Data Analytics & Cost Benchmarking

Data analytics and Cost Benchmarking are the often complex process of examining big data to uncover information — such as hidden patterns, correlations, market trends and customer preferences — that can help organizations make informed business decisions. On a broad scale, data analytics technologies and techniques give organizations a way to analyze data sets and gather new information. Business intelligence (BI) queries answer basic questions about business operations and performance. Big data analytics is a form of advanced analytics, which involve complex applications with elements such as predictive models, statistical algorithms and what-if analysis powered by analytics systems.

Organizations can use data analytics systems and software to make data-driven forecasts that can improve cost items-related outcomes. The benefits may include more accurate assessments, customer personalization and improved operational efficiency. With an effective strategy, these benefits can provide competitive advantages for Cost Estimating organizations.

Project Cost Benchmarking combined with data analytics together represent the most powerful method to make accurate the process of Project Cost Estimation.


Cost estimator Professionals together with data analysts, data scientists, predictive modelers, statisticians and other analytics professionals collect, process, clean and analyze growing volumes of structured transaction data as well as other forms of data.

Project Data Analytics and Cost Benchmarking process takes normally three common ways:

1.- Pre-investment cost and schedule benchmarking, which includes the due diligence reviews for financial investment purposes (ahead view).

2.- Project performance benchmarking, to evaluate the cost and schedule performance of projects (backwards view)


For KPI’s Ranges for Decision Make

3.- Project Components Costs / Weights/ Metrics & Norms forecasting.

Costs / Weight s/ Metrics & Norms for next estimation

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