Rate how well the speed of joint issue resolution matches the speed at which agent-caused problems can spread

The mean rating was 3.7 and the median 4.0 (n = 809 respondents). Ratings of 3 or below, the distressed range, made up 49.44% 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 = 0.60, 95% CI 0.46 to 0.72, 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 = −0.64, cluster bootstrap 95% CI −0.71 to −0.57, 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 38.06, Holm p < 0.001, omega squared 0.378) and respondent role (Welch F 10.45, Holm p < 0.001, omega squared 0.023).

Few written responses addressed the indicator: 18, all from C156, the comment field on joint management, of which 16 were negative and 2 positive. Most described an agent that kept acting while the two firms resolved the problem: fifty responses sent during a three-day escalation, twenty more new hires moved through a misfiring step before anyone read the alert, a hundred more lines processed while the firms discussed a wrong supplier record. Several said no one on either side could pause the agent without a ticket or a meeting. Written sentiment was not associated with the study measures, though the base is too small for that test to carry weight.

Ratings of 3 or below, the distressed range, accounted for 400 of the 809 answers (49.44%). The engagement mean fell in the distressed range in 61 of 150 engagements.

The primary responses numbered 18, 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.” No response from any other question addressed the indicator, so every response was primary.

Of the 18 responses, eleven described an agent that kept acting, or a problem that kept spreading, while the joint resolution waited. The waits were measured in days: two days whenever the agent did something odd, three or four days for an answer to come back through four hands, six days between weekly meetings while a bad role assignment sat live, eleven days to establish whose change board owned a question while three monthly attribution packs went to an investment committee. Six stated that no one on either side could, or would, pause the agent without raising a ticket, waiting for the weekly call, or deciding first whose problem it was.

Four responses drew a distinction between two speeds. Detection was fast, or the bridge call met within the hour, or stopping a bad run took minutes. The fix, the sign-off, or the question of whose fault it was took days. One respondent wrote that the fix took a week longer than the catch.

Of the 18 responses, 16 (88.89%, 95% CI 72.22% to 100.00%) were negative and 1 (5.56%) carried the strongest negative score of −10. Positive responses numbered 2 (11.11%), and no response was neutral. The mean written score was −4.2 (95% CI −5.6 to −2.4, n = 18 responses), and the median was −5.0.

Of the 18 responses, 17 came from respondents who also rated the indicator. Among them, the written score rose with the rating (Spearman rho 0.61, 95% CI 0.27 to 0.84, p = 0.009, n = 17 responses). The written responses corroborated the rating. Of the 15 negative responses with a rating, 7 (46.67%) came from respondents whose rating was in the distressed range.

Respondents who wrote about the indicator and gave a rating numbered 17, with a mean rating of 3.6. The 792 respondents who rated the indicator without writing about it had a mean of 3.7. The difference, 0.0 (95% CI −1.1 to 1.2), included zero. Ratings in the distressed range made up 41.18% of the ratings from respondents who wrote (7 of 17) and 49.62% of the ratings from respondents who did not (393 of 792).

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 38.06, Holm p < 0.001, omega squared 0.378). Active engagements in Build-Out rated highest (mean 4.7, n = 168 respondents) and canceled engagements lowest (mean 2.3, n = 306 respondents). Ratings also differed by respondent role (Welch F 10.45, Holm p < 0.001, omega squared 0.023). Portfolio directors rated highest (mean 5.2, n = 30 respondents) and individual contributors lowest (mean 3.5, n = 628 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 17 engagements with a written response (Kruskal-Wallis H 3.49, df 3, p = 0.322). Fewer than two groups held 10 or more responses, so the groups are reported as counts only: active engagements in Build-Out (3), active engagements in Transition/Cut-Over (5), active engagements in Production (3) and canceled engagements (7).

No test across respondent roles was run, because fewer than two roles had 30 or more written responses. Individual contributors wrote 14, engagement managers wrote 3 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 = −0.62, 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 = 0.60, 95% CI 0.46 to 0.72, 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 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 = −0.64, 95% CI −0.68 to −0.60, 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 135 other engagements, 133 had no written response addressing the indicator. These two comparisons therefore do not isolate written sentiment. Of the 15 engagements with a negative response, 6 (40.00%) were canceled, against 50 of the 135 other engagements (37.04%). The difference did not reach significance (Fisher exact p = 1.000). The comparison of customer satisfaction was not computed, because one of the two groups held too few active engagements.

Two correlations test written sentiment directly. Across the 17 engagements with a written response, the engagement mean written score was not associated with cancellation (point-biserial r −0.36, p = 0.157). Across 15 respondents, the respondent mean written score was not associated with intent to leave (Spearman rho −0.16, p = 0.570). Of the three 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 = 0.543).

Answers clustered within engagements (ICC 0.67). Clustering reduced the 809 respondent answers to the equivalent of about 205 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, 88.89%, ranked 16th from the highest, against a median of 80.82%. Its mean written score, −4.2, ranked 47th from the most negative, against a median of −4.7.

The indicator most often present in the same responses was C143, “Rate how quickly the two firms together can stop an agent that is behaving badly in live operations.”, in 7 of the 18 responses (38.89%). C136, “Rate how effectively the customer and vendor jointly manage this engagement now that agents perform part of the work.” (6 responses), C141, “Rate how effectively the two firms manage issues arising from agent work as one team rather than through two separate processes.” (6 responses), C157, “Rate the factual reliability of the AI tools' outputs on this engagement before any human review.” (5 responses) and C153, “Rate how closely the speed of joint decision making matches the speed at which the agents act.” (4 responses) followed.

The most frequent theme was “Raised it, nothing came back”, in 3 responses (16.67%). The second was “Positive with an embedded negative”, in 3 responses.

Nearly half of all ratings of how well the speed of joint issue resolution matches the speed at which problems caused by agents can spread fell in the distressed range (400 of 809 answers, 49.44%). 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 2.3, n = 306 respondents).

The few written responses describe how an agent's error spreads. An error made by a person stops when the person stops. An error made by an agent continues at the agent's pace until someone with authority pauses it. The respondents described joint arrangements in which that authority was missing, or reachable only through the weekly call.

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 (18 responses on 17 engagements). Intervals for written sentiment therefore used a bootstrap by engagement.

The written responses number fewer than 30, so their shares and the written-sentiment tests rest on a small base.