Data Mining tools and techniques in construction

by Knowledge Areas: State of the Art situation



By Danilo Arba

Milan, Italy




Managing Project Controls, both from an owners perspective as from a contractor organization, is commonly, and as per the Compendium of the Guild of Project Controls[1], divided in 12 modules that make excellent use of Information technologies, generating an incredible amount of data, making analyzing and organizing the data crucial for the effective use of the data to improve initiating, planning, controlling and closing in the construction sector.

This paper aims to establish which data mining tools and techniques are best for use in construction to help to maximize opportunities and reduce risks in the 12 modules of the Compendium of the Guild of Project Controls.

Project Managers and Project Controls professionals can leverage the use of the validated data to ensure better decision making, faster and with the most significant benefit to the projects.

KEYWORDS:    Data Mining, Knowledge Area, KDD process, Classification, Big Data, Business Intelligence, Enterprise Data Mining, Correlation, Knowledge Area, Data Validation


“Hope is NOT a valid management Strategy”[2]. History is studded with denial and project failures around the world, with “a significant number of the construction project have encountered problems during the construction phase, 98% of projects incur in cost overruns or delays”[3], related to the fact that “risk has not been dealt with adequately, that subsequently resulted in a limited performance in the built of the project with increasing cost and time delays.”[4]

There are various theories and methods to manage data in the construction industry, and with the help of new technologies, the construction industry is adapting and start to implement it, such as using of data mining to manage the various knowledge areas more productively and efficiently. The use of data mining can discover patterns on construction risks from raw data in a previously unknown way.

Two items are essential in this research, data mining tools and techniques and how this relates to the knowledge areas to achieve project success based on the specifications we have set-up for our project or product or both.

In a general way, risk/opportunity can be “defined as decisions to accept exposure or reduce vulnerabilities by either mitigating the risk or applying adequate controls[5]“, And this should be associated primarily with the measure of deviation from the pre-planned values, and it is usually defined as the probability of those deviations.

In more detail risk can be defined as “A probability or threat of damage, injury, liability, loss, or any other negative occurrence that is caused by external or internal vulnerabilities, and that may be avoided through preemptive action.”[6]

How can we define data mining? It is like a type of deep technology analysis of data, which can establish a forecasting model instead of a back retrospective model. Traditionally statistical analysis tools are used to test the past situation while data mining technology aimed at finding unexpected relationships through discoverable, predictable, pattern matching algorithms, traditionally statistical analysis tools used to test the previous case…



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How to cite this paper: Arba, D. (2020). Data Mining tools and techniques in construction by Knowledge Areas: State of the Art situation, PM World Journal, Vol. IX, Issue X, October. Available online at https://pmworldlibrary.net/wp-content/uploads/2020/09/pmwj98-Oct2020-Arba-Data-mining-tools-and-techniques-in-construction.pdf



About the Author

Danilo Arba

Milan, Italy
Lima, Peru


Danilo Arba is a project controls & management enthusiast, with 20 years of experience. He is a Certified Cost Engineer with an Executive MBA from Politecnico di Milano. With a thorough understanding of EPC (Engineering, Procurement, and Construction) industry, he has a verifiable track record of planning multimillion/billion-dollar construction projects worldwide. He lived & worked all his life around the world from South America, Africa, South East Asia to Europe. He is adept at building and leading cross-functional teams from project conception to completion, optimising performance, contractual, and financial deliverables. Currently he is furthering his education by way of a distance learning mentoring course, under the tutorage of Dr Paul D. Giammalvo, CDT, CCE, MScPM, MRICS, GPM-m Senior Technical Advisor, PT Mitrata Citragraha, to attain Guild of Project Controls certification.

Danilo lives in Milan, Italy and Lima, Peru and can be contacted at danilo.arba@mip.polimi.it


[1] Guild Process Modules Mapped to the 5 Project Management Process Groups. Guild of project controls compendium and reference (Car). (n.d.). Planning Planet | dedicated to Project Controls. https://www.planningplanet.com/guild/gpccar/introduction-to-managing-project-controls

[2] (n.d.). PTMC/APMX Building Project Management Competency-Asean Project Manager’s Center of Excellence. https://build-project-management-competency.com/wp-content/uploads/2010/09/Glenn.Butts-Mega-Projects-Estimates.pdf

[3] McKinsey & Company, The Construction Productivity Imperative. Retrieved from www.mckinsey.it/file/5209/download?token=mGewq6Zc

[4]Bizon-Górecka J, Górecki J. Risk of the construction investment project in perspective of the execution model. Studies & Proceedings of Polish Associations for Knowledge Management. 2015;74:4-15

[5] Business Dictionary, Risk Management. Derived from https://www.entrepreneur.com/encyclopedia/search/Risk

[6] When was the last time you said this? (n.d.). BusinessDictionary.com. https://www.businessdictionary.com/definition/risk.html