Estimators typically work with an average performance of the cost codes over time. However, using averages of data without considering the range and statistical outliers skews the results. To use the available data correctly, factors such as geography, cost code mix, allowance for pre-assembly, and type of construction need to be considered to make confident decisions based on more than just averages. Good estimators do this intuitively; EAE® allows those “gut feels” to be supported by verifiable data. EAE® allows jobs to be identified according to a number of criteria. First, jobs are selected based on relevant criteria (size, type of work, crew, etc.) From there, an analysis of the estimate vs. final performance can be made in terms of hours or cost, including the following:

1. Data for estimated vs. actual hours or cost per cost code, per job in the category set selected
2. Graphical comparison of estimated vs. actual hours or cost, overall and per cost code
3. Comparison of cost code performance between all jobs within the selected categories, and a particular job in the same set
4. Interquartile range (IQR) analysis of the cost codes in the job set, which gives the spread of the selected jobs’ performance and the position of a particular job within that set
5. Timeline charting to track changes over time
6. Risk analysis based on the historical differences between jobs

Connection to JPAC® and SIS®

The analysis of data for estimation accuracy can be enhanced by improving the quality of the data. The data analysis is only as good as the data upon which it is based. The closer the measurement is to the actual work, the more useful it will be as input to the estimation process. JPAC® measures labor productivity, and provides feedback from the field on a regular basis of Construction Put in Place (CPIP). JPAC® can provide invaluable information to estimation about the actual installation efforts. Using trend monitoring, estimators can review what impacted the job at various points and take those impacts into account for a similar estimate. SIS® measures the obstacles that hamper the field’s short interval scheduling. These causes for productivity loss could become magnified in the view of JPAC®, and can also be useful for estimation to understand what daily obstacles should be considered on similar jobs.

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