Per the current plan, how many months from today until the engagement reaches Production/Delivery?

Respondents reported a mean expected time to Production/Delivery in months on the current plan (mean 3.9, median 4.0, n = 545 respondents). Engagements with a longer expected time to Production/Delivery were canceled less often (r = −0.37, 95% CI −0.53 to −0.19, p < 0.001, n = 104 engagements). Expected time and customer satisfaction on active engagements showed a tested null (TOST p 0.006). A longer expected time came with a higher engagement indicator mean (r = 0.20, 95% CI 0.01 to 0.38, p 0.038, n = 104 engagements). Respondents who expected a longer time to Production/Delivery reported lower intent to leave (r = −0.28, cluster bootstrap 95% CI −0.44 to −0.09, p 0.005, n = 514 respondents). Expected time differed after Holm control by vendor type (Welch F 8.21, Holm p < 0.001, omega squared 0.033).

One written response was coded to the indicator, from 1 of 850 respondents on 1 of 150 engagements. The single scored response was negative, with a score of −5. It was a secondary response, written in answer to a question outside the indicator’s own survey section.

The study set mean was 3.9 on 545 answering respondents, with a median of 4.0.

The single response coded to the indicator was a secondary response. The response was written in answer to C156, a question outside the indicator’s own survey section.

The indicator has no good or bad end. Under the coding rulebook’s rule for such indicators, the written score records the effect each response states on the engagement or on the respondent. The survey question is “Per the current plan, how many months from today until the engagement reaches Production/Delivery?” The frequency, scope and consequence a response states set the strength of its score. A score of +10 marks a response that describes “this attribute of the engagement as helping the engagement at its best.” A score of −10 marks a response that describes “this attribute as harming the engagement at its worst . . . .”

The distribution was reported as counts only, because fewer than 10 responses carried a score. The single scored response carried a score of −5.

Figures are respondent level. Means are on the scale as recorded. A level under 30 prints no interval and a level under 10 prints counts only.

Engagement families were tested on engagement means, and respondent role and vendor type were tested on respondents. A distressed p marked exact is a Fisher exact test for a two by two table, and one marked simulated is a Monte Carlo test run until its p is stable to the third decimal, both used where an expected count is under 5. Vendor type differed after Holm control (Welch F 8.21, Holm p < 0.001, tested on respondents). In Descriptive Statistics by Segment, Pure-play agentic AI firm had the highest mean, 5.2 (n = 46 respondents), and IT services major the lowest, 3.1 (n = 218 respondents). No difference held after Holm control for outsourcing model, institution type, process family, class of work and respondent role.

The share of engagements canceled on the study date, measured at engagement level (base 150 engagements, 56 canceled). The association is a descriptive contrast, inflated because canceled engagements were rated after cancellation, and is not predictive.

The study set r was −0.37 (95% CI −0.53 to −0.19, Holm p 0.002, n = 104 engagements). Of the 16 tested segment levels, 1 held after Holm control.

The satisfaction score recorded against each engagement on a 100-point scale. The primary estimate uses the 94 active engagements. A descriptive contrast uses all 150 engagements.

The study set r was −0.04 (95% CI −0.24 to 0.16, Holm p 1.000, n = 94 engagements). The association did not hold after Holm control. Equivalence Tests of Null Results found it equivalent to zero inside the bound. Of the 15 tested segment levels, 0 held after Holm control.

The mean of an engagement’s 100 indicator ratings, measured at engagement level (base 150 engagements). Where this indicator is one of the 100, the mean is recomputed without it.

The study set r was 0.20 (95% CI 0.01 to 0.38, Holm p 0.711, n = 104 engagements). The association did not hold after Holm control. The primary test in Comparison of Associations Across the Four Measures gave p 0.038 before Holm control, so the association held before that control. Of the 19 tested segment levels, 0 held after Holm control.

The respondent’s stated likelihood of leaving the current job within 12 months, rated 1 to 10 (C019). Measured at respondent level on up to 798 respondents, with the engagement-level form reported alongside.

The study set r was −0.28 (95% CI −0.35 to −0.19, Holm p < 0.001, n = 514 respondents). Of the 35 tested segment levels, 13 held after Holm control.

Pairs were compared on the engagement level form of every measure, each turned so that a higher value was the better outcome, on the 104 engagements where the indicator and all four measures existed. Of the 6 pairs, 0 differed after Holm control.

Clustering reduced the 545 respondent answers to about 104 independent answers. Respondent level intervals therefore used the cluster bootstrap, and respondent level tests on intent to leave used cluster-robust errors.

Tested null, equivalent to zero: customer satisfaction. No result was inconclusive. The detection floor column is the study floor at 150 engagements. Intent to leave was tested on its effective n.

Each change was computed before rounding, so it can differ by 0.01 from the difference of the two printed values.

Checks that did not hold: “Rank correlation in place of Pearson” on engagement indicator mean, “Active engagements only” on engagement indicator mean, “Active engagements only” on intent to leave, “Bootstrap of engagements” on engagement indicator mean, “Thin-base segments removed” on cancellation rate, “Thin-base segments removed” on engagement indicator mean and “Thin-base segments removed” on intent to leave. A check holds when its test lands on the same side of 0.05 as the primary test and, where the primary test is below 0.05, its r keeps the primary sign. Thin-base rule: engagements in any level under 30 engagements of outsourcing model or process family removed. Institution type is not used, because every one of its levels is under 30.

Each of the four measures was computed from data this indicator does not contain, so each result is a finding rather than an arithmetic consequence.

Each deviation was computed before rounding, so it can differ by 0.01 from the difference of the two printed values.

The comparison ran on 104 engagements. The indicator departed from the study’s typical pattern on cancellation rate, customer satisfaction, engagement indicator mean and intent to leave.

The response coded to the indicator was also coded to 7 other indicators. The theme “Raised it, nothing came back” of the coding rulebook was the only theme in the same response.

Pure-play agentic AI firm respondents expected the longest time to Production/Delivery (mean 5.2, n = 46 respondents), and IT services major respondents expected the shortest (mean 3.1, n = 218 respondents). A longer expected time came with less cancellation (r = −0.37, 95% CI −0.53 to −0.19, p < 0.001, n = 104 engagements) and lower intent to leave (r = −0.28, cluster bootstrap 95% CI −0.44 to −0.09, p 0.005, n = 514 respondents).

The indicator is a survey question that is not a rating, so the written responses were not set against a rating. Written responses were voluntary. They recorded what the respondents who wrote reported, and how common it was is measured by the answers. The analysis of the written responses rested on 1 response, a base of anecdote strength.

The evidence is reported experience: what the delivery team said about its own engagement, gathered in one cross-section. The figures showed associations, not causes. Indicators about the financial institution were reported at second hand by vendor staff. Cancellation is a descriptive contrast, because canceled engagements were rated after they ended.

Tests across respondent role and vendor type were run at respondent level and treated respondents as independent. The section Clustering and Effective Sample Size states whether, and by how much, clustering within engagements reduced the information in respondent level figures.

Answers agreed fully within each engagement, so the effective number of independent answers fell to the count of engagements that answered (ICC 1.00, 545 answers worth about 104 independent answers). The robustness checks held in part (15 of 22 checks), and the failures included the bootstrap and the thin-base removals.

Fewer than 10 responses carried a score, so written sentiment was reported as counts, with no statistic. Coding was performed by AI coders under a fixed rulebook. No response coded to the indicator fell in the sample second-coded under rulebook 0.5, so agreement on whether a response was coded to the indicator could not be assessed. No response coded to the indicator was second-scored under rulebook 0.6, so agreement on the score could not be assessed.