Rate how quickly the customer responds when this engagement raises issues that need customer action

Ratings of how quickly the financial institution responded when the engagement raised issues that needed its action (mean 3.5, median 3.0, n = 789 respondents) were associated with all four study measures. Engagements with higher ratings were canceled less often (r = −0.60, 95% CI −0.69 to −0.48, p < 0.001, n = 150 engagements). Higher ratings came with higher customer satisfaction on active engagements (r = 0.74, 95% CI 0.63 to 0.82, p < 0.001, n = 94 active engagements). Ratings rose with the engagement indicator mean, computed with this item left out (r = 0.84, 95% CI 0.78 to 0.88, p < 0.001, n = 150 engagements). Respondents who gave higher ratings reported lower intent to leave (r = −0.59, cluster bootstrap 95% CI −0.65 to −0.51, p < 0.001, n = 740 respondents). Ratings differed after Holm control by engagement status and lifecycle stage (Welch F 33.76, Holm p < 0.001, omega squared 0.345) and by respondent role (Welch F 18.16, Holm p < 0.001, omega squared 0.022).

The indicator had 498 written responses coded to it, from 382 of 850 respondents on 142 of 150 engagements. Negative responses numbered 437 of the 498 scored responses (87.75%). The strongest negative score, −10, was carried by 208 of the 498 scored responses (41.77%). Secondary responses, written in answer to questions outside the indicator’s own survey section, numbered 354 of the 498 responses (71.08%). Respondents who wrote rated the indicator lower than respondents who did not (mean 3.0, n = 358 respondents, against mean 3.9, n = 431 respondents), a difference whose interval excluded zero.

The study set mean was 3.5 on 789 answering respondents, with a median of 3.0. 404 answers, 51.20% of the 789, were at the distressed end. A distressed engagement mean was recorded in 64 of 150 engagements.

Of the 498 responses, 144 (28.92%) were primary and 354 (71.08%) were secondary. The secondary responses came from 282 respondents on 127 engagements, in answer to 9 questions outside the indicator’s own survey section (most often C208 with 152 responses, C210 with 66 responses and C202 with 54 responses). Both a primary and a secondary response came from 44 respondents. Among the Part 2 indicators with 30 or more scored responses, the secondary share of the indicator ranked 12 of 71 from the highest. The median secondary share was 18.92% across the 71 indicators.

Negative responses made up 351 of the 354 secondary responses (99.15%), against 86 of the 144 primary responses (59.72%). The difference reached significance at 0.05 (Fisher exact p < 0.001, n = 498 responses). The share of negative responses was larger among secondary responses than among primary responses.

Of the 498 scored responses, 437 (87.75%) were negative, 208 (41.77%) carried the strongest negative score and 59 (11.85%) were positive. The responses had a mean written score of −5.8 (95% CI −6.3 to −5.3, n = 498 responses on 142 engagements).

Respondents who rated the indicator 3 or below wrote 302 of the 407 negative responses with a rating. Written score and rating showed a weak positive correlation that reached significance at 0.05 (Spearman rho 0.28, 95% CI 0.19 to 0.38, p < 0.001, n = 468 responses on 140 engagements). Its interval excluded zero. Where a written score diverges from the same respondent’s rating, the rating is the measure of the indicator.

Respondents who wrote about the indicator rated it 0.8 points lower than respondents who did not (mean 3.0, n = 358 respondents, against mean 3.9, n = 431 respondents, difference 95% CI −1.1 to −0.6, cluster bootstrap by engagement). The difference was computed before rounding, so it differs by 0.1 from the difference of the two printed means. The interval of the difference excluded zero. Ratings of 3 or below came from 229 of the 358 respondents who wrote and gave a rating (63.97%), against 175 of the 431 respondents who did not write and gave a rating (40.60%). Respondents who wrote formed a self-selected group and not a random sample of the answering base, because written responses were voluntary.

Figures are respondent level. Means are on the goodness view. 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. Engagement status and lifecycle stage differed after Holm control (Welch F 33.76, Holm p < 0.001, tested on engagement means). In Descriptive Statistics by Segment, Active, Production had the highest mean, 4.4 (n = 96 respondents), and Canceled the lowest, 2.4 (n = 297 respondents). Respondent role differed after Holm control (Welch F 18.16, Holm p < 0.001, tested on respondents). In Descriptive Statistics by Segment, Portfolio Director had the highest mean, 4.6 (n = 29 respondents), and Individual Contributor the lowest, 3.4 (n = 609 respondents). No difference held after Holm control for outsourcing model, institution type, process family, class of work and vendor type.

Scored responses came from 29 engagements in the Active, Build-Out group, 40 engagements in the Active, Transition/Cut-Over group, 18 engagements in the Active, Production group and 55 engagements in the Canceled group. A test of mean written scores across the groups, with each engagement counted once, showed a difference that reached significance at 0.05 (Kruskal-Wallis H 10.79, df 3, p = 0.013, n = 142 engagements). Among the groups with 10 or more responses, the lowest mean written score came from the Canceled group (−6.8, n = 236 responses). The highest came from the Active, Build-Out group (−4.7, n = 75 responses).

The role test compared individual contributors and engagement managers, the roles with 30 or more scored responses. A test of mean written scores between the two roles, with each respondent counted once, showed a difference that reached significance at 0.05 (Kruskal-Wallis H 16.58, df 1, p < 0.001, n = 377 respondents). Of the two roles compared, the lower mean written score came from individual contributors (−6.3, n = 446 responses). The higher came from engagement managers (−2.3, n = 46 responses). Roles under 10 responses are reported as counts only. Among portfolio directors, negative responses numbered 3 of 6.

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 −0.60 (95% CI −0.69 to −0.48, Holm p < 0.001, n = 150 engagements). Of the 20 tested segment levels, 12 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 0.74 (95% CI 0.63 to 0.82, Holm p < 0.001, n = 94 engagements). Of the 16 tested segment levels, 15 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 0.84 (95% CI 0.78 to 0.88, Holm p < 0.001, n = 150 engagements). Of the 24 tested segment levels, 24 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 −0.59 (95% CI −0.63 to −0.54, Holm p < 0.001, n = 740 respondents). Of the 37 tested segment levels, 35 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 16 other engagements, of which 8 had no scored written response coded to the indicator and 8 had only scored responses that were not negative. Cancellation was recorded for 55 of the 134 engagements with a negative response (41.04%), against 1 of the 16 other engagements (6.25%). The difference reached significance at 0.05 (Fisher exact p = 0.006). Mean customer satisfaction was 61.86% on the 79 active engagements with a negative response, against 75.87% on the 15 other active engagements. The difference reached significance at 0.05 (Welch t −5.93, p < 0.001). 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 reached significance at 0.05 (r = −0.28, p < 0.001, n = 142 engagements). The association of the respondent mean written score with intent to leave reached significance at 0.05 (rho = −0.16, p = 0.003, n = 353 respondents). All four outcome comparisons reached significance at 0.05. Both comparisons with cancellation were descriptive, because responses on canceled engagements were written after cancellation.

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, 4 differed after Holm control.

Clustering reduced the 789 respondent answers to about 227 independent answers. Respondent level intervals therefore used the cluster bootstrap, and respondent level tests on intent to leave used cluster-robust errors.

No measure showed a tested null. No result was inconclusive. The detection floor column is the study floor at 150 engagements. Intent to leave was tested on its effective n.

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

Every check held. 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. This indicator is one of the 100 components, so the engagement indicator mean was recomputed without it, and the correction changed r by 0.00, from 0.84 to 0.84.

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 followed the study’s typical pattern on every measure.

The peer set comprised 71 indicators of Part 2 with 30 or more scored responses. The indicator was within the peer set. Its share of negative responses ranked 19 of 71 from the highest. Its mean written score (−5.8, n = 498 responses) ranked 19 of 71 from the most negative. The peer median of the mean written score was −4.7 across the 71 indicators.

The responses coded to the indicator were most often also coded to “I have altered client processes” (C205, 229 responses). The second most frequent co-coded indicator was “Rate the quality of the customer’s data across the systems this engagement depends on” (C094, 83 responses). The most frequent theme of the coding rulebook in the same responses was “Raised it, nothing came back” (121 responses).

Distressed answers made up more than half of the study set (404 of 789 answers, 51.20%). Active, Production had the highest mean by lifecycle stage (mean 4.4, n = 96 respondents), and Canceled had the lowest (mean 2.4, n = 297 respondents). Portfolio Director respondents gave the highest ratings by role (mean 4.6, n = 29 respondents), and Individual Contributor respondents gave the lowest (mean 3.4, n = 609 respondents). The associations held under every robustness check run on this item (22 of 22 checks).

The written responses corroborated the rating at respondent level, with a weak positive correlation between written score and rating. Of the 229 responses also coded to C205, 220 were secondary responses to the indicator. Written responses were voluntary. They recorded what the respondents who wrote reported, and how common it was is measured by the ratings.

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.

Tests across respondent role and vendor type were run at respondent level and treated respondents as independent. The section Clustering and Effective Sample Size states whether, and by how much, clustering within engagements reduced the information in respondent level figures.

Customer Management Executive answers were at anecdote strength (n = 1). Answers clustered within engagements, which reduced the effective number of independent answers (ICC 0.58, 789 answers worth about 227 independent answers).

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 66 responses second-coded under rulebook 0.5, with the coders agreeing on 56 of 66. Agreement on the score rested on 56 responses second-scored under rulebook 0.5, with the scores agreeing in 54 of 56. These bases of second-coded responses are too small for an indicator-level alpha.