Rate how clearly the two firms have settled who decides what agents may do without human approval

The mean rating was 3.6 and the median 3.0 (n = 808 respondents). Ratings of 3 or below, the distressed range, made up 50.25% of the answers. The rating was associated with all four study measures. Higher ratings came with less cancellation (r = −0.62, 95% CI −0.71 to −0.51, p < 0.001, n = 150 engagements), higher customer satisfaction among active engagements (r = 0.59, 95% CI 0.44 to 0.71, p < 0.001, n = 94 engagements), a higher engagement indicator mean computed without the indicator (r = 0.84, 95% CI 0.79 to 0.88, p < 0.001, n = 150 engagements) and lower intent to leave (r = −0.67, cluster bootstrap 95% CI −0.73 to −0.60, p < 0.001 with standard errors clustered by engagement, n = 758 respondents). After Holm correction, ratings differed by engagement status and lifecycle stage (Welch F 40.01, Holm p < 0.001, omega squared 0.381) and respondent role (Welch F 9.94, Holm p < 0.001, omega squared 0.017).

Written responses addressing the indicator numbered 48, from 48 respondents on 42 engagements. Of these, 34 were negative and 12 positive. Half of the responses said the two firms had never settled or written down what the agent may do without a person, so each analyst decided case by case. The remedy respondents proposed was simple: one agreed list. Where the list existed, respondents said it held, and placed the remaining weakness in the depth of review. Written sentiment was not associated with the study measures.

Ratings of 3 or below, the distressed range, accounted for 406 of the 808 answers (50.25%). The engagement mean fell in the distressed range in 68 of 150 engagements.

The primary responses numbered 38, all written in answer to C156, “Add any comments on the joint management of this engagement that the ratings in this section do not capture.” The remaining 10 responses, 20.83% of the total, were secondary and came from 6 other questions. That secondary share ranked 33rd from the highest among the 71 Part 2 indicators with 30 or more written responses, against a median of 18.92%. Respondents who wrote both a primary and a secondary response numbered 0. Negative responses made up 68.42% of primary responses (26 of 38) and 80.00% of secondary responses (8 of 10).

Twenty-four responses stated that the two firms had not settled, or had not written down, what the agent may do without a person, such as the replies to customers it may send, the alerts it may close and the access requests it may approve. In one engagement the conversation with the institution's compliance leadership had been deferred twice. In the absence of a rule, respondents wrote, every analyst guessed, and every edge case came back to a person. Seven asked for the same remedy: a single list, page or checklist agreed by both sides. Five described the cost: analysts checking output at nine at night, leads spending every Friday clearing tickets that should never have been held, and work slower than the manual process the agent replaced.

Against these, nine positive responses to C156 said the boundary had been agreed and written down, in some cases in the first two weeks, and that both sides kept to it. Four of these placed the remaining weakness in review: approvers who signed the queue without opening the vendor file, or two people signing off a couple of hundred triage notes at the end of a shift. Three responses described the boundary kept informally, by a half-hour conversation each morning, a whiteboard updated in the huddle, or habit and email. One respondent described the opposite pressure: a vendor that wanted the agent to run with less oversight to meet cost goals, and an institution that would not allow it.

Of the 48 responses, 34 (70.83%, 95% CI 57.45% to 83.67%) were negative and 23 (47.92%) carried the strongest negative score of −10. Positive responses numbered 12 (25.00%), and 2 were neutral. The mean written score was −4.6 (95% CI −6.4 to −2.7, n = 48 responses), and the median was −5.0.

Of the 48 responses, 48 came from respondents who also rated the indicator. Among them, the written score rose with the rating (Spearman rho 0.74, 95% CI 0.56 to 0.86, p < 0.001, n = 48 responses). The written responses corroborated the rating. Of the 34 negative responses with a rating, 21 (61.76%) came from respondents whose rating was in the distressed range.

Respondents who wrote about the indicator and gave a rating numbered 48, with a mean rating of 3.7. The 760 respondents who rated the indicator without writing about it had a mean of 3.6. The difference, 0.1 (95% CI −0.6 to 0.7), included zero. Ratings in the distressed range made up 45.83% of the ratings from respondents who wrote (22 of 48) and 50.53% of the ratings from respondents who did not (384 of 760).

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 40.01, Holm p < 0.001, omega squared 0.381). Active engagements in Build-Out rated highest (mean 4.7, n = 163 respondents) and canceled engagements lowest (mean 2.2, n = 309 respondents). Ratings also differed by respondent role (Welch F 9.94, Holm p < 0.001, omega squared 0.017). Portfolio directors rated highest (mean 4.8, n = 31 respondents) and individual contributors lowest (mean 3.5, 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 42 engagements with a written response (Kruskal-Wallis H 1.82, df 3, p = 0.610). Of the groups with 10 or more responses, responses from canceled engagements were the most negative (mean −6.2, 17 responses) and responses from active engagements in Transition/Cut-Over the least negative (mean −3.5, 20 responses). Responses from active engagements in Build-Out (9) and active engagements in Production (2) 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 30, engagement managers wrote 13 and portfolio directors wrote 5 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 = −0.62, 95% CI −0.71 to −0.51, Holm p < 0.001, n = 150 engagements). The association held after Holm correction in fourteen 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 = 0.59, 95% CI 0.44 to 0.71, Holm p < 0.001, n = 94 engagements). The association held after Holm correction in eleven 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 is one of the rated indicators. Each comparison therefore uses the mean recomputed without it.

Higher ratings came with a higher engagement indicator mean (r = 0.84, 95% CI 0.79 to 0.88, 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 = −0.67, 95% CI −0.71 to −0.63, Holm p < 0.001, n = 758 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 119 other engagements, 108 had no written response addressing the indicator. These two comparisons therefore do not isolate written sentiment. Of the 31 engagements with a negative response, 12 (38.71%) were canceled, against 44 of the 119 other engagements (36.97%). The difference did not reach significance (Fisher exact p = 1.000). Customer satisfaction among active engagements did not differ between the two groups (mean 63.37% on 19 engagements against 64.28% on 75, Welch t −0.27, p = 0.791).

Two correlations test written sentiment directly. Across the 42 engagements with a written response, the engagement mean written score was not associated with cancellation (point-biserial r −0.17, p = 0.289). Across 48 respondents, the respondent mean written score was not associated with intent to leave (Spearman rho −0.22, p = 0.128). Of the four comparisons, none 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 customer satisfaction the weakest. The associations with customer satisfaction and intent to leave did not differ (Holm p = 0.366).

Answers clustered within engagements (ICC 0.68). Clustering reduced the 808 respondent answers to the equivalent of about 202 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. The indicator is one of the rated indicators, and the engagement indicator mean was recomputed without it. The correction changed r by 0.00, from 0.84 to 0.84.

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 followed the study's typical pattern on all four measures, and no deviation held after Holm correction.

Among the 71 Part 2 indicators with 30 or more written responses, the indicator's share of negative responses, 70.83%, ranked 58th from the highest, against a median of 80.82%. Its mean written score, −4.6, ranked 40th from the most negative, against a median of −4.7.

The indicator most often present in the same responses was C136, “Rate how effectively the customer and vendor jointly manage this engagement now that agents perform part of the work.”, in 12 of the 48 responses (25.00%). C147, “Rate how well human review points are placed across the two firms at the moments where agent errors would matter most.” (9 responses), C148, “Rate how well joint human review capacity keeps up with the volume of output the agents produce.” (7 responses), C149, “Rate how much genuine scrutiny agent outputs receive at human review points rather than routine approval.” (5 responses) and C109, “Rate how quickly the customer responds when this engagement raises issues that need customer action.” (4 responses) followed.

The most frequent theme was “Respondent proposes a remedy”, in 10 responses (20.83%). The second was “Comparison to a prior engagement”, in 6 responses.

Just over half of all ratings of how far the two firms had settled who decides what agents may do without human approval fell in the distressed range (406 of 808 answers, 50.25%). 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 2.2, n = 309 respondents).

The written responses present the boundary of agent autonomy as a single document that either existed or did not. Where it did not, the decision fell to each analyst on each case, and the agent saved little time. Where it did, respondents turned to the next question: whether the people reviewing the agent's work could keep pace with it.

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 (48 responses on 42 engagements). Intervals for written sentiment therefore used a bootstrap by engagement.