Data provides a granular activity for analysts, whilst being a component of every project. It is an underestimated cost and essential in facilitating internal and external communication. As an industry we need to appreciate the positive consequences of managing data efficiently and the negative consequences of managing data badly. How to get it right, first time, every time?
ISC has implemented many data programmes for our investment management clients and we are convinced that data governance is the critical success factor.
Data Strategy is not Governance
Sadly data governance cannot be achieved by implementing one of several data strategies. The strategies below are important components of the middle office, but they do not deliver governance.
Data governance does cover the standards and principles of data management, but it determines ownership versus usage and is the mechanism used to measure the status of data within the organisation.
Data Governance does cover the standards and principles of data management, but it determines ownership v usage and is the mechanism used to measure the status of data within the organisation.
The Components of Successful Data Governance
Data standards and principles are the building blocks of good data governance. However, more importantly, data governance relies on an analysis of true ownership and usage of data to facilitate the production of meaningful management information. This information can then be used to drive appropriate and efficient change.
Good data governance is therefore predicated on the true understanding of who owns each element of the data in an organisation. Data governance determines who defines the standards and principles that the right of ownership confers. Data governance maps out the true community of data users.
Ownership (stewardship) and usage determines who delivers data changes and how the process of data change is delivered using the various data strategies. This process is measureable. True data governance tracks each element of changes from owner to user. It is able to record this change, produce management information and quantify success to data quality. The management information produced provides a health check as to the status of data. It identifies weakness and directs project spend.
Good data governance moves an organisation up the data maturity ladder from ungoverned to governed data. At the bottom of the ladder executives have little or no sight into the costs of badly integrated and maintained data. At the top of the ladder organisations have governed data and are equipped to deliver business-critical projects from the single, unified view of data.
Poor data governance will lead to failed or poorly delivered projects, overly large data operations and an inertia that inhibits growth.