The comp band was 22% below market, and the client didn’t believe it until they saw the data.
I’d have bet the problem was our interviews. The data settled it in one meeting with HQ. We were underpaying, and we could prove it.
The outcome, in numbers.
The situation
The centre was losing finalist after finalist late in the process and had been re-engineering its interview loop to fix it. Leadership was reluctant to look at compensation — HQ set the bands, and challenging them meant a hard conversation across a time zone.
Without hard numbers, that conversation was unwinnable. "We think we’re underpaying" doesn’t move a headquarters. A defensible gap, measured against live data, might.
What we did
We benchmarked the affected senior roles against live placement data for the same profiles in the same city — not a survey median, but what people at that level had actually accepted recently.
The gap came back at roughly 22% at the senior end. We packaged it as the evidence pack the GCC head needed to take to HQ: role by role, with the offer-loss pattern mapped against the shortfall.
- 01 Live-data benchmarking of the affected roles against real recent acceptances.
- 02 A role-by-role gap analysis, not a single headline number.
- 03 An HQ-ready evidence pack linking the pay gap to specific lost finalists.
- 04 A revised offer framework the centre could deploy immediately once approved.
The outcome
The data made the HQ conversation short. Bands were corrected for the senior roles, and with a defensible offer in hand the centre started converting finalists again — the first accepted offers landed inside a month.
The interview loop the team had been rebuilding turned out to be fine. The engagement stopped them spending another two quarters fixing a process that was never broken.
If a case like this looks like your problem, that's usually a sign.
Send us a brief or just describe what you're dealing with. We'll come back with one observation — even if we don't end up working together.