Site Performance Analytics Product Owner

Beschreibung

Career Area:

Job Description:

Your Work Shapes the World at Caterpillar Inc.

When you join Caterpillar, you're joining a global team who cares not just about the work we do – but also about each other. We are the makers, problem solvers, and future world builders who are creating stronger, more sustainable communities. We don't just talk about progress and innovation here – we make it happen, with our customers, where we work and live. Together, we are building a better world, so we can all enjoy living in it.

Role Definition

Owns the end-to-end design, definition, validation, and adoption of site performance dashboards and KPIs, ensuring that users across different personas (executive, operational, frontline) can effectively manage and improve productivity, utilization, safety, health, and operational efficiency through actionable insights.

This role is accountable for persona-driven user flow design, KPI logic ownership, dashboard validation, and adoption. It requires hands-on experience in building dashboards that drive real operational decisions, not just reporting or visualization.

Candidates must demonstrate direct, hands-on experience creating dashboards that improve site productivity, utilization, safety, or operational outcomes.

Responsibilities

• Designing and structuring persona-based dashboard user flows (Executive → Operational → Actionable), ensuring seamless drill-down from high-level summaries to root-cause insights and corrective actions.
• Creating dashboards that are decision-oriented, role-specific, and actionable, eliminating non-value-adding or unused views.
• Defining and owning site-level KPIs, including logic, formulas, thresholds, and assumptions aligned to actual site operations.
• Taking final accountability for KPI correctness, resolving conflicting definitions and misleading metrics without dependency on data/BI teams.
• Validating dashboards across data, logic, and visualization layers, ensuring alignment with real site behaviour and operational conditions.
• Identifying and resolving data gaps, inconsistencies, and mismatches, establishing a reliable single source of truth.
• Driving dashboard adoption across sites, dealers, and stakeholders, ensuring dashboards are actively used for decision-making.
• Generating insights to highlight performance loss, inefficiencies, and abnormal behaviour, enabling actionable improvements.
• Owning requirements clarity, delivery quality, velocity, and validation, ensuring outputs meet operational expectations.
• Reviewing and validating outputs from data engineering and BI teams for accuracy, usability, and actionability.

Degree Requirement

Degree required

Skill Descriptors

Industry Knowledge

Level Extensive Experience:
Knowledge of site operations, fleet performance, productivity drivers, utilization patterns, safety metrics, and operational constraints; ability to translate operational realities into meaningful KPIs and actionable dashboards.

Level Extensive Experience:
• Applies deep understanding of site operations to define relevant KPIs.
• Connects operational behaviours with performance metrics and dashboard signals.
• Evaluates impact of operational practices on KPI accuracy and interpretation.
• Educates stakeholders on productivity, utilization, uptime, and safety drivers.
• Interprets trends and identifies operational inefficiencies.
• Builds KPI frameworks aligned to real-world site conditions.

Problem Solving

Knowledge of structured problem-solving approaches to identify, diagnose, and resolve performance issues using data and operational context.

Level Extensive Experience:
• Diagnoses root causes of performance issues using dashboards and data.
• Identifies inconsistencies in KPIs and analytics outputs and drives correction.
• Synthesizes multi-source data into actionable insights.
• Develops solutions to improve KPI accuracy and data reliability.
• Resolves complex issues impacting operational decision-making.
• Establishes best practices for analytics-driven problem solving.

Software Development Life Cycle

Knowledge of SDLC processes; ability to translate dashboard and KPI requirements into structured development outputs.

Level Working Knowledge:
• Translates business needs into structured dashboard specifications.
• Works effectively with development teams across lifecycle stages.
• Understands dependencies between requirements, design, and delivery.
• Supports validation and refinement during development cycles.
• Ensures alignment between design intent and implementation.
• Contributes to iterative improvement processes.

Software Product Testing

Knowledge of testing approaches to ensure dashboard accuracy and usability.

Level Working Knowledge:
• Validates dashboards against real site conditions.
• Ensures KPI calculations are consistent across scenarios.
• Identifies deviations between expected and actual outputs.
• Supports testing for usability and decision accuracy.
• Verifies dashboards enable correct operational decisions.
• Contributes to validation prior to deployment.

Application Development Tools

Knowledge of BI and analytics tools; ability to evaluate dashboards and support implementation improvements.

Level Working Knowledge:
• Uses tools such as Power BI for dashboard validation and review.
• Understands tool strengths, limitations, and design implications.
• Collaborates with engineering teams on implementation improvements.
• Evaluates effectiveness of dashboards in delivering insights.
• Supports enhancements to analytics tools and outputs.
• Ensures tools accurately represent operational data.

Artificial Intelligence

Knowledge of applying AI/analytics insights to operational decision-making.

Level Working Knowledge:
• Interprets predictive or anomaly-based insights for operational use.
• Aligns AI outputs with business and site outcomes.
• Validates AI-driven insights against real-world behaviour.
• Uses data patterns to identify early performance issues.
• Supports integration of advanced analytics into dashboards.
• Ensures AI outputs are practical and actionable.

Programming

Knowledge of KPI logic, data transformations, and debugging analytical implementations.

Level Working Knowledge:
• Understands KPI calculation logic and data transformations.
• Supports debugging of KPI and dashboard issues.
• Reviews implementation logic for correctness.
• Collaborates with developers to refine solutions.
• Ensures alignment between designed KPIs and system outputs.
• Interprets analytics pipelines and transformations.

Technical Troubleshooting

Knowledge of troubleshooting across data, logic, and dashboard layers.

Level Extensive Experience:
• Identifies root causes of inaccurate dashboards or KPIs.
• Resolves issues across data, transformation, and visualization layers.
• Drives correction of inconsistencies affecting decision-making.
• Ensures reliability of analytics in operational environments.
• Prevents recurrence through validation and governance.
• Leads resolution of high-impact analytics issues.

Posting Dates:

Caterpillar is an Equal Opportunity Employer. Qualified applicants of any age are encouraged to apply

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