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Estimate Hours Used Report

Compare estimated labor hours to actual hours to evaluate estimating accuracy.

Accessing the Report

Reports > General > Estimate Hours Used

Key Metrics

MetricDescription
ProjectProject name
Estimated HoursHours in estimate
Actual HoursHours logged
VarianceActual - Estimated
Variance %Percentage over/under

Available Filters

FilterDescription
Date RangeProject date filter
DivisionBusiness unit
Opportunity TypeProject category
Project ManagerFilter by PM

Understanding Variance

Positive Variance (Over Estimate)

Actual > Estimated = Over budget

Reasons:

  • Underestimated scope
  • Unforeseen conditions
  • Efficiency issues
  • Scope creep

Negative Variance (Under Estimate)

Actual < Estimated = Under budget

Reasons:

  • Conservative estimate
  • Improved efficiency
  • Scope reduction
  • Incomplete tracking

Variance Percentage

Variance % = ((Actual - Estimated) ÷ Estimated) × 100

Analysis by Category

By Project Type

Compare accuracy across types:

  • Some types harder to estimate
  • Adjust markup accordingly
  • Improve estimating methods

By Estimator

If tracked:

  • Identify training needs
  • Calibrate individuals
  • Share best practices

By Size Range

Small vs. large projects:

  • May have different accuracy
  • Adjust approach by size
  • Set appropriate contingency

Improving Estimates

Track Patterns

Look for consistent issues:

  • Always over on specific types
  • Certain phases underestimated
  • External factors

Adjust Factors

Based on historical data:

  • Increase hours for problem areas
  • Add contingency factors
  • Update labor rates

Feedback Loop

Share results with estimators:

  • Show variance data
  • Discuss causes
  • Implement improvements

Benchmarks

Variance RangeRating
-5% to +5%Excellent
-10% to +10%Good
-15% to +15%Acceptable
Beyond ±15%Needs improvement

Export Options

Click Export CSV to download:

  • Variance data
  • For estimating calibration
  • Historical tracking

Tips

  • Review completed projects only
  • Compare similar project types
  • Investigate large variances
  • Update estimates from learnings