01 · Mechanics and boundaries
Mechanics and boundaries
Time analysis decomposes a process into clearly defined intervals. Elapsed lead time follows one order from a defined start to a defined finish. Processing time describes when the order is actively worked on. Labor time sums worker effort and may exceed elapsed time when two people work together. Observed cycle time describes completion or repetition at a defined operation; state that operation and unit explicitly.
A single stopwatch reading is an observation, not a standard for every worker or order. Different routes, line counts, interruptions, and workload conditions change durations. Distinguish natural variation from data errors and changed definitions before comparing times. Do not use the smallest observed time as normal capacity.
02 · Construct the analysis
Construct the analysis
Define events that observers can recognize consistently. Partition the trace into mutually exclusive order states such as queue, active operation, hold, and completed transfer. Use timestamps for long waits and direct observation for short elements. Record overlaps separately if simultaneous actions are important. Synchronize clocks before linking electronic and manual observations.
Collect multiple complete traces across relevant conditions. Preserve individual values, order sequence, and context before summarizing. Report medians, spread, and upper-tail behavior when appropriate; a mean alone hides long exceptions. Pair short-element timings with quality and safe working methods so a faster but incomplete action is not counted as improvement.
03 · Worked warehouse-dispatch example
Worked warehouse-dispatch example
The fictional North Quay warehouse dispatches a single parcel-order family. Its boundary starts when an order is accepted for release and ends at confirmed carrier handover. Demand is 240 orders in a 420-minute net working day. Each order contains three lines on average, but the example keeps the parcel order as the unit of flow. No number below describes a real organization or a demonstrated improvement. The purpose is to make the reasoning traceable rather than to present a success story.
A representative order spends 12 minutes awaiting release, 2 minutes being released, 18 minutes awaiting picking, 8 minutes being picked, 24 minutes awaiting packing, 5 minutes being packed, 10 minutes awaiting checking, 2 minutes being checked, 15 minutes awaiting loading, and 3 minutes being loaded. These mutually exclusive intervals total 99 minutes: 20 minutes of processing and 79 minutes of waiting. They describe one complete normal-route trace, not a statistically estimated mean for every order. A separate 100-order diagnostic sample contains 20 late orders, defined as handover more than 120 minutes after acceptance. The normal trace and late-order sample therefore answer different questions.
Three pickers, three packers, two checkers, and two loaders work in parallel within their respective stages. At the illustrated processing times, theoretical stage capacities are 157.5, 252, 420, and 280 orders per day. Picking is below the 240-order requirement even before interruptions or rework. Release has two staff and a theoretical capacity of 420. These capacities assume dedicated resources, identical order mix, and no overlapping assignments. They are not observed outputs and should never be reported as effective capacity.
The normal trace gives 12+18+24+10+15=79 minutes waiting and 2+8+5+2+3=20 minutes processing, totaling 99 minutes elapsed. The longest individual wait is before packing at 24 minutes. This does not by itself establish packing as the capacity bottleneck: picking's nominal capacity is lower, while release waves can create a downstream batch queue.
Suppose a two-person loading action takes three elapsed minutes with both people engaged throughout. That particular order uses six labor minutes for loading, although its lead-time contribution remains three. The standard example's stage-capacity assumption treats loading as two independent three-minute servers. If loading is actually paired work, revise capacity to one team producing an order every three minutes, or 140 theoretical orders per day.
04 · Order-time composition
Order-time composition
05 · Interpretation and decisions
Interpretation and decisions
Choose the measure matching the decision. Staffing needs labor content and available resource time; customer service needs elapsed lead time; workstation balancing needs repeatable operation times and resource interaction. A 30-second reduction in walking can improve pick processing without removing an 18-minute queue when demand exceeds available picking capacity.
A weak application adds every worker's time and labels the total customer lead time. A sound application builds an order timeline, records parallel effort separately, and reconciles start-to-finish elapsed time. It also identifies whether an observed hold belongs inside the operation or between operations, keeping definitions stable across comparisons.
06 · Sound application and adaptations
Sound application and adaptations
For machine-assisted operations, use a combined worker-machine chart to distinguish manual work, unattended operation, and overlap. For time-of-day delays, graph acceptance and completion rates alongside queues. Capture cutoff effects, since two orders with similar processing can have very different lead times if one misses the final collection.
Time analysis does not prove why a delay occurred. Add mechanism observations and stratification. Avoid overly precise decimals when timestamp accuracy is only one minute. Review censored traces and observer effects. When evaluating a change, compare like order families and equivalent workload periods; changing the sample from large to small orders can create an apparent time saving without improving the process.
07 · Evidence and follow-through
Evidence and follow-through
Make the observation auditable before debating a countermeasure. Preserve an anonymous order identifier, acceptance and handover timestamps, route, line count, shift, exception flag, and the observer's definitions. A timestamp from a completed screen action may describe data entry rather than physical completion. Reconcile several records with direct observation and ask the person doing the work what each event actually means. Keep an uncertainty note when clocks differ or two actions overlap; rounding cannot repair an ambiguous boundary.
Observe ordinary work and exceptions over a period that includes opening, replenishment, breaks, and the carrier cutoff. Selecting only easily followed orders produces a clean-looking but biased picture. When an order is unfinished at observation end, keep it visible as unfinished rather than silently deleting it. For multi-line orders, establish whether timing ends at the first line or the complete order. Include all three lines in the latter case, because the customer receives the order only after its final requirement is satisfied.
Turn the analysis into a bounded decision. Describe the proposed change, the mechanism expected to alter performance, the measure that would detect the change, and the conditions under which it would be withdrawn. A small layout change might reduce walking yet increase congestion; an extra release wave might lower one queue yet overload picking. Monitor handover performance, first-pass accuracy, work in process, and staff workload together. Treat the proposed numbers as planning assumptions until a comparable observation period supplies evidence.
08 · Boundary and robustness review
Boundary and robustness review
Before implementing the selected countermeasure, check the boundary one more time. If the analysis starts after order release, an upstream acceptance hold is outside its measured lead time even though the customer experiences it. If the analysis ends at the loading bay, a parcel waiting for the carrier is still incomplete within the stated dispatch outcome. Keep those events inside the customer-facing boundary, or state exactly why a narrower operational measure is also being used.
Assess robustness across normal variation. A proposed operating rule should specify what happens when an urgent order arrives, stock is unavailable, a staff member is absent, or the carrier changes collection time. Those conditions do not invalidate the main analysis; they define where its assumptions need adaptation. Rehearse an exception through the proposed route with the people responsible for each decision. Record which assumptions remain unverified and what evidence would be sufficient to proceed.
Finish with an explicit learning statement: what the evidence currently supports, what it does not establish, and which observation is needed next. A quantified hypothesis can be useful without becoming a guaranteed result. Retain the current-state observations so a later comparison can use the same event definitions and population. When the observed outcome differs from the prediction, revisit the mechanism and resource assumptions rather than adjusting the target after the fact.
Connections
Related methods and phase use
Placed under Analyze because of the outcome it supports. Use the method in other phases when its purpose and assumptions fit the work; the phase list is a guide to selection, not a compulsory sequence.
Sources
Professional foundations and further reading
The explanation and fictional teaching examples are written for LeanTrainingLab. Linked primary sources provide professional foundations; example values and local conventions are stated in the guide. The accepted toolset draws on Six Sigma+Lean Toolset, second edition (Lunau, editor; Springer, 2013). No book text or examples are reproduced here.