Improving the Performance of Guyana s Construction Industry through the use of Benchmarking and Industry Maturity Modeling

CIB W107 Construction in Developing Countries International Symposium Construction in Developing Countries: Procurement, Ethics and Technology 16 18 January 2008, Trinidad & Tobago, W.I.. Improving the Performance of Guyana s Construction Industry through the use of Benchmarking and Industry Maturity Modeling Christopher J. Willis and Jeff H. Rankin Department of Civil Engineering, University of New Brunswick, PO Box 4400, Fredericton, New Brunswick, Canada, E3B5A3, E-mail: a0r2g@unb.ca Abstract Guyana s construction industry is used extensively in the country s national development strategy and therefore its performance is critical to national prosperity. Indications are that the industry is not performing to its capabilities, thereby presenting an opportunity to research the influences on performance and develop solutions to effect positive changes. One approach to improving construction industry performance is the adaptation and use of benchmarking. An innovative approach to improving construction industry performance is through the use of maturity modeling, first developed and used by the computer software manufacturing industry. Both benchmarking and maturity modeling have relative strengths and weaknesses, but when used together, are likely to provide a comprehensive assessment of the industry s performance and foster holistic plans for performance improvement. This paper reports on issues associated with the proposed use of benchmarking and industry maturity modeling as a means of assessing and improving the performance of Guyana s construction industry. It has been found that there are issues associated with the use of benchmarking as the sole method of assessing the industry s performance and the use of industry maturity modeling will provide an appreciation of the industry s capabilities as it regards innovations and sustainability, which at the moment, is lacking. Keywords: Benchmarking, Construction Industry, Guyana, Industry Maturity Model, Innovative Introduction Guyana s construction industry is greatly relied upon in the country s National Development Strategy (NDS). The NDS places emphasis on the construction of physical infrastructure, more so the construction of paved roadways throughout the country which will encourage: the resettlement of the country s population from the coast to the interior, easy access to the country s natural resources and increased trade with Brazil which will greatly benefit the economy [NDS, 2000a]. The importance of Guyana s construction industry is also highlighted in the World Bank [2007] country report which mentions the need for Guyana to improve and expand its insufficient physical infrastructure in the areas of water distribution, health care, education and housing so as to improve the standard of living of its citizens. In addition, the increased activity and importance of Guyana s construction industry is reflected in the increase of the industry s GDP from about 265 million Guyana dollars in 1993 to about

468 million Guyana dollars in 2003 [Bank of Guyana, 2004] and is projected to further increase to about 1501 million Guyana dollars in 2010 [NDS, 2000b]. Guyana s construction industry has been performing poorly and for this reason it has often been the subject of debate in articles from Guyana s print media such as Stabroek News [2007a, 2007b, 2007c]. Also, the poor performance of Guyana s construction industry has often been highlighted through sporadic subjective criticisms by local industry observer groups such as the Guyana Association of Professional Engineers (GAPE). Lacking at the moment is substantial research focusing on how to assess and improve the performance of Guyana s construction industry. Recently, benchmarking has been used as a mechanism for the assessment, and by extension, the improvement of the performance of the construction industry. Benchmarking is a management tool which has its genesis in the copier industry, being pioneered by Xerox [McCabe, 2001] and is defined as a systematic process of measuring and comparing an organization s performance against that of other similar organizations in key business activities [Costa et al, 2006]. Benchmarking is currently implemented in the construction industry at the project and organizational levels through various schemes in countries such as the US, UK, Canada, Australia and the Netherlands [Bakens (2005), Benjamin (2007)]. The application of benchmarking in the construction industry, being relatively new, has some unresolved issues. The major unresolved issue is it is not clear as how to aggregate aspects of project performance so as to represent the performance of the entire industry [CCIC, 2007], which would allow for a holistic approach to improving the industry s performance. Also, benchmarking provides a weak assessment of the performance of the construction process with respect to innovation and sustainability. Maturity modelling, which has its genesis in the software manufacturing industry is a relatively novel approach of assessing and improving the performance of the construction industry. Recently, maturity modelling has been adopted and used by the Project Management Institute (PMI) as a means of assessing and improving organizational project management practices in the form of the Organizational Project Management Maturity Model (OPM3). [PMI, 2005] The approach used by PMI OPM3 appears to be a suitable method of assessing maturity at the level of the construction industry and will provide a context in which the performance of the construction projects can be interpreted and plans for improvement developed. This paper reports on a proposed research which will benchmark the performance of construction projects in Guyana and model the maturity of Guyana s construction industry based on the approach used by PMI OPM3. This research is based on the old axiom: you can not improve what you do not measure, and as such, will provide a methodology which can be replicated and used as a means of assessing and improving the performance of the construction industry in developing countries. The remainder of this paper discusses the current use of benchmarking and maturity modelling in the construction industry highlighting their unresolved issues. The paper concludes by briefly discussing the combined use of benchmarking and industry maturity modelling as a method of assessing and improving the performance of the construction industry.

Current Construction Industry Benchmarking Schemes Benchmarking is currently implemented in the construction industry at the organizational and project levels, with the developed countries such as the US, UK, Canada, Singapore, Australia, Hong Kong and Holland leading the way. Bakens [2005] discussed the benchmarking schemes used in the UK, USA, Netherlands, Australia, Singapore, Denmark and Hong Kong. Costa et al [2006] discussed the benchmarking schemes used in Brazil and Chile, whereas Benjamin [2007] discussed the benchmarking schemes used in Canada. At present the UK has five active benchmarking schemes in its construction industry and along with the US has led the way in the development and implementation of construction benchmarking schemes. The construction benchmarking schemes used in other countries have adopted performance metrics and data collection approaches developed by the US and UK. [Bakens, 2005] At present there appears to be no construction benchmarking schemes in developing countries which implies that developing countries are yet to fully accept and implement benchmarking as a means of improving the performance of the construction industry. The current benchmarking schemes in the developed countries have one of three areas of focus which are procurement, performance improvement and customer satisfaction. The operations of the schemes range from self assessment questionnaires to benchmarking clubs and in most cases the main outputs of the schemes are publications and quality ratings used to certify high performing firms and projects. Also, in some progressive construction industries such as the one is Queensland Australia benchmarking is used as a basis for the award of public sector construction contracts. Current Issues In Construction Benchmarking Current issues concomitant with the use of benchmarking as a means of assessing and improving the performance of construction projects range from determining which construction activities / objectives to benchmark, how to efficiently collect benchmarking data and how to best analyze the benchmarking data. In order, therefore, to refine and improve the benchmarking of construction projects we must firstly seek to resolve these issues. Identification of Construction Activities / Objectives to be Benchmarked The identification of construction activities / objectives to be benchmarked is usually done based on the goals / objectives of the construction industry and its stakeholders. Fisher et al [1995] in their early benchmarking pilot study on the US construction industry identified the top 10 construction activities / objectives to be benchmarked at the project level, which in order of importance, were: actual versus authorized costs, actual schedule versus estimated schedule, scope changes, engineering rework, actual construction labour versus estimated construction labour, field rework, worker hours per drawing, project cost distribution, field defects, and percent of rejected welds. In a more recent study done by Canadian Construction Innovation Council or CCIC [2007] it was found that the Canadian construction industry considered the following as being important to the industry s performance: capitol cost, project delivery time, predictability, defects, accidents, productivity, revenue and profit, research and innovation investment, projects with sustainability in the procurement process and projects procured based on life cycle cost. While the objectives of cost, time and quality

are common to both industries and time periods, CCIC [2007] highlights a shift in the focus of the construction industry. There is currently an interest in the industry s performance as it relates to innovation and sustainability; construction activities / objectives that are important to both developed and developing countries. The current challenge in this regard is to get developing countries such as Guyana to recognize the benefits of assessing and improving the performance of its construction industry with respect to innovation and sustainability, in addition to the construction activities / objectives of cost, time and quality. The most appropriate way of achieving this is to carry out pilot study which will prove to industry stakeholders that the performance of the industry with respect to innovation and sustainability can be properly assessed and improved. If this is achieved, it will be the first step in promoting innovative and sustainable construction in developing countries such as Guyana. Data Collection in Construction Benchmarking The data collection phase of the project level benchmarking process is often the most critical and time consuming phase and directly affects the accuracy and relevance of the resulting performance measures. Based on this, it is important to ensure that benchmarking data is accurate and representative of the actual performance of construction projects. For example, in an attempt to collect accurate and representative benchmarking data, the recent CCIC [2007] benchmarking pilot study used a data collection approach which was based on personal and telephone interviews as well as on the review of project files at study participants sites. This approach, according to CCIC [2007] resulted in the impact of the workload on the participants being kept to a minimum thereby encouraging cooperation in the execution of the study. Also, it was found that there was little difference in the completeness and accuracy of the information collected between the in-person interviews and the telephone interviews [CCIC, 2007]. The CCIC [2007] pilot study identified the main issues associated with the collection of data required by the various performance metrics as being those concerned with availability and accuracy. The findings of the CCIC [2007] benchmarking pilot study highlight the need to develop a method of data collection which will address the issues of availability and accuracy. While some may argue that the approach to data collection in construction benchmarking will depend on the circumstances and situations present in the construction industry, it can be argued that construction industries use project management and monitoring practices that are universal and will therefore have similar approaches in record keeping, especially as it regards the common construction objectives of cost, time and quality. Based on this, a construction benchmarking data collection manual can be developed which will provide guidance with respect to the sources of the various types of project data and methods of verifying the accuracy of the various types of data. A manual of this type will be an invaluable tool to developing countries seeking to improve the performance of their construction industries through the use of benchmarking. Data Analysis in Construction Benchmarking The data analysis aspect of benchmarking schemes and studies allows for a comprehensive understanding of how the industry is performing as a whole and how the industry s performance is changing overtime. [CCIC, 2007] Current data analysis

techniques in construction benchmarking include the use of radar charts, box plots and cumulative distribution curves. Work done by Benjamin [2007] and CCIC [2007] found that radar charts were the most easily understood data analysis techniques in construction benchmarking and contractors in particular found box plots to be easy to follow. Cumulative distribution curves were useful in showing an organization s performance compared against overall industry performance for a specific metric but were unsuitable for indicating the performance of a specific project. [CCIC, 2007] In addition to radar charts, box plots and cumulative distribution curves, data envelopment analysis (DEA) has been used as a means of analysis by Pilateris and McCabe [2003] in benchmarking the financial performance of Canadian contracting firms, i.e. benchmarking performance at the organizational level; and by Hantziagelis and McCabe [2006] to benchmark the operational performance of airports before and after reconstruction. Despite its use by Pilateris and McCabe [2003] and by Hantziagelis and McCabe [2006], DEA has been described by CCIC [2007] as being rarely used in the construction industry and does not appear to be as intuitive as other methods [CCIC, 2007]. The difficulty associated with using DEA as a means of analysing the performance of construction projects is that it requires a very large data set or sample size. Hantziagelis and McCabe [2006] seem to concur as they concluded in their study that the results of DEA analysis at the project level were biased due to a small sample size. Maturity Modeling In The Construction Industry One of the earliest attempts at maturity modeling in the construction industry has been through the application of the Fuzzy Industry Maturity Grid (FIMG) by Tay and Low [1994]. The FIMG is a systematic and systemic approach to qualitatively analyze an industry according to three fundamental dimensions, i.e. markets, technologies and structures [Tay & Low, 1994]. The overall maturity of the industry is determined based on the maturity of the three dimensions which in turn depends on the maturity of their respective characteristics. The maturity of the characteristics is assessed using a linguistic scale which is translated into a vector representing the maturity of the industry with respect to the three dimensions. The vector describes the maturity of the three dimensions as being either mature or developing. In another attempt at maturity modeling in the construction industry, researchers at Salford University developed the Standardized Process Improvement for Construction Enterprises (SPICE) based on the Capability Maturity Model (CMM) developed by Carnegie Mellon University [Finnemore et al., 2000]. Unlike the FIMG as discussed by Tay and Low [1994], SPICE focuses on the organizational level as opposed to the industry level and seeks to improve the processes of an organization. SPICE is a five step process improvement framework in which immature organizations are characterized by the unpredictability of their projects and are plagued by negative issues as it relates to cost, time and quality. Mature organizations on the other hand, perform better and are able to align technology, people management and process improvement efforts [Finnemore et al., 2000]. SPICE considers the maturity of a process to be the extent to which a specific process is explicitly defined, managed, measured, controlled and effective [Sarshar et al., 2007]. In this regard, SPICE uses a framework which places the organization at one of five levels of maturity which are basically evolutionary steps for continuous process improvement. The lowest level of

maturity is described as processes being chaotic while the highest level of maturity occurs when processes are being continuously improved by the organization. A recent attempt at maturity modeling is PMI s OPM3 which is similar to the approach used by SPICE. PMI s OPM3 is used by organizations to measure their maturity in relation to organizational project management best practices, with the results being used in the development of plans for organizational improvement in project management. The application of PMI s OPM3 is based on three interlocking elements: knowledge, assessment and improvement. The knowledge element is comprised of a body of knowledge of organizational project management best practices developed by PMI. In the assessment element, organizations assess their organizational project management maturity by comparing their practices with those in PMI s OPM3 body of knowledge. In order to assess its maturity an organization must be able to compare the characteristics of its current maturity state with those described by OPM3. [PMI, 2005] The assessment element of PMI s OPM3 has 2 phases. In the 1 st phase the organization determines which of the best practices in OPM3 s body of knowledge of best practices are currently demonstrated by the organization. In the 2 nd phase of the assessment, the organization gathers information at a detailed level in order to assess which specific capabilities, associated with each best practice, the organization does and does not demonstrate [PMI, 2005]. Figure 1 depicts the relationship between a best practice and its associated capabilities. The existence of a capability is identified by the existence of an associated outcome which in turn is identified by a KPI. BEST PRACTICE CAPABILITY 2 OUTCOME B KPI CAPABILITY 1 OUTCOME A KPI Figure 1: A Schematic showing the relationship between a best practice and its associated capabilities (developed from figures 3.2, pg16 and 3.3 pg17 [PMI, 2005]) As an example, consider Health and Safety practices in the construction industry. Appendix 1 lists some of the possible Health and Safety practices and their associated capabilities, outcomes and indicators. As with PMI OPM3, unique identification numbers are used to show the relationships between the best practices, capabilities, outcomes and indicators. This makes it easy to link the practices being demonstrated by the industry with their specific capabilities. Using the practices and capabilities listed in Appendix 1, we can comment that the construction industry is very mature with respect to Health and Safety when it has capabilities that lead to continuous improvement practices, such as capabilities 100.1 and 100.2 which lead to practice 100. On the other hand, the construction industry is least mature or developing with respect to Health and Safety when its capabilities are limited to those that lead to standardization practices, such as capabilities 103.1 and 103.2 which

are linked to practice 103. The possible levels of maturity of the construction industry are shown in figure 2 and include developing, transitional, mature and very mature. Very Mature: Continuous Improvement Mature: Control Increasing level of maturity Transitional: Measure Developing: Standardize Figure 2: Possible levels of maturity of the construction industry The approach to maturity modelling as done in OPM3 is yet to be applied at the industry level. While there are similarities between SPICE and OPM3, OPM3 appears to be better suited for use at the industry level as it provides a systematic and systemic approach to assessing the maturity of the industry s practices as opposed to the assessment of processes as done by SPICE. This is based on the fact that construction industry practices are likely to be universal whereas construction industry processes are likely to be unique. The FIMG as described by Tay and Low [1994] provides a method of assessing the industry s maturity that is inconsistent and unreliable given that it is based on fuzzy set theory, i.e. it uses imprecise data and makes approximations. Conclusion This paper has highlighted some of the issues associated with the use of benchmarking and maturity modeling in the construction industry. It is being proposed that the performance of the construction industry in developing countries such as Guyana will be best assessed and improved through the combined use of benchmarking and industry maturity modeling. The benchmarking of construction projects will provide an indication of the performance of the construction industry relative to the performance of other industries and construction industries. This will highlight where there is need for improvement and provide an opportunity to copy and implement best practices and processes. The benchmarking of the performance of construction projects, however, has an inherent weakness in that it ignores the conditions and circumstances under which projects are executed. This results in a false understanding of the performance of the construction industry and leads to the development of performance improvement plans that are out of sync with the real capabilities of the construction industry. Industry maturity modelling based on the approach used by PMI OPM3 provides a solution to the inherent weakness of project level benchmarking by providing a context in which the performance of construction projects can be interpreted. Also, industry maturity modelling will foster plans for performance improvement that are holistic in their approach. In addition, industry maturity modelling will provide a better understanding of the construction industry s propensity to be innovative and promote sustainable development, which at the moment is not accurately assessed by the use of benchmarking.

The ultimate benefit of this type of research is that it will provide developing countries such as Guyana with a performance assessment and improvement tool, which when used correctly will bring about desired changes in the construction industry s performance, especially as it relates to innovations and sustainability. References Bakens, W (2005) International Review of Benchmarking in Construction: Executive Summary. Roger Courtney Construction Innovations Ltd, UK. Benjamin, A (2007) Benchmarking Performance in Construction: A Case Study of the Canadian Public Sector. M.Sc Project Report, Department of Civil and Environmental Engineering, University of Alberta CCIC (2007) Measuring the Performance of the Canadian Construction Industry: Pilot Project Final Report, Canadian Construction Innovation Council, Toronto, ON. Canada. Costa, D. B., Formoso, C. T., Kagioglou, M. Alarcon, L.F. and Caldas, C (2006) Journal of Management in Engineering, 22: 158-167. Finnemore, M., Sarshar, M. & Haigh, R. SPICE: A Structured Process Improvement Tool for Construction. Located @ www.research.scpm.salford.ac.uk/spice/, accessed on June 30 2007 Fisher, D., Miertschin, S. and Pollock, D (1995) Benchmarking in Construction Industry. Journal of Management in Engineering, 11: 50-57. Hantziagelis, S. & McCabe, B (2006) Benchmarking Airport Reconstruction Projects. Canadian Journal of Civil Engineering, 33: 1571-1584 Hutchinson, A. & Finnemore, M (1999) Standardized Process Improvement for Construction Enterprises. Total Quality Management, 10 (4&5): 576-583 McCabe, S (2001) Benchmarking in Construction. Blackwell Science Ltd., London. National Development Strategy (2000a) NDS: Overview. Located @ http://www.sdnp.org.gy/nds/overview.pdf, accessed on 2007/05/24 National Development Strategy (2000b) NDS: GDP by Activity at Constant Factor Cost. Located @ http://www.sdnp.org.gy/nds/gdp2.html, accessed on 2007/05/24 Pilateris, P. & McCabe, B (2003) Contractor Financial Evaluation Model (CFEM). Canadian Journal of Civil Engineering, 30: 487-499 PMI (2005) Organizational Project Management Maturity Model: OPM3 Knowledge Foundation. Project Management Institute, Inc, Newtown Square, Pennsylvania.

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Appendix 1: A section of the proposed standard of construction industry best practices STANDARD OF CONSTRUCTION INDUSTRY BEST PRACTICES (Health & Safety) Directory 1: Best Practices (Health and Safety) ID# 100 The construction industry has mechanisms in place to continuously improve H&S ID# 101 The construction industry regulates H&S compliance ID#102 The construction industry maintains a database of accidents ID#103 The construction industry uses a H&S standard Directory 2: Capabilities (Health and Safety) ID#100.1 There are H&S training programs within the industry ID#100.2 The industry has active H&S awareness campaigns ID#101.1 The industry checks whether firms are complying with H&S regulations ID#101.2 The industry enforces laws governing compliance ID#101.3 Industry allocates funds towards H&S compliance ID#102.1 Contractors keep track of accidents occurring on their sites ID#102.2 Consultants discuss H&S issues in their monthly progress reports to the client ID#103.1 Aspects of a H&S standard are included / referred to in construction contracts ID#103.2 Contracting firms prepare H&S management plans for their individual projects Directory 3: Outcomes (Health and Safety) ID#100.1.A Workers receive training in H&S ID#100.2.A Workers are aware of their rights as it relates to H&S issues ID#101.1.A Firms are acknowledged as complying with regulations ID#101.2.A Firms are taken to court and fined for non compliance ID#101.3.A Contracts include a provision for H&S compliance ID#102.1.A Records of accidents are kept in site log book ID#102.2.A Progress reports contain a section dedicated to H&S issues ID#103.1.A Contract documents include clauses addressing H&S on the project ID#103.2.A Projects have H&S management plans Directory 4: Observable Indicators (Health and Safety) ID#100.1.A.x % of industry workers trained in H&S ID#100.1.A.y No. & frequency of H&S training programs within the industry ID#100.2.A.x No. of H&S brochures produced ID#100.2.A.y No. of H&S advertisements in the print and electronic media ID#101.1.A.x No. of acknowledgement letters and certificates issued ID#102.1.A.x No. of firms fined for non-compliance ID#102.1.A.y No. of H&S related cases heard in court ID#103.1.A.x No. of contracts which have a provision for H&S compliance ID#102.1.A.x No. of sites with a log book for recording accidents ID#102.2.A.x No. of progress reports which report on H&S issues ID#102.2.A.y Extent to which H&S issues are included in monthly progress reports ID#103.1.A.x No. of contracts which address H&S issues ID#103.2.A.x No. of projects with H&S management plans