The analysis of pretender building price forecasting performance: a case study

The financial management of the construction procurement process is dependent upon on the performance of the managers involved. This paper describes an analysis of pre-tender building price forecasts (estimates) made by a Hong Kong consulting organisation for a series of 89 building projects from 1995 to 1997 to identify factors influencing the accuracy of the forecasts made for possible improvement in performance. This involved the consideration of two distinct sets of models the purpose of which was (1) to identify and explain the underlying systematic causes of errors and (2) to assist in improving the predictive ability of the forecasts. The analysis for (1) first followed the conventional approach of summarising the distributional characteristics of the errors for subgroups of each of the variables available – building size (value), building size (floor area), forecasting (estimating) method (approximate quantities and superficial), nature of the work (new build and alteration work), type of client and type of project. The statistical results of this analysis (ANOVA) showed the only significant effect, in both bias and consistency, to be the forecasting method used. This was followed by the recently developed Gunner-Skitmore Price Intensity (PI) theoretic analysis, which simultaneously removed the confounding effects of the conventional treatment and confirmed the applicability of PI theory to the case study. The analysis for (2) involved regressing all the independent variables, and a variety of transformations, on an additive as well as multiplicative version of the dependent variable, using cross-validation analysis to simulate the ex-post errors. No significant improvement on current practice was possible. It is concluded that the forecasting performance of the case study company was excellent for the period under study, in terms of both relative accuracy and resistance to improvement by statistical modelling. The original aspects of the paper are: 1 The provision of a new data set 2 The first direct comparison of accuracy of conventional forecasting (estimating) methods since the 1950s and only the second ever. 3 A new, simplified, approach is used, which involves partialling out the effects of price intensity before testing for the effects of other variables. 4 The first confirmation of Gunner-Skitmore’s PI theory since the original paper 5 The first conscious application of PI theory to prediction (as opposed to explanation) 6 For the first time, current practice is shown to be near-optimal, in terms of resistance to improvement by statistical modelling 7 The method described contributes to a variety of potential methods for benchmarking practice and quality monitoring/improvement