EkoSuryahadi
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AI & MLEPCLIVE

PMO Intelligence System

Turns project-control data into portfolio-level early warnings, budget visibility, and executive-ready PMO reporting.

Scenario model estimates USD 750K-1.2M annual value for a 10-project portfolio when delays are reduced earlier.

PythonFastAPIReactPostgreSQL

The Challenge

PMO leaders need a portfolio view that identifies schedule, budget, and delivery risk before monthly reports become historical evidence.

The Solution

Created an intelligence layer for portfolio health, delay prediction, budget control, and executive reporting workflows.

Key Features

  • Portfolio risk overview
  • Schedule and budget health
  • AI risk flags
  • Management reporting views

Business Impact

  • Frames an on-time delivery target around measurable portfolio signals
  • Gives executives a clearer view of project exposure
  • Connects ROI narrative to schedule-risk reduction

Lessons Learned

  • Portfolio analytics should start from business questions, then map back to data.
  • A PMO tool must be explainable enough for non-technical decision makers.

Project Proof

Designed placeholder for architecture and evidence.

Real screenshots can be added later. For now, this proof layer documents the workflow, stack shape, and delivery logic behind the case study without inventing unavailable assets.

Architecture Summary

Created an intelligence layer for portfolio health, delay prediction, budget control, and executive reporting workflows.

Workflow

01

Frame the operational question

02

Prepare and validate source data

03

Portfolio risk overview

04

Frames an on-time delivery target around measurable portfolio signals

Stack Grouping

Data & ML

Python

Application Layer

FastAPIReact

Infrastructure

PostgreSQL

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