Product Manager - Business Intelligence & Analytics

📋 Description

• • Lead the development and execution of the business intelligence strategy for the Core Platform & Services (CPS) Applications team, defining key performance indicators (KPIs) and operational metrics that measure the health of the CPS ecosystem.
• • Design, build, and maintain high-impact BI dashboards that deliver real-time visibility into application adoption, service utilization, and centralized cost management across Motorola Solutions’ portfolio.
• • Analyze complex operational datasets spanning hardware, software, and cloud services to identify trends, inefficiencies, and opportunities for performance optimization and cost reduction.
• • Serve as the primary data interpreter for executive leadership, translating technical telemetry into clear, actionable business narratives that demonstrate the value and progress of the CPS team.
• • Partner closely with Engineering, Finance, and Product teams to ensure accurate, automated collection of metrics from core services including Unified ID, AMS, and other platform integrations.
• • Use internal usage data and market trends to inform and prioritize product backlogs, directly influencing the broader product strategy across the MSI portfolio.
• • Establish a unified source of truth for operational data by collaborating across procurement, engineering, and sales teams to consolidate disparate data streams.
• • Collaborate with cross-functional stakeholders to align BI initiatives with organizational goals, ensuring data integrity and consistent reporting standards.
• • Drive the evolution of analytics capabilities by evaluating emerging BI tools and methodologies to enhance decision-making speed and accuracy.
• • Communicate complex data insights to non-technical audiences through polished presentations, executive summaries, and visual storytelling techniques.
• • Support strategic planning by delivering data-backed recommendations that impact resource allocation, product roadmap prioritization, and go-to-market initiatives.
• • Maintain deep familiarity with cloud infrastructure, Kubernetes environments, and enterprise data integrations to ensure accurate sourcing and interpretation of platform metrics.
• • Ensure all BI outputs are aligned with corporate data governance policies and security standards for sensitive operational data.
• • Act as a trusted advisor to leadership by proactively identifying emerging patterns and risks before they impact business performance.
• • Continuously refine dashboard functionality and data pipelines based on stakeholder feedback and evolving business needs.
• • Contribute to the AI-driven innovation agenda by identifying opportunities where predictive analytics can enhance operational intelligence.