Construction labour productivity analysis and benchmarking : the case of Tanzania
This research aimed at investigating strategies for construction performance improvement in Tanzania. The research established that the Total Quality Management (TQM) philosophy provides a feasible long term performance improvement strategy. Benchmarking was identified as a tool for initiating and sustaining the TQM programme. Labour productivity was selected as the key construction performance indicator. A framework for labour productivity benchmarking was developed, on the basis of current mean productivity (CMP) and target mean productivity (TMP). Construction labour productivity at macroeconomic level and site level were also investigated. Analysis at macro economic level over a twenty five year period between 1969 and 1993 indicated a continuous decline in productivity expressed in value added per person engaged. Site labour productivity was investigated for eight construction activities on 46 sites belonging to 23 different contractors. Two significant findings emerged in the analysis: first, the variability quantified by coefficient of variation was considerably higher than in similar studies elsewhere; and secondly the distribution was skewed to the left suggesting that productivity was low for most of the operatives. These characteristics were indicative of the productivity improvement potential in the Tanzanian building construction industry. A distribution modelling exercise established that Johnson SB distribution (with shape parameters, 11=1 and y=1) model well represented productivity distribution for most activities. From this distribution, it was established that about 85 per cent of operatives productivity was below the median, which provided a basis for quantifying the potential for improvement. The benchmarking model established that there was an improvement potential of about 133 per cent. This potential was verified through an opinion survey of operatives. Factors that influence operatives productivity were identified through an opinion survey. Factor related to motivation were ranked highest in the survey. Possible influence of various factors on productivity was quantified through regression modelling based on actual construction operation observations. This analysis indicated that productivity depended on productive time which is largely influenced by operative motivation, supporting the results of the opinion survey.