top of page

Data Model & Reporting Needs Assessment

Project Overview

 

A cross-functional product team was preparing to scale its platform capabilities but lacked a unified approach to managing data, reporting, and stakeholder needs. I led a comprehensive needs assessment to align priorities across business units, define a future-state data model, and translate requirements into an actionable product backlog.

The Challenge

​

  • Teams had fragmented reporting requirements with inconsistent data definitions and ownership

  • Development resources were blocked by unclear business logic and a lack of documented processes

  • Stakeholders didn’t have visibility into data governance or confidence in existing reports

  • The product lacked a scalable data structure to support future automation, reporting, or integrations

The Approach

​

  • Facilitated a series of working sessions with senior leadership, product owners, and business leads to surface pain points and strategic goals

  • Conducted a detailed AS-IS analysis of data flows and usage across multiple departments

  • Designed a future-state data model based on aligned definitions, entity relationships, and user needs

  • Created workflow diagrams and reporting use cases to anchor priorities and drive decision-making

  • Developed a refined backlog with user stories and acceptance criteria to guide development across sprints

Key Deliverables

​

  • Final State Data Model: Defined entities, attributes, and relationships mapped to user and system workflows

  • AS-IS Process & Reporting Inventory: Documentation of existing reports, users, and known limitations

  • Workflow Diagrams: Visual representation of how data is captured, processed, and consumed across systems

  • Backlog & Story Library: Clear, testable user stories with acceptance criteria to guide delivery

  • Governance Recommendations: Clarified data ownership, update cycles, and metrics definitions

The Impact

​

  • Unified the product and leadership teams around a shared understanding of data priorities

  • Improved developer efficiency by clarifying data dependencies and aligning technical and business needs

  • Created the foundation for scalable, governed, and user-aligned reporting across departments

  • Reduced friction by turning abstract data strategy into concrete delivery plans with clear next steps

What Made This Work

​

By pairing technical modelling with business-first facilitation, I was able to bridge the gap between data strategy and delivery, helping teams move from confusion to clarity and enabling progress without needing everything to be perfect up front.

bottom of page