1.7 Requirements for Making Improvements

1.7 Requirements for Making Improvements

Too often executives look at quality problems as isolated instances instead of symptoms. This is a natural reaction, considering that they do not want to believe they have problems in the first place. They tend to be reactive instead of proactive. Making large improvements in the accuracy of data and the quality of information from the data can only be accomplished through proactive activities.

Considering the broad scope of quality problems, this is not an area for quick fixes. The attitude that should be adopted is that of installing a new layer of technology over their information systems that will elevate their efficiency and value. It is the same as adding a CRM system to allow marketing to move to a new level of customer care, resulting in higher profits.

The scope of quality problems and the potential for financial gain dictate that a formal program be initiated to address this area. Such a program needs to have a large component dedicated to the topic of data accuracy. Without highly accurate data, information quality cannot be achieved.

To get value from the program, it must be viewed as a long-term and continuous activity. It is like adding security to your buildings. Once you achieve it, you do not stop pursuing it. In spite of the fact that data quality improvement programs are long term, it is important to repeat that significant returns are generally achievable in the short term.

Some of the problems will take a long time to fix. The primary place to fix problems is in the systems that initially gather the data. Rebuilding them to produce more accurate data may take years to accomplish. While long-term improvements are being made, short-term improvements can be made through filtering of input data, cleansing of data in databases, and in creating an awareness of the quality that consumers of the data can expect will significantly improve the use of the data.

A major theme of this book is that you need to train all of your data management team in the concepts of accurate data and to make accurate data a requirement of all projects they work on. This is in addition to having a core group of data quality experts who pursue their own agenda.

There will still be times when overhauling a system solely for the purpose of improving data accuracy is justified. However, most of the time the best way to improve the overall data accuracy of your information systems is to make it a primary requirement of all new projects. That way, you are getting double value for your development dollars.