Data quality issues in practice and theory : a cross-cultural example

Practical considerations and traditions play a substantial role in data collection exercises, often limiting the focus of study to either qualitative or quantitative issues. An industry with a particularly strong quantitative emphasis is the insurance and reinsurance industry, where actuarial decisions are based on detailed and exacting numerical analysis of data that are assumed to be reliable and valid. However, the qualitative investigation of the quality of data in one reinsurance setting reported in this paper shows that where the meanings of the questions asked and of the answers provided are subject to interpretation, the quality of data collected for entry to databases can be poor. While this can be exacerbated in cross-cultural contexts, it is also generally true. Due to the constrained nature of insurance practice, the existence of a range of techniques combining qualitative and quantitative methods is somewhat academic. Therefore, because researchers have the latitude to investigate both qualitative and quantitative factors in the industrial context, a call is made for researchers and industry to work more closely together.<br />