Last week, I spoke with a product leader who was frustrated. His team was working harder than ever. Sprint velocity looked good on paper. But business outcomes remained flat. “We’re delivering,” he said, “but nothing’s moving fast enough.”
I asked him one question: “How much of your team’s time is spent waiting versus working?”
He didn’t know. And that’s the problem.
The 15% Reality
Most product teams operate at 15–25% flow efficiency. That means for every hour of actual work, there are three to five hours of waiting. Your team isn’t slow because they’re lazy. They’re slow because 75–85% of the time, work is sitting idle — waiting for approval, waiting for dependencies, waiting for the next handoff.
According to research on flow metrics, this efficiency gap is the single largest predictor of delivery performance. Yet most organizations don’t measure it. They track velocity, throughput, and cycle time. Those metrics tell you how much you’re delivering. Flow Efficiency tells you why you’re not delivering more.
You can’t transform what you can’t measure. But most teams measure activity, not latency.
Why Velocity Hides the Problem
Velocity measures output: how many story points you complete per sprint. Throughput measures items delivered over time. Both are useful. But neither reveals the difference between “busy” and “productive.”
A team can have high velocity while flow efficiency remains terrible. They’re completing work, but each item takes three times longer than it should because of wait states: approval chains, dependency queues, handoffs between specialized teams, context switching from excessive work-in-progress.
Flow Efficiency exposes the difference between theater and capability: busy teams versus effective systems.
In a former article, I wrote about capability gaps in product transformation. Flow Efficiency exposes which gaps cost you the most. It’s the diagnostic metric that makes latency visible.
The Five Flow Metrics Framework
Mik Kersten introduced the Five Flow Metrics framework to give product teams a complete view of delivery health:
- Flow Time: Total time from start to finish
- Flow Velocity: Number of items completed over time
- Flow Efficiency: Percentage of time spent on active work
- Flow Load: Work currently in progress
- Flow Distribution: Balance of work types (features, defects, risk, debt)
All five matter. But Flow Efficiency is the one that reveals bottlenecks.
The calculation is simple:
Flow Efficiency = (Active Time / Total Time) × 100
Active Time is when someone is actually working on the item. Total Time is from idea to production. If a feature takes 20 days end-to-end but only 4 days of actual work, your Flow Efficiency is 20%.
That means 16 days were spent waiting.
The Five Latency Bottlenecks
Where does that waiting time hide? Most organizations have five common bottlenecks:
1. Handoffs Between Specialized Teams Work moves from product to design to engineering to QA to ops. Each handoff adds queue time. The item sits in a backlog until that team has capacity.
2. Approval Chains and Dependencies Every gate, review, or dependency creates a wait state. Work can’t move forward until someone signs off or another team delivers their piece.
3. Context Switching from Excessive WIP When teams have too much work in progress, people constantly switch contexts. Each switch costs time. Items spend more time waiting in someone’s mental queue than being actively worked on.
4. Technical Debt and Architectural Constraints Legacy systems, brittle code, and architectural dependencies slow everything down. Teams spend time working around problems instead of solving them.
5. Decision-Making Delays Product decisions get escalated, debated, or deferred. Work waits while teams seek clarity, alignment, or permission.
According to LinearB’s analysis of flow metrics, reducing these bottlenecks has a direct impact on business outcomes. McKinsey’s research on product operating models shows that organizations with streamlined flow deliver 20–30% faster time-to-market and measurably better business results.
But you can’t improve what you don’t measure. And most teams don’t measure latency.
The 4-Week Flow Efficiency Diagnostic
Here’s a pragmatic framework you can start using next week. No consultants. No expensive tools. Just evidence-based diagnosis.
Week 1: Instrument One Value Stream
- Map the end-to-end journey for one product or feature area (idea → production)
- Identify all wait states (approval queues, handoffs, dependencies) and active states (design, coding, testing)
- Don’t try to fix anything yet. Just make latency visible.
Week 2: Measure Baseline
- Track one batch of work items through the system (5–10 items is enough)
- For each item, record active time versus total time
- Calculate: Flow Efficiency = (Active Time / Total Time) × 100
- Identify your top 3 latency bottlenecks (where work waits the longest)
Week 3: Run One Experiment
- Target the highest-impact bottleneck
- Reduce a handoff (cross-functional team), limit WIP (reduce context switching), or empower decision-making (eliminate an approval gate)
- Measure the impact on flow efficiency for the next batch of work
Week 4: Review and Scale
- Compare before/after flow efficiency
- Share findings with stakeholders: “We improved efficiency from 18% to 27%, cutting waiting time by 1/3 — without adding people or budget.”
- Decide: scale the experiment, iterate the approach, or pivot to a different bottleneck
Success Metric: If flow efficiency improves from 20% to 30%, you’ve reduced waiting time by 33%. That’s a third less latency — without changing headcount, budget, or tooling.
From Measurement to Action
Flow Efficiency is a diagnostic, not a goal. The goal is business outcomes: faster time-to-market, better product-market fit, stronger competitive advantage.
But you can’t achieve those outcomes without reducing latency.
Start small. Instrument one value stream. Measure one baseline. Run one experiment. According to ProductPlan’s 2025 State of Product Management report, more product leaders are shifting from activity metrics (velocity, output) to outcome metrics (impact, efficiency). And as EasyAgile’s 2025 trends analysis highlights, the teams winning in 2025 are the ones focusing on practical delivery improvements — not transformation theater.
Flow Efficiency connects capability to outcomes. It reveals where your system is broken. And it gives you evidence to prioritize fixes that matter.
Agility isn’t a framework. It’s a capability. And capability requires reducing latency, not just increasing activity.
Where to Start
Pick one product. Map one value stream. Measure flow efficiency for one month. You’ll learn more from that data than from a year of sprint retrospectives.
The intelligence is in the diagnosis. Once latency is visible, bottlenecks become solvable problems. And when you remove bottlenecks empirically — one experiment at a time — evolution becomes inevitable.
Ralph Jocham is Europe’s first Professional Scrum Trainers, co-author of “Professional Product Owner,” and contributor to the Scrum Guide Expansion Pack. As a ICF ACC certified coach, works with organizations to build Product Operating Models where strategic clarity, operational excellence, and adaptive learning create measurable competitive advantage. Learn more at effective agile.