Insights from New Data on Australian Construction

Construction Industry Survey 2024

 

The ABS has published detailed data on the Construction industry for 2023-24. Although released as part of the Australian Industry data, this is the seventh of a series of irregular and infrequent Construction Industry Surveys done by the ABS [1]. The ABS collected employment, wages and salaries, income, expenses, operating profit, earnings before interest tax depreciation and amortisation (EBITDA), and industry value added (IVA) for private sector construction businesses. 

 

Construction is an industry division, divided into three subdivisions: 

·      Subdivision 30 Building construction, with the two groups of Residential and Non-residential building;

·      Subdivision 31 Heavy and civil engineering construction; and

·      Subdivision 32 Construction services with five groups of Land development and site preparation services, Building structure services, Building installation services, Building completion services, and Other construction services.

 

The survey divides income by: 

·      Type of client;

·      Nature of contract (contracting, subcontracting or speculative);

·      Type of asset (houses, other residential building, non-residential building, road and bridge construction, and other non-building construction); and

·      Type of work (new construction work, alterations, additions, renovations and improvements, and repairs and maintenance).

 

This post first looks at industry totals and the Construction subdivisions and groups, and details income and expenses. It then compares the amount per employee for income, wages and salaries, EBITDA and IVA across the subdivisions and groups to show their relative performance. The data on capital expenditure, work done by type of asset and type of work is presented. 

 

Australia is in the fortunate position of having one of the world’s best statistical agencies with the ABS, at a time when other countries are having issues with their data collections [2].

 

 

 Industry Totals

 

Total employment was 1,291,000 people, of which Construction services were 883,000 or 68%. Within Construction services, the largest groups were Building installation services (329,000 people) and Building completion services (223,000 people). Building construction employed 254,000 with 173,00 in Residential building, and Heavy and civil engineering construction employed 154,000. 

 

Total income includes income from non-construction services and sales of land and goods, but the survey also has income from contracting and subcontracting. Construction total income was $633.6 billion with $438.6bn from contracting and subcontracting (69%), with $77bn of contracting income from the public sector (17.5%). For the three subdivisions:

·      Building construction’s total income was $235.2bn, with $130.8bn from contracting and $21.5bn from subcontracting, contributing $152.3bn. 

·      Heavy and civil engineering construction’s total income was $122.4bn with $85bn from contracting, of which $47.2bn (55.5%) was for the public sector, and $13.2 from subcontracting, contributing $98.2bn. 

·      Construction services’ total income was $276.1bn, with $116.6bn from subcontracting and $71.4bn from contracting, contributing $188bn. 

·      Within Construction services, Building installation services was the largest group by income ($94.2bn), followed by Building completion services ($53.2bn), which together were 53% of Construction services income. 

 

 

Table 1. Construction totals 

Source: ABS 8155DO008. 

Note: W & S is Wages and salaries, Total income includes income from non-construction services and sale of land and goods, Profit is Operating profit before tax, EBITDA is Earnings before interest tax depreciation and amortisation, IVA is Industry value added. 

 

Figure 1. Contracting income by client type

 

 

Non-construction income was 31% of total income, with $113.2bn from the sale of goods and $61.2bn from services. Income from sales of land and goods was a high proportion of contracting and subcontracting income for Residential building (67%) and Land development and site preparation services (53%). Income from Non-construction services (including professional, scientific and technical services) was a high proportion of contracting and subcontracting income for Heavy and civil engineering (14%), for Land development and site preparation services (43%), and for Building installation services (18%). 

 

Figure 2. Non-construction income by source

 

 

Expenses were $570.7bn in 2023-24. The largest were purchases of goods and materials ($255.4b) and selected labour costs ($105.7b). Payments to other businesses for construction services, building and industrial cleaning services was $91.6b, and this will have included Professional services like architectural, engineering and surveying services, and rental and hire of machinery and equipment .

 

Purchases of land for property development was $12.2 bn, with Residential building accounting for $7bn and Land development and site preparation $3bn of the total. Those purchases incurred $2.1bn and $1.3bn in interest costs for the groups, which also had $762mn and $1.4bn in depreciation and amortisation expenses. 

 

Performance Per Employee

 

Comparing the amount per employee for income, wages and salaries, EBITDA and IVA highlights the differences between the industry subdivisions and groups. The Non-residential building and Heavy and civil engineering construction subdivisions had much higher average wages and salaries and income than the rest of the industry, and the highest IVA per employee. The highest operating profit per employee and EBITDA was in Land development and site preparation, which was also the group with the highest income from non-construction services, and Building installation services had the lowest operating profit per employee and EBITDA.

 

Table 2. Amount per employee

Source: ABS 8155DO008. 

Note: W & S is Wages and salaries, Total income includes income from non-construction services and sale of land and goods, Profit is Operating profit before tax, EBITDA is Earnings before interest tax depreciation and amortisation, IVA is Industry value added. 

 

The figures below show the differences between the groups for wages, profits, EBITDA and IVA per employee. The general pattern is that Construction services have lower values than Building and Engineering, often around half as much, particularly for wages and contracting income. Average wages are notably low for Residential building and Building completion services. Contracting income per employee is highest in Non-residential building, by a considerable margin over Residential building and Engineering, and the three groups of Building installation, Building completion and Other construction services have almost the same contracting income per employee.

 

Figure 3. Wages and salaries per employee

 

 

Figure 4. Income per employee

 

Note: Includes contracting and subcontracting income, excludes non-construction income from sales of land and goods.

 

For EBITDA and IVA where non-construction services income is included, Land development and site preparation had the highest EBITDA and third highest IVA per employee. Residential building had lower IVA per employee but higher EBITDA than both Non-residential building and Engineering, which were the two groups with the highest IVA per employee. Interestingly, there is only a weak relationship between EBITDA and IVA per employee across the industry groups. 

 

Figure 5. EBITDA per employee

 

Note: EBITDA is Earnings before interest tax depreciation and amortisation.

 

The four Construction services groups of Building structure services, Building installation services, Building completion services and Other construction services have IVA per employee values around half that of Engineering, and around two thirds of Building. 

 

Figure 6. IVA per employee

 

Note: IVA is Industry value added.

 

Capital Formation

 

There is a well-established relationship between the amount of capital (both physical and intellectual) available for each worker and their level of productivity. All else equal, the more capital the higher the productivity. The survey has capital expenditure (capex) and gross fixed capital formation (GFCF) for the eight industry groups, and Figure 5 shows  the relationship between IVA per employee, capex and GFCF per employee.

 

Land development and site preparation had the highest level for both capex and GFCF per employee indicators, due to including purchases of land and equipment. Similarly, Engineering has a high capex that includes purchases of machinery and equipment, and also the highest IVA per employee. Capex is low for Residential and Non-residential building  because of the low level of ownership of heavy equipment and machinery due to extensive use of hiring and leasing, however that equipment and machinery lifts the level of IVA per employee. The other four trades in Construction services have capex and GFCF tracking IVA per employee, and are the best example of the relationship between capital and productivity.

 

Figure 7. IVA, capex and GFCF per employee in 2023-24. 

 

Note: Capex is capital expenditure and GFCF  is gross fixed capital formation.

 

Work Done by Type of Asset and Type of Work

 

Building Construction and Construction Services Income

 

There is a new set of data in this year’s survey that has the income from different types of asset built, divided into houses, other residential building and non-residential building, and the type of work done, divided into new construction work, alterations, additions, renovations and improvements, and repairs and maintenance. This is given for the three Building groups of Residential and Non-residential building and Construction services. 

 

Table 3. Income from construction services by type of work

 

 

Residential projects provided the largest source of income for Construction services, with $55.6bn from House construction and $17bn from Other residential building, a total of $72.6bn, compared to Construction services’ Non-residential building income of $66.2bn and Non-building construction’s $49.3bn. For the Non-residential building group, Alterations etc. income of $18bn was 58% of income from New work of $31bn.

 

Table 4. Type of work done by Building construction and Construction services

 

 

The distribution of income across type of work and type of asset can be found from this data. This has not previously been available and it allows a comparison of the relative importance of type of building work done. New work is 72% of the total, but of particular interest is that 9% is repair and maintenance, which is generally inefficient and labour intensive compared to new work. Around three quarters of R&M is (unsurprisingly) done by trades in Construction services and, except for Non-residential building, most of the alterations and additions.

 

Engineering Construction Income

 

Heavy and civil engineering construction total income was $98.2bn, of which $85.1bn was from contracting. Income was broken down by project type and into New work and Improvements and Repairs and maintenance (R&M): 

·       Road and bridge construction ($37.5bn; New work $34.5bn, R&M $2.6bn );

·       Railways, tramways and harbour construction ($17.3bn; New work $17bn);

·       Water storage and supply, sewerage and drainage construction ($7.2bn; New work $6.1bn, R&M $1.1bn);

·       Electricity generation, transmission and distribution construction ($11.5bn; New work $11.1bn);

·       Telecommunications construction ($1.2bn; New work $$567mn, R&M $595mn);

·       Oil, gas, coal, pipelines (not water) and other heavy industry construction ($9.4bn; New work $7.2bn, R&M $2.2bn);

·       Other non-building construction ($8.2bn; New work $7.6bn);

·       Building construction ($5.1bn; New work $5.5bn, Alterations & additions plus R&M $593mn). 

 

Roads and railways are by far the largest categories of new engineering work ($37.5bn and $17.3bn respectively), and it should be noted that 2023-24 was a year with exceptionally high public expenditure on infrastructure, with major projects underway in NSW, Victoria and Queensland. The third highest category was Electricity generation, transmission and distribution construction, reflecting expenditure on the energy transition with $11.1bn of new work. Repair and maintenance was 8.3% of total Engineering income. 

 

 

Key Points

 

Total income included income from non-construction services and sales of land and goods as well as income from contracting and subcontracting. Construction total income was $633.6 billion with$438.6bn or 69% from contracting and subcontracting. Contracting income from the public sector was $77bn. Sales of land and goods was a high proportion of contracting and subcontracting income for Residential building (67%) and Land development and site preparation services (53%).

 

Construction services have lower wages, profits, earnings before interest, tax, depreciation and amortisation (EBITDA) and industry value added (IVA) per employee values than the Building and Engineering groups, particularly for wages and contracting income. Contracting income per employee is highest in Non-residential building, much more than Residential building and Engineering, and the three groups of Building installation, Building completion and Other construction services have almost the same contracting income per employee. 

 

When non-construction services income is included, Land development and site preparation had the highest EBITDA and third highest IVA per employee. Residential building had lower IVA per employee but higher EBITDA than both Non-residential building and Engineering, which were the two groups with the highest IVA per employee. There is only a weak relationship between EBITDA and IVA per employee across the industry groups. The four Construction services groups of Building structure services, Building installation services, Building completion services and Other construction services have IVA per employee values around half that of Engineering, and around two thirds of Building. 

 

The survey has capital expenditure and gross fixed capital formation (GFCF). Land development and site preparation had the highest and Engineering the second highest for capex and GFCF per employee, due to purchases of land and equipment. Capex is low for Residential and Non-residential building  because of hiring and leasing of heavy equipment and machinery. The other four trades in Construction services have capex and GFCF closely tracking IVA per employee, a good example of the relationship between physical capital and productivity.

 

Data on the distribution of income across type of work and type of asset has not previously been available. For Building construction New work is 72% of the total, alteration, additions and improvements 19%, and repair and maintenance is 9%, with around three quarters of R&M done by trades in Construction services. However, the data does not include the number of people employed in R&M. 

 

For Heavy and civil engineering, total income was $98.2bn, of which $85.1bn was from contracting. Roads and railways are by far the largest categories of new work ($37.5bn and $17.3bn respectively). 2023-24 was a year with high public expenditure on infrastructure and 55.5% of income came from the public sector. Repair and maintenance was 8.3% of total Engineering income. 

 

The 2023-24 Construction Industry Survey has provided a level of detail previously unavailable. Key insights are that 69% of total income is from contracting and subcontracting, with the rest from provision of services and sale of land and goods, and 9% of income is from repair and maintenance. Although only 18% of total contracting income is from the public sector, for Engineering it is 56%. Purchases of land by Residential building was $7bn and by Land development and site preparation $3bn, with $2.1bn and $1.3bn in interest costs respectively. In Non-residential building work, Alterations, additions, renovations and improvements income of $21.2bn was 41.2% of the income from New work of $51.3bn. For House construction by Construction services, income from New work was $30.6bn, and for Alterations etc. was $17.6bn, 57% of New work income. 

 

Non-residential building and Engineering had the highest IVA per employee, followed by Land development and site preparation and Residential building. There is a wide productivity differential across the industry groups, as measured by IVA per employee. That may be an imprecise measure, but it is indicative of the labour intensity of the trades, and the higher capital intensity of the Building and Engineering subdivisions. One way to improve overall industry productivity would be through lifting the capital intensity of Construction services by providing incentives for them to increase capex. 

 

Conclusion

 

The ABS 2023-24 Australian Industry data included a survey of the Construction industry, with previously unavailable data on income from work done and type of work, clients and other variables at the level of eight industry groups. Therefore, this data has much more detail compared to the three industry subdivisions of Building, Engineering and Construction services used in regular ABS publications, because subdivisions are made up of industry groups.  

 

The first three groups are Residential building, Non-residential building and Heavy and civil engineering, and there are five groups of Construction services: Land development and site preparation services, Building structure services, Building installation services, Building completion services, and Other construction services.

 

In terms of policy and industry development, this detailed data is important because it clearly shows the differences in the characteristics of the industry groups, their clients and sources of income. It will also allow recalculation of construction labour productivity for the different types of work done. 

 

Construction is better viewed as three sub-industries when the differences between Residential building, Non-residential building and Engineering construction are taken into account. These structural differences affect the way clients, contractors, subcontractors, designers and suppliers work and interact, and these ABS subdivisions have their own characteristics and ways of working. For example, house builders have pattern books, commercial building uses architects, and infrastructure is designed by engineers.

 

Industry policies that target Construction will be challenged by sub-industries with limited, though important, similarities, and are unlikely to be relevant across them. The specific nature of the individual subdivisions often makes recommendations and policy directed at Construction as a single industry hard to implement or ineffective, separate policies are required. 

                                                              *

 

 

[1] ABS 8155DO008 Australian Industry 2023-24, ABS 8155DO001 Construction Industry Survey 2011-12. ABS 8772  Private Sector Construction Establishments 2002-03, 1996-97,1988-89,1984-85 and 1978-79. 

The 2002-03 survey used different industry categories and is not comparable with the other surveys. The ABS notes that survey data ‘were understated in the 1978/79 collection as there were significant coverage deficiencies in this survey.’

 

[2] In the US the Bureau of Labor Statistics issued a notice in June 2025 that said CPI collection reduction and suspension affected the Commodity and Services survey and the Housing survey. The ‘BLS makes reductions when current resources can no longer support the collection effort.’  

 

The UK Office of National Statistics published a wrong CPI figure in April 2025 and 

a Systemic Review of ONS Economic Statistics noted  ‘there are widely recognised problems with the Labour Force Survey’ and  ‘resource pressures on economic statistics and on the ONS as a whole have intensified in the last two years.’ In 2014 issues with UK construction data were so serious they led to Construction Output being de-designated as a National Statistic. 

 

 

 

Recent Research on Construction Productivity

 Four papers on US statistics and McKinsey’s latest report 

 

 

 

The lack of growth in construction productivity is a well-known and universal issue. This post reviews US research into construction productivity, with summaries and comments on four recent research papers, followed by the most recent McKinsey report on improving construction productivity. Two papers develop a physical measure of productivity as houses per employee, providing alternative measures to the official statistics.

 

The first paper discussed argues that increasingly strict land-use regulation has resulted in more small, low productivity firms in residential construction, and this has lowered the overall industry level of productivity. The two papers that follow looked at problems in the statistics and methods used to measure it, and found strong evidence that mismeasurement does not explain the lack of productivity growth. The fourth paper also addresses issues in the statistics and develops four deflators for four specific construction sub-industries. 

 

The McKinsey report starts with industry level analysis, then goes on to address project level issues. It lists seven issues in construction that lead to low productivity, and offers five ‘transformative approaches that owners and delivery partners could adopt’.  

 

 

Why Has Construction Productivity Stagnated? The Role of Land-Use Regulation

D'Amico, L., Glaeser, E., Gyourko, J., Kerr, W., and Ponzetto, G. 2024. 

 

The paper discusses construction productivity in the US and argues land-use regulation has affected the size and productivity of residential construction firms, and uses a new productivity measure using housing units started per employee. They admit this is an ‘imperfect’ series, because the employment data has missing years and excludes some subcontractors, but nonetheless is used in the comparison with manufacturing and car production. Despite the data problems, this is a useful measure of physical productivity (as output per employee) that avoids the issues associated with productivity estimates from official construction statistics 

 

Figure 1. US house building labour productivity 1900-2020 

 

The paper says “From 1935 to 1970, homes produced per construction worker grew at a pace that at times exceeded the growth in the number of cars produced per automobile industry worker or the growth of total manufacturing output per industrial worker. Since 1970, these three series have diverged sharply. Car and manufacturing output per worker continued to soar but houses built per worker fell dramatically.” [1]

 

Figure 2. Construction compared to manufacturing and cars

 

In the 1950s the US developed new towns and suburbs with thousands of houses, using a production line method that moved site workers from one building to the next in a highly coordinated system integrated with the supply of materials. D’Amico et al. suggest such large scale developments with their economies of scale cannot be done today, due to the “increase in regulatory tightness in construction from the mid-1970s to today. Developing large projects and coordinating construction teams over different projects all working at the same time is becoming more and more difficult … It is also hard to obtain permits to develop a single type of housing unit on large plots of land given that zoning laws discourage such types of projects.”

 

The argument is that land-use regulations affect firm size by reducing the average size of home builders, and firm size restricts returns from scale and diminishes incentives to invest in technology [2]. With reduced technology investment comes lower productivity: “Project-level regulations have been put in place that reduce innovation, not by barring it, but by limiting project and firm size. The small scale of the firms, and the fact that they could not grow dramatically even if they made a breakthrough, then limits innovative activity.”  

 

They argue there will be less construction activity in areas with stricter land use regulation, because stricter regulation leads to smaller establishments and forces contractors to undertake many small projects. This stretches their span of control, creates inefficiency and causes lower productivity. Therefore, in more regulated areas residential construction firms will be smaller and less productive.

 

Their econometric model links project-level regulation, firm size and productivity, and they suggest firm size could explain a significant fraction of the low productivity seen in American residential construction. For bigger firms, fixed costs are relatively less important and productivity is higher. Smaller firms are less productive and in jurisdictions where regulation is more intense, average firm size and firm productivity are both lower.

 

Using the model, there is a detailed analysis of residential construction firm productivity, with regressions against regulation, size, revenues, housing units produced, and profits. For regulation the Wharton Residential Land Use Regulation Index is used, and the model finds a one standard deviation increase in the Index is associated with an 12.8 % reduction in revenue per firm, a 5.4% decrease in revenue per employee, and a 4.3% reduction in employment in large building firms’

 

Comment

This is an interesting paper built on the well-known fact of lower productivity in smaller firms. The intuitively appealing argument is that increasingly strict land-use regulation has resulted in more small firms doing more small projects. Using regression analysis they find this is has indeed been the case in the US sine the 1970s, when construction productivity stopped growing. 

 

However, does stricter land-use regulations lead to smaller firm sizes, and therefore lower productivity, in construction? The answer is more maybe than definitely, for two reasons. First, the comparison with the 1950s and 1960s house building boom is misleading. That period was uniquely different because of the size of the sites available and repetition of a large number of houses, in many places developments had over 10,000 houses built over a few years. Those sites are no longer available and developments of that size are not possible today. That is not due to regulation, but because the opportunities are not there. 

 

Second, construction is a local business, There is a physical limit to managing projects based on the time and cost constraints of distance. Small firms work within their local area, and larger firms typically operate as a series of semi-independent project offices. Regulation might enhance the effect of location through local planning laws, but does not create the diseconomies of distance. 

 

Finally, does project-level regulation reduce incentives to invest in technological innovation? The paper does not provide any evidence for that beyond firm size, but it is a well-known characteristic of small firms that they do not invest in innovation and have limited capex budgets. That is because they are small, not because they are over regulated. 

 

The paper links regulation, firm size and productivity. Basically, land-use regulations reduce project and firm size, leading to smaller and less productive firms. ​The analysis finds some support for that argument, because there is less building in places where regulation is more intense, but there are other good reasons why there are so many small residential construction firms. This is original research, but does not conclusively prove increased regulation is responsible for the prevalence of small firms in house building in the US. 

 

 

The Strange and Awful Path of Productivity in the U.S. Construction Sector

 Goolsbee, A. and Syverson, C.  2023. 

 

This paper is from two experienced researchers into the construction industry, and they look at several key issues in measurement of productivity. Their intent is to show that the lack of growth in construction productivity is not due to problems in the statistics or method used to measure it. The time period covered in their research is 70 years, from 1950 to 2019. 

 

They focus on measurement problems as an explanation of poor performance: ‘we update some of this previous work and extend it to some new data sources and hypotheses. Together, these new approaches seem to reinforce the view that the poor performance is not just a figment of measurement error.’ 

 

First, mismeasurement of capital stock or labour inputs is not the problem. They find both capital intensity (capital stock per full time employee) and intellectual property have grown at rates comparable to the whole economy since 1970. The growth rate of labour inputs was lower after 1970 than before, not faster as a mismeasured productivity slowdown would imply. Therefore, the problem should be in measuring output.

 

Second, in the US, construction’s nominal value added has grown at a similar rate to the economy, but the construction output deflator and the GDP deflator start to diverge in the late 1960s: ‘From 1950-69, the average annual growth rates of the construction and GDP deflators were almost identical—2.40 percent and 2.42 percent. From 1970 on, however, the GDP deflator averaged annual growth of 3.37 percent, while the construction value added deflator grew 5.47 percent per year.’  

 

By deflating nominal construction activity with the whole-economy deflator, construction productivity will look like overall productivity. Is this the smoking gun? Unfortunately, no. The issue here is the change in relative prices, which is the price change of inputs in construction compared to the changes in overall prices in the GDP deflator. They find the increase in the construction price deflator cannot be explained by increasing relative prices of construction inputs. 

 

They then measure productivity in physical units in residential housing construction, using units per employee and square feet per employee for houses and apartments. These also show declining or stagnant productivity, although the multi-family series are extremely variable, falling by half in 2001 and 2010 during economic downturns. 

 

Figure 3. US house building labour productivity 1972-2020

 

 

Finally, they consider construction’s ability to transform intermediates into finished products. Again, performance has deteriorated. They also provide evidence that something keeps producers in areas where construction is more productive from growing, and ‘this problem with allocative efficiency may be accentuating the aggregate productivity problem for the industry.’

 

Comment

By working through the likely suspects of mismeasurement of capital and labour inputs, output and the deflator used to adjust for price changes, the paper finds that measurement error is ‘probably not the sole source of the stagnation’, i.e. the statistics may have some issues, but the problem is real. Using alternative measures like the physical measure of housing units produced per employee and the use of intermediate inputs also finds no increase in productivity. 

 

Construction productivity, despite the improvements in materials, tools and techniques over the last few decades, has not increased. And this is not unique to the US, for countries around the world, the same result has been found. 

 

 

Can Measurement Error Explain Slow Productivity Growth in Construction?

Garcia, D. and Molloy, R. 2022. 

 

Garcia and Molloy are economists at the US Federal Reserve, and for them the answer was no: ‘we estimate that productivity was essentially flat in the construction sector from 1987 to 2019.’  However, it was not as low as the negative -0.05% annual change found by official statistics when they adjusted for what they call ‘unmeasured structure quality’ of houses. Quality changes were improved energy efficiency, better finishes, more bathrooms and larger buildings. These improvement were real but ‘undramatic’, and adjusting for improved quality gave an annual increase in productivity of 0.02%.

 

Their analysis found a small upward bias in deflators related to unobserved improvements in structure quality, ‘but the magnitude is not large enough to alter the view that construction-sector productivity growth has been weak. We also find only small contributions from other potential sources of measurement error.’ They conclude construction is very labour-intensive and there have not been many labour-saving innovations due to low investment in intellectual property.

 

They found the average length of time from start to completion of single-family homes increased from 6.2 months in the mid-1980s to 7.0 months in 2019, ‘suggesting that any time-saving productivity improvements have been more than offset by delays elsewhere in the construction process.’ Although this could be due to increased regulation causing delays, they did not find evidence for increased costs from regulation.

 

Another potential restraint on productivity growth is more construction taking place in already dense areas: ‘new homes built between 2016 and 2019 were more likely constructed in tracts with a population density above 3000 persons per square mile, while new homes built between 1991 and 1994 were more likely to be built in tracts with less than 100 persons per square mile’. Higher density makes building on small parcels of land more expensive because it is more difficult to take advantage of scale, compared with large developments of hundreds of new homes.

 

Comment

The result of this research is that a small increase in productivity has been absorbed by higher but unobserved (i.e. not in the data) quality, therefore there has been no growth in measured construction productivity since 1987. Using a variety of sources on building quality, land and house prices, and potential bias in the deflators from measurement of output and labour input, their adjusted measure finds a small average annual increase rather than the small annual average decrease in official statistics. While something is better than nothing, the gap between construction and other industries’ productivity growth remains. 

 

 

Measuring Productivity Growth in Construction

Sveikauskas, L., Rowe, S., Mildenberger, J., Price, J. and Young, A. 2018. Updated 2024.

 

Addressing the problem of measuring real output in construction, Sveikauskas and his colleagues at the US Bureau of Labour Statistics estimated real construction value added per hour worked in four construction sub-industries, using four specific deflators and including subcontractor hours. The research methods were published in 2018. 

 

Using more recent data for a time period comparable to the papers discussed above, between 2007 and 2020 productivity fell in single-family residential and multiple-family housing construction, but rose in industrial and highway, street, and bridge construction, following a rising volume of work in the latter two sub-industries. Overall productivity for the four sub-industries was flat because these rises and falls balanced out.

 

Figure 4. Productivity for four construction sub-industries 

Source: Bureau of Labor Statistics, 

 

Comment

The BLS research addresses the deficiencies found in construction deflators. There is a downward bias to output estimates because there is no adjustment for quality changes in buildings and structures.  If real construction value added is underestimated due to the deflators used, construction productivity has also been understated.

 

These estimates used four different deflators, providing high quality estimates of real construction value added per hour worked in those industries, including subcontractor hours. The BLS research improves on previous research by using appropriate output deflators to develop measures of productivity growth, these measures are more reliable because the deflators are specifically designed for each sub-industry. The 2024 update for 2019 to 2023 shows labour productivity falling for single family residential and highway and bridge construction, but rising for multi-family residential and a large increase in industrial construction productivity. 

 

 

Construction Productivity is No Longer Optional

Mische, J., Stokis, K., and Vermelfoort, K. August 2024

 

The article starts with data on the lack of growth in labour productivity, defined as the value added per hour of work, adjusted for increases in construction and input prices, for 42 countries with about 90% of construction value added. McKinsey has released a series of report on construction productivity since 2017, and this latest addition updates the data without changing the picture of lower growth in construction compared to other industries. [3] 

 

Figure 5. Construction compared to manufacturing and global economy

 

 

There are seven specific issues holding back measurable productivity gains (links below are in original):

 

1.        The construction industry’s uptake of technology has been slow over the past several decades. Historically, construction companies spent an average of less than 1 percent of revenues on IT, less than a third of what is common, for example, in automotive and aerospace. Technological innovations in construction largely focus on increasing control or other priorities, such as design, safety, and usage of new materials, and less on direct workforce productivity

2.        Improvement in projects don’t scale across the entire project portfolio. Companies typically start projects as soon as possible with a smaller team that focuses on technical aspects, procurement, and project deliveries rather than on improvement initiatives. Projects have little incentive to act as the pilot for the benefit of future projects. 

3.        In some cases where the industry has improved its productivity and where construction companies could have improved their margins, many of these benefits are passed upward (to suppliers) or downward (to their customers) in the value chain. tender teams factor gains from productivity into cost estimates within proposals, keeping margins thin

4.        Tender dynamics and low margins limit investment in productivity.

5.        Current approaches to risk-sharing and cost estimation cannot keep up with the ever-growing increase in project complexity, risk, and scope.

6.        Productivity declines because of firms having to bring inexperienced workforces onto projects. A large part of skill level is built on tenure and apprenticeship. New workers may require additional training and control and, consequently, achieve lower rates of productivity.

7.        Timely delivery takes priority over productivity improvements. Reducing idle times across all subcontractors and tasks while meeting throughput requirements would require systemwide efforts to improve workflows, reduce bottlenecks and variability, balance loads, and improve project production rates.

 

The transformative approaches that owners and delivery partners could adopt are quoted in full:

• Adopt project steering 2.0. Conventional project management relies on earned-value-management systems, but these s-curves can disguise performance issues and delay intervention, enabling further cost and schedule delays. Project teams can follow the lead of manufacturing and shift their focus to production rate metrics, such as meters welded, volumes excavated, and drawings reviewed. Steering projects in this way will allow teams to be more proactive and help them resolve issues before they materialize.
• Nurture a supplier ecosystem across projects. Supplier ecosystems can help delivery partners provide owners with transparency, credibility, and predictability by providing teams more stability, which will help improve learning curves, interfaces, ways of working, and innovation. Instilling habits across an ecosystem can build the trust and better practices required to gradually promote positive end-to-end change across projects.²⁷ Owners will typically set up these partnerships and role model the desired way of working.
• Upskill project staff. Skilled labour shortages pose a massive upskilling and leadership challenge for the industry. Given high-pressure and short timelines, project staff are tempted to fall back on suboptimal behaviours and ways of working. Leaders can foster an aptitude for learning among their teams to help team members upskill regularly. Technology-supported learning journeys, systematic apprenticeships, and project academies focused on hard and soft skills will all become more popular in years to come.
• Scale initiatives across project portfolios. There are many examples of successful productivity improvements within specific project teams. However, rolling out improvements across a project portfolio is difficult. Change management in a project portfolio context is even harder than in an individual project. Tailored approaches and different capabilities are needed to establish improvement at scale.
• Apply technology in ways that have a direct impact on productivity. Technologies such as generative AI could fundamentally transform how capital projects are delivered. Investments in technology should shift from the “shiny objects” like drones or monitoring software to technology that streamlines and accelerates engineering, procurement, and construction.

 

Comment

The McKinsey report does not specifically address residential construction, which has been the focus of the other research discussed above. However, the issues and recommendations apply as much to house builders as to larger contractors in non-residential construction who are more likely to be McKinsey clients. Their seven issues are common to construction companies everywhere. As McKinsey notes, productivity is not how companies measure the success of projects, and ‘companies prioritize hitting the delivery date over any other goalpost.’

 

Their recommendations are less ‘transformative’ than statements of the obvious. These are all well-known and widely appreciated, and have been discussed in government reports and the academic literature for decades. The problem for the industry is that all these ‘transformative approaches’ require upfront investment that clients do not, and will not, cover (including government), and few contractors have the scale necessary to spread those investment and capital costs across enough projects to make them feasible. And for those companies, profits do not always a follow the investment. 

 

A more germane question, that McKinsey does not answer, is why it is so difficult for so many construction companies to make their recommended changes if they would improve margins and profits? This is the core issue: what or where is the new business model that construction companies can use that will both improve productivity and increase profitability. How do companies benefit from these changes?

 

 

Conclusion

 

A recent paper on the lack of productivity growth in US construction by D’Amico et al. argued increased regulation leads to more small, low productivity builders in residential construction. However, the structure of the residential construction industry is many small firms working on small projects and contracts in a local area, but the authors do not consider the possibility that industry structure is aligned with this demand pattern.

 

Other recent research into construction productivity growth in the US has focused on issues with the statistics used to measure it. That is because problems in measurement and particularly deflation of output are widely accepted reasons for the low rate of growth. The research is thorough and approaches the problem in several different ways, and concludes that while there is some mismeasurement that understates growth, it does not account for the lack of growth in the long-run.

 

Goolsbee and Syverson looked at potential mismeasurement of capital and labour inputs, output, and the deflator used to adjust for price changes. They find the statistics may have some issues, but the problem is real. Using a physical measure of the number of housing units produced per employee also finds no increase in productivity.

 

Garcia and Molloy found a small increase in productivity since 1987 in their adjusted estimate, but it has been absorbed by higher but unobserved quality that is not included in the data, such as larger houses, better finishes and improved energy efficiency. Therefore, there has been no growth in construction productivity as measured by official statistics.

 

Sveikauskas et al. estimated real construction value added per hour worked in four construction sub-industries, using alternative deflators specific to the four types of building. Their estimates found growth in two of the sub-industries but declines in the other two, thus no growth in overall productivity as these rises and falls cancel each other out. 

 

McKinsey’s prescription for transformation of the industry has a focus on projects, technologies, and information, in a top-down approach that has to date not delivered any meaningful changes in the industry or productivity. McKinsey does not address why it is so difficult for construction companies to make their recommended changes, or how they improve margins and profits. What or where is the new business model that construction companies can use to improve productivity and increase profitability?

 

That construction needs to improve productivity is something all industry stakeholders can agree upon. Despite all the time, effort, and words expended on this over many decades there has been no increase in industry-wide productivity. There is good evidence for differences between firms [4], with large firms having significantly higher productivity than small ones, but the great majority of firms are small and many are doing labour intensive repair and maintenance work. This structural characteristic of the industry has and will continue to limit growth in construction productivity.

 

*

 

[1] A previous post argued against comparison with manufacturing. 

 

[2] Ed Glaeser has done previous research on this, in Glaeser, E. L. and Ward, B. A. 2009. The causes and consequences of land use regulation: Evidence from Greater Boston. Journal of Urban Economics, 65(3):265-278. See here for Gyourko, Saiz, and Summers, 2006, on their Wharton Residential Land Use Regulatory Index.

 

[3] The article uses data for 42 countries that represent about 90 percent of construction’s global VA. Sources used include the International Labour Organization, IHS Markit and S&P Global, the OECD, the United Nations, and national statistical agencies, such as the National Bureau of Statistics of China and the US Bureau of Labor Statistics.

 

[4] A 2024 post on Australian firms noted ‘large firms are less than one percent of the number of firms, they employ 14 percent of the people and produce 21 percent of industry value added. Medium and large firms have much higher levels of productivity, measured as IVA per employee. For large firms this is $195,000, nearly twice the micro firm IVA per employee of $100,000.’