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RF2268AM - CONSTRUCTION PRODUCTIVITY MEASUREMENT: A COMPARISON OF TWO CASE STUDIES 1
دوشنبه 29 فروردین 1390

CONSTRUCTION PRODUCTIVITY MEASUREMENT: A COMPARISON OF TWO CASE STUDIES 1

   نوشته شده توسط: عارف محمدی    نوع مطلب :مدیریت منابع سازمانی ،

 

Paul Chan[1] and Ammar Kaka2

                                  

1 Salford Centre for Research and Innovation in the Built and Human Environment (SCRI), University of Salford, Bridgewater Building, Salford, Postcode M7 1NU, UK

 

2 School of the Built Environment, Heriot-Watt University, Edinburgh Campus, Edinburgh, Postcode EH14 4AS, UK

 

 

The construction industry remains one of the few most labour intensive industries in the developed world. It is therefore imperative to understand the measure of construction labour productivity. Furthermore, recent institutional and industrial calls for an increase in productivity suggest a desperate need to get the measurement of productivity levels right. The research reported in this paper forms part of an ongoing Ph.D. study into the issue of construction labour productivity. An earlier study highlighted that less than 50% of the industry actually actively measure and monitor productivity levels, with a majority of those companies that claim to measure go about measuring on the basis of the intuition of key site management personnel. This may seem alarming, however, it was argued that productivity measurement techniques could be perceived as theoretical, arduous and expensive for construction companies to adopt. This paper reviews the methods of productivity measurement available and describes two case studies conducted during this research, with a view of reporting the problems and issues faced when attempting to establish productivity levels at a project level. Lessons learnt are then drawn from the experience.

 

 

Keywords: construction, measurement, productivity, project site.

 

 

 

 

 

INTRODUCTION

The quest for productivity improvements in the UK construction industry has been an especially important agenda over the last decade (Latham, 1994; Egan, 1998). However, what is found baffling is the fact that the measure of productivity is often conflated with the measure of performance. One only needs to turn to the Construction Productivity Network (CPN) to seek an instance of such misapprehension. Indeed, the very name of the network is misleading since it deals with such far wider issues as risk management and knowledge management. Clearly, the network might be more suited to have adopted the term Construction Performance Network as compared to the use of the term productivity, which traditionally refers to the quantifiable ratio between inputs and outputs in physical terms.

 

Indeed, the industrial Key Performance Indicators (KPIs) rightly recognise the clear distinction by acknowledging the measure of productivity as a subset of the wider measure of business performance. However, in the pursuit of convincing the industry to take on board improvement programmes and initiatives, recommendations have tended to represent simplistically improvements through headline measures such as reduction in construction time, defects, accidents etc., for instance, in the case of the Movement for Innovation (M4I) demonstration projects. Productivity, interestingly, was measured by the M4I by taking the median of the company value added in monetary terms per employee. This value added approach mirrors the value-added approach conventionally applied at the industrial (macroeconomic) level (see e.g. Jonsson, 1996). While it is understandable, from a marketing perspective, to report headline indicators per se, given the fact that embarking on any initiative undoubtedly needs corporate buy-in by senior managers, it is felt that capturing productivity measurements at the strategic level may be insufficient to guarantee that improvements actually occur at the operational level. Therefore, it is firmly believed that going back to the basics of measuring productivity at the project site level would be necessary in facilitating improvements. This is because the construction industry is largely project-based. Groák, for instance, issued a stern warning that there is an inherent “failure to recognise that the site was the defining locus of production organisation (1994: 288)” for construction.



1 Author for correspondence. E-mail: p.w.c.chan@salford.ac.uk

However, there lies a problem here. Apart from the formal measures propounded by such initiatives as the M4I stated above, many construction companies just do not have formal measures in place at the project level. For example, Chan and Kaka (2003), in a questionnaire survey to 400 UK contractors, found that of the 77 respondents, more than half of them do not monitor productivity levels at the project level. Furthermore, a third of those who claim to do so base their judgement of productivity on gut feeling and experience of dealing with contract schedules. Similar findings were noted in a large study commissioned by the Investors in People in the UK, which was aimed at examining productivity measurements inter alia across sectors including manufacturing, transport, service and construction. The Investors in People (2001) noted that while 22% of the respondents did not measure productivity levels at all, 36% and 22% of the respondents used formal and informal techniques to establish productivity levels respectively. Yet, past research have shown that the very process of formalising on-site productivity measurements itself delivers project improvements. For example, Winch and Carr (2001) notably identified a growing competitive spirit among the workforce as they progressed in their study investigating the benchmarking of on-site productivity, thus reinforcing an earlier comment made about the importance of measuring productivity levels at the project site level.

 

Nonetheless, Chan’s and Kaka’s (2003) and the Investors in People (2001) reports beg the question as to why there is reluctance for formal productivity measurements, and which forms the premise of this paper. The chief aim of this paper is to explore the pertinent issues that would explain some of the reasons behind what we would call industrial inertia towards productivity measurement at the project level. In so doing, we would tackle it from both theoretical and practical perspectives. The next section briefly reviews the key textbook approaches to measuring on-site productivity and highlights the limitations in terms of reliability and relevance of these approaches that restrict industrial adoption. Thereafter, we will report on the relevant findings of two live projects observed as part of a wider study into understanding the concept of construction labour productivity, revealing some of the practical issues encountered when measuring on-site productivity. Conclusions are then drawn from both the review and the case studies that lead to the recommendations for future research that would hopefully encourage the industry to measure on-site productivity.

 

PRODUCTIVITY MEASUREMENT TECHNIQUES

Construction textbooks are awash with details of key productivity measurement techniques and it would be inappropriate to replicate the explanation of these techniques within the constraints of this paper. According to Noor (1998), productivity measurement techniques fall within a spectrum between two broad categories of observational methods, namely continuous observation (e.g. direct observation and work study) and intermittent observation (e.g. audio-visual methods, delay surveys and activity sampling).

 

Noor recognised that while continuous observations such as direct observation and work study provide high levels of accuracy and detailed data for understanding productivity, these are often time-consuming, arduous and costly. Given the operational imperative of construction projects and the ever increasing time pressures exerted on project schedules, the cost of employing personnel to conduct such observations both in terms of the monetary cost of wages and the time value of observation that does not result in the physical growth of buildings (i.e. non value added) would deter companies from adopting such measurement techniques. Furthermore, the benefits of continuous observations are marred by the inexorable restriction of scope and thus, would make it difficult for large projects to pursue this approach. Where the use of technical equipment for audio-visual methods is concerned, Winch and Carr (2001) were especially cautious that the workers might feel that the surveillance was unnecessarily intrusive. As such, they avoided the use of such methods to observe the workers and opted instead for direct observation where the researchers got to know the individual workers on a personal level. Therefore, while the absence of the workers’ uneasiness was achieved, the inability to observe the whole construction process became an evident trade-off.

 

With respect to intermittent observations, Noor noted that these are prone to errors in determination since the data tends to be aggregated statistically through the observation of a representative sample. To add to this, Radosavljevic and Horner (2002) recently revisited formwork and masonry productivity data sets across eleven sites in the USA and the UK, only to confirm their suspicion that productivity is not normally distributed, thereby implying that “some basic statistical diagnostics… may give misleading results and are not applicable (p. 3)”. Accordingly, this questions the dubious reliability of conventional productivity measurement techniques. Serendipitously, Radosavljevic and Horner made a brief comparison of the data with volatility studies in econometrics to reveal surprising similarity with Pareto distributions, which are typical of chaotic systems. They concluded therefore that “using test statistics that rely on normality usually have been taken for granted, and consequently not much could have been done to achieve a better understanding of the ubiquitous complexity (p. 11)” as they call for a paradigm shift to understand the complexities of construction labour productivity, possibly through chaos theory. However, it is felt that such complex methods of analysing productivity levels might further discourage companies to measure productivity since this would mean additional investment of statistical expertise.

 


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