SONAR Friction Index
Strength 78rising since the previous report
Client Onboarding & KYC
High-load weeks keep coinciding with redone decisions — three of the last four weeks, not a one-week spike.
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 reportExample data
SONAR Friction Index
Client Onboarding & KYC
RECOMMENDEDAll six signals for this team
Built around your institution. Reported only at group level.
For banks, funds, corporations and hospitals.
A client account is ready to open. The file needs one sign-off.
Two desks could give it; neither is sure the case is theirs.
The analyst asks twice, gets no answer, and redoes the checklist to be safe.
The client waited three extra days.
Without a change, the same thing happens again next week.
That repeating pattern is decision friction.
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.
One team. Six reports. Example data.
Report 6
Client Onboarding & KYC
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.
Your problem. Your teams. Your words.
Number of questions
Teams
Your setup: 6 questions · weekly · 5 teams.
An illustration. The real setup is agreed with you. Nothing entered here is stored or sent.
How often are decisions made unsure, or redone?
How often is the owner, or the rule, unclear?
Do high-load weeks keep coinciding with rework?
How often do people escalate because time ran out?
Where is work sitting still, waiting on another team?
What holds deals up?
What stops the line for the same reason twice?
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.
Four examples. Four different setups. Yours would be a fifth.
SONAR — Summary
Example data
Bank · Where client files slow down between teams.
Strength 78rising since the previous report
Client Onboarding & KYC
High-load weeks keep coinciding with redone decisions — three of the last four weeks, not a one-week spike.
Strength 76rising since the previous report
Product Control
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.
Strength 66unchanged since the previous report
Sales & Client Support
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.
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
The method
From one answer to one status, in five steps. One example, followed all the way through.
Example data
Each week, count the share of check-ins that report the condition.
Formula
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.
Compare the team with its own recent history, using measures that one unusual week cannot distort.
Formula
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.
With a mean, one crisis week would hide the next problem. With a median, it does not.
Measure how far this week sits from the team's own normal, in units of its own spread.
Formula
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.
Convert the distance into a score from 0 to 100, then reduce it when participation is thin.
Formula
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.
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.
Press a week to toggle it. The status follows the rule.
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.
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.
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
These references describe the statistical tools used. They are not a claim that SONAR has been independently validated.
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.
The executive
HR
Risk and compliance
The teams