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Value stream mapping

Value stream map — current and future state

Value stream map — current and future state is licensed CC BY 4.0. Attribution: Katafacts (katafacts.com).

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1 · What it is

What it is

A value stream map follows one product or service from the moment a customer asks to the moment they receive it, across every process it passes through — timing the work at each step and the wait between steps. This tool draws the map from the data you collect on the walk: process boxes with their data, the queues between them, and the timeline that shows how little of the total time is actual work. It computes lead time, flow efficiency, takt time from customer demand, and the capacity constraint — the step that needs the most time per unit once downtime is counted — and then carries the same data into a future-state design with a before-and-after comparison. It doesn't replace walking the process; it replaces the error-prone arithmetic and redrawing afterwards.

2 · When to use it

When to use it — and when not to

Use it when

  • You can walk the actual process, or have direct, recent observation data — not just what people believe happens.
  • The work crosses several processes or departments and you need to see where it waits between them.
  • The process has a clear start and end a customer would recognise as "when I asked" and "when I got it."

Not when

  • You only have secondhand or old data — observe the current process first; a map built from memory inherits every gap in that memory.
  • The process branches heavily with no dominant path — scope down to one product or service family that follows the same route, and map that.
  • You're designing the future state before the current state is measured — you can't improve a flow you haven't quantified.
  • The problem is inside one process — handoffs, re-keying, approvals, work coming back — zoom into that process with a Makigami process map rather than adding more boxes here.

3 · How to fill it in

How to fill it in

Scope
State which product or service family this covers and where it starts and ends, in a sentence or two. Name the supplier and customer if you know them — they anchor the two ends of the drawn map. A value stream with no stated boundary quietly becomes a map of everything, which maps nothing well.
Customer demand and takt
Enter how many units the customer needs per day or week and how much working time is available in that period. Takt time — available time divided by demand — is the pace the whole stream has to keep. It's optional, but without it nobody can say whether the constraint is actually too slow.
Process steps
List each process in order with its process time — how long one person takes to complete one unit at that step — and how long work waits after it before the next step starts. Operators are the people working that step side by side; if a crew works on each unit together, enter the crew's elapsed time and 1 operator. Work in days or weeks when waits run that long; calendar time counts nights and weekends. Add operators, uptime, defect rate and the number of units waiting only where you actually observed them — a blank is honest, a guess isn't. Keep each step a whole process or department: if two steps belong to the same team, you're mapping too small for a value stream map — map the inside of that process with a Makigami instead. Working as a team: save the map, share it with the people who run each step, and ask each of them to confirm their own step. They check its numbers against what really happens and confirm or correct them, and the map shows who confirmed what and when. If someone later changes numbers another person confirmed, that step needs confirming again.
The map
Drawn for you from the steps: process and data boxes, the queues between them, and the timeline — waits on the high rungs, process time on the low. Bursts mark the capacity constraint and the longest wait, and a thick outline marks any step slower than takt. Note how work is scheduled, and under each step whether work is pushed on when it's done, pulled by the next step, or waits its turn in a first-in-first-out lane — that's the information flow, and pushed work is usually where the queues build. To change the picture, change the steps.
Lead time · Flow efficiency · Constraint
Lead time, process time, flow efficiency and takt are computed from the step data with the arithmetic shown. The capacity constraint is the step with the least capacity: process time stretched by recorded downtime, then shared across the operators working that step in parallel. It's checked against takt, and when it's too slow the tool says how many people working in parallel takt would need. If a number looks wrong, fix the step data, not the formula.
Waste — the eight wastes
Waiting, inventory and defects are quantified directly from your step data wherever you captured it; with demand entered, inventory also shows how many days of demand are sitting in queues. The other five wastes stay marked as needing direct observation until your notes give them something concrete — the tool won't invent a number it can't support.
Where the wait concentrates
Every step ranked by the wait that follows it, so the queue worth attacking first is obvious. It's computed from the wait times — there's nothing to enter or override.
Future state
Start from a copy of today's steps, then redesign them against the future-state questions: the customer's pace, where work can flow with no queue, where the next step should pull instead of being pushed, and which single step sets the pace. The pace-against-takt chart shows how many people each step needs working in parallel to keep up. The before-and-after table compares lead time, flow efficiency, work in progress, rolled yield, steps slower than takt and handoffs where work is pushed. Use "Save as a copy" to try another scenario without losing this one.
Countermeasures
Rank by impact and effort, and name the specific finding each one addresses — the constraint, a step slower than takt, the longest wait, a pile-up of work in progress or a named waste. A countermeasure that doesn't trace to a finding is a good idea with no evidence behind it.

4 · What good looks like

What good looks like

The example below maps a custom cabinet shop from confirmed order to shipping: six processes with timing, uptime, defects and a counted queue; customer demand of four cabinets a day, giving a takt of 112.5 minutes; the drawn map and timeline; a capacity constraint (the cutting machine, down a quarter of the time) that is slower than takt; the longest wait and the pile-up of work in progress at material staging; honest waste findings; a future state that brings every step under takt and cuts lead time from 1,180 to 550 minutes; and countermeasures that each name the finding they close.

Same example, as a downloadable xlsx workbook.

Value stream map — current and future state

Custom cabinet order fulfillment

Marcus Webb, Shop Supervisor · 2026-03-02

Team: Dana Ruiz, Scheduling, Priya Nair, Materials · Sponsor: Oksana Petrova, Plant Manager

Scope

Scope runs from a confirmed custom cabinet order landing in the shop to the finished unit being packaged for shipment. One product family (custom kitchen cabinet runs), one shop. Excludes design/quoting before order confirmation and delivery after it leaves the dock.

Customer demand and takt

4 units per day, 450 min available per day.450 minutes available per day ÷ 4 units needed per day = 112.5 minutes per unit

Process steps

StepProcess timeWait afterOperatorsUptimeDefect %Units waiting after
Order intake & spec review20 min180 min1———
Material staging40 min360 min2——8
Machine cutting90 min120 min175%4%—
Assembly150 min90 min3—6%—
Finish & quality check60 min45 min2—3%—
Packaging & ship25 min0 min1———

The map

Lead time · Flow efficiency · Constraint

Lead time

1180 min

Process time

385 min

Flow efficiency

32.63%

Takt

112.5 min

20 + 40 + 90 + 150 + 60 + 25 (process time) + 180 + 360 + 120 + 90 + 45 + 0 (wait time) = 1180 minutes

385 / 1180 × 100 = 32.63%

450 minutes available per day ÷ 4 units needed per day = 112.5 minutes per unit

Capacity constraint

Machine cutting

90 minutes process time ÷ 75% uptime = 120 minutes per unit; the least capacity in the stream — slower than takt of 112.5 minutes, so this step can't keep pace with demand as it runs today. At takt it needs 120 ÷ 112.5 = 1.07 operators working in parallel — 2 once rounded up — and it has 1.

Longest wait

Material staging

360 min · 30.51% of lead time

Pace against takt

  • Order intake & spec review

    20 min per unit

  • Material staging

    20 min per unit

  • Machine cutting

    120 min per unit — slower than takt; needs 2 working in parallel, has 1

  • Assembly

    50 min per unit

  • Finish & quality check

    30 min per unit

  • Packaging & ship

    25 min per unit

The black line is takt (112.5 min). Bars show each step's time per unit once downtime and people working in parallel are counted.

Slower than takt: Machine cutting — these steps can't keep pace with customer demand as they run today.

Where work waits

  • Order intake & spec review — Work waits 180 minutes after this step — 15.25% of total lead time, above the 15% flag threshold.
  • Material staging — Work waits 360 minutes after this step — 30.51% of total lead time, above the 15% flag threshold.

Where work piles up

  • Material staging — 8 of the 8 units counted waiting in queues (100.00%) sit after this step, above the 25% flag threshold. At 4 units needed per day, that's 8 ÷ 4 = 2 days of demand sitting in the queue.

Waste — the eight wastes

  • Defects12.47 %

    Rolled throughput yield across the 3 steps with a recorded defect rate is 87.53% — about 12.47% of units need rework or scrap somewhere in the stream, so first-pass output is lower than any single step suggests.

    (1 - 4/100) × (1 - 6/100) × (1 - 3/100) × 100 = 87.53% yield — from Machine cutting (4%), Assembly (6%), Finish & quality check (3%); defects = 100 − 87.53 = 12.47%

  • OverproductionQualitative

    Not quantified from step timings. On the next walk, look for producing more than the next process pulls, or running ahead of takt — batches built early, reports nobody reads.

  • Waiting795 minutes

    Work sits idle for 795 minutes in total across this value stream, queued after 5 of 6 steps.

    180 + 360 + 120 + 90 + 45 + 0 = 795 minutes

  • Non-utilized talentQualitative

    Not quantified from step timings. Look for operators' process knowledge or improvement ideas going unused — people closest to the work with no route to change it.

  • TransportationQualitative

    Not quantified from step timings. Look for unnecessary movement of material or information between steps — handoffs, re-keying, files shuttled between systems.

  • Inventory8 units

    8 units of work in progress sit in queues after 1 of 6 steps — about 2 days of customer demand — every one of them is finished effort not yet paid for.

    Material staging (8) = 8 units; 8 ÷ 4 units needed per day = 2 days of demand

  • MotionQualitative

    Not quantified from step timings. Look for unnecessary operator movement within a step — reaching, searching, walking to fetch what the work needs.

  • Extra-processingQualitative

    Not quantified from step timings. Look for doing more to the product or information than the customer actually values — extra approvals, duplicate checks, unused detail.

Where the wait concentrates

Ranked by wait time after each step

  • Material staging360 min
  • Order intake & spec review180 min
  • Machine cutting120 min
  • Assembly90 min
  • Finish & quality check45 min
  • Packaging & ship0 min

Future state

MeasureCurrentFutureChange
Lead time1180 min550 min-53.39%better
Process time385 min350 min-9.09%better
Wait time795 min200 min-74.84%better
Flow efficiency32.63%63.64%+95.04%better
Steps660.00%
Work in progress8 units4 units-50.00%better
Rolled yield87.53%93.16%+6.43%better
Steps slower than takt10-100.00%better
Handoffs where work is pushed52-60.00%better

Orders are reviewed the day they arrive and released to the cutting machine by a pull signal from a 4-pallet staging cap. Assembly runs as two balanced stations to beat takt. Preventive tool changes at shift start lift the cutting machine's uptime. The finish and quality check pulls directly from assembly with no batch queue.

Countermeasures

  • Move tool changes on the cutting machine to a planned slot at the start of each shift and fix the dust-extraction fault, so the machine is available enough to cut each cabinet inside takt.

    Linked finding: Machine cutting — capacity constraint at 120 minutes per unit (90 minutes at 75% uptime), slower than the 112.5-minute takt

    Impact: high · Effort: medium · Owner: Marcus Webb · Due: 2026-03-30

  • Cap material staging at 4 pallets and pull the next order onto the cutting machine only when a slot frees up, instead of staging everything as soon as it's confirmed.

    Linked finding: Material staging — longest wait at 30.51% of lead time, 8 units waiting (2 days of demand)

    Impact: high · Effort: medium · Owner: Priya Nair · Due: 2026-03-23

  • Move spec review from a once-daily batch to same-day, and add a dimension-conflict checklist so cut-list rework is caught before cutting and assembly time is spent.

    Linked finding: Order intake & spec review — 15.25% of lead time waiting; Defects — 12.47% lost across machine cutting, assembly and the finish and quality check

    Impact: medium · Effort: low · Owner: Dana Ruiz · Due: 2026-03-16

5 · Common mistakes

Common mistakes

  • Flow efficiency is estimated instead of computed from real step data.

    A guessed 30% and a computed 14% lead to very different conversations. The whole point of measuring is to replace the guess.

  • The constraint is assumed to be the step with the longest process time.

    A shorter step that's down a quarter of the time, or staffed by one person, can have less capacity than a longer step with three people working it side by side. Record uptime and operators where you saw them, and check the constraint against takt.

  • Every step gets flagged as a problem.

    If everything is flagged, nothing is prioritised. Name the one or two findings actually worth acting on first — usually the constraint and the longest wait — not every step with some wait.

  • Boxes are people or tasks rather than whole processes.

    A value stream map with two boxes for the same team is a process map drawn at the wrong scale, and it buries the waits between departments under detail. Keep boxes at process level; map the inside of a single box separately when you need to.

  • The future state is drawn as the ideal, with nothing that has to change to get there.

    A future state only earns its numbers if something makes them possible — uptime fixed, a queue capped, a handoff removed. Each of those changes belongs in the countermeasures with an owner and a date.

  • The value stream's scope keeps growing mid-analysis.

    A value stream mapped without a stated start and end drifts to cover every variant and exception, and the resulting numbers describe nothing in particular.

6 · What it connects to

What it connects to

upstream

  • Go-see protocol

    How to collect the step data on a real walk — watching the work as it happens rather than reconstructing it from memory.

  • Eight wastes (DOWNTIME) worksheet

    A waste walk on the same process gives the five wastes step timings can't measure something concrete to point to.

downstream

  • Makigami process map

    When one box hides a tangle of handoffs, approvals and rework, explore that step with a Makigami — its work time and first-pass yield flow back into this map's step.

  • A3 problem solving

    The constraint, a step slower than takt, or the longest wait is exactly the kind of bounded, data-backed problem an A3 exists to close.

  • Implementation plan

    Turns the future state's countermeasures into dated, owned milestones so the design actually gets built.

Part of these playbooks

7 · Where AI helps

Where AI helps

Judgement — stays yours

  • Deciding where to draw the value stream's scope boundary
  • Choosing the future-state design and what has to change to make it work
  • Committing to which finding to act on first

Analysis — AI helps

  • Drafting waste narratives from raw gemba observation notes
  • Pressure-testing whether a proposed countermeasure actually addresses the named finding
  • Ranking countermeasures by impact and effort

Drudgery — automated

  • Drawing the map and timeline from the step data
  • Computing lead time, flow efficiency, takt and the capacity constraint, with every calculation shown
  • Quantifying waiting, inventory and defect waste wherever the data supports it
  • Comparing the future state with the current state, measure by measure
  • Exporting to xlsx in the house format

9 · Rate this kata

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