This case follows our established public-case verification process, not a new demonstration format, and no case-specific product mode has been added. Sourced from IBM Consulting's official public case study, we first isolate the later-stage answers, then reconstruct only the information available at the moment of decision into a teaching dataset. Minerva Advisor completed one paid live run, and this video is a verified replay of an actual Decision Room. This is an independent teaching simulation built on a public source. It does not imply that IBM Consulting used, reviewed, endorsed, sponsored, certified, or commissioned Minerva Advisor, and it does not represent real correspondence or real client outcomes.

The case opens with a major retailer whose legacy commerce infrastructure could no longer reliably support traffic once pandemic-driven demand pushed volume from about seven thousand visitors per minute to a peak of nineteen thousand. Minerva was asked to weigh two paths: committing immediately to full-scale platform modernization with a single cutover, or first running a time-boxed, stoppable capacity-stabilization and migration-evidence gate to determine scope before committing further.

The run leaves an auditable, five-item work receipt. First, it draws on a single verified source. Second, it identifies four distinct advisory roles. Third, it separates confirmed facts from inferences and from open questions. Fourth, it compares exactly two competing paths side by side. Fifth, it preserves three alternative explanations and one explicit reversal condition, so every judgment can be traced back to what was known, what was assumed, and what was left open.

Here is what was known and unknown at decision time. Known: the legacy infrastructure, the surge in online demand, and the peak-period failure. Unknown: how much each factor, capacity, version currency, database load, integration, search, checkout, or monitoring, contributed to that failure, which dependencies could be isolated, whether a workable recovery path existed, and how much time short-term stabilization could realistically buy before the next peak.

The system preserves its strongest counterargument. The failure could result from several interacting factors at once, so the evidence gate might never isolate one clean, fixable layer. The reversal condition is explicit: if stabilization measures cannot reliably hold through the next peak window and no diagnostic gain is achieved on which subsystems are truly at fault, the decision should flip immediately to phased modernization rather than continuing to wait.

The published answer was excluded from the input Minerva received. IBM Consulting's later-stage account describes the Garage methodology, IBM Cloud and Red Hat OpenShift, more than a year of building and testing, a single-weekend infrastructure and version cutover, zero incidents, support for more than twenty-seven thousand peak visitors, and two-year revenue growth above one hundred fifteen percent. None of that entered the decision input. Minerva did not see the technology stack chosen or the outcome achieved.

Three advisors then cross-check a single judgment from different angles. Marcus frames the real decision as whether a reliable stabilization gate can be established before the next peak. Sofia traces the consequences for digital commerce, platform reliability, customer operations, and decision-makers. Evelyn challenges whether short-term stabilization simply delays the underlying architectural problem, noting that capacity, database, search, and checkout issues can amplify one another, so demanding a single root cause before expanding migration risks missing the window entirely. All three converge on the same recommendation: adopt the time-boxed, stoppable stabilization-and-evidence gate first.

This is where the system shows whether executive input changes the judgment. The executive enters one condition: first quantify the next peak window and the tolerable failure level; if short-term stabilization cannot bridge that window, accelerate a scope-limited, recoverable migration without delay. Minerva logs a formal response receipt. The underlying recommendation is unchanged, but the reversal condition is strengthened and made explicitly time-based.

Comparing the two options directly: immediate full-scale modernization addresses the architecture problem head-on, but with dependencies and recovery paths still unclear, a single large cutover carries high customer risk. Capacity stabilization with a migration-evidence gate allows scope decisions to be based on staged evidence, at the cost of continued peak-period pressure in the near term. The executive selects the stabilization path while explicitly preserving an accelerated-migration exit if the evidence turns against it.

The committed action: within three weeks, the digital commerce and platform reliability teams must quantify failure root causes, define the next peak window, map dependencies, and confirm recovery paths, all as the threshold for deciding whether to expand into full migration. Minerva makes no claim that a cloud platform has been selected, that any cutover has occurred, or that growth outcomes have been achieved.

This IBM Consulting public case passed ten out of ten decision-quality checks. The Decision Room used four model calls, delivering its first decision in 17.762 seconds and completing the full three-advisor cross-check in 24.513 seconds, passing the thirty-second first-decision threshold and the forty-five-second complete-result threshold. Decision quality and speed both passed, but this remains a single-case test, not equivalent to production-level service standards or real client outcomes.