Valuation by probabilistic rather than deterministic methods
Is the construction industry witnessing the end of deterministic methods in quantity surveying in favour of probabilistic approaches?
In my experience working on large-scale projects such as airports, transport infrastructure, and data centres, it has become increasingly clear that cost estimation and procurement are evolving towards probabilistic models. With the advent of AI, these methods are likely to expand.
Author: Vincent Fogarty, Managing Director of Diales Technical, Quantum and Technical Expert, London, UK
The Royal Institution of Chartered Surveyors (RICS) predicted these changes[1] in 2020, recognising that the “scale ruler” for measuring cost elements was nearing the end of its life cycle, particularly for large-scale complex infrastructure. This shift is particularly evident in target cost[2] procurement contracts designed to accommodate a more flexible and risk-aware approach to construction. As the industry adapts to a growing uncertainty, the role of probabilistic cost prediction is becoming beneficial and essential.
The limitations of deterministic methods
Traditionally, quantity surveying has relied on deterministic methods to predict construction costs. This approach involves measuring quantities, applying rates for materials and labour, determining indirect costs such as preliminaries, and calculating overhead and profit percentages. However, this method has one significant drawback: it assumes that all inputs and outputs are predictable and fixed, which is rarely the case in modern construction projects. In fixed sum contracts, the design must be mature and fully defined to provide a reliable cost point. But in practice, especially in Design & Build contracts, designs often remain fluid at contract formation, sometimes only reaching the Employer's Requirements stage and/or a Royal Institute of British Architects (RIBA) Stage 3[3]. As a result, the deterministic method cannot accurately address the inherent uncertainties in the design and delivery process.
Enter probabilistic methods
In contrast, probabilistic methods take uncertainty into account. Instead of relying on a single value cost estimate, these methods use historical data to create a range of possible outcomes. This range is then analysed through models such as Monte Carlo simulations which account for the risk and variability inherent in complex projects. Over the past few years, there has been a noticeable increase in the use of Monte Carlo simulations within the construction industry. This trend has been partly driven by the heightened awareness of risks highlighted by events such as the COVID-19 pandemic, but also by a broader shift in the industry toward data-driven, analytics-based decision-making. Monte Carlo simulations are particularly powerful tools for cost and programme/schedule forecasting. By running thousands of random simulations based on a range of input parameters—such as Expected Value, Best Case, and Worst Case —Monte Carlo analysis can produce a probability distribution of potential project outcomes. This allows stakeholders to assess the likelihood of various cost and programme/schedule scenarios and to make more informed decisions.
The role of Monte Carlo in today's construction industry
The technique has proven to be very useful in complex and high-stakes projects. As an example, in a recent expert appointment at Diales under joint instructions, we utilised Monte Carlo simulations to determine an “On Demand” bond value that provided surety in the event of default[4] concerning a Settlement Agreement. The diversity and complexity of the scope, coupled with strict time constraints, made the probabilistic approach not only useful but necessary. By incorporating a range of scenarios we established a reasonable and well-supported bond value that balanced all the relevant factors. The UK’s Treasury and Cabinet Office[5] and the Infrastructure and Project Authority have recognised this shift and are actively promoting probabilistic techniques to ensure greater cost certainty in largescale infrastructure projects. This is not just about improving the accuracy of cost predictions but is also about providing the confidence necessary for stakeholders to make sound, data-driven decisions. The UK’s Environment Agency mandates the use of Monte Carlo cost modelling.
The future of quantity surveying
The shift towards probabilistic methods does not spell the end of deterministic approaches, but it does signify a profound transformation in how quantity surveying and cost management are practised.
The rise in the use of Monte Carlo simulations and similar probabilistic techniques highlights a growing need for data literacy and an ability to handle complex risk modelling.
As the construction industry continues to innovate, the quantity surveyor's role will likely evolve into a more analytical and strategic one, blending traditional expertise with new methodologies that can better address the uncertainties of modern construction. For those in the profession, staying ahead of this shift means embracing the technologies and techniques that can provide deeper insights into project risks and cost implications. This evolving skill set will not only enhance the accuracy of cost predictions but also instil greater confidence among clients, investors, and the public, increasing the likelihood that construction projects can be delivered successfully on time and within budget. In the expert witness world, this will mean that those with practical experience in applying cost model techniques ought to flourish.
This article was originally written for issue 28 of the Diales Digest. You can view the publication here: www.diales.com/diales-digest-issue-28
Do not hesitate to get in touch with Vincent directly if you have any queries following-on from this article.
You can view his expert profile and get in touch with him via this page: www.diales.com/en/expert/vincent-fogarty
1. RICS, Cost Prediction, 1st edition, dated November 2020, effective from 1 July 2021.
2. Such as NEC Option C forms and similar target cost contracts.
3. RIBA Stage 3: Spatial Coordination Formerly known as the 'Developed Design' stage; this is where the practical aspects of the concept are decided. For instance, at RIBA Stage 3, the design team should consider how the project will meet legal requirements, such as building regulations.
4. In the event where defects were not remediated within a time limitation period.
5. Infrastructure and Projects Authority; Cost Estimation Guidance, A best practice approach for infrastructure projects and programmes, Crown Office, 2021.