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Cost of quality and challenges in construction

Cost of Quality

Many concepts related to Quality Management have originated in the manufacturing industry and their implementation is being attempted in the construction industry. Manufacturing industry is characterized by steady‐state processes whereas the construction industry operates quite differently. Some examples of these differences are given below:

Therefore, methods or principles used to evaluate quality-related parameters like assessment, cost, etc. in the manufacturing industry need to be modified suitably, so that they may be applied effectively in the construction industry. The objective in a construction project is to meet the client requirements at the lowest possible cost. Any attempt to improve the quality, therefore, must consider the associated costs. It is here that the concept of ‘Cost of Quality’ (COQ) becomes relevant. Juran believed that it was important to link Quality issues with cost. Linking Quality efforts to conformance, defects and costs (and profits) is the only way to drive sustainable change in the management’s approach towards Quality. 

There are different definitions and associated models of COQ proposed by different experts/researchers. One of the simpler definitions/models of COQ is P-A-F model. As per this, COQ is the sum of the following elements.

These are called P (prevention), A (assessment) and F (failure) costs and the model that evolves out of this is known as the P-A-F model. This model is easy to understand and can use much of the data already available at the projects. Further, it can be applied by any contractor regardless of the sector, project size, employee competence and strength of the QMS in place. While the above sounds simple in theory, there are quite a few challenges in implementing it on a project. Some of these, in the context of the real estate sector in India are highlighted below.
Regardless of the challenges listed above, the need and benefit of measuring COQ in construction projects has been established beyond doubt. Studies in Australia, US, UK and Turkey have reported costs of failure to be in the range of 10-15% of the total project cost. This means that the COQ must be a much larger part of the total project cost. 

If we can identify the COQ and break it down into P-A-F costs, optimising the COQ and thereby total project cost should be possible. I hope that this is a strong enough driver for interested parties to start investing in identifying COQ [the cost of this effort itself will be ‘P’ cost]!

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