This one tripped me up a bit because removing user feedback and engagement data feels like taking away the two most obvious answers.
Acknowledge the constraint of ignoring user feedback and engagement metrics, then pivot to alternative data sources that reveal strategic, market, and competitive insights. Structure your answer by categorizing these sources—such as market and competitive intelligence, internal business data, and technical/operational signals—and explain how each informs the build decision. Conclude by emphasizing the need to synthesize these signals into a holistic business case.
Pro tip: Demonstrate strategic thinking by linking data sources to SAP's enterprise context, such as leveraging existing customer advisory boards or partner ecosystem signals, and always tie insights back to potential ROI and strategic fit.
Analyze external sources like competitor earnings calls, press releases, analyst reports (e.g., Gartner, Forrester), and patent filings to understand the feature's strategic intent and market traction.
Examine internal data such as sales win/loss reasons, support ticket trends, churn analysis, and total addressable market (TAM) estimates to assess potential revenue impact and operational burden.
Review system telemetry, API usage patterns, and infrastructure costs to gauge technical feasibility, scalability, and potential integration challenges with existing SAP solutions.
Evaluate how the feature aligns with SAP's product vision, platform strategy, and partnership ecosystem, ensuring it doesn't cannibalize existing offerings or divert from core priorities.
Combine insights from all sources to build a business case, weighing opportunity cost, competitive urgency, and resource requirements before making a build/no-build recommendation.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.