This is not a new product demonstration. It follows Minerva Advisor's established public-case verification process. The material comes from a published Cognizant case study. We isolated the later-stage outcomes, then rebuilt only what was knowable at the moment of decision into a training data package. This is an independent teaching simulation based on an official public source. It is not real correspondence, not a real client engagement, and not a Cognizant-endorsed result.

The case involves a large UK composite insurer facing rising costs and competitive pressure. Its outdated robotic process automation platform was generating more than thirty bot-execution failures every day. The prior vendor struggled to scale delivery and offered little transparency into its work. Invoice processing was both slow and in need of higher accuracy. The decision Minerva Advisor evaluated: should the insurer migrate all automation immediately, or first stabilize the highest-failure, highest-value processes on a defined timeline while validating vendor controls and accuracy?

Every run leaves an auditable receipt of five work items. First, the system reviewed the one official source available at decision time. Second, it identified the relevant decision-maker roles. Third, it separated confirmed facts from inferred conclusions. Fourth, it logged open questions still unresolved. Fifth, it recorded alternative explanations together with a reversal condition. Each item is timestamped and traceable, so an executive can audit exactly how the judgment was built.

Known facts: failures were frequent, legacy software limited process improvement, and invoice processing needed to be both faster and more accurate. What remained unknown: how much of the failure came from infrastructure, process design, data exceptions, or the vendor itself, and which processes were actually suited for early migration versus longer stabilization.

The strongest challenge the system preserved: daily failures might stem mainly from employee skill gaps rather than the platform, invoice slowness could be a third-party process problem unrelated to any automation platform choice, and vendor transparency issues might be specific to prior large deployments rather than predictive of a smaller, higher-priority pilot. The reversal condition: if root-cause diagnosis shows failures are platform-driven rather than process or skill-based, and the vendor demonstrates transparency in a small trial, then moving faster toward broader migration could be justified.

The published case later described Cognizant's own work: an assessment of the migration backlog, discovery workshops, a new automation platform, a proof of concept for document understanding and process mining, and new monitoring reporting. It also reported that more than seventy automations eventually delivered about seven and a half million pounds in annual savings and roughly two hundred sixty full-time-equivalent capacity, with incidents falling from more than thirty per day to one or two per month. None of that was given to Minerva Advisor. It was held out specifically to test whether the system could independently reach a sound sequencing judgment without seeing the answer.

Minerva Advisor then ran a three-advisor cross-check on that single judgment. Marcus focused on which processes actually qualified for early stabilization or migration. Sofia modeled the impact across operations, claims finance, vendor governance, and staff. Evelyn challenged whether an immediate full migration would lock unresolved unknowns into the new platform. All three converged on a time-boxed pilot for the highest-risk processes, and Evelyn separately warned that watching bot-execution rates alone could mask invoice errors and exception-handling failures.

The executive brought one condition into the Decision Room: prioritize the highest-failure, highest-payment-risk processes first, preserve manual fallback throughout, and use payment accuracy, failure rate, and vendor transparency together as the thresholds for stopping or scaling. The system logged this as a formal response receipt and used it to test whether the underlying judgment would change.

Minerva Advisor compared two paths side by side. Immediate full migration could retire the legacy platform faster, but it would also lock unknown root causes and unresolved vendor dependency into the new environment. A time-boxed pilot validates process design, controls, and accuracy first, at the cost of tolerating some ongoing failures in the short term. This comparison let the executive see directly whether adding their own operating condition shifted which option the system preferred.

The executive chose the pilot path. The committed next action: commission a root-cause diagnosis across infrastructure, process, data, and vendor factors for the highest-failure processes, and define pilot scope, stop-or-scale thresholds, and vendor transparency criteria before any migration decision is made. Automation operations, claims finance, and vendor governance teams were assigned to select the high-risk processes and set the manual fallback and accuracy conditions.

This run used four model calls. The first decision-ready judgment was delivered in 15.610 seconds, with the complete result finished in 23.425 seconds, passing the thirty-second first-decision and forty-five-second complete-result thresholds. The case passed all ten out of ten decision-quality checks. Minerva Advisor does not claim that Cognizant's new platform, its more than seventy automations, or its reported savings have occurred as a result of this simulation. This remains a single case test of decision quality and speed, not a production-grade service guarantee or a real customer outcome.