Expert Witness Journal Issue 63 October 2025 - Flipbook - Page 106
The changing landscape
of determining quantum
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?
by Vincent Fogarty, Managing Director of Diales Technical, Quantum and Technical Expert,
London, UK
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.
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 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 largescale 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 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, datadriven decisions. The UK’s Environment Agency
mandates the use of Monte Carlo cost modelling.
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.
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.
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
EXPERT WITNESS JOURNAL
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.
104
OCTOBER/NOVEMBER 2025
