The authors highlight how faulty decisions often stem from the process of decisionmaking itself , such as when alternatives are not properly defined , relevant information is not collected , or the costs and benefits are inaccurately gauged . Sometimes the fault lies with decision makers , whose cognitive biases and heuristics might inadvertently sabotage the decision . Anchoring , a bias the authors identify , is a particularly dangerous pitfall . It describes the tendency to give disproportionate weight to the first piece of information received , thereby influencing subsequent thought processes and judgments . This cognitive bias is glaringly evident in the construction industry , where initial cost estimates or project timelines can become immovable anchors , guiding all subsequent calculations .
An inaccurate cost estimate or illconceived timeline can cause spiraling budget overruns and delayed project completion . In their report , ‘ Reinventing Construction : A Route to Higher Productivity ’ ( 2017 ),
Predictability and proactiveness are a dream in construction where much of the time we are highly reactive to the situations that arise
the McKinsey & Company Global Institute confirms this . It found that large construction projects typically take 20 percent longer to finish than initially scheduled and are up to 80 percent over budget . This highlights the massive financial burden that poor decision-making can impose .
To steer clear of these biases and ensure better decision-making , the industry is increasingly looking towards AI . Unencumbered by human cognitive biases , AI provides a more objective viewpoint . It leverages its ability to process vast amounts of data to provide real-time , accurate cost and project assessments . Instead of anchoring to an initial estimate , AI constantly adapts and adjusts based on market trends and data . In the construction context , this could
28