Value stream mapping

Funnel PCE calculator

Funnel PCE calculator is licensed CC BY 4.0. Attribution: Katafacts (katafacts.com).

1 · What it is

What it is

Process cycle efficiency (PCE), also called flow efficiency, is the share of total time a deal is actually being worked versus sitting idle: process time divided by total lead time (process time plus wait time), across every stage. It's the single most useful number in a funnel value stream map (see the sales funnel value stream map), pulled out on its own for the case where a full documented map is more than you need right now. Most funnels come back under 10% — the finding almost every revenue team is missing is not which stage is slow, it's how little of the pipeline's total duration is spent on active work at all.

2 · When to use it

When to use it — and when not to

Use it when

You want the headline flow-efficiency number fast — a sanity check before deciding whether a full funnel value stream map is worth the time.
You already have per-stage process and wait time from the CRM and just want it turned into a defensible percentage with the arithmetic shown.
You're building a case for why pipeline velocity work matters and need one number a leadership team will immediately understand is too low.

Not when

You need to know *which* stage to fix, not just the overall number — that's the sales funnel value stream map or the bottleneck analysis, both of which compute this same number as part of a fuller picture.
You want waste findings, a Pareto ranking, or countermeasures — this calculator deliberately doesn't ask for the observation notes those are drawn from.
You only have a single blended total-cycle-time figure with no per-stage breakdown — flow efficiency needs at least process time and wait time distinguished per stage, not just a start and end date.

3 · How to fill it in

How to fill it in

Scope: Just the one-line description at the top — what pipeline segment this is. There's no separate scope field here; keep it as tight as you would for a full funnel map (one deal source or segment, not the whole blended pipeline).
Process steps: List each stage in order with its process time and the wait time after it before the next stage starts. This is the only real intake this calculator asks for — paste rows straight from a CRM export if you have them.
Lead time · Process time · Flow efficiency: Flow efficiency, lead time, and the stage capping throughput are computed for you the moment you submit — this is the whole point of the calculator, not a step you fill in.
Waste — the eight wastes: Not part of this calculator's output — it only computes flow efficiency and the constraint. Use the sales funnel value stream map for the full eight-wastes breakdown.
Where the wait concentrates: Not part of this calculator's output. The full sales funnel value stream map ranks every stage by wait-time contribution; this tool only surfaces the single largest one.
Countermeasures: Not part of this calculator's output — there's no observation-notes field feeding a countermeasure narrative here. Once you know the number's worth acting on, the sales funnel value stream map 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 flow-efficiency number this calculator produces is exactly the same number that map computes as part of its fuller analysis, not a different calculation. What's different is the path to get here: this page only asked for stage names, process time, and wait time.

Same example, as a downloadable xlsx workbook.

Download .xlsx

Value stream map — current state

Mid-market outbound pipeline — current-state analysis

Jordan Ellis, Sales Manager · 2026-03-16

Team: Priya Anand, RevOps, Sam Cole, Sales Enablement · Sponsor: Renee Okafor, VP Sales

Scope

Scope runs from a lead reaching SQL (sales-qualified) status to closed-won or closed-lost, for outbound-sourced mid-market deals only. Excludes pre-SQL marketing nurture and post-close onboarding — those are separate value streams with their own owners.

Process steps

Step	Process time (hours)	Wait after (hours)	Operators	Defect %	WIP after
Lead qualification	2	24	1	40%	—
Discovery call	3	96	1	35%	—
Solution demo	4	120	1	25%	22
Proposal & pricing	6	168	2	30%	—
Negotiation	5	72	1	15%	—
Contract signed	2	0	1	—	—

Lead time · Process time · Flow efficiency

Lead time

502 hours

Process time

22 hours

Flow efficiency

4.38%

2 + 3 + 4 + 6 + 5 + 2 (process time) + 24 + 96 + 120 + 168 + 72 + 0 (wait time) = 502 hours

22 / 502 × 100 = 4.38%

Capacity constraint

Proposal & pricing

6 hours · 1.20% of lead time

Largest wait contributor

Proposal & pricing

168 hours · 33.47% of lead time

WIP flags

Discovery call — Wait time here is 19.12% of total lead time, above the 15% flag threshold — this is where WIP is piling up.
Solution demo — Wait time here is 23.90% of total lead time, above the 15% flag threshold — this is where WIP is piling up.
Proposal & pricing — Wait time here is 33.47% of total lead time, above the 15% flag threshold — this is where WIP is piling up.

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 cost

Proposal & pricing168
Solution demo120
Discovery call96
Negotiation72
Lead qualification24
Contract signed0

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, and the capacity constraint at 6 hours of active work per deal
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 units of WIP queued, wait time 23.90% of lead time
Impact: medium · Effort: medium · Owner: Jordan Ellis · Due: 2026-04-13
Tighten the SQL handoff criteria with marketing so fewer poorly-fit leads enter the pipeline only to drop out at qualification — add one firmographic checkpoint before a lead is marked SQL.
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 a low flow-efficiency number as the finding itself, with no next step.
A single percentage tells you the pipeline is mostly waiting, not why or where. Once the number is low enough to act on, move to the full funnel value stream map to find the specific stage worth fixing.
Mixing deal segments with genuinely different natural cycles to get one 'overall' number.
A blended self-serve-plus-enterprise flow efficiency describes neither segment — same scope discipline as every other VSM-family artifact in this catalogue.
Estimating stage timing from memory instead of pulling actual CRM stage-entry and stage-exit timestamps.
Flow efficiency is only as trustworthy as the timing data behind it — a guessed number that looks precise is worse than an honest 'we don't have this data yet.'

6 · What it connects to

What it connects to

upstream

downstream

Sales funnel value stream map
Once the flow-efficiency number is low enough to warrant real attention, this is where you find which specific stage to act on and what to do about it.
Bottleneck analysis
If the question is specifically 'which stage is capping throughput' rather than 'what's my overall efficiency,' this is the more direct next step.

7 · Where AI helps

Where AI helps

Judgement — stays yours

Deciding whether the number is low enough to justify a full funnel value stream map
Drawing the pipeline segment's scope boundary

Analysis — AI helps

Nothing here — flow efficiency is a deterministic calculation, not an analysis judgement call

Drudgery — automated

Computing lead time and flow efficiency, with the arithmetic shown
Identifying the single largest wait contributor
Exporting to xlsx in the house format

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