Organizations have never been confronted with more data management challenges and the costs & risks associated with inaccurate data have never been higher. With the sheer volume of data accumulating in organizations, it is not always easy to find the right data, let alone translate it into business insight.
Goals may be defined at all levels of the enterprise and doing so may aid in acceptance of processes by those who will use them.
Some goals include:
- Increasing consistency and confidence in decision making
- Decreasing the risk of regulatory fines
- Improving data security, also defining and verifying the requirements for data distribution policies
- Maximizing the income generation potential of data
- Designating accountability for information quality
- Enable better planning by supervisory staff
- Minimizing or eliminating re-work
- Establish process performance baselines to enable improvement efforts