Measuring What Matters

The dashboard is green.

Every metric within threshold. Every SLA met. Every ticket closed on time.

The board is happy. The exec team is celebrating.

And yet, people are struggling.

They’re working around the system. Creating shadow processes. Emailing colleagues instead of using the official channels. Building spreadsheets because the “approved” process doesn’t fit their reality.

The metrics say everything is fine.
The humans say it’s broken.

Who’s right?

The Tyranny of the Measurable

We’ve been conditioned to believe that what gets measured gets managed.

But we rarely ask the harder question: Are we measuring the right things?

Most service metrics were designed for control, not insight:

• Request volume (activity, not outcome)
• Processing time (speed, not quality)
• Compliance rates (contractual coverage, not real satisfaction)
• Service availability (presence, not usability)

These aren’t bad metrics. They’re just incomplete.

They tell us what the system is doing.
They don’t tell us what people are experiencing.

And when we optimize for incomplete metrics, we get perverse outcomes - because these metrics aren’t insight, they’re concealment. Like hiding behind a window, we think the display of measurement protects us from admitting we don’t really understand what’s happening. We can see out (sort of), but we convince ourselves no one can see in. Except they can. The customers can. The teams can. Everyone can see we’re measuring activity while value slips away.

• Tickets closed quickly but problems unresolved
• Services “available” but unusable
• SLAs met while trust erodes
• Everything green while morale collapses

We measure noise and miss signal.

What We’re Actually Measuring

Let’s be honest about what traditional service metrics really capture:

Activity Masquerading as Progress

“We processed 10,000 requests this month!”

Great. How many of those created real value vs. people completing forms because they had to?

In HR, it’s applications processed. In Finance, it’s transactions cleared. In Legal, it’s contracts reviewed.

But volume measures engagement with the system, not value delivered to humans.

It’s like measuring hospital admissions and calling it healthcare.

Speed Without Quality

“Average processing time: 2.4 hours!”

Brilliant. How many of those outcomes actually worked?

In procurement: How many purchase orders had to be corrected?
In onboarding: How many new hires needed follow-up support?
In customer service: How many cases got reopened?

Speed metrics measure completion, not resolution.

Compliance Without Trust

“99.9% SLA compliance!”

Wonderful. Do people trust the service?

Because compliance is a contractual floor, not a ceiling.
You can hit every SLA and still have a service nobody wants to use.

Meeting SLAs measures defensive success, not positive impact.

Availability Without Usability

“Five nines uptime!”

Fantastic. Can people actually do what they need to do?

A service can be “up” and still be:

• Too slow to be useful
• Too confusing to navigate
• Too fragmented to complete a task
• Too frustrating to trust

Uptime measures technical availability, not human effectiveness.

These metrics aren’t lies. They’re just incomplete truths.

And incomplete truths, when treated as complete, become dangerous fictions.

The Human Dimensions We Ignore

So what are we missing?

If traditional metrics capture system behavior, what would human-centric metrics look like?

OSM introduces three core dimensions that most organisations never measure:

Friction: The Effort Tax

Friction is the invisible cost of getting things done.

It’s not about whether the service works - it’s about how hard people have to work to make it work.

Friction shows up everywhere:

• In HR: The unofficial “ask Jenny” channel because the HRIS doesn’t cover edge cases
• In Sales: The spreadsheet that reconciles what CRM says vs. what actually happened
• In Finance: The manual journal entries fixing what the system can’t handle
• In Legal: The email chain explaining what the contract management system obscures
• In Operations: The tribal knowledge about which supplier to actually call

Friction isn’t failure. It’s tax.

A tax on time, energy, trust, and credibility.

And unlike technical debt, we rarely acknowledge it - let alone measure it.

How to detect friction:

• Time spent outside the “happy path”
• Frequency of escalations and exceptions
• Shadow systems and unofficial processes
• Knowledge that exists only in people’s heads
• Requests that require “someone who knows how it really works”

When friction is high, people survive - but they don’t trust.

Flow: The Movement of Value

Flow is about whether value is actually moving through the system.

Not activity. Not busyness. Not tickets being shuffled.
But real progress toward real outcomes.

Flow asks:

• Is work moving forward, or looping?
• Are decisions being made, or deferred?
• Are handoffs smooth, or causing rework?
• Is the service creating momentum, or drag?

We’ve covered this before: activity without flow is just exhausting theatre.

How to detect flow (or the lack of it):

• Work in progress that never completes
• Decisions revisited multiple times
• Deliveries that require heroic effort
• Services where “done” keeps changing
• Teams that are busy but making no visible progress

When flow is broken, effort multiplies but outcomes don’t.

Faith: The Belief That It Will Work

Faith is the most human metric of all.

It’s not about satisfaction surveys or NPS scores.
It’s about whether people believe the service will actually help them.

Faith is what makes someone:

• Use the official process instead of working around it
• Trust the system instead of calling a colleague who “knows how it really works”
• Try the service again after it failed them once
• Recommend it to a peer

Faith isn’t blind optimism. It’s earned credibility.

And it erodes silently:

• One unresolved ticket at a time
• One ignored escalation at a time
• One “we’re working on it” that never delivers

How to detect faith (or the loss of it):

• Declining service adoption (people voting with their feet)
• Rising exceptions (people bypassing the system)
• Shadow systems and workarounds (people building their own solutions)
• Silence in feedback channels (people have stopped expecting change)
• Cynicism in conversations (people have given up)

When faith is lost, no amount of compliance can restore it.

You can’t SLA your way back to trust.

Why Traditional Metrics Can’t Capture This

Here’s the uncomfortable truth:

Friction, flow, and faith can’t be measured the way we measure uptime.

They’re emergent properties of complex human systems.

You can’t instrument them directly.
You can’t put a probe on “trust” or set a threshold for “belief.”

But you can detect their presence - or absence - through signals:

• Conversations people have (or avoid)
• Decisions people make (or defer)
• Paths people take (or work around)
• Energy people invest (or withdraw)

This requires a different kind of measurement:

Not precision, but pattern recognition.
Not dashboards, but sensemaking.
Not single metrics, but coherent stories.

The Multi-Dimensional Truth

Here’s where it gets harder.

Human-centric metrics are multi-dimensional.

You can’t optimize for one without affecting the others.

• Make it faster → might increase friction (less care, more rework)
• Remove friction → might slow flow (more approvals, more coordination)
• Increase compliance → might erode faith (people feel controlled, not supported)

These trade-offs are real.
And they matter.

That’s why OSM treats services as dynamic ecosystems, not atomic units.

Everything co-exists in a web of influence:

• Speed affects quality
• Quality affects trust
• Trust affects adoption
• Adoption affects demand
• Demand affects speed

Life is not linear. Experience is messy.

Any model that flattens this complexity risks doing more harm than good.

Simplicity is valuable - but only when it honors the richness of what it represents.

What Human-Centric Measurement Looks Like in Practice

So how do you actually measure friction, flow, and faith?

Not with dashboards. With rituals, signals, and stories.

Rituals: Create Space for Reflection

Build lightweight, recurring moments where teams surface what traditional metrics miss:

• Flow replays: Once a fortnight, walk through one real request end-to-end. Where did it stall? Where did someone have to intervene? What would have happened if they hadn’t?

• Friction audits: Monthly, ask: “What’s one thing people are working around?” Not to fix everything - just to acknowledge it exists and decide if it matters.

• Faith checks: Quarterly, ask the people who actually use the service: “Do you believe this will help you?” Not a survey. A conversation.

These rituals don’t produce charts.
They produce awareness.

And awareness, in complex systems, is often more valuable than certainty.

Signals: Watch What People Actually Do

Human behavior reveals what surveys hide:

• Are people using the service, or working around it?
• Are escalations rising or falling?
• Are the same issues being reopened?
• Is tribal knowledge becoming more concentrated or more distributed?
• Are teams building shadow systems?

You don’t need new tools. You need new questions.

Look at:

• Request patterns (repeated issues, frequent follow-ups)
• Exception trends (are people trusting the standard process?)
• Workaround frequency (how often do people bypass the official route?)
• Manual intervention rate (how often does someone need to “fix” what the system did?)
• Adoption rates (are people choosing to use this?)
• Time-to-value (how long before someone gets actual benefit?)

These aren’t perfect measures.
But they’re honest ones.

Stories: Listen to the Narrative

The most revealing metric is often qualitative:

What story do people tell about the service?

Not in the boardroom. In the hallway.

• In HR: “Just call Maria, she knows who to talk to in payroll.”
• In Finance: “The system will reject it, so prepare the manual workaround first.”
• In Sales: “Put the real notes in the email, not the CRM - no one reads the CRM.”
• In Legal: “The workflow is for show; the real approvals happen in the coffee queue.”
• Everywhere: “I gave up and built a spreadsheet.”

These aren’t complaints to be dismissed.
They’re signals of system health.

When the story is cynical, compliance won’t fix it.
When the story is one of workarounds, automation won’t solve it.
When the story is about people, not process, no framework will save you.

The OSM Approach: Credible Over Complete

OSM doesn’t demand perfect measurement.

It demands credible measurement.

Measurement that’s:

• Honest about what it knows and doesn’t know
• Contextual to the service and the people who use it
• Dynamic enough to adapt as the service evolves
• Human enough to capture what actually matters

The Service Intelligence Base (SIB) supports this by creating a living model where:

• Friction points are tagged and tracked (not hidden in tribal knowledge)
• Flow breaks are visible (not buried in backlogs)
• Faith trends are documented (not dismissed as “soft” data)

It’s not about measuring everything.
It’s about measuring enough to act with confidence.

The Courage to Measure Differently

Here’s the challenge:

Human-centric metrics require vulnerability.

They surface uncomfortable truths:

• The service people celebrate internally might be the one users hate
• The metrics we’re proudest of might be the least meaningful
• The places we feel most in control might be where trust is most fragile

Traditional metrics protect us from these truths.

They let us say “everything’s fine” when it’s not.
They let us optimize for appearances instead of outcomes.

Human-centric metrics don’t allow that luxury.

They ask:

• Are people getting value, or just activity?
• Is the service building trust, or eroding it?
• Are we making it easier or harder to get things done?

And those questions don’t have green-light answers.

They have honest answers.

Which is why most organisations don’t ask them.

What Changes When We Measure What Matters

When you start measuring friction, flow, and faith:

• Priorities shift. You stop celebrating processing volume and start investigating why people need so many interventions in the first place. Why are so many HR requests exceptions? Why do so many purchase orders need manual correction? Why do sales reps maintain shadow spreadsheets?

• Conversations change. Governance meetings stop being compliance theatre and start being genuine service improvement sessions.

• Ownership becomes real. Service owners can finally see what’s actually happening, not just what the dashboard says.

• Investment decisions improve. You fund the things that reduce friction and restore faith, not just the things that look impressive in a roadmap.

• Trust rebuilds. People notice when you measure what they care about, not just what’s easy to measure.

This isn’t soft. This is strategic.

Because in the end, services succeed or fail based on human adoption and trust - not technical compliance.

The Question We Need to Ask

So here’s where we land:

Are your metrics helping you see truth, or just helping you sleep at night?

Because dashboards full of green lights might feel reassuring.

But if people are struggling, working around the system, and losing faith - those green lights are lies.

Not malicious lies. Just incomplete ones.

And incomplete truths, when we treat them as gospel, become the most dangerous kind of fiction.