IEM Roadmap:
Building the Methodology in the Open
A method for identifying and measuring decision-risk caused by incomplete, disconnected, or low-confidence delivery data. I publish it as it takes shape, including the results that weren’t flattering — a full audit against 29 project-management standards scored just over 50 out of 100, which is the point of running it.
The Architecture
What It Covers
Program & Portfolio Data Integrity
Measures delivery-data gaps across projects, traces each discrepancy to its root origin, and scores reporting integrity 0–100 on evidence alone — no self-assessment, no narrative.
Field-tested, not finished. A full audit against 29 project-management standards scored just over 50 out of 100 and surfaced 4 genuine gaps. Two further audits ran on live client-engagement data. 9 of the 29 standards are packaged as audit-cited checklists; the remaining 20 are not.
Read the founding white paperAI Security Lab
Security for AI and AI for security — red-teaming AI systems and running AI-assisted security operations — tracked on their own dedicated page.
Go to AI Security LabWhat was actually tested in production — not what’s planned, not what’s theoretical.
Validated Against Real Audits
- A real audit of a live, fast-moving client project caught genuine errors in the evidence base: mismatched costs, conflicting dates, a missing risk entry.
- A full audit against 29 project-management standards scored the portfolio just over 50 out of 100 and surfaced 4 genuine gaps. The score measures the evidence, not the team — around 50 is what an unaudited portfolio typically looks like, which is the reason to run it.
- Two further audits ran on live client-engagement data — one against the client’s own process, one against outside standards.
- 9 of the 29 standards are packaged as audit-cited checklists. The other 20 are not yet.
Where It Stands
Built and field-tested. Audit engine proved against 29 standards and live client data across three real audits.
In progress. Founding white paper published; a practitioner article on delivery-data integrity in draft.
The Road Ahead
Engine Field-Validated
Built and proved the audit engine against 29 real project-management standards and live client data. Packaged as a ready-to-install tool.
Publish the Body of Work
Foundational white paper published. Regular LinkedIn series and a practitioner article on PMO data integrity, in draft for ProjectManagement.com.
Validate in the Field
Conference talks, field-observation case studies, and published patterns — including potential PMI webinars and blog contributions.
Codify the Discipline
A long-form reference, and adoption of the methodology beyond the founding domain.