By: Joe Polizzano, Principal
An effective data governance program is an enabler of business value and not a series of complex control mechanisms that may impede delivery. An effective program can help optimize business processes, improve the customer experience, and unlock new commercial opportunities while protecting the firm with prudent risk management practices. How does one define and execute an effective program? In my experience, successful programs address these six primary areas:
1. Practical Strategy – Insurance and financial services firms are complex entities with multiple business lines driven by mergers, acquisitions, spinoffs, new ventures, and of course, changing technology. Leading companies are establishing transformation initiatives that cross business lines to unlock additional value from data. An effective governance program has a vision that aligns to business value, with an execution roadmap that is driven by specific business priorities. This usually requires cross-functional teams of data, technology, and business lines. Incremental execution keeps the teams focused on business priorities while delivering measurable value sooner rather than later. The aggressiveness of the roadmap can be tailored to the maturity of the organization, starting with a selection of high-value projects and extending to a dozen or more concurrent projects in a mature organization. You want to avoid gaps between strategy formulation and execution.
2. Organization and Culture – Massive reorganizations are not embraced by large companies to avoid disrupting ongoing operations. A governance program must recognize this reality to be effective. Keeping a focus on business value as described in the first point above helps. In addition, commitments from the various groups in an organization are crucial to executing the roadmap. Governance leadership is critical to establish these commitments, and effective leadership does not shy away from gaining these commitments. You want to avoid any tendency to isolate governance to those projects where it has control, which is especially essential regarding technology or the solutions may be as non-optimal as the current state. An incremental roadmap can also help gain consensus across stakeholders.
3. Focus – Organizations have a plethora of data. An effective governance program melds data priority with business priorities. For example, a customer experience program may require data from multiple business lines. Certain critical data elements must be aligned to ensure data quality. An internal business process improvement may have another set of critical data elements. A risk management initiative may be concerned with private or confidential data to meet PII or GDPR regulations. Avoid boiling the ocean and treating governance of all data equally. As the organization matures, critical data elements that apply across the organization will surface usually related to identifiers of significant data assets such as customer, sponsors, plans, securities, prices, etc. and will need to be treated with special care.
4. Stewardship and Quality – Mature organizations treat data as an enterprise asset. Data stewards are responsible for the definition, quality, and lineage of these data assets. Organizations vary as to where these data stewards reside. They may reside in business lines since that is where the domain expertise is most urgent, or in a corporate group. An effective governance program defines universal data principles that guide all data stewards regardless of location. These principles ensure governance is appropriate for both the business line and the broader firm. Avoid stewardship that operates in silos or, worse, the lack of data stewardship altogether.
5. Technology – I mentioned earlier the need to partner with technology. Roadmaps must align since improvements to the data ecosystem often require changes to architecture and the introduction of new technology. Technology is rapidly adopting new processes such as agile development to accelerate delivery. The classic model of governance as a control point does not work in this environment. Effective governance programs embed data stewards into the agile process itself. Guided by data principles and their domain knowledge, this allows the data organization to be an enabler of rapid delivery rather than an inhibitor. Avoid isolating data governance in its bubble. Additionally, emerging technologies such as automated semantic identification of elements and automatic classification of data can be used to improve the data governance process.
6. Communication and Change Management – Finally, effective governance programs communicate to stakeholders. This is a form of internal marketing that is critical to success. Change management is equally important. Are operational processes defined? Is issue management effective? Are ownership and accountability clear? Are training programs in place?
By driving a data governance program based on business value, an organization can ensure the quality of data within its business areas as well as become an enabler of new business opportunity.
Interested in learning more? NEOS has extensive experience helping companies modernize data practices and unlock the value of their data to drive business results.