BCIS basics: eight principles of benchmarking during market volatility

Benchmarking can become less straightforward during periods of market volatility. This is often because there is greater variability in costs and pricing behaviour which makes it harder to draw meaningful comparisons between similar projects, identify trends and make confident decisions.

In these conditions, benchmarking requires greater care, judgement and consistency of approach. Applying clear benchmarking principles can help organisations maintain robust and relevant benchmarks while supporting more informed decision making.

Extend the use of cost ranges

Cost ranges in benchmarking are designed to help absorb risk and uncertainty and are most commonly used during the early stages of a project.

In more stable market conditions, cost ranges are often relatively narrow from the outset or quickly become more defined as the project progresses. During periods of market volatility, extending both the range itself and the period over which a broader range is used can help to account for inflationary risk.

In turn, this can help build client confidence with the provision of a clearer, more reliable indication of where project costs may fall while market conditions remain uncertain.

Avoid using excessively broad ranges

Extending cost ranges can help manage risk during periods of uncertainty, but ranges that are too broad may lose their practical value. Cost ranges should still be based on considered and relevant data that reflects the characteristics of the project being assessed.

To this end, upper and lower cost bounds should reflect plausible outcomes. Benchmark data should help explain the wider context of cost volatility without compromising the integrity of the benchmark or distorting the result.

Compare context with context

During periods of market volatility, it can be useful to benchmark projects delivered under comparable market conditions. For example, comparing two projects undertaken during different periods of conflict where there was an impact on energy markets. Projects delivered during the period following Russia’s invasion of Ukraine, for example, may provide a useful comparator where the focus project is being delivered under similar market conditions, including disruption to global supply chains, volatility in commodity and energy prices, and constraints on labour availability.

However, contextual benchmarking alone should be supported by a more detailed analysis of the underlying cost drivers affecting both the focus project and the benchmark projects. This helps reduce the risk of drawing inaccurate conclusions from broad market comparisons that may mask important differences in project-specific conditions.

Identify common reference points

Even during periods of market volatility, where projects may not appear directly comparable, there are often common conditions or cost drivers that provide valuable reference points for benchmarking purposes.

Competition for resources is one example. Major infrastructure programmes such as HS2, Hinkley Point C and the London Olympic Games created sustained pressure on regional labour markets, supply chains and specialist subcontractor availability.

While these larger projects may not represent direct comparators in terms of scope, scale or sector, their influence on labour costs, productivity and resource availability – and consequently on the pricing of smaller projects delivered concurrently within the same location – may still provide relevant market context. This can be particularly informative where the focus project is being delivered in a region experiencing similar constraints arising from competing demand for labour and key resources.

Assessing whether comparable pressures are affecting the current market can help contextualise potential cost movements and contractor pricing behaviour, even where broader macroeconomic conditions differ between projects.

Prioritise a focus set of highly comparable projects

During periods of volatility, a smaller group of closely aligned benchmark projects is often more valuable than a larger dataset linked only by building function.

Confidence in benchmark data can become harder to maintain when costs and prices are changing significantly in a short space of time. Focusing on a smaller number of robust and closely matched projects can help to improve consistency and support more reliable benchmarking outcomes.

Benchmark selection should consider as many relevant variables as possible, rather than relying on one or two similarities between projects alone. These may include location, site conditions, procurement route and the wider economic context in which projects are being delivered.

Market conditions vs project specifics

It is important to recognise that some building types will always carry project-specific costs. These should not be mistaken for wider, market-related cost drivers when comparing projects.

For example, the refurbishment of a heritage building will likely involve additional costs associated with specialist materials, conservation requirements or bespoke component replacements designed to meet planning and listed building constraints. These costs are often project-specific and should be distinguished from broader market-driven cost movement when assessing benchmark data.

Prioritise confidence over conforming to expectation

Clients understandably want projects to represent good value for money, particularly in periods of volatility when prices may be subject to rise more significantly. While they may have expectations around what a project should cost, benchmark data should provide a reliable and evidence-led explanation of cost estimates.

The role of the cost professional is to build confidence in the cost assessment through robust benchmarking and clear analysis, even where the outcome may differ from a client’s initial expectations or aims. The objective is to support informed decision making and ensure the project remains deliverable.

Use BCIS tools to narrow down comparators

BCIS provides access to a dataset of more than 30,000 real-world projects that cost professionals can use for benchmarking. The dataset can be refined using a range of filters to help identify closely aligned comparators.

For example, searches can be filtered by region, client type and specification characteristics. A project search focused on the South East may be broadened to the wider South of England where sample sizes for a specific building type are limited. The aim is to balance specificity with a sufficient sample size to support meaningful comparisons.

In volatile markets, effective benchmarking depends on more than selecting comparable projects alone. It requires clear judgement, careful interpretation of data and an understanding of the market conditions influencing costs at a particular point in time.

By combining robust benchmark data with informed analysis and appropriate context, cost professionals can support more confident decision making and help clients develop projects that remain realistic, evidence-led and deliverable.

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