The Question Executives Are Actually Asking
Here's the question I get from every executive sponsor in
every agile transformation I've ever run:
"Are we predictable?"
Not "are we busy?" Not "are we shipping
features?" Not "is velocity trending up?"
Are the commitments we make to the business actually
holding up?
That's the whole game. And yet — after 30 years and 150+
implementations — I can tell you that almost no team is measuring
predictability directly. They're measuring velocity. They're tracking story
points. They're running burn down charts.
And then they're wondering why leadership still doesn't
trust the sprint.
This episode is about PACE — the
Predictability and Capacity Engine. The third AI agent in this series. And it
answers that question directly.
The Problem With Agile Metrics As We Know Them
Velocity is a lagging indicator. So is burn down. So are
story points.
They tell you what happened. They don't tell you why stories
slipped, whether you're getting better or worse over time, or what to do about
it.
Here's the contrarian truth: velocity going up
doesn't mean you're getting better. It might mean you're getting
faster at moving unfinished work to the next sprint.
I've seen teams with 40% velocity growth and deteriorating
stakeholder trust. Because the metric wasn't measuring what mattered.
The Distinction That Changes Everything
PACE makes one critical distinction that most agile tools
completely ignore:
Is the problem capacity — or readiness?
Capacity is team size, sprint commitment, available hours.
Readiness is whether stories enter the sprint with clear requirements, complete
designs, resolved dependencies, and defined acceptance criteria.
You cannot fix a readiness problem by adding people. You
cannot fix a capacity problem by tightening story quality. These are different
problems with different solutions — and confusing them is expensive.
PACE separates them. Every sprint, every team, over time.
Two Metrics That Actually Matter
Slide Rate — the percentage of stories committed
to a sprint that don't finish in that sprint.
Benchmark: under 15%, ideally under 10%. Consistently above
20%? You're either over-committing or accepting unready work. Probably both.
Readiness Debt — the percentage of stories that
entered a sprint without meeting readiness criteria: requirements unclear,
designs incomplete, dependencies unresolved, acceptance criteria undefined.
Here's why readiness debt is the more important
metric: it's a leading indicator. It predicts slide rate
before the sprint closes.
Forty percent readiness debt will cause
slide. Not if. How much.
The Real Client Story
Large financial services company. Two years of agile.
Forty-three sprint cycles. Nearly 50,000 user stories.
Surface metrics? Fine. Velocity trending up. Cost per story
point trending down. Team getting more efficient by every standard measure.
But leadership had this persistent feeling that commitments
weren't holding. They couldn't quantify it. They just knew something was off.
I pulled 48,621 Jira issues and ran them
through PACE.
The finding wasn't what anyone expected. The team wasn't
getting worse at execution. They were getting worse at readiness — and
it was accelerating.
Slide rate had climbed from 11.8% to 18% for Team A, and the
newer team was sitting at 28%.
The instinct in the room was to ask: "How do we
increase velocity?" PACE revealed the real question: "Why are
we accepting unready work into sprint?"
One story stayed with me. Marked complete. But couldn't be
tested — undiscovered dependencies surfaced mid-sprint. The entire team spent
that sprint discussing what to do with the ticket. Should have been resolved
pre-sprint.
That's not an execution failure. That's a readiness failure.
And you'd never see it in a velocity chart.
How PACE Works
Export your sprint history from Jira, Azure DevOps, Planner,
or even a spreadsheet. PACE ingests it, normalizes the data, identifies
committed, completed, and slipped stories, and calculates slide rate and
readiness debt per sprint — then trends them over time.
Four deliverables come out the other side:
Sprint dashboard — color-coded by health. Green:
slide rate under 10%, readiness debt under 15%. Yellow: 10–20% / 15–30%. Red:
above that. You see the trend at a glance.
Best and worst sprint identification — best
sprints are benchmark proof that the team can be predictable
when conditions are right. Worst sprints are investigation targets. What
happened? What entered unready?
Trend analysis narrative — "Slide rate
increased from 10% to 25% over 12 months. The team isn't getting worse at
execution. They're being asked to execute unready work." That distinction
is critical — it tells leadership this is a process problem, not a people problem.
Action recommendations — targeted to what the
data actually shows. Capacity recommendations for capacity problems. Readiness
recommendations for readiness problems. Retrospective targets for the worst
sprints.
Minutes to run. Months of insight.
The Cost Per Story Point Metric
This is my signature metric. Sprint by sprint, it shows team
efficiency over time — not just "did velocity go up?" but "did
we get more done per dollar?"
When you add three people, PACE shows whether you actually
got more efficient, or whether you just added cost. When you split a team, PACE
shows the productivity impact on both resulting teams —
because splitting a high-performing team often tanks both for months before
they stabilize.
The portfolio-scale version of this question: "If
I add 40 people, how do I know we're more productive?"
PACE answers it. Trending cost per story point and velocity
across the full backlog over time. Metrics that were previously impossible to
calculate without a data science team and six months of work.
The Discipline Paradox
Here's the thing about discipline: it feels like friction.
It feels like you're slowing down to do readiness checks, to enforce acceptance
criteria, to push back on stories that aren't ready.
But discipline is what makes you fast.
When stories enter ready, they complete on time. When
sprints finish clean, velocity stabilizes. When commitments hold up,
stakeholders trust you. When stakeholders trust you, you get more autonomy,
more resources, more runway.
PACE doesn't just measure output. It measures discipline.
And discipline compounds.
Portfolio Scale
Run PACE across 10, 20, 100 teams. Now you have a
portfolio-level view: which teams are predictable, which are degrading, which
have chronic readiness debt.
Compare Team A — 8% slide rate — to Team B — 30% slide rate
— on similar projects. What's different? Spread what works. Identify where
coaching is needed before the team hits a wall.
That's organizational learning at portfolio scale. Most
organizations have the data for this already sitting in their sprint tools.
They just don't have the engine to surface it.
PACE and ARIA: Better Together
ARIA — the risk intelligence agent from Episode 10 —
operates at the project level. Health scores, risk indicators, executive
dashboards.
PACE operates at the team execution level. Sprint
discipline, readiness, predictability.
Together, they answer the two questions every delivery
leader needs answered: Is this project healthy? (ARIA)
and Is this team predictable? (PACE).
PACE's health check looks forward at the current sprint —
how many stories are committed, how many have entered unready, what the
projected slide rate is if current trends hold. Leadership doesn't wait until
sprint close to know there's a problem.
Early warning. Portfolio-wide.
Next Up: Gatekeeper
Episode 13 is the finale — Gatekeeper, the
portfolio intelligence agent that decides which projects should even start.
Most organizations say yes to too many things. When
everything is a priority, nothing is. Gatekeeper reality-checks the portfolio,
surfaces impossible dates, shows where capacity doesn't exist, and forces the
hard conversations before commitment — not after.
That one's going to challenge some deeply held
organizational habits.
For more resources: PMThatWorks.com
— Rick A. Morris
