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4.3.1.5 Common Data Metrics for Project Management - Coggle Diagram
4.3.1.5 Common Data Metrics for Project Management
The Benefits of Analyzing Data
Improved Decision-Making
Data guides better decisions,
Improves processes,
identifies problems.
Example:
Analyzing customer buying patterns helps optimize product orders and meet user needs.
Process Refinement
Project trackers provide:
insights into tasks,
escalations,
issues to pinpoint areas for improvement.
Example:
Identifying where processes are slowing down allows you to focus efforts and resolve issues efficiently.
Definition:
Data
:
Information gathered on various aspects of the project.
Metrics
:
Measurements used to track
productivity,
quality,
engagement.
Analytics
:
The process of analyzing metrics to uncover patterns,
predict outcomes,
optimize performance.
Productivity Metrics
Definition
:
Measures progress and output over time to evaluate project effectiveness.
Example
Tasks and Milestones
:
milestone achievement
to monitor project status.
task completion
On-Time Completion Rates
:
How well deadlines are being met.
Duration
:
time taken for tasks and milestones
to improve future timeline estimates.
Projections
:
Use current trends to predict future outcomes
such as productivity, costs, and performance.
Performance and Velocity
:
how efficiently the team completes tasks over time.
Quality Metrics
Definition
:
Measures outcomes to ensure they meet acceptable standards.
Examples:
Number of Changes
:
Tracks project deviations from the original plan,
indicating potential risks.
Issues
:
Identifies problems impacting task completion.
Cost Variance
:
Compares budgeted and actual costs
to assess financial planning accuracy.
Happiness and Satisfaction Metrics
Purpose
:
Measures user satisfaction with the project’s product or service.
Examples:
Customer Satisfaction Scores
:
Combined-metric reflecting user satisfaction, across areas like appearance, usability, and recommendation likelihood.
User Feedback
:
Tracks revenue,
customer retention,
product returns to gauge user sentiment.
Adoption and Engagement Metrics
Adoption Metrics
: Output is accepted and used.
Conversion Rates
Time to Value (TTV)
Onboarding Completion Rates
Frequency of Purchases
Providing Feedback
Engagement Metrics
: Monitor how actively a output is used.
Daily Usage Rates
Order Tracking
Customer and Team Interaction
Monitoring Stakeholder and Team Engagement
Track meeting participation, email responses, and communication frequency to assess involvement.
Poor engagement can lead to unmet expectations and project delays.