Diagnose a sudden drop in accessibility adoption for knowledge search assistant

Problem Statement Description

You are investigating a sudden decline in accessibility adoption among review operations teams using a knowledge search assistant. These teams rely on the assistant to quickly find policy guidance, precedent decisions, workflow instructions, and escalation criteria while reviewing content, transactions, cases, or other operational queues. Accessibility adoption may include usage of features such as keyboard navigation, screen-reader-compatible flows, captions or transcripts, high-contrast modes, text resizing, simplified layouts, or other assistive experiences built into the search assistant.

The drop is unexpected and needs to be diagnosed before any fixes are proposed. Your task is to frame the anomaly clearly, determine whether the decline is real or measurement-related, identify which users, workflows, surfaces, regions, tools, or feature paths are affected, and build a structured set of hypotheses. You should consider that review operations environments are often high-throughput, policy-sensitive, globally distributed, and dependent on internal tooling reliability.

Focus on the investigation approach rather than jumping to product changes. The interviewer is looking for how you would isolate the cause, use data and qualitative evidence, validate instrumentation, and determine whether the issue stems from product experience, accessibility compatibility, training, workflow changes, policy updates, user mix, platform behavior, or reporting definitions.

The experience should consider:

- How to define “accessibility adoption,” including numerator, denominator, event triggers, eligible users, active usage, and repeat usage.

- How to confirm the timing, magnitude, and scope of the drop across cohorts such as role, region, language, queue type, device, browser, assistive technology, and tenure.

- How to check instrumentation, logging changes, event taxonomy, experiment exposure, permission changes, and dashboard definitions before assuming user behavior changed.

- How to segment the knowledge search workflow, from query entry to result scanning, answer consumption, policy citation, follow-up search, and case resolution.

- What recent changes may have occurred in the assistant, review operations tooling, accessibility settings, search ranking, UI components, authentication, training, or operating procedures.

- What qualitative signals to gather from reviewers, team leads, accessibility users, support tickets, QA sessions, and internal incident channels.

- How to distinguish between reduced need, reduced discoverability, broken accessibility support, degraded search utility, workflow displacement, and organizational process changes.

- What evidence would be needed to prioritize mitigation, monitor recovery, and prevent recurrence.

The goal is to present a clear RCA plan that narrows the problem from “accessibility adoption dropped” to a validated explanation of what changed, who was affected, why it matters operationally, and what confidence you would need before recommending fixes.