Adopting Big Data to Forecast Success of Construction Projects: A Review

Sunder Narayan, Hai Chen Tan

Research output: Contribution to journalArticlepeer-review

7 Citations (Scopus)


Forecasting the success probability of a construction project is a critical activity in the ever expanding construction industry. The present trend of forecasting is focused on cost (budgeting) and time (scheduling) i.e. the two of three apex of iron triangle. However, increasing demands of stakeholders and generation of large amount of data, owing to the new information and communication system implemented, have made the researchers look at success beyond iron triangle and tools currently adopted for its measurement. This paper starts with an extensive literature review on project success criteria, and the need for forecasting project success with considerable accuracy. The paper investigates the concept of forecasting in various industries including construction, new challenges faced in forecasting, and the concept of Big Data. It tries to bridge the gap between the three aspects namely project success criteria, forecasting and tool required for the same. It then delves into Big Data in various industries and its potential to facilitate accurate forecast of the success of construction project, which has hitherto not been sufficiently addressed. The paper then looks at the possible challenges identified such as data veracity, connectivity, storage etc. and their solutions in the adoption of Big Data for the purpose. The paper concludes by suggesting further research in bridging of the gap in forecasting the project success and its benefits and suggests looking at Big Data as tool. A model to predict project success of construction project using Big Data is suggested as a future work.
Original languageEnglish
Pages (from-to)132-143
Number of pages12
JournalMalaysian Construction Research Journal
Issue number1
Publication statusPublished - 27 Aug 2019


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