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Level: Intermediate
TCM Section(s):
10.1. Project Performance Assessment
10.4. Project Historical Database Management
Venue: 2020 AACE International Conference & Expo
Abstract: Effective project cost estimate preparation depends upon having reliable, competitive reference data. The data is used both for inputs to the estimate (i.e., the resources and their costs) and to develop metrics (usually ratios or factors that reflect cost estimating relationships or CERs) for quantitative validation (a quality assurance process) of the estimate outputs. Metrics are also used to benchmark and guide improvement of capital project system performance. Historical data collection, analysis and use in project and project system benchmarking have been shown to correlate with better project outcomes.To achieve a reliable and useful data process, one must apply reliable methodologies to facilitate proper data collection and management.
This paper addresses two topics. First, it addresses database development including a process for data collection using a standard breakdown structure at an appropriate level of detail for use in benchmarking metrics development. Specifically, it outlines the use of the International Construction Measurement Standard (ICMS). [1] although other structures can be used. The database aspect also addresses an effective methodology for data collectionand maintenance including data conditioning and normalization and capturing other project attributes including key quantities. This process can and should be used for both cost estimates and actual project data.Second, the paper defines the use of a key metric called “unit price” for estimate development reference and for estimate benchmarking. Unit cost data, i.e., ratios of cost to key quantities, is perhaps the most common metric used in cost estimates of all classifications. There are many metrics that can be used, but unit prices are often of most interest to estimators and readily understood. Particularly for contracts based on unit pricing for which the client has no insight into hours or cost breakdowns within the units. A more robust set of metrics and rounded estimate validation process is covered in a draft AACE RP currently in review.
TCM Section(s):
10.1. Project Performance Assessment
10.4. Project Historical Database Management
Venue: 2020 AACE International Conference & Expo
Abstract: Effective project cost estimate preparation depends upon having reliable, competitive reference data. The data is used both for inputs to the estimate (i.e., the resources and their costs) and to develop metrics (usually ratios or factors that reflect cost estimating relationships or CERs) for quantitative validation (a quality assurance process) of the estimate outputs. Metrics are also used to benchmark and guide improvement of capital project system performance. Historical data collection, analysis and use in project and project system benchmarking have been shown to correlate with better project outcomes.To achieve a reliable and useful data process, one must apply reliable methodologies to facilitate proper data collection and management.
This paper addresses two topics. First, it addresses database development including a process for data collection using a standard breakdown structure at an appropriate level of detail for use in benchmarking metrics development. Specifically, it outlines the use of the International Construction Measurement Standard (ICMS). [1] although other structures can be used. The database aspect also addresses an effective methodology for data collectionand maintenance including data conditioning and normalization and capturing other project attributes including key quantities. This process can and should be used for both cost estimates and actual project data.Second, the paper defines the use of a key metric called “unit price” for estimate development reference and for estimate benchmarking. Unit cost data, i.e., ratios of cost to key quantities, is perhaps the most common metric used in cost estimates of all classifications. There are many metrics that can be used, but unit prices are often of most interest to estimators and readily understood. Particularly for contracts based on unit pricing for which the client has no insight into hours or cost breakdowns within the units. A more robust set of metrics and rounded estimate validation process is covered in a draft AACE RP currently in review.