A successful data management organization enables the achievement of business goals and objectives efficiently and in a cost effectively manner. DM organizations which consistently achieve this have a clear, robust, and well-defined data management strategy. Overlooking these five simple but often forgotten considerations when building your data management strategy and you diminish the data management organization’s ability to enable business success.
1. Work to Achieve Data Governance Owned by the Business
In order for a data governance program to be successful, it must be owned by the business. While the business owns governance, IT is a necessary partner in modifying applications to allow for assessment and enforcement. In successful data governance the business owns the responsibility of defining and implementing policies and standards, additionally providing input into the direction of the data management organization. Policies and standards which govern data require a deep knowledge of the business and are the most effective way to manage and control its valuable data. Without ownership from the business, data governance may falter or fail altogether. Through a business-IT partnership, data governance can by effective and productive.
2. Incorporate Legal and Compliance Requirements
It’s easy to neglect the legal and compliance aspects of data management, but doing so can lead to costly issues in the future. Many times legal and compliance issues arise long after the initial data has been created and stored. However, being able to quickly find information which was archived long ago or ensuring that 3rd party data retention and usage policies are being adhered to, can prevent headaches down the road.
3. Actively Manage Data Quality
We work in a world of data-driven decision-making. Ask employees and they will likely tell you they spend hours validating the data necessary to do their jobs. Measuring, monitoring, and ensuring the quality of data allows the business decision makers to have confidence that their decisions are informed and accurate. Managing data quality enables the business to proactively identify and react to anomalies in the data. This in turn measurably increases the time employees can spend on value-add activities: a clear win for the DM organization.
4. Identify the Single Source of Truth for Each Data Set
In conjunction with data quality, identifying a single trusted source for each data set is vital. This reduces the time that employees spend searching for and validating data. By using a single trusted source, employees are able to consistently access up-to-date, quality data. When the focus is keeping the trusted source updated and accurate, then the result is economies of scale. Employees no longer spend time compiling, validating, cross-checking, or guessing which data source to use. The added benefit is that maintaining a single source reduces data silos – key information is tracked centrally and readily shared across the organization for many uses.
5. Business Champions Increase Adoption and Ultimately Success
To derive full value from the data management strategy, it must be used and adopted by the business community. This requires an effective communication and change management plan. This plan will help to embed the data management processes and standards across the organization, ensuring successful adoption by the business.
Conclusion:
An effective data management strategy requires collaboration between the business and IT to ensure that the necessary business capabilities are in place. Keep these five considerations in mind as you develop your data management strategy: avoid common pitfalls and reap the greatest benefit from data management.
