Value stream mapping
Bottleneck analysis
Bottleneck analysis is licensed CC BY 4.0. Attribution: Katafacts (katafacts.com).
Customise with AISkill file ↓1 · What it is
What it is
Every value stream has two distinct constraint questions, and they don't always have the same answer: which stage has the least capacity (the capacity constraint — active work per deal, stretched by any downtime you record, shared across the people working that stage in parallel, and checked against takt if you give demand), and which stage chokes flow worst (the one with the largest wait time — where deals sit stalled longest). A bottleneck analysis answers both directly from your stage data, the same computation the sales funnel value stream map runs as part of its fuller picture, pulled out on its own for when the question is specifically 'which stage do I fix first,' not a full documented map.
2 · When to use it
When to use it — and when not to
Use it when
- You already suspect the pipeline has a problem stage and want it named with the arithmetic behind it, not just a gut feeling confirmed.
- You need to decide where to focus limited attention first — one specific stage, not a general 'speed up the funnel' initiative.
- You have per-stage process and wait time and want the capacity constraint and the largest wait contributor identified without building a full map.
Not when
- You want the overall flow-efficiency percentage, not a specific stage — that's the funnel flow efficiency calculator.
- You want waste findings, a Pareto ranking of every stage, or countermeasures — this deliberately only surfaces the two constraint findings, not the fuller picture the sales funnel value stream map builds.
- Every stage in your pipeline has roughly the same process and wait time — there's no single bottleneck to name, and forcing one would misdirect the fix.
3 · How to fill it in
How to fill it in
- Scope
- Just the one-line description at the top. Keep it to one comparable pipeline segment, same discipline as every other value-stream kata — a blended segment produces a bottleneck finding that describes neither.
- Customer demand and takt
- Optional, but it sharpens the answer: with the deals needed per week or month, the tool says whether the constraint stage is actually too slow for demand, not just the slowest.
- Process steps
- List each stage in order with its process time and the wait time after it. This is the only real intake — paste rows straight from a customer relationship management (CRM) export if you have them.
- The map
- Drawn from your stages, with bursts on the capacity constraint and the longest stall so the two answers are visible side by side.
- Lead time · Flow efficiency · Constraint
- The capacity constraint (the stage with the least capacity once downtime and the people working it in parallel are counted) and the largest wait contributor are identified for you the moment you submit — that's this tool's whole output, with the arithmetic shown.
- Waste — the eight wastes
- Not part of this tool's output. The full sales funnel value stream map runs the complete eight-wastes breakdown; this one only names the two constraint stages.
- Where the wait concentrates
- Not part of this tool's output as a ranked list — you get the single largest wait contributor directly, not a ranking of every stage. Use the full sales funnel value stream map if you want every stage ranked.
- Future state
- Optional — once the constraint is named, sketch the funnel with it relieved in the same editor and check whether the next constraint appears.
- Countermeasures
- Not part of this tool's output — there's no observation-notes field feeding a countermeasure narrative here. Once the constraint stage is named, the sales funnel value stream map or a deal A3 is where you'd work through what to do about it.
4 · What good looks like
What good looks like
The example below is the same six-stage outbound funnel as the full sales funnel value stream map, because the constraint findings this tool surfaces are exactly the ones that map computes as part of its fuller analysis. What's different is the path: this page only asked for stage names, process time, and wait time.
Same example, as a downloadable xlsx workbook.
Value stream map — current state
Mid-market outbound pipeline — current-state analysis
Jordan Ellis, Sales Manager · 2026-03-16
Team: Priya Anand, Revenue Operations, Sam Cole, Sales Enablement · Sponsor: Renee Okafor, Vice President of Sales
Scope
Scope runs from a lead being accepted as sales-qualified to closed-won or closed-lost, for outbound-sourced mid-market deals only. Excludes marketing nurture before a lead is sales-qualified and post-close onboarding — those are separate value streams with their own owners.
Customer demand and takt
No customer demand recorded, so takt isn't checked.
Process steps
| Step | Process time | Wait after | Operators | Uptime | Defect % | Units waiting after |
|---|---|---|---|---|---|---|
| Lead qualification | 2 h | 24 h | 1 | — | 40% | — |
| Discovery call | 3 h | 96 h | 1 | — | 35% | — |
| Solution demo | 4 h | 120 h | 1 | — | 25% | 22 |
| Proposal & pricing | 6 h | 168 h | 2 | — | 30% | — |
| Negotiation | 5 h | 72 h | 1 | — | 15% | — |
| Contract signed | 2 h | 0 h | 1 | — | — | — |
The map
Drag to move around · Ctrl or ⌘ + scroll, pinch, or + and − to zoom · 0 to fit
Lead time · Flow efficiency · Constraint
Lead time
502 h
Process time
22 h
Flow efficiency
4.38%
Takt
—
2 + 3 + 4 + 6 + 5 + 2 (process time) + 24 + 96 + 120 + 168 + 72 + 0 (wait time) = 502 hours
22 / 502 × 100 = 4.38%
Takt: add customer demand to check each step against the pace the customer needs.
Capacity constraint
Negotiation
5 hours process time (no downtime recorded); the least capacity in the stream — add customer demand to check it against takt.
Longest wait
Proposal & pricing
168 h · 33.47% of lead time
Where work waits
- Discovery call — Work waits 96 hours after this step — 19.12% of total lead time, above the 15% flag threshold.
- Solution demo — Work waits 120 hours after this step — 23.90% of total lead time, above the 15% flag threshold.
- Proposal & pricing — Work waits 168 hours after this step — 33.47% of total lead time, above the 15% flag threshold.
Where work piles up
- Solution demo — 22 of the 22 units counted waiting in queues (100.00%) sit after this step, above the 25% flag threshold.
Waste — the eight wastes
- Defects82.6 %
Rolled throughput yield across the 5 steps with a recorded defect rate is 17.40% — about 82.60% of units need rework or scrap somewhere in the stream, so first-pass output is lower than any single step suggests.
(1 - 40/100) × (1 - 35/100) × (1 - 25/100) × (1 - 30/100) × (1 - 15/100) × 100 = 17.40% yield — from Lead qualification (40%), Discovery call (35%), Solution demo (25%), Proposal & pricing (30%), Negotiation (15%); defects = 100 − 17.40 = 82.60%
- 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.
- Waiting480 hours
Work sits idle for 480 hours in total across this value stream, queued after 5 of 6 steps.
24 + 96 + 120 + 168 + 72 + 0 = 480 hours
- 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.
- Inventory22 units
22 units of work in progress sit in queues after 1 of 6 steps — every one of them is finished effort not yet paid for.
Solution demo (22) = 22 units
- 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
- Proposal & pricing168 h
- Solution demo120 h
- Discovery call96 h
- Negotiation72 h
- Lead qualification24 h
- Contract signed0 h
Future state
No future state designed yet.
Countermeasures
Pre-approve standard pricing tiers for deals under a set contract-value threshold so they skip the two-approver review entirely; keep the full review only for genuinely custom terms.
Linked finding: Proposal & pricing — largest wait contributor at 33.47% of lead time
Impact: high · Effort: medium · Owner: Priya Anand · Due: 2026-04-06
Cap the number of deals allowed to sit between Solution demo and Proposal at any time, pulling the next demo only when a proposal slot frees up, instead of running demos as fast as reps can book them.
Linked finding: Solution demo — 22 deals stalled in the queue, wait time 23.90% of lead time
Impact: medium · Effort: medium · Owner: Jordan Ellis · Due: 2026-04-13
Tighten the criteria marketing uses to hand over sales-qualified leads so fewer poorly-fit leads enter the pipeline only to drop out at qualification — add one firmographic checkpoint before a lead is marked sales-qualified.
Linked finding: Defects — 17.40% rolled throughput yield across 5 stages; Lead qualification is the single largest contributor at 40% drop-off
Impact: medium · Effort: low · Owner: Sam Cole · Due: 2026-04-06
5 · Common mistakes
Common mistakes
Treating the capacity constraint and the largest wait contributor as the same stage without checking.
They frequently aren't the same stage — one caps how much work can move through per unit time, the other is where already-started work sits stalled longest. Fixing the wrong one for the problem you actually have wastes the attention this tool is meant to focus.
Naming a bottleneck from a pipeline segment that blends genuinely different deal types.
Same scope discipline as every other value-stream kata — a blended segment's 'bottleneck' is an artifact of the blend, not a real constraint in either underlying segment.
Acting on the bottleneck finding without re-running the analysis after the fix.
Removing one constraint reliably surfaces the next one — a bottleneck analysis is a snapshot, not a one-time diagnosis, the same theory-of-constraints principle that applies on a shop floor.
6 · What it connects to
What it connects to
upstream
downstream
Once the constraint stage is named, this is where you'd build the fuller picture — waste findings, a full Pareto ranking, and countermeasures tied to the finding.
Funnel flow efficiency calculator
If the question shifts from 'which stage' to 'how bad is it overall,' this is the more direct next step.
Deal A3 — win-rate root cause analysis
Once a specific constraint stage is named, a deal A3 is where you'd run root cause analysis on why that stage specifically is capping throughput or choking flow.
Part of these playbooks
- Sales Funnel Management Katas — 13 katas in the order they are used
7 · Where AI helps
Where AI helps
Judgement — stays yours
- Deciding whether the capacity constraint or the largest wait contributor is the more urgent one to act on first
- Judging whether a named bottleneck is structural or a one-off caused by unrelated circumstances
Analysis — AI helps
- Nothing here — identifying the constraint stages is a deterministic calculation, not an analysis judgement call
Drudgery — automated
- Identifying the capacity constraint and the largest wait contributor from stage data, with the arithmetic shown
- Exporting to xlsx in the house format
9 · Rate this kata