How to Get a Job For Project Managers

Learn how to write resume and interview

Leadership for Project Managers

Learn how to lead and drive project success.

Project Management with AI

From a beginner to project management professional.

Agile Project Management and SCRUM with AI

Learn to run Scrum and Agile with AI.

vanity metric

A metric that looks impressive on the surface but offers little or no actionable insight to guide decisions.

Key Points

  • Emphasizes appearance over insight; it seems positive but is not decision-useful.
  • Often lacks a clear link to outcomes, customer value, or strategic objectives.
  • Can mislead stakeholders and hide real problems if used to claim success.
  • Prefer actionable, outcome-focused indicators; if tracked, use vanity metrics only as context.

Example

An Agile team celebrates a spike in page views for a new feature announcement. However, activation rate, task completion in the feature, and retention do not improve. Page views alone are a vanity metric because they do not show real user value or inform next steps.

PMP Example Question

Which metric is most likely a vanity metric for an Agile team evaluating a recent release?

  1. Total page views of the release announcement
  2. Lead time from commit to production
  3. Customer retention rate 30 days after release
  4. Defect escape rate to production

Correct Answer: A — Total page views of the release announcement

Explanation: Page views can look impressive but do not indicate behavior change or delivered value, and they do not directly guide decisions.

AI Systems with Claude, for Scrum Masters and Project Managers

Most AI pilots in project management do not fail on the model. They fail because somebody pointed the thing at a decision instead of at a task. This course is built around that distinction, and around the work that follows once you get it right.

Eight teaching sections, taught against one running project from the first lecture to the last. You watch a system get built, then you build the same one against your own sprint. Nothing here is a demo that works only on the example.

You finish with five working systems and you keep them. The sprint report machine turns your board export and standup notes into the report you currently write by hand. The retro intelligence system tells you what the team keeps saying, not just what it said this time. The stakeholder comms engine drafts the update in the register the audience expects. The backlog health monitor flags the quiet decay nobody has time to check for. The risk and dependency tracker follows the chains that actually bite.

Seventy-six working files ship with it, across four sections, so every system is built against real sprint data rather than material invented for a slide. Four sprints of retrospectives, board exports, standup notes, backlog and risk data.

Explore the Course


Build the Sprint Reporting System, Not Another Prompt

AI Systems with Claude is our own course for Scrum Masters and Agile Project Managers, taught against one running project across eight teaching sections. You build five working systems and keep them: the sprint report machine, the retro intelligence system, the stakeholder comms engine, the backlog health monitor, and the risk and dependency tracker. Direct from HK School of Management and Technology, not on Udemy.

See What Is Included