencies . This systematic approach combines time study (chronographing tasks) with motion study (analyzing physical movements) to optimize labor productivity and workflow.

Here is how the process is structured step-by-step:

1. Preparation and Scoping
   • Process Selection : Identify the bottleneck or high-cost activity to study (e.g., order picking, packing, or receiving put-away).
   • Stakeholder Buy-In : Communicate the study's purpose to warehouse associates to ease anxieties about monitoring and ensure natural behavior.
   • Baseline Metrics : Gather existing KPIs like current throughput, labor hours, and error rates.
2. Deconstruction of Tasks
   • Element Breakdown : Split the macro-process into discrete, measurable micro-elements. For example, "picking an item" is broken down into: Walk to location → Scan barcode → Pick item → Place in tote.
   • Standardization : Document the exact current method (Standard Operating Procedure) being used so variations can be tracked.
3. Data Collection (Observation and Measurement)
   • Time Measurement : Use a stopwatch or video recording to time each micro-element across multiple cycles and different workers to account for variance.
   • Performance Rating : Adjust the observed time based on the operator's pace relative to a "standard" or normal pace using a rating factor (R).
   • Allowance Factor : Add allowances (A) for personal needs, fatigue, and unavoidable delays (PF&D).
4. Calculating Standard Time
   • Normal Time Calculation : Multiply the average observed time (OT) by the performance rating factor (R):
     Normal Time = OT × R
   • Standard Time Calculation : Apply the allowance percentage to the normal time to arrive at the final benchmark time required for an average worker to complete the task:
     Standard Time = Normal Time × (1 + A)
5. Motion Analysis and Optimization
   • Waste Identification : Scan for the 7 wastes of lean (e.g., excessive walking, bending, reaching, or double-handling inventory).
   • Ergonomic and Layout Adjustments : Redesign the workspace, re-slot fast-moving inventory to golden zones (waist-to-chest height), or introduce mobile picking carts to reduce travel time.
6. Implementation and Continuous Improvement
   • Training : Roll out the optimized SOPs and train warehouse staff on the new, streamlined methods.
   • Performance Tracking : Monitor post-implementation metrics to ensure the projected efficiency gains are realized and adjust standards as warehouse dynamics shift.

If you're working on a specific warehouse layout or process, let me know:

• Which warehouse process you are targeting (e.g., picking, packing, replenishment)
• What main challenge you are facing (e.g., high travel time, bottlenecks)

I can help you outline specific data collection methods or metrics to focus on.

An operations analyst conducts a time and motion study in a warehouse by breaking down complex fulfillment processes into discrete, measurable steps to eliminate waste, optimize worker movement, and establish accurate labor standards.

Here is the step-by-step methodology used to improve warehouse efficiency:

1. Project scoping and selection
   • Target identification : Select a specific, high-impact warehouse process to study (e.g., order picking, put-away, packing, or receiving).
   • Objective setting : Define clear goals, such as reducing cycle time per order by $15% or increasing units processed per hour.
2. Process mapping and task breakdown
   • Workflow visualization : Create a detailed process map of the current state.
   • Micro-motion division : Break the operation down into distinct, repeatable elements (e.g., for picking: walk to bin → scan location → pick item → scan item → place in tote).
3. Data collection and observation
   • Time measurement : Use a stopwatch or video recording to time each micro-motion across multiple workers and varying shift conditions.
   • Motion tracking : Document physical movements, ergonomic strains, travel paths (spaghetti diagrams), and instances of idle or waiting time.
   • Sample sizing : Ensure an adequate number of observations to account for worker variability and statistical confidence.
4. Performance rating and normalization
   • Pacing adjustment : Evaluate the observed worker's pace relative to a "standard" or normal pace (performance rating).
   • Allowance integration : Add standard allowances for fatigue, personal needs, and unavoidable delays (PF&A allowances) to calculate a realistic baseline.
5. Data analysis and waste identification
   • Standard time calculation : Compute the normal time and standard time for each task using formulas like Standard Time = Normal Time × (1 + Allowance Percentage).
   • Waste hunting : Identify non-value-added activities—such as excessive walking, backtracking, double-handling of goods, or searching for misplaced inventory (7 Wastes of Lean).
6. Redesign and optimization
   • Method redesign : Reorganize the workflow, layout, or slotting strategy (e.g., moving high-velocity SKUs closer to the packing station to minimize travel distance).
   • Tool integration : Recommend ergonomic aids, better mobile scanning hardware, or pick-to-light systems to reduce motion friction.
7. Implementation and continuous monitoring
   • Standard Operating Procedures (SOPs) : Document the newly optimized method and train warehouse associates.
   • Performance tracking : Monitor KPIs (like labor productivity and order lead time) post-implementation to ensure the projected efficiencies are realized.

If you're working on a specific warehouse layout or bottleneck, tell me:

• Which process you are looking to optimize (picking, packing, receiving, etc.)
• What primary constraint you are facing (long travel times, packing delays, congestion)

I can give you more tailored metrics and lean tools for your exact scenario.

A time and motion study in a warehouse is a structured way to measure what workers do, how long each step takes, how often they do it, and where time or movement is being wasted. An operations analyst typically combines stopwatch/video observations with warehouse data to redesign the process.

1. Define the problem and objective

Start with a specific process and measurable goal, such as:

• Reduce order-picking time by 15%
• Increase picks per labor hour
• Reduce travel distance
• Reduce dock-to-stock time
• Improve receiving throughput
• Reduce overtime without reducing service levels

Avoid studying the entire warehouse at once. Pick one high-volume or problematic process—order picking, packing, receiving, replenishment, or shipping.

2. Map the current process

Break the job into observable elements.

For example, an order picker might perform:

Receive assignment → travel to location → locate SKU → reach/bend → pick item → verify → place in tote → travel to next location

Record both productive and nonproductive time:

This often reveals that the actual "pick" is a small portion of the total cycle.

3. Observe enough cycles

Don't base the standard on one unusually fast or slow worker. Observe multiple employees, shifts, order types, and operating conditions.

Video can be particularly useful because it allows the analyst to review movements frame-by-frame. OSHA's technical guidance recommends recording repeated cycles and examining movements, posture, workstation configuration, and whether the observed production pace represents normal operations. www.osha.gov

Also explain the purpose of the study to employees. The goal should be process improvement, not simply finding the fastest worker.

4. Measure the important variables

Besides elapsed time, capture factors that explain variation:

• SKU and order characteristics
• Number of items per order
• Walking distance
• Pick location
• Cart/tote type
• Equipment used
• Congestion
• Waiting time
• Inventory availability
• Errors/rework
• Shift and time of day
• Employee experience level

Then calculate metrics such as:

Cycle time = productive time + delay time

Labor productivity = units processed ÷ labor hours

Travel percentage = travel time ÷ total cycle time

For example, if a picker completes 120 lines in 4 hours:

120 ÷ 4 = 30 lines/hour

If the study finds that 35% of those four hours is spent walking, that becomes an obvious candidate for improvement.

5. Separate value-added from waste

A useful question for every activity is:

"Does this step physically or informationally advance the order toward completion?"

Common warehouse wastes include:

• Excessive walking
• Searching for inventory
• Waiting for equipment
• Waiting for replenishment
• Double handling
• Unnecessary scanning
• Poor slotting
• Congestion
• Rework caused by errors
• Excessive reaching, bending, or twisting

For example, suppose a picker spends 60 seconds per order:

• 15 sec picking
• 25 sec walking
• 10 sec searching
• 5 sec scanning
• 5 sec waiting

The study suggests that walking and searching—not picking itself—are the major opportunities.

6. Look at ergonomics at the same time

Efficiency shouldn't come from making people move faster. Warehousing involves risks from lifting, bending, reaching, pushing/pulling, awkward postures, and repetitive motions. OSHA specifically notes that good ergonomic design can reduce fatigue while improving productivity.

Look for opportunities such as:

• Moving high-volume SKUs closer to the picker
• Putting frequently picked items at convenient heights
• Reducing excessive reaches
• Using conveyors or carts to reduce horizontal carrying
• Moving heavy products to waist-level storage
• Using lift-assist equipment

OSHA's guidance specifically recommends minimizing weight, reach distance, range of motion, and frequency, and using equipment such as conveyors, carts, and lift tables where appropriate.

7. Analyze the data and identify root causes

After collecting observations, use a spreadsheet or BI tool to compare:

Current time → potential cause → proposed change → expected benefit

For example:

8. Design the improved method

Now create a future-state process.

For example:

Before:
Picker receives order → walks 500 ft → searches shelf → picks → walks back → repeats.

After:
Batch similar orders → re-slot fast movers → use optimized pick path → pick multiple orders in one trip.

The analyst then estimates the expected labor-hour savings and throughput improvement.

9. Pilot the change

Don't immediately roll the change across the warehouse.

Test it in one zone, shift, or product category. Compare the before vs. after results using the same metrics.

For example:

The improvement is only successful if productivity improves without creating safety, quality, or service problems.

10. Standardize and continuously monitor

Once the new method works:

1. Document the standard work.
2. Train employees.
3. Update warehouse layouts/WMS parameters if necessary.
4. Establish a performance baseline.
5. Monitor the KPI over time.
6. Repeat the study when products, layouts, equipment, or processes change.

OSHA emphasizes that ergonomic improvement should be an ongoing process involving management and workers rather than a one-time project.

A simple analyst's framework

Think of the study as:

Observe → Measure → Break down → Find waste → Redesign → Pilot → Measure again → Standardize

The most valuable insight is often not "the worker needs to move faster." It's that the system is making the worker spend 40% of the shift walking, searching, waiting, or handling the same item multiple times.

A good operations analyst therefore uses time-and-motion data to redesign the process, layout, technology, staffing, and work method so that higher productivity comes from eliminating unnecessary work—not simply increasing the pace of the employee.