Navigating the Organization to Ensure Data Governance - Data Governance: Creating Value from Information Assets - page 39

organizational objectives, and providing people with the resources they
need to act. Realistic metrics to measure the effectiveness of the data
governance program should be developed and an incentive mechanism
installed to reward those who meet or exceed their performance targets.
Value Recognition
For successful data governance, its value must be recognized. It is difficult
to quantify the value of data in dollar terms, but data is one of the most
important assets of any organization today and it has many intangible
benefits. The organization cannot function effectively without data stan-
dards and quality. Poor-quality data leads to compromised information
internally and dissatisfied customers externally. Therefore, in any data
governance effort, appreciation for the true value of business data is criti-
cal, along with upper management's financial support for the time, effort,
and expense to effectively manage that data.
Communication, especially from the upper management, including the
CEO, COO, CIO, and CFO, is crucial to building awareness of the impor-
tance of a data governance program. It leads to a cultural shift in thinking
about data as not just a commodity, but one of the organization's most
valuable assets. It leads to the creation of an organizational mindset of
accountability. Communication is vital to getting buy-in from the orga-
nization as a whole. The internalization of the value of data governance
is reflected in the formal communication by the sponsors of the data gov-
ernance program who are valued by the organization. Communication
from the executive sponsors and the chief data officer is key to getting
buy-in from the different quarters of the organization. The organization
culture should be one that supports and rewards openness, sharing, and
exchanging information within the organization.
Data Policies and Procedures
Effective data governance requires effective data policies and procedures.
To be effective, the data policies and procedures must be cross-functional
and not be dictated by the requirements of individual business units.
The data policies should be enterprise-wide and apply to the business as
a whole. If there is a lack of an enterprise-wide data governance model
and vision, data chaos will likely follow, leading to immense data quality
problems. A clear data governance strategy and consensus on what makes