The cost – significant item (CSI) method is a way to develop a simple cost estimate model by using historical bills of quantities (BOQ) in the construction industry (Horner, 1986; Saket, 1986; Horner and Asif, 1988; Bouabaz and Horner, 1990; Murray et al., 1990; Zakieh, 1991; Al-Hubail, 2000 cited Wang and Horner, 2007). Boqs as historical records of previous projects can be used to forecast the cost of future similar projects.
The various items in the bill contribute to its total value to different degrees. It has been found that a small number of items (around 20%) in a BoQ account for a large proportion of the total value (Barnes and Thompson, 1971; Saket, 1986; Asif, 1988; Bouabaz and Horner, 1990; Al-Hajj, 1991; Rahman, 1991; Zakieh, 1991; Liakou, 1997 cited Wang and Horner). These items are so important that about 80% of the price is shared by them in a BoQ. As these items contribute much more to the total than other items, they are named cost-significant items (CSIs). The mean value theorem (see Appendix 1) says that the cost drivers of a set of data are those significant items whose values exceed the average of the set of data, the mean value (Horner and Zakieh, 1996). The mean value theorem is explained by the cumulative distribution curve (Figure 1) which is the cumulative percentage item value versus cumulative percentage of item number. These items represent the majority of the total value, so they potentially offer an efficient way to handle the total value of a set of data by controlling only the significant items.
For similar projects, the CSIs have been found to be roughly the same, representing a consistent proportion of the total value of a project (Horner, 1986; Saket et al., 1986; Asif, 1988; Horner and Asif, 1988; Bouabaz and Horner 1990; Murray et al., 1990; Zakieh, 1991; McGowan, 1994). Many cost-significant models have been developed on the basis of this principle (Shereef, 1981; Horner, 1986; Saket et al., 1986; Horner and Asif, 1988; Al-Hajj, 1991; Zakieh, 1991; Asif, 1988; Bouabaz and Horner, 1990; Horner et al., 1990; Rahman, 1991; Liakou, 1997; Al-Hubail, 2000). The main sources of data for cost-significant models are historical BoQs. The cost-significance principle can simplify complex processes by focusing only on a small number of CSIs so that the minimum effort results in the greatest efficiency possible. For example, Saket (1986) found that projects can be categorized in such a way that the CSIs within any one category are more or less the same. Bouabaz and Horner (1990) found the same fact and developed a simple model for bridge repair work that reduces model complexity by some 60%.
The various items in the bill contribute to its total value to different degrees. It has been found that a small number of items (around 20%) in a BoQ account for a large proportion of the total value (Barnes and Thompson, 1971; Saket, 1986; Asif, 1988; Bouabaz and Horner, 1990; Al-Hajj, 1991; Rahman, 1991; Zakieh, 1991; Liakou, 1997 cited Wang and Horner). These items are so important that about 80% of the price is shared by them in a BoQ. As these items contribute much more to the total than other items, they are named cost-significant items (CSIs). The mean value theorem (see Appendix 1) says that the cost drivers of a set of data are those significant items whose values exceed the average of the set of data, the mean value (Horner and Zakieh, 1996). The mean value theorem is explained by the cumulative distribution curve (Figure 1) which is the cumulative percentage item value versus cumulative percentage of item number. These items represent the majority of the total value, so they potentially offer an efficient way to handle the total value of a set of data by controlling only the significant items.
For similar projects, the CSIs have been found to be roughly the same, representing a consistent proportion of the total value of a project (Horner, 1986; Saket et al., 1986; Asif, 1988; Horner and Asif, 1988; Bouabaz and Horner 1990; Murray et al., 1990; Zakieh, 1991; McGowan, 1994). Many cost-significant models have been developed on the basis of this principle (Shereef, 1981; Horner, 1986; Saket et al., 1986; Horner and Asif, 1988; Al-Hajj, 1991; Zakieh, 1991; Asif, 1988; Bouabaz and Horner, 1990; Horner et al., 1990; Rahman, 1991; Liakou, 1997; Al-Hubail, 2000). The main sources of data for cost-significant models are historical BoQs. The cost-significance principle can simplify complex processes by focusing only on a small number of CSIs so that the minimum effort results in the greatest efficiency possible. For example, Saket (1986) found that projects can be categorized in such a way that the CSIs within any one category are more or less the same. Bouabaz and Horner (1990) found the same fact and developed a simple model for bridge repair work that reduces model complexity by some 60%.
No comments:
Post a Comment