Setting a Benchmark: How Pre-Construction Has Shifted in Modern Construction
Major construction projects require a high level of diligence when it comes to planning and estimating. Errors of judgement or a failure to consider all outcomes early in the process can have a significant impact as that build progresses.
The big players in construction are increasingly turning to data analysis to support their pre-construction processes. Aggregated data from projects of a similar scope can be used to form conceptual estimates with greater accuracy than ever before.
It’s not as simple as just entering a series of figures to form an estimate, but extensive data access is proving to be a helpful addition for planning. Our latest blog post covers the use of cost benchmarking by large developers who are striving for a competitive edge.
The Rise of Data Analysis
The advent of big data in construction has revolutionised pre-construction for major developments. Those who have access to huge repositories of data can produce more accurate conceptual estimates than those using older methods.
Say for example that you are tasked with benchmarking the cost of a 50,000 square-metre office development in central Manchester. If you have access to extensive historical data, you can leverage this knowledge to produce basic order-of-cost estimates during pre-construction.
By looking in-depth at the cost of similar projects in the region and applying index factors to account for inflation and other cost differences, you can establish a benchmark figure with a stronger degree of confidence.
Major retail enterprises, banks, airlines and other service industries have been using this sort of data analysis for years, and the big players in construction are starting to realise the competitive advantages it can provide.
Data-Driven Cost Benchmarks
Major developers and businesses in 2018 have made benchmarking a major priority. These organisations are looking to aggregate client data, internal records and publicly available information for pre-construction planning.
There are several steps involved for organisations looking to establish benchmarks. First, they must gather data from long lists of international and domestic projects of similar scope and filter these projects onto a relevant shortlist. From here, project costs must be normalised to account for current dollar values and project geography.
Benchmark data can be adjusted to account for specific location factors. Market constraints, material costs, wage differences, remote access and a range of other variations can be adjusted to inform a specific project.
Using historical data for benchmarking leads to evidence-based decision-making and allows professionals to use their expertise for assessing value-for-money. These data-driven models can streamline processes and lead to much quicker decisions on feasibility. In an industry where time is money, this competitive edge carries significant value.
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