With data quality still one of the biggest challenges facing business intelligence, companies should consider appointing data stewards.
According to Gartner, the success of data stewardship requires organisations to move toward a culture that views data as a competitive asset rather than a necessary evil and define clear goals for data-quality improvement.
"Data quality is a business issue, not an IT matter, and it requires the business to take responsibility and drive improvements," says Ted Friedman, research vice-president at Gartner. Appointing data quality stewards help organisations achieve data quality improvement goals. Such individuals should be considered subject-matter experts for their departments and act as trustees of data, rather than owners of it. They will ensure that quality is maintained to make the data support business processes.
For example, a marketing specialist from the company¹s marketing department could act as the data steward in the data quality improvement programme by keeping marketing data complete, correct, consistent, honest and not redundant. In this role, they would have responsibility for ensuring marketing-relevant information adheres to the corporate data quality standards.
Poor data quality severely inhibits many strategic business initiatives such as customer relationship management (CRM), business intelligence (BI) or any effort requiring significant integration of data. A recent European Gartner BI survey of more than 600 BI users found that more than 35% identified data quality as a top-three BI problem facing their organisation in the next 12-18 months, making it the second biggest challenge overall.
To alleviate this problem, Friedman recommends that each major business function have data stewards, including sales, marketing, service, production, finance, HR and IT.
"Successful and effective data stewards reside in the business, are visible, respected and influential they must have the vision to understand the importance of data quality to the overall business objectives, as well as the impact of quality issues on downstream business processes," he adds.
The leader of the steward team – the corporate sponsor for data quality – will serve as the ultimate point of decision on issues and conflicts occurring across stewards and teams.
"Many data stewardship programmes have resulted in little or no improvement because the organisation selected the wrong individuals as stewards or because those individuals were not organised and managed in a way that ensures success," Friedman says.
Successful stewards are placed closest to the point of data capture and maintenance, are intimately knowledgeable about the data and its use in a business context. They have also a stake in improving quality. As such, they are empowered to make business process changes and apply resources to address quality issues. Furthermore, they can influence how their peers execute business processes to achieve further improvements.
In addition, stewards are in an ideal position to help with an effective governance strategy for data quality, since governance must cascade across the entire organisation to ensure that appropriate accountability is enacted and enforced.
According to Gartner, the governance duties of stewards are to:
* Ensure the consistency and accuracy of data as it flows from one application to the next.
* Implement governance tasks and achieve data quality metrics pertaining to the accuracy and completeness of information in their domain.
* Be responsible for the elements that support data sharing and master data management objectives (such as official product hierarchies, valuation models, customer segmentation profiles and preferred suppliers).
* Support ongoing profiling activities and identify issues with source systems (such as calculation routines and missing values).
* Create or update document taxonomies and actively participate in the semantic reconciliation of data models.