Headcount

Engagement headcount had a mean close to its median across the study set (mean 8.4, median 8.0, n = 150 engagements). The association with cancellation was equivalent to zero (TOST p 0.010). The association with customer satisfaction on active engagements was equivalent to zero (TOST p 0.003). The association with the engagement indicator mean was equivalent to zero (TOST p 0.005). The association with intent to leave was equivalent to zero (TOST p < 0.001). Headcount differed after Holm control by process family (Welch F 4.28, Holm p 0.022, omega squared 0.061) and by class of work (Welch F 12.32, Holm p 0.003, omega squared 0.070).

The indicator had 33 written responses coded to it, from 33 of 850 respondents on 29 of 150 engagements. Negative responses numbered 23 of the 33 scored responses (69.70%). The strongest negative score, −10, was carried by 6 of the 33 scored responses (18.18%). Every response was a secondary response.

The value was recorded once per engagement, so every figure in this section counts out of 150 engagements. The mean was 8.4 and the median was 8.0, on 150 engagements.

All 33 responses were secondary responses. The secondary responses came from 33 respondents on 29 engagements, in answer to 10 questions (most often C135 with 14 responses, C156 with 5 responses, C030 with 3 responses and C114 with 3 responses). Among the Part 1 indicators with 30 or more scored responses, the secondary share of the indicator ranked 1 of 6 from the highest, tied with 4 other indicators. The median secondary share was 100.00% across the 6 indicators.

The indicator has no good or bad end. Under the coding rulebook’s rule for such indicators, the written score records the effect each response states on the engagement or on the respondent. The engagement field is “ENG:Headcount.” The frequency, scope and consequence a response states set the strength of its score. A score of +10 marks a response that describes “this attribute of the engagement as helping the engagement at its best.” A score of −10 marks a response that describes “this attribute as harming the engagement at its worst . . . .”

Of the 33 scored responses, 23 (69.70%) were negative, 6 (18.18%) carried the strongest negative score and 6 (18.18%) were positive. The responses had a mean written score of −3.5 (95% CI −4.9 to −1.9, n = 33 responses on 29 engagements).

Figures are engagement level. Means are on the scale as recorded. A level under 30 prints no interval and a level under 10 prints counts only.

Engagement families were tested on engagement means, and respondent role and vendor type were tested on respondents. A distressed p marked exact is a Fisher exact test for a two by two table, and one marked simulated is a Monte Carlo test run until its p is stable to the third decimal, both used where an expected count is under 5. Process family differed after Holm control (Welch F 4.28, Holm p 0.022, tested on engagement means). In Descriptive Statistics by Segment, Client servicing and communications had the highest mean, 9.3 (n = 16 engagements), and Corporate and back-office functions the lowest, 7.4 (n = 47 engagements). Class of work differed after Holm control (Welch F 12.32, Holm p 0.003, tested on engagement means). In Descriptive Statistics by Segment, LOB Operational had the highest mean, 9.0 (n = 76 engagements), and Corporate Functional the lowest, 7.7 (n = 74 engagements). No difference held after Holm control for outsourcing model, institution type and engagement status and lifecycle stage.

Scored responses came from 6 engagements in the Active, Build-Out group, 11 engagements in the Active, Transition/Cut-Over group, 1 engagement in the Active, Production group and 11 engagements in the Canceled group. A test of mean written scores across the groups, with each engagement counted once, showed no difference that reached significance at 0.05 (Kruskal-Wallis H 0.54, df 2, p = 0.765, n = 28 engagements). The test compared the Active, Build-Out group, the Active, Transition/Cut-Over group and the Canceled group. It left out the Active, Production group, which held fewer than two engagements. Groups under 10 responses are reported as counts only. Negative responses numbered 4 of 7 in the Active, Build-Out group and 1 of 1 in the Active, Production group.

Across respondent roles, no test was run, because fewer than two roles reached 30 scored responses. Roles under 10 responses are reported as counts only. Among engagement managers, negative responses numbered 5 of 6. Among portfolio directors, negative responses numbered 0 of 1.

The share of engagements canceled on the study date, measured at engagement level (base 150 engagements, 56 canceled). The association is a descriptive contrast, inflated because canceled engagements were rated after cancellation, and is not predictive.

The study set r was 0.12 (95% CI −0.05 to 0.27, Holm p 1.000, n = 150 engagements). The association did not hold after Holm control. Equivalence Tests of Null Results found it equivalent to zero inside the bound. Of the 20 tested segment levels, 0 held after Holm control.

The satisfaction score recorded against each engagement on a 100-point scale. The primary estimate uses the 94 active engagements. A descriptive contrast uses all 150 engagements.

The study set r was 0.02 (95% CI −0.18 to 0.22, Holm p 1.000, n = 94 engagements). The association did not hold after Holm control. Equivalence Tests of Null Results found it equivalent to zero inside the bound. Of the 16 tested segment levels, 0 held after Holm control.

The mean of an engagement’s 100 indicator ratings, measured at engagement level (base 150 engagements). Where this indicator is one of the 100, the mean is recomputed without it.

The study set r was −0.10 (95% CI −0.26 to 0.06, Holm p 1.000, n = 150 engagements). The association did not hold after Holm control. Equivalence Tests of Null Results found it equivalent to zero inside the bound. Of the 24 tested segment levels, 0 held after Holm control.

The respondent’s stated likelihood of leaving the current job within 12 months, rated 1 to 10 (C019). Measured at respondent level on up to 798 respondents, with the engagement-level form reported alongside.

The study set r was 0.09 (95% CI 0.02 to 0.16, Holm p 0.282, n = 798 respondents). The association did not hold after Holm control. Equivalence Tests of Null Results found it equivalent to zero inside the bound. Of the 28 tested segment levels, 8 held after Holm control.

The cancellation and customer satisfaction contrasts compared engagements with a negative written response against all other engagements. The comparison group comprised 129 other engagements, of which 121 had no scored written response coded to the indicator and 8 had only scored responses that were not negative. The two contrasts therefore did not test written sentiment by themselves. Cancellation was recorded for 7 of the 21 engagements with a negative response (33.33%), against 49 of the 129 other engagements (37.98%). The difference did not reach significance at 0.05 (Fisher exact p = 0.810). Mean customer satisfaction was 62.79% on the 14 active engagements with a negative response, against 64.33% on the 80 other active engagements. The difference did not reach significance at 0.05 (Welch t −0.45, p = 0.659). The association of written sentiment itself with the study measures was tested by two correlations. The association of the engagement mean written score with cancellation did not reach significance at 0.05 (r = 0.19, p = 0.332, n = 29 engagements). The association of the respondent mean written score with intent to leave did not reach significance at 0.05 (rho = 0.06, p = 0.729, n = 31 respondents). None of the four outcome comparisons reached significance at 0.05. Both comparisons with cancellation were descriptive, because responses on canceled engagements were written after cancellation. Every comparison rested on a thin base, because fewer than 30 engagements had a scored written response.

Pairs were compared on the engagement level form of every measure, each turned so that a higher value was the better outcome, on the 150 engagements where the indicator and all four measures existed. Of the 6 pairs, 0 differed after Holm control.

Not applicable. The field was recorded once per engagement, so every respondent in an engagement shared one value.

Tested null, equivalent to zero: cancellation rate, customer satisfaction, engagement indicator mean and intent to leave. No result was inconclusive. The detection floor column is the study floor at 150 engagements.

Each change was computed before rounding, so it can differ by 0.01 from the difference of the two printed values.

Checks that did not hold: “Rank correlation in place of Pearson” on intent to leave. A check holds when its test lands on the same side of 0.05 as the primary test and, where the primary test is below 0.05, its r keeps the primary sign. Thin-base rule: engagements in any level under 30 engagements of outsourcing model or process family removed. Institution type is not used, because every one of its levels is under 30.

Each of the four measures was computed from data this indicator does not contain, so each result is a finding rather than an arithmetic consequence.

Each deviation was computed before rounding, so it can differ by 0.01 from the difference of the two printed values.

The comparison ran on 150 engagements. The indicator departed from the study’s typical pattern on cancellation rate, customer satisfaction, engagement indicator mean and intent to leave.

The peer set comprised 101 indicators of the four Parts with 30 or more scored responses. The indicator was within the peer set. Its share of negative responses ranked 75 of 101 from the highest. Its mean written score (−3.5, n = 33 responses) ranked 67 of 101 from the most negative. The peer median of the mean written score was −4.6 across the 101 indicators.

The indicator’s twin, C040, records the same fact under the coding rulebook’s twin rule. The twin was coded in all 33 responses coded to the indicator. The twin is left out of the counts that follow. The responses coded to the indicator were most often also coded to “Rate the adequacy of your employer’s investment in training its workforce” (C123, 6 responses). The second-highest count was shared by “My manager is effective” (C080, 5 responses) and “Rate your employer’s current supply of qualified agentic AI talent against what its engagements need” (C122, 5 responses). The most frequent theme of the coding rulebook in the same responses was “Team or colleagues” (3 responses).

Client servicing and communications engagements had the largest headcount (mean 9.3, n = 16 engagements), and Corporate and back-office functions engagements had the smallest (mean 7.4, n = 47 engagements). LOB Operational engagements were staffed larger (mean 9.0, n = 76 engagements) than Corporate Functional engagements (mean 7.7, n = 74 engagements). Headcount varied with the kind of work without any association with the four study measures.

The indicator is an engagement field, so the written responses were not set against a rating. Written responses were voluntary. They recorded what the respondents who wrote reported, and how common it was is measured by the recorded values.

The evidence is reported experience: what the delivery team said about its own engagement, gathered in one cross-section. The figures showed associations, not causes. Indicators about the financial institution were reported at second hand by vendor staff. Cancellation is a descriptive contrast, because canceled engagements were rated after they ended.

Segment levels at anecdote strength were Private equity and private capital, Credit, underwriting and suitability, Regulatory, audit, tax and legal, and Financial crime and client onboarding (n = 9, n = 9, n = 9, n = 7). 20 of 21 checks held. The rank correlation on intent to leave did not hold.

Shares of written sentiment were shares of responses, not of the study set of respondents. The written score took five fixed values, so its mean and median were coarse. Responses clustered within engagements. Intervals for written sentiment used a bootstrap by engagement. Coding was performed by AI coders under a fixed rulebook. Agreement on whether a response was coded to the indicator rested on 1 response second-coded under rulebook 0.5, with the coders agreeing on 1 of 1. Agreement on the score rested on 3 responses second-scored under rulebook 0.6, with the scores agreeing in 3 of 3. These bases of second-coded responses are too small for an indicator-level alpha.