Proactive Project Control Using Productivity Data and Time Series Analysis

Abstract

Managing construction projects requires constant monitoring of project performance and follow-up schedule updates. With updated project performance data, project managers can take corrective actions in a timely manner, thereby mitigating any negative impacts on both the cost and schedule of a project. Among project performance data, productivity data from the field plays a key role in evaluating and predicting project performance in terms of cost and schedule. Despite its importance, most contractors do not take full advantage of the benefits of analyzing productivity data and proactively control a project. Although computerized systems are commonly used in the construction industry today, few project managers make full use of on-site productivity data to accurately predict future project performance. As a result, schedule delays and cost overruns are detected at a much later stage than they should be, causing costly fixes and overtime work. This paper presents the preliminary results of an on-going research that aims to develop a new approach to achieve proactive project control based on better prediction of project performance which utilizes time series analysis techniques with integrated historical productivity data and on-going field productivity. This research proposes a new methodology, named “Pro-Con”, that extends the effectiveness of using productivity data that exists in most construction companies’ computer systems. The paper presents the potential use of time series analysis in the construction domain to predict performance of a project in progress using integrated productivity data. Two case studies are presented to explain the methodology. The Pro-Con concept enhances field data processing and supports decision making for projects by incorporating up-to-date productivity data into existing project control systems.