For most organizations, improving data management practices requires changing how people work together and how they understand the role of data in their organizations, as well as the way they use data and deploy technology to support organizational processes. Successful data management practices require, among other factors:
- Learning to manage on the horizontal by aligning accountabilities along the Information Value chain
- Changing focus from vertical (silo) accountability to shared stewardship of information
- Evolving information quality from a niche business concern or the job of the IT department into a core value of the organization
- Shifting thinking about information quality from ‘data cleansing and scorecards’ to a more fundamental organizational capability
- Implementing processes to measure the cost of poor data management and the value of disciplined data management
This level of change is not achieved through technology, even though appropriate use of software tools can support delivery. It is instead achieved through a careful and structured approach to the management of change in the organization. Change will be required at all levels. It is critical to manage and coordinate change to avoid dead-end initiatives, loss of trust, and damage to the credibility of the information management function and its leadership.
Data management professionals who understand formal change management will be more successful in bringing about changes that will help their organizations get more value from their data. To do so, it is important to understand:
- Why change fails
- The triggers for effective change
- The barriers to change
- How people experience change
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