4 common problems with project portfolios.

Sudden project failures, unacknowledged business dependencies, cumbersome project-management frameworks and botched set-up:

  1. Projects fail slowly then fast.

  2. Dependencies on the business and between projects are after-thoughts.

  3. Companies mandate fixed and bulky project-management frameworks and life-cycles.

  4. Setting-up the portfolio is botched. Portfolio management never catches up with the latest project changes.

How

This library of tools is intended to address each of these.

  1. Projects fail slowly then fast.
  • Machine learning allows project success prediction and anomaly detection
  1. Dependencies on the business and between projects are after-thoughts.
  • Tracking the portfolio in a graph database like @neo4j brings relationships into the foreground
  1. Companies mandate fixed and bulky project-management frameworks and life-cycles.
  • Build a smaller, relevant portfolio framework by selecting some service modules, and tuning them to the business domain by text-mining project documents
  1. Setting-up the portfolio is botched. Portfolio management never catches up with the latest project changes.
  • Deploy portfolios in GitHub to re-use your best working-practice before whilst tracking every change you need to make.

Getting started

  • Fix the worst problem, not all of them.

  • A portfolio team can fix it themselves.

  • There are so many Open Source project-management tools that have matured.

  • There’s no need for an all-in, end-to-end integrated system until the team knows exactly what it needs.

  • Deploying your own portfolio is the best way of getting to know the projects inside-out.

Summary

Sudden project failures business dependencies , cumbersome frameworks botched set-up
project success prediction Graph database Modular project frameworks Framework deployment