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Progress tracking

As explained in AI for Everyday IT

Progress tracking is the systematic monitoring of movement toward a goal over time.

Progress tracking turns goals into a routine view of movement, risks, and needed support. Managers can review progress during one-on-ones, identify early warning signs, and adjust unrealistic goals before the end of a review cycle. section 15.3.3

A practical tracking setup can:

  • Record objectives, actions, metrics, deadlines, milestones, status, feedback, incidents, and KPI scores. section 16.1.3
  • Use trends to support realistic adjustments rather than treating tracking as an end-of-cycle surprise. section 15.3.3

Example: performance improvement dashboard

Ask an AI assistant to create an Excel dashboard for a senior Database Administrator’s performance improvement plan. Include objectives, actions, measures, deadlines, milestones, current status, KPI scores, bar graphs, and an incident log. Let the assistant ask for missing details, then review and tailor the resulting template; the generated file may need additional calculations. section 16.1.3

How AI for Everyday IT covers it

How deep it goes
Provides prompt and dashboard procedures, but leaves predictive usefulness dependent on solid data and some spreadsheet tailoring.
Examples
Demonstrates spreadsheet dashboards, KPI bar graphs, milestone logs, incident records, and AI-generated tracking templates.
What it assumes
Assumes defined goals and performance measures while teaching users to clarify objectives, milestones, actions, and deadlines.
What you can do after
Operate an Excel-based dashboard to measure goals, flag risks, review trends, and refine tracking fields.
How it connects
Connects SMART goals, one-on-ones, performance improvement plans, dashboards, KPIs, and performance feedback.

Related concepts

This explainer was generated by Manning's knowledge graph from the text of AI for Everyday IT. The section links point to the parts of the book it draws on.