Role: Project Manager
Context: Large-scale technical consultancy engagement requiring coordination across engineering, finance, and delivery teams
🔪 Challenge
The project manager needed to:
- Track work-in-progress against project milestones and budgets
- Report progress to multiple stakeholders—including engineering leads and finance
- Access consistent data on effort, cost, and risk exposure from multiple systems (e.g. time tracking, ERP, proposal documents)
Problems included:
- Manual collation of data from spreadsheets and SharePoint files
- Inconsistent naming conventions and project codes across systems
- Difficulty reconciling time bookings with actual budgeted work
- Misalignment between proposal expectations and delivery reporting
“I spent hours each week trying to make sense of data from five different places—and still couldn’t guarantee it was accurate.”
🚀 Solution
The Data Engineering team:
- Built a Project.Value and Project.Details_Plus view, aligning cost, time, and delivery data into a single, consistent model
- Created clear mappings between proposal estimates, ERP project IDs, and timesheet codes
- Implemented automated updates via scheduled pipelines—removing manual reporting
- Integrated key fields such as PRU, Risk Status, and Estimated vs Actual Cost into self-serve dashboards
- Provided documentation and support through the KnowHow portal and regular walkthroughs
🌟 Outcome
- ✅ Saved over 10 hours per month in manual data prep
- ✅ Reduced reporting errors and duplication
- ✅ Enabled earlier identification of budget risks and scope changes
- ✅ Increased stakeholder confidence in project data
- ✅ Freed up time to focus on delivery, not data wrangling
“Now I spend my time leading the project—not chasing down data or second-guessing the numbers.”
📊 Key Data Engineering Value Areas
- Alignment of disparate data sources into one unified view
- Automation of data preparation, reducing human error
- Access to self-serve, timely data without needing IT intervention
- Support through documentation, QA, and collaboration
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Have a project challenge you’d like to explore? Reach out to the Data Engineering team—we’re here to help.