The quality of information is paramount. Ask business executives whether they have enough information to do their job and they will say no. Ask the same executives whether the information they do get is entirely trustworthy and they will also say no. Even more dramatic, consider the success and failure of major information technology initiatives. Systems that have been implemented with poor user interfaces but high-quality content are generally regarded as successful, whereas systems that have failed to correctly migrate data, even with the best user interfaces, are regarded as abject failures. In other words, in both business management and technology implementation, there is a direct causal relationship between the quality of information and successful outcomes.
While everyone agrees that data quality is important, there is very little that is truly agreed about either measuring or improving data quality. The problem seems to relate to a common misunderstanding about how to measure or manage the quality of information. Some of the techniques are sophisticated while others simply require a logical and consistent approach.
As you know, yesterday Fannie Mae filed a Form 8-K/A with the SEC amending our third quarter press release to correct computational errors in that release. There were honest mistakes made in a spreadsheet used in the implementation of a new accounting standard.
|--Jayne Shontell, Fannie Mae Senior Vice President ...|