Product & Solution Design
In my client-facing roles, I’ve led numerous discovery and design sessions to uncover business needs, align stakeholders, and translate requirements into actionable product roadmaps. I specialize in bridging the gap between technical teams and business users—turning complex data and analytics challenges into clear product strategies. From defining MVP scope to prioritizing features and designing scalable solutions, I ensure projects are driven by both user insights and measurable business impact. My experience spans data analytics platforms, workflow optimization, and enterprise system integrations, where I’ve consistently delivered roadmaps that balance near-term wins with long-term vision.
Discovery & Problem Framing
Product Management: Conduct stakeholder interviews, discovery sessions, and workshops to identify pain points, user needs, and business objectives. Define the problem space clearly and align it with organizational strategy.
Data Analytics: Assess data availability, quality, and sources. Identify where gaps exist (e.g., missing metrics, siloed systems). Translate business questions into measurable data requirements.
Research & Opportunity Analysis
Product Management: Analyze competitors, market trends, and user personas. Prioritize opportunities by impact vs. effort and ensure they ladder up to the product vision.
Data Analytics: Perform exploratory data analysis to validate hypotheses. Use descriptive analytics to uncover current-state performance and identify leading indicators for potential improvement.
Ideation & Solution Design
Product Management: Facilitate design thinking sessions to co-create potential solutions. Outline multiple solution paths and evaluate tradeoffs. Draft high-level product concepts.
Data Analytics: Translate use cases into analytical workflows or models (e.g., dashboards, predictive models, or reporting frameworks). Design data flows and integration points needed to enable the solution.
Roadmapping & Prioritization
Product Management: Define the MVP (Minimum Viable Product) and sequence features into a roadmap that balances quick wins with long-term scalability.
Data Analytics: Identify critical datasets and models for MVP. Define phased deliverables (e.g., proof-of-concept dashboards, pilot analytics use cases) that can deliver value early while building toward advanced capabilities.
Detailed Design & Prototyping
Product Management: Translate requirements into detailed user stories, acceptance criteria, and wireframes. Collaborate with UX/UI designers and engineering to validate feasibility.
Data Analytics: Build data models, define KPIs/metrics, and develop prototypes in BI tools (e.g., Power BI, Tableau, Looker). Validate against user workflows and iterate based on feedback.
Development & Iteration
Product Management: Manage the agile process—running sprint planning, standups, and reviews. Ensure alignment across engineering, analytics, and stakeholders while tracking progress against roadmap goals.
Data Analytics: Implement ETL pipelines, create validated datasets, and refine dashboards/models. Test performance, accuracy, and usability with real-world data.
Testing & Validation
Product Management: Coordinate UAT (User Acceptance Testing) with stakeholders, ensuring that the solution meets both business and user expectations. Track bugs, usability issues, and feature gaps.
Data Analytics: Validate data integrity, accuracy of calculations, and alignment with business definitions. Perform scenario testing to ensure models hold under edge cases.
Deployment & Change Management
Product Management: Launch the MVP, define success metrics, and implement change management strategies to drive adoption. Provide training, documentation, and communication plans.
Data Analytics: Deploy data pipelines and dashboards to production. Monitor adoption, performance, and system health. Enable role-based access and ensure compliance/security standards.