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Digital Transformation

You Asked Us: Minimising project risk through big data analytics and AI

Do the risks associated with bad data outweigh the benefits of good practice? Can smaller firms really afford to invest in AI? And how do we stop talking about collaboration and actually start collaborating? During our recent webinar, Minimising project risk through big data analytics and AI, you asked us. Here, our expert panel responds.

World Built Environment Forum
4 June 2021

Our expert panel:

Njeri Ngaara, Lead Project Manager, Faithful+Gould North America

Jeff Okeson, Director of Consult Services, Faithful+Gould North America

Is there a danger that mismanagement and misapplication of big data and AI will actually project delays, budget overruns and other issues?

Jeff Okeson: Great question! The old adage "garbage in; garbage out" really applies in this instance. Having incorrect data will absolutely cause delays and a host of associated problems. An example: incorrect or insufficient schedule data fed into an AI model could lead to unrealistic schedule dates and resource loading. This could result in materials being procured or delivered late and the incorrect allocation of labour resources. In fact, resources could be lost entirely if the plan calls for them sooner or later than required. These sorts of logistical issues are the outputs that result from poor data input. It is extremely important to ensure that your project data, as well as the AI model that it informs, is managed correctly and regularly audited for quality.

Minimising project risk through big data analytics and AI

In this webinar, in partnership with Faithful+Gould, we explore how big data analytics and AI can reduce and manage project risks.

Construction is a big money business. Is the sector truly committed to investing in big data and AI, or is it seen as an unnecessary expenditure?

Njeri Ngaara: I think that the big construction companies and big developers are already seeing the value of investing in big data and AI. The challenge is different for smaller firms, working with tighter margins and without the luxury of time and money to invest in this way. Typically, such companies want to get in and out of a job and move on to the next one.

JO: Moving forward, such investment will certainly be as common as existing and well-established investments in human capital and such like. It will be crucial to the prospects of any company operating in the built environment. As the benefits of big data and AI become better understood, the speed of adoption will increase.

Collaboration will be key to enabling data interoperability and fully harnessing the potential of big data and AI. How can we encourage this collaborative culture in the construction industry?

JO: International institutions, and professional and trade groups can really drive collaborative best practices, as well as common standards, for the collection and management of construction data. I‘m thinking here of RICS, CII, PMI, AACEi, etc. An authentic community approach is needed if we are to bring industries together, reduce silos and encourage adoption. In this case, it will most definitely take a village.