Assessing the Influence of Automated Data Analytics on Cost and Schedule Performance

This article assesses the combined influence of information integration and automated data analytics on project performance. To this end, retrospective data on 78 completed projects, with a total installed value of $8 billion, was collected. The data collection effort characterized, for each project, the level of internal and external information integration. Information integration was assessed as the seamlessly interoperable sharing of data produced from a work function with other functions/stakeholders so that no manual data transfer was required. Also, the level of automated data analytics, understood as the full automation of the data analysis function after input data are entered, was also characterized on a project basis. Then, non-parametric statistical techniques were used to assess the impact of such functions on cost and schedule performance. The statistical analysis was also stratified by project type, e.g. greenfield and brownfield, additions, and modifications or shutdowns. Overall, projects with a sophisticated degree of information integration and automated data analytics can control their projects with more reliable information and in a proactive manner so that informed decisions can be timely made on behalf of the project and the organization.