How happy are you with your current job?

The mean rating was 4.2 and the median 4.0 (n = 780 respondents). Ratings of 3 or below, the distressed range, made up 46.79% of the answers. The rating was associated with all four study measures. Higher ratings came with less cancellation (r = −0.81, 95% CI −0.86 to −0.75, p < 0.001, n = 150 engagements), higher customer satisfaction among active engagements (r = 0.76, 95% CI 0.65 to 0.83, p < 0.001, n = 94 engagements), a higher engagement indicator mean (r = 0.86, 95% CI 0.81 to 0.89, p < 0.001, n = 150 engagements) and lower intent to leave (r = −0.91, cluster bootstrap 95% CI −0.92 to −0.89, p < 0.001 with standard errors clustered by engagement, n = 732 respondents). After Holm correction, ratings differed by engagement status and lifecycle stage (Welch F 145.77, Holm p < 0.001, omega squared 0.652).

Of the 250 written responses, 126 answered C030, on what the respondent loves most about the job, and split almost evenly between positive and negative. The other 124 came from questions on the work itself, and 60 said the respondent or the team was tired, exhausted or worn down, most often from fixing the same data or process every cycle. All four written outcome tests reached significance.

Ratings of 3 or below, the distressed range, accounted for 365 of the 780 answers (46.79%). The engagement mean fell in the distressed range in 63 of 150 engagements.

The primary responses numbered 126, all written in answer to C030, “What are the top 3 things that you love most about your job?” The remaining 124 responses, 49.60% of the total, were secondary and came from 10 other questions. That secondary share ranked 11th from the highest among the 11 Part 4 indicators with 30 or more written responses, against a median of 100.00%. Respondents who wrote both a primary and a secondary response numbered 16. Negative responses made up 48.41% of primary responses (61 of 126) and 90.32% of secondary responses (112 of 124).

The responses to C030 divided along the engagement. Of its 126 responses, 64 were positive and named interesting work, a manager who backed the team (31 responses) and a cooperative financial institution. The other 61 were negative, and 60 of these opened by naming nothing, little or not much to like before listing a teammate, a skill or the pay. The pay appeared in 12 negative responses, often as the only thing left, and several named the relief that the engagement had ended.

The other 124 responses answered questions on the work, and 60 said the respondent or the team was tired, exhausted, drained or worn down. Most traced the tiredness to cleaning the same data or applying the same workaround every cycle, to deciding alone because no one would give a ruling, or to waiting on the financial institution. Eight responses said teammates had left, were looking elsewhere or had asked to move off, and five said the respondent had stopped caring how the engagement ended. Of the twelve positive responses outside C030, one said the AI tool had made the job better by taking the repeated questions, and several said the respondent liked fixing the problem without waiting for others.

Of the 250 responses, 173 (69.20%, 95% CI 60.78% to 77.12%) were negative and 22 (8.80%) carried the strongest negative score of −10. Positive responses numbered 76 (30.40%), and 1 was neutral. The mean written score was −2.3 (95% CI −3.2 to −1.4, n = 250 responses), and the median was −5.0.

Of the 250 responses, 228 came from respondents who also rated the indicator. Among them, the written score rose with the rating (Spearman rho 0.61, 95% CI 0.49 to 0.71, p < 0.001, n = 228 responses). The written responses corroborated the rating. Of the 158 negative responses with a rating, 134 (84.81%) came from respondents whose rating was in the distressed range.

Respondents who wrote about the indicator and gave a rating numbered 200, with a mean rating of 3.4. The 580 respondents who rated the indicator without writing about it had a mean of 4.5. The difference, −1.1 (95% CI −1.5 to −0.6), excluded zero. Ratings in the distressed range made up 63.00% of the ratings from respondents who wrote (126 of 200) and 41.21% of the ratings from respondents who did not (239 of 580).

The respondents who wrote came disproportionately from the distressed end of the scale. The written evidence therefore gives more weight to the respondents who rated the indicator worst.

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 145.77, Holm p < 0.001, omega squared 0.652). Active engagements in Production rated highest (mean 6.0, n = 95 respondents) and canceled engagements lowest (mean 1.8, n = 300 respondents). Outsourcing model, institution type, process family, class of work, respondent role and vendor type showed no difference.

Written sentiment differed by engagement status and lifecycle stage across the 113 engagements with a written response (Kruskal-Wallis H 21.10, df 3, p < 0.001). Of the groups with 10 or more responses, responses from canceled engagements were the most negative (mean −4.5, 134 responses) and responses from active engagements in Build-Out the least negative (mean 1.3, 38 responses).

No test across respondent roles was run, because fewer than two roles had 30 or more written responses. Individual contributors wrote 222, engagement managers wrote 25 and portfolio directors wrote 3 responses.

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 = −0.81, 95% CI −0.86 to −0.75, Holm p < 0.001, n = 150 engagements). The association held after Holm correction in twenty 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 = 0.76, 95% CI 0.65 to 0.83, 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 = 0.86, 95% CI 0.81 to 0.89, Holm p < 0.001, n = 150 engagements). The association held after Holm correction in twenty-three 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 = −0.91, 95% CI −0.92 to −0.89, Holm p < 0.001, n = 732 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 69 other engagements, 37 had no written response addressing the indicator. These two comparisons therefore do not isolate written sentiment. Of the 81 engagements with a negative response, 46 (56.79%) were canceled, against 10 of the 69 other engagements (14.49%). The difference reached significance (Fisher exact p < 0.001). Customer satisfaction among active engagements differed between the two groups (mean 59.26% on 35 engagements against 66.97% on 59, Welch t −3.34, p = 0.001).

Two correlations test written sentiment directly. Across the 113 engagements with a written response, a more negative engagement mean written score came with cancellation (point-biserial r −0.42, p < 0.001). Across 207 respondents, a more negative respondent mean written score came with higher intent to leave (Spearman rho −0.56, p < 0.001). Of the four comparisons, all 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 intent to leave was the strongest and the association with customer satisfaction the weakest. The associations with cancellation and the engagement indicator mean did not differ (Holm p = 0.114).

Answers clustered within engagements (ICC 0.83). Clustering reduced the 780 respondent answers to the equivalent of about 173 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 cancellation, customer satisfaction and intent to leave. Its association was stronger than the norm on cancellation, customer satisfaction and intent to leave.

Among the 11 Part 4 indicators with 30 or more written responses, the indicator's share of negative responses, 69.20%, ranked 3rd from the highest, against a median of 33.33%. Its mean written score, −2.3, ranked 3rd from the most negative, against a median of 0.8.

The indicator most often present in the same responses was C205, “I have altered client processes”, in 26 of the 250 responses (10.40%). C080, “My manager is effective.” (25 responses), C199, “I have altered client-provided data” (25 responses), C109, “Rate how quickly the customer responds when this engagement raises issues that need customer action.” (23 responses) and C094, “Rate the quality of the customer's data across the systems this engagement depends on.” (21 responses) followed.

The most frequent theme was “Team or colleagues”, in 58 responses (23.20%). The second was “Skills learned”, in 51 responses.

Nearly half of all ratings of job happiness fell in the distressed range (365 of 780 answers, 46.79%). The rating was associated with all four study measures, and every association held under each of the 22 robustness checks. Canceled engagements rated far below the three active stages (mean 1.8, n = 300 respondents).

The written evidence ties unhappiness to the daily work of the engagement: the same data cleaned every cycle, decisions made alone, teammates leaving and respondents who had stopped caring. Engagements with a negative written response were canceled more often, active engagements with a negative written response had lower customer satisfaction, a more negative engagement mean written score came with cancellation, and respondents whose written responses were more negative reported higher intent to leave.

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 (250 responses on 113 engagements). Intervals for written sentiment therefore used a bootstrap by engagement.