How happy is your extended team with the current engagement?

The mean rating was 4.3 and the median 4.0 (n = 788 respondents). Ratings of 3 or below, the distressed range, made up 45.30% 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 = 0.68, 95% CI 0.56 to 0.78, p < 0.001, n = 94 engagements), a higher engagement indicator mean (r = 0.87, 95% CI 0.82 to 0.90, p < 0.001, n = 150 engagements) and lower intent to leave (r = −0.76, cluster bootstrap 95% CI −0.80 to −0.71, p < 0.001 with standard errors clustered by engagement, n = 742 respondents). After Holm correction, ratings differed by engagement status and lifecycle stage (Welch F 149.75, Holm p < 0.001, omega squared 0.654), respondent role (Welch F 6.66, Holm p = 0.012, omega squared 0.013) and vendor type (Welch F 6.79, Holm p < 0.001, omega squared 0.032).

Of the 56 written responses, 43 were negative. The 47 responses outside C030 came from questions on the work, and 34 said the team was tired, exhausted or worn down. Ten said team members had left, were applying elsewhere or had asked to move. All four written outcome tests reached significance.

Ratings of 3 or below, the distressed range, accounted for 357 of the 788 answers (45.30%). The engagement mean fell in the distressed range in 61 of 150 engagements.

The primary responses numbered 9, all written in answer to C030, “What are the top 3 things that you love most about your job?” The remaining 47 responses, 83.93% of the total, were secondary and came from 8 other questions. That secondary share ranked 10th 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 0. Negative responses made up 1 of the 9 primary responses and 89.36% of secondary responses (42 of 47).

Most responses came from respondents describing their team in answer to questions on the work, with C114, on the financial institution's side, and C156 contributing the most. 34 of the 47 responses outside C030 said the team was tired, exhausted, worn down or burned out. The respondents traced it to waiting on the financial institution for files, access or answers, to cleaning the same data by hand, and to decisions that no one would own: nine responses said the team made or waited on calls that were never its own. Eight said the team's day had turned into checking the AI tool's output, and one said the strongest engineers found that work boring.

Ten responses said team members had left, were applying elsewhere or had asked to move or transfer, several within the first months. Four responses that described the strain said the financial institution's people were willing or its data was good, and placed the cost in process, notice or access. The eight positive responses to C030 named team pride, good energy and visible results. One response outside C030 said the AI tool had left the team less bored and less tired, and another said the logs had taken stress off the team.

Of the 56 responses, 43 (76.79%, 95% CI 64.29% to 88.24%) were negative and 2 (3.57%) carried the strongest negative score of −10. Positive responses numbered 12 (21.43%), and 1 was neutral. The mean written score was −2.9 (95% CI −4.1 to −1.7, n = 56 responses), and the median was −5.0.

Of the 56 responses, 53 came from respondents who also rated the indicator. Among them, the written score rose with the rating (Spearman rho 0.52, 95% CI 0.33 to 0.66, p < 0.001, n = 53 responses). The written responses corroborated the rating. Of the 42 negative responses with a rating, 29 (69.05%) came from respondents whose rating was in the distressed range.

Respondents who wrote about the indicator and gave a rating numbered 51, with a mean rating of 3.6. The 737 respondents who rated the indicator without writing about it had a mean of 4.3. The difference, −0.8 (95% CI −1.4 to −0.1), excluded zero. Ratings in the distressed range made up 54.90% of the ratings from respondents who wrote (28 of 51) and 44.64% of the ratings from respondents who did not (329 of 737).

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 149.75, Holm p < 0.001, omega squared 0.654). Active engagements in Production rated highest (mean 6.2, n = 99 respondents) and canceled engagements lowest (mean 1.7, n = 293 respondents). Ratings also differed by respondent role (Welch F 6.66, Holm p = 0.012, omega squared 0.013). Portfolio directors rated highest (mean 5.8, n = 27 respondents) and individual contributors lowest (mean 4.1, n = 610 respondents). Ratings also differed by vendor type (Welch F 6.79, Holm p < 0.001, omega squared 0.032). Consulting firms rated highest (mean 4.9, n = 107 respondents) and BPO specialists lowest (mean 3.4, n = 185 respondents). Outsourcing model, institution type, process family and class of work showed no difference.

Written sentiment differed by engagement status and lifecycle stage across the 44 engagements with a written response (Kruskal-Wallis H 13.28, df 3, p = 0.004). Of the groups with 10 or more responses, responses from canceled engagements were the most negative (mean −5.4, 25 responses) and responses from active engagements in Transition/Cut-Over the least negative (mean −1.0, 15 responses). Responses from active engagements in Build-Out (7) and active engagements in Production (9) are reported as counts only.

No test across respondent roles was run, because fewer than two roles had 30 or more written responses. Individual contributors wrote 33 and engagement managers wrote 23 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 = 0.68, 95% CI 0.56 to 0.78, Holm p < 0.001, n = 94 engagements). The association held after Holm correction in twelve 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 = 0.87, 95% CI 0.82 to 0.90, 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 = −0.76, 95% CI −0.78 to −0.72, Holm p < 0.001, n = 742 respondents). The association held after Holm correction in thirty-six of the 37 segment levels tested.

Two comparisons set the engagements with at least one negative response against all other engagements. Of the 114 other engagements, 106 had no written response addressing the indicator. These two comparisons therefore do not isolate written sentiment. Of the 36 engagements with a negative response, 19 (52.78%) were canceled, against 37 of the 114 other engagements (32.46%). The difference reached significance (Fisher exact p = 0.032). Customer satisfaction among active engagements differed between the two groups (mean 57.76% on 17 engagements against 65.49% on 77, Welch t −3.17, p = 0.003).

Two correlations test written sentiment directly. Across the 44 engagements with a written response, a more negative engagement mean written score came with cancellation (point-biserial r −0.51, p < 0.001). Across 51 respondents, a more negative respondent mean written score came with higher intent to leave (Spearman rho −0.63, 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, two of the six pairs differed. The association with the engagement indicator mean was the strongest and the association with customer satisfaction the weakest.

Answers clustered within engagements (ICC 0.83). Clustering reduced the 788 respondent answers to the equivalent of about 175 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, 76.79%, ranked 2nd from the highest, against a median of 33.33%. Its mean written score, −2.9, ranked 2nd from the most negative, against a median of 0.8.

The indicator most often present in the same responses was C018, “How happy are you with your current job?”, in 14 of the 56 responses (25.00%). C021, “How likely are members of your current team to leave their jobs in the next 12 months?” (10 responses), C109, “Rate how quickly the customer responds when this engagement raises issues that need customer action.” (6 responses), C123, “Rate the adequacy of your employer's investment in training its workforce.” (4 responses) and C181, “Rate the quality of advance notice third-party providers give before changes that can affect the agents on this engagement.” (4 responses) followed.

The most frequent theme was “Occurs every cycle or most days”, in 7 responses (12.50%). The second was “Team or colleagues”, in 6 responses.

Nearly half of all ratings of the extended team's happiness fell in the distressed range (357 of 788 answers, 45.30%). 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 1.7, n = 293 respondents).

The written evidence describes teams worn down by waiting, repeated manual correction and decisions no one would own, and members leaving as a result. 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 1 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 (56 responses on 44 engagements). Intervals for written sentiment therefore used a bootstrap by engagement.