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SONAR

Measure the friction.Act on it. Track the result.

Friction is what your people run into every day and your reports don't show: where work slows down, piles up or stays unclear. SONAR measures it, pairs each finding with one action, and shows what changed.

A short check-in, built around your institution. A regular executive report. One action per problem.

See a sample report

Example data

SONAR Friction Index

50750↑

Client Onboarding & KYC

RECOMMENDED

All six signals for this team

  • 0Friction Index
  • 0Ownership
  • 0Rule
  • 0Pressure
  • 0Load
  • 0Recurring

Built around your institution. Reported only at group level.

For banks, funds, corporations and hospitals.

Nobody did anything wrong.

  1. 1

    A client account is ready to open. The file needs one sign-off.

  2. 2

    Two desks could give it; neither is sure the case is theirs.

  3. 3

    The analyst asks twice, gets no answer, and redoes the checklist to be safe.

  4. 4

    The client waited three extra days.

  5. 5

    Without a change, the same thing happens again next week.

That repeating pattern is decision friction.

It shows up later, as something else.

  • A client who waited.

  • A decision made twice.

  • An escalation made because time ran out.

  • A good person who stopped raising it.

By the time it reaches a report, it is weeks old and has another name. The people doing the work see it as it happens. SONAR gives what they see a consistent place in the management conversation, and a way to follow it over time.

One difficult week is noise. Repetition is a signal.

Measure. Act. Measure again.

One team. Six reports. Example data.

0

Report 6

Client Onboarding & KYC

IN RANGE
Threshold 50Action taken311442783694555416

4 · Moved

Three reports later, the signal is back in the team's own range.

Example data. A signal that moves after an action is consistent with the action working. It is not proof of cause.

Built around your institution.

Your problem. Your teams. Your words.

You decide

Rhythm

Number of questions

6

Teams

5

Your setup: 6 questions · weekly · 5 teams.

An illustration. The real setup is agreed with you. Nothing entered here is stored or sent.

What never changes

  • Every team is measured against its own baseline.
  • Results are reported only at group level.
  • No individual is ever scored.
  • Small groups are never shown.
  • A signal has to recur before an action is recommended.

What would you want to know?

  • Decisions

    How often are decisions made unsure, or redone?

  • Clarity

    How often is the owner, or the rule, unclear?

  • Workload

    Do high-load weeks keep coinciding with rework?

  • Pressure

    How often do people escalate because time ran out?

  • Working together

    Where is work sitting still, waiting on another team?

  • Sales

    What holds deals up?

  • Production

    What stops the line for the same reason twice?

  • Yours

    The question only your institution would ask.

Examples only. Every engagement starts from what you want to understand.

Tailored before the first check-in. Consistent after it, so each reading can be compared with the last.

What lands on your desk.

Four examples. Four different setups. Yours would be a fifth.

Page 1 of 5

SONAR — Summary

Example data

Bank · Where client files slow down between teams.

8
questions
weekly
rhythm
5
teams
443
employees
912
decision records

Two teams have recommended actions. One team is on watch.

  • 2 teams — recommended
  • 1 team — watch
  • 2 teams — in range

SONAR Friction Index

Strength 78rising since the previous report

Client Onboarding & KYC

RECOMMENDED

High-load weeks keep coinciding with redone decisions — three of the last four weeks, not a one-week spike.

Pressured Escalation

Strength 76rising since the previous report

Product Control

WATCH

A rising share of escalations is linked to uncertainty or deadline pressure. Two weeks is not yet a condition. Keep watching; prepare the response, but do not deploy it.

Ownership Ambiguity

Strength 66unchanged since the previous report

Sales & Client Support

RECOMMENDED

Ownership is unclear at exactly the wrong moments — when a client file moves between teams, and at deadlines. Workload stays in range; unclear ownership keeps recurring.

Strength = against the team's own normal. Squares = the last 4 weeks.

What we found

Onboarding & KYC is the priority — broad and load-linked. Client Support needs a one-page map of who decides before adding headcount. Product Control: prepare the escalation rule, don't deploy it. No action is recommended for the other two teams.

Reports describe working conditions, not conclusions about individuals, controls or compliance.

The same answers, read your way.

  • People and workload

    High-load weeks keep coinciding with redone decisions.

    Example data

  • Risk and compliance

    16 of 39 escalated decisions were linked to uncertainty or deadline pressure.

    Example data

  • Clients

    Ownership is unclear at exactly the wrong moments: when a client file moves between teams, and at deadlines.

    Example data

  • AI use

    When AI is involved, “unclear rule” appears in 34% of records, against 17% without.

    Example data

How to read these examples
  • Each example shows one institution's setup. The number of questions, the rhythm, the teams and the signals were chosen by that institution.
  • Strength, 0 to 100: how unusual the latest period is against the same team's own recent history. Never a comparison between teams. In these examples, about 18 is normal; shading turns light orange from 50 and burnt orange from 75.
  • The four squares show the last four weeks, filled when elevated. In these examples, elevated 2 of 4 weeks is WATCH and 3 of 4 is RECOMMENDED.
  • Arrows show the trend against the previous report only.
  • Individuals are never reported. A minimum of 10 means 10 unique people, not 10 responses.

The method

How a signal is computed.

From one answer to one status, in five steps. One example, followed all the way through.

Example data

  1. 1Count

    Each week, count the share of check-ins that report the condition.

    Formula

    p=knp = \frac{k}{n}

    Worked example23 of 60 check-ins = 38.3%.

    WhyEach check-in describes the most significant decision of the week. The method shows where friction concentrates and recurs. It does not estimate how often it occurs across all work.

  2. 2Baseline

    Compare the team with its own recent history, using measures that one unusual week cannot distort.

    Formula

    m=median of the team’s historys=robust spread of the team’s history\begin{gathered}m = \text{median of the team's history} \\ s = \text{robust spread of the team's history}\end{gathered}

    Worked examplemedian 22.0%, robust spread 5.9 points.

    WhyA mean and a standard deviation move when one crisis week enters the history. The median and the robust spread do not.

    • The robust spread is built on the median, not the mean.
    • The reference window holds up to 12 completed weeks, with a minimum of four. Readings are provisional until it matures.
    • The week being tested is never part of its own reference.
    • The spread never falls below what chance alone would produce for a share measured on that many responses.
    0%20%40%60%median 22.0% · ± s

    With a mean, one crisis week would hide the next problem. With a median, it does not.

  3. 3Distance

    Measure how far this week sits from the team's own normal, in units of its own spread.

    Formula

    z=p−msz = \frac{p - m}{s}

    Worked examplez = (38.3 − 22.0) / 5.9 = 2.75

    WhyThe same number of points means different things for a steady team and a variable one. Dividing by the team's own spread makes readings comparable over time for that team.

    0%20%40%60%median 22.0% · ± s2.75this week
  4. 4Strength

    Convert the distance into a score from 0 to 100, then reduce it when participation is thin.

    Formula

    strength=100×σ(z−1.5)×a,σ(x)=11+e−x\text{strength} = 100 \times \sigma(z - 1.5) \times a,\quad \sigma(x) = \frac{1}{1 + e^{-x}}

    Worked example100 × σ(1.25) × 1.00 = 78

    WhyThe curve is bounded, so one extreme week cannot dominate. It puts “elevated” at 50, which makes scores easy to read. The adequacy factor a lowers a score smoothly when few people answer: a thin week can mute a signal, never create one.

    05075100z -1z 0z 1z 2z 3z 4z 518, the team's own median50, elevated75, strong82
    0
  5. 5Persistence

    Wait for the pattern before recommending anything.

    Rule

    Elevated 2 of the last 4 weeks = WATCH. Elevated 3 of the last 4 weeks = RECOMMENDED. Otherwise IN RANGE.

    Worked exampleelevated in 3 of the last 4 weeks = RECOMMENDED.

    WhyOne difficult week is noise. A recommendation requires repetition.

    RECOMMENDEDelevated 3 of 4 weeks

    Press a week to toggle it. The status follows the rule.

  • How change is checked

    When a reading moves from one period to the next, the change is tested before it is reported. Shares are compared with a two-proportion test. Ordered scales are compared with the Mann–Whitney U test, with the rank-biserial correlation as the size of the effect. Because the same people answer repeatedly, the checks resample by respondent.

  • Fixed in advance

    The thresholds, 50 for elevated and 75 for strong, are set before reporting begins. Any recalibration applies going forward only, is versioned and documented. Past scores are never restated.

  • What the method does not claim

    It describes; it does not establish cause. It shows where friction concentrates, not how often it occurs overall. It never compares one team with another. Groups below 10 people are not shown.

References

  • Hampel, F. R. (1974). The influence curve and its role in robust estimation. Journal of the American Statistical Association.
  • Mann, H. B. and Whitney, D. R. (1947). On a test of whether one of two random variables is stochastically larger than the other. Annals of Mathematical Statistics.
  • Kerby, D. S. (2014). The simple difference formula: an approach to teaching nonparametric correlation. Comprehensive Psychology.
  • Western Electric (1956). Statistical Quality Control Handbook.

These references describe the statistical tools used. They are not a claim that SONAR has been independently validated.

Why it holds up.

This is not a survey.

A survey asks what people think. SONAR asks what happened.

An opinion survey

SONAR

  • Asks how people feel in general.

    Asks about one real decision, as it happens.

  • Once or twice a year.

    At the rhythm you choose, all year.

  • Compared with other teams or a benchmark.

    Compared only with the team's own baseline.

  • One loud week can move the score.

    A signal has to recur before it counts.

  • Ends with a score.

    Ends with one action and one owner.

  • The next reading is months away.

    The next report shows whether it moved.

  • Reports every score.

    Says so when nothing needs action.

A survey has its place: it tells you how people feel about the institution. SONAR does a different job.

Everyone in the room has a reason to say yes.

  • The executive

    • Built around your priorities.
    • One page to forward.
    • A report that reads in 90 seconds.
  • HR

    • Working conditions, not people.
    • No individual scores.
    • Voluntary throughout.
  • Risk and compliance

    • Conditions, not verdicts.
    • No finding about misconduct or control adequacy.
    • Thresholds fixed in advance.
  • The teams

    • About a minute at a time.
    • No app and no login.
    • They hear back: you said, here is what changed.