I am being used effectively by my employer

The mean rating was 4.9 and the median 5.0 (n = 808 respondents). Ratings of 3 or below, the distressed range, made up 26.24% of the answers. The rating was associated with all four study measures. Higher ratings came with less cancellation (r = −0.61, 95% CI −0.70 to −0.50, p < 0.001, n = 150 engagements), higher customer satisfaction among active engagements (r = 0.77, 95% CI 0.67 to 0.84, p < 0.001, n = 94 engagements), a higher engagement indicator mean (r = 0.80, 95% CI 0.74 to 0.85, p < 0.001, n = 150 engagements) and lower intent to leave (r = −0.78, cluster bootstrap 95% CI −0.82 to −0.73, p < 0.001 with standard errors clustered by engagement, n = 756 respondents). After Holm correction, ratings differed by engagement status and lifecycle stage (Welch F 34.54, Holm p < 0.001, omega squared 0.364) and respondent role (Welch F 15.64, Holm p < 0.001, omega squared 0.030).

Of the 33 written responses, 21 were negative, and every negative response came from a question outside C030. Eight described a team too small for the work or teammates who left and were not replaced, and six said the respondent spent the day on work it was not hired for. The 11 responses to C030 were positive and named a steady pace or workload. Two of the four written outcome tests reached significance.

Ratings of 3 or below, the distressed range, accounted for 212 of the 808 answers (26.24%). The engagement mean fell in the distressed range in 24 of 150 engagements.

All 33 responses were secondary. Each answered a question outside the indicator's survey section and addressed the indicator in its content. They came from 7 questions. That secondary share ranked 1st from the highest among the 11 Part 4 indicators with 30 or more written responses, tied with seven other indicators, against a median of 100.00%.

The 11 responses to C030, on what the respondent loves most about the job, were all positive, and 9 named a steady or reasonable pace, workload or bandwidth among the three things listed.

The negative responses came from questions on the employer, the financial institution, joint management and the AI tools. Eight described a team too small for the work: three people for all the queues, two analysts covering nights since the first day, teammates who left and were not replaced, and one respondent doing three people's work while no one above noticed. Six said the respondent's day went on work it was not hired for, such as retyping payslips photographed on a phone, verifying identities one call at a time, or reading every line the tool produced. Four described people put on the work without training or the right experience, or senior staff spending days teaching newcomers in place of their own work. Two described the opposite waste, staff left waiting for files or decisions. One respondent with eleven years in the trade said they had never felt this far from useful.

Of the 33 responses, 21 (63.64%, 95% CI 45.71% to 80.65%) were negative and 3 (9.09%) carried the strongest negative score of −10. Positive responses numbered 12 (36.36%), and no response was neutral. The mean written score was −1.8 (95% CI −3.7 to 0.1, n = 33 responses), and the median was −5.0.

Of the 33 responses, 31 came from respondents who also rated the indicator. Among them, the written score did not track the rating (Spearman rho 0.24, 95% CI −0.15 to 0.55, p = 0.193, n = 31 responses). Of the 20 negative responses with a rating, 7 (35.00%) came from respondents whose rating was in the distressed range.

Respondents who wrote about the indicator and gave a rating numbered 31, with a mean rating of 4.6. The 777 respondents who rated the indicator without writing about it had a mean of 4.9. The difference, −0.3 (95% CI −1.1 to 0.5), included zero. Ratings in the distressed range made up 29.03% of the ratings from respondents who wrote (9 of 31) and 26.13% of the ratings from respondents who did not (203 of 777).

Every figure in the segment tables is at respondent level. Segments with fewer than 30 respondents carry no interval. Segments with fewer than 10 report counts only.

Segment families recorded at engagement level were tested on engagement means. Respondent role and vendor type were tested on respondents. Where an expected count fell below 5, the test of the distressed share used Fisher's exact test for a two-by-two table, marked exact, or a Monte Carlo test, marked simulated. After Holm correction, ratings differed by engagement status and lifecycle stage (Welch F 34.54, Holm p < 0.001, omega squared 0.364). Active engagements in Production rated highest (mean 5.9, n = 99 respondents) and canceled engagements lowest (mean 3.5, n = 307 respondents). Ratings also differed by respondent role (Welch F 15.64, Holm p < 0.001, omega squared 0.030). Portfolio directors rated highest (mean 6.4, n = 31 respondents) and individual contributors lowest (mean 4.7, n = 625 respondents). Outsourcing model, institution type, process family, class of work and vendor type showed no difference.

Written sentiment did not differ by engagement status and lifecycle stage across the 31 engagements with a written response (Kruskal-Wallis H 5.49, df 3, p = 0.140). Fewer than two groups held 10 or more responses, so the groups are reported as counts only: active engagements in Build-Out (9), active engagements in Transition/Cut-Over (7), active engagements in Production (5) and canceled engagements (12).

No test across respondent roles was run, because fewer than two roles had 30 or more written responses. Individual contributors wrote 28, engagement managers wrote 4 and portfolio directors wrote 1 responses, reported as counts only.

Cancellation rate is the share of engagements canceled by the study date, measured at engagement level (150 engagements, 56 canceled). Canceled engagements were rated after cancellation. The association is therefore a descriptive contrast and not a forecast of cancellation.

Across the study set, higher ratings came with less cancellation (r = −0.61, 95% CI −0.70 to −0.50, Holm p < 0.001, n = 150 engagements). The association held after Holm correction in seventeen of the 20 segment levels tested.

Customer satisfaction is the percentage recorded against each engagement. The primary estimate uses the 94 active engagements. A descriptive contrast uses all 150 engagements.

Across the active engagements, higher ratings came with higher customer satisfaction (r = 0.77, 95% CI 0.67 to 0.84, Holm p < 0.001, n = 94 engagements). The association held after Holm correction in fifteen of the 16 segment levels tested.

The engagement indicator mean is the mean of an engagement's ratings across the rated indicators, measured at engagement level (150 engagements). The indicator does not enter the mean.

Higher ratings came with a higher engagement indicator mean (r = 0.80, 95% CI 0.74 to 0.85, Holm p < 0.001, n = 150 engagements). The association held after Holm correction in twenty-four of the 24 segment levels tested.

Intent to leave is the answer to C019, “How likely are you to leave your current job in the next 12 months?”, rated 1 to 10. It is measured at respondent level on up to 798 respondents, with the engagement-level form reported alongside.

Respondents who gave higher ratings reported lower intent to leave (r = −0.78, 95% CI −0.80 to −0.75, Holm p < 0.001, n = 756 respondents). The association held after Holm correction in thirty-seven of the 37 segment levels tested.

Two comparisons set the engagements with at least one negative response against all other engagements. Of the 130 other engagements, 119 had no written response addressing the indicator. These two comparisons therefore do not isolate written sentiment. Of the 20 engagements with a negative response, 10 (50.00%) were canceled, against 46 of the 130 other engagements (35.38%). The difference did not reach significance (Fisher exact p = 0.223). Customer satisfaction among active engagements did not differ between the two groups (mean 62.10% on 10 engagements against 64.33% on 84, Welch t −0.84, p = 0.415).

Two correlations test written sentiment directly. Across the 31 engagements with a written response, a more negative engagement mean written score came with cancellation (point-biserial r −0.43, p = 0.017). Across 31 respondents, a more negative respondent mean written score came with higher intent to leave (Spearman rho −0.41, p = 0.023). Of the four comparisons, two reached significance at 0.05.

The four associations were compared in pairs on their engagement-level forms, each oriented so that a higher value is the better outcome, across the 150 engagements with all four measures. After Holm correction, five of the six pairs differed. The association with the engagement indicator mean was the strongest and the association with cancellation the weakest. The associations with customer satisfaction and the engagement indicator mean did not differ (Holm p = 0.059).

Answers clustered within engagements (ICC 0.61). Clustering reduced the 808 respondent answers to the equivalent of about 220 independent answers. Respondent-level intervals therefore used the cluster bootstrap. Respondent-level tests of intent to leave used standard errors that allow for clustering by engagement.

No association was equivalent to zero. Each of the four differed from zero. The detection floor shown is the study floor at 150 engagements. Intent to leave was tested on its effective sample size.

Each change was computed before rounding and may differ by 0.01 from the difference between the two printed values.

All 22 checks held. A check holds when its test falls on the same side of 0.05 as the primary test. Where the primary test falls below 0.05, the check must also keep the sign of the primary correlation. The thin-base check removes the engagements in any level of outsourcing model or process family with fewer than 30 engagements. Institution type is not used for that check, because every one of its levels has fewer than 30 engagements.

Each of the four measures was computed from data the indicator does not contain. Each result is therefore a finding and not an arithmetic consequence.

Each deviation was computed before rounding and may differ by 0.01 from the difference between the two printed values.

The comparison covered 150 engagements. The indicator departed from the study's typical pattern on intent to leave. Its association was stronger than the norm on intent to leave.

Among the 11 Part 4 indicators with 30 or more written responses, the indicator's share of negative responses, 63.64%, ranked 4th from the highest, against a median of 33.33%. Its mean written score, −1.8, ranked 4th from the most negative, against a median of 0.8.

The indicator most often present in the same responses was C080, “My manager is effective.”, in 6 of the 33 responses (18.18%). C018, “How happy are you with your current job?” (5 responses), C021, “How likely are members of your current team to leave their jobs in the next 12 months?” (4 responses), C122, “Rate your employer's current supply of qualified agentic AI talent against what its engagements need.” (3 responses) and C157, “Rate the factual reliability of the AI tools' outputs on this engagement before any human review.” (3 responses) followed.

The most frequent theme was “Skills learned”, in 4 responses (12.12%). The second was “Told vendor-side management”, in 3 responses.

About a quarter of all ratings of whether the respondent is used effectively by the employer fell in the distressed range (212 of 808 answers, 26.24%). The rating was associated with all four study measures, and every association held under each of the 22 robustness checks. Canceled engagements rated well below the three active stages (mean 3.5, n = 307 respondents).

The written evidence describes skilled staff spread too thin, set to retyping or checking, or left idle, and short of the training or colleagues the work needed. A more negative engagement mean written score came with cancellation, and respondents whose written responses were more negative reported higher intent to leave. The comparisons of cancellation and customer satisfaction between engagements with and without a negative response did not reach significance.

The evidence is the reported experience of the vendor's delivery teams, collected in a single cross-section. The associations reported here are not causal.

Tests by respondent role and by vendor type treated respondents as independent. The section on clustering reports how far clustering within engagements reduced the information in respondent-level figures.

Customer management executives gave 2 answers, a base of anecdote strength.

Shares of written sentiment are shares of responses and not of the study set of respondents. The written score takes five fixed values, so its mean and median are coarse. Responses clustered within engagements (33 responses on 31 engagements). Intervals for written sentiment therefore used a bootstrap by engagement.