About
Work
Blog
Projects

Shega Media — Profitability Dashboard

An internal profitability dashboard centralizing financial data to improve forecasting and project viability analysis.Next.js · PostgreSQL · Node.js
+15%
forecast accuracy
1
source of truth for finance data
Shega Media — Profitability Dashboard
November 1, 2024

Overview

Architected and delivered an internal dashboard for Shega Media & Technologies to calculate project viability and financial performance.

What I built

  • Data pipelines to centralize costs and revenue into a single source of truth.
  • Visualizations and KPIs for project-level profitability and forecasting.
  • Exportable reports for executive review.

Impact

Centralizing financial data improved C-level forecast accuracy by over 15% and accelerated decision-making.

Technologies used

  • Next.js, React
  • PostgreSQL
  • Node.js

Outcome

A production-ready dashboard used by stakeholders to assess project viability and financial performance.

Problem

Finance and delivery teams lacked a single source to evaluate project profitability. Spreadsheets were out-of-date and inconsistencies in cost allocation led to poor forecasting.

Solution

I built an internal profitability dashboard that combined automated ingestion of billing and cost data with an intuitive UI for analysts and executives to inspect project-level metrics.

Architecture

Text
Ingest (ETL) -> Central Postgres (normalized schemas) -> API (Next.js) -> Frontend (Reports & Visualizations)

Key components

  • ETL jobs to import billing and time-sheet data
  • Normalized data model for costs, revenues, and allocations
  • Forecasting module that projects revenue and costs based on historical trends
  • Role-based UI with exportable investor-style reports

Features

  • Interactive waterfall charts and unit-economics breakdowns
  • Scenario mode for 'what-if' projections
  • Scheduled exports and executive summary emails

Screenshots / Media

Shega profit 1
Shega profit 2
Shega profit 2
Shega profit 2

Metrics

  • Improved forecast accuracy by over 15%
  • Reduced manual reconciliation time by ~60%

Lessons learned

  • Establish canonical data boundaries early — it saved time when integrating external billing sources.
  • Presenting clear KPIs to stakeholders changed behavior quicker than complex models.

Next steps

  • Add more 'what-if' scenarios and integrate with accounting systems for automated month-end reconciliation.