If you work with data in large enterprises, you will be aware that the data, and the ability of the business to access that data is seldom as “good” as it should be. But just how “good” or “bad” is it?
This post outlines a process for assessing the status of common Enterprise-Wide Data Governance issues within your enterprise, or that of a client. I use it as the basis for my “Data Governance Health Check”.
These issues can impact your ability to deliver the underlying data required for meaningful CRM, Business Intelligence, etc.. More seriously, they can impact your ability to satisfy regulatory compliance demands (e.g. GDPR, BCBS 239, Solvency II, Anti Money Laundering, BASEL II etc.) in a timely cost effective manner.
Do issues like these affect your enterprise? If not, how have you resolved or prevented them? Please share your experience by posting a comment.
Common Enterprise-wide data governance issues:
Explanation of the scale and the process for using it:
There are 6 levels on the scale, starting at level 1, and increasing to level 6. The higher the score, the better prepared the organisation is to deal with the issue. The worst case scenario is actually a score of ZERO, which means that management in the enterprise is not even aware that the issue exists. To assess the actual status of an issue, ask for documentary evidence to illustrate that the Enterprise has actually reached that level:
Figure 1: Status of a (data governance) issue.
|1. Aware||Senior Management is aware that the issue exists.e.g. Data Quality is not measured, or measured in ad-hoc manner.#Evidence: Captured in Issues Log or Requirements document.|
|2. Understands||Senior Management fully understands the issue; the impact of not addressing it; options available to address it, complete with the pros and cons of each option.e.g. Issue paper explains the impact of no Data Quality Metrics on downstream data dependent projects etc.Evidence: Issue Paper, Rationale paper or Point of View paper(s).|
|3. Policy defined||Senior Management has a clearly stated policy/strategy identifying the selected option.e.g. Data Quality Measurement must be performed by each Business Unit, using a standard Enterprise Wide Data Quality Measurement process….Evidence: Policy document / Design Principles/ Communications/ education material|
|4. Process defined||The organistaion has a clearly defined process detailing exactly how the policy / strategy will be implemented, which common services / utilities must be used, and exactly how to use them.E.g. The standard Enterprise Wide Data Quality Measurement process will use ‘off the shelf tool X’, to produce a standard set of Data Quality metrics….Each BU must train N staff in the use of the tool. Training will take place……Evidence: End To End Process documentation / Education and Training material.|
|5. Infrastructure in place||Infrastructure (systems / common services / utilities) needed to implement the process is in place.E.g. ‘off the shelf tool X’ has been licenced and installed Enterprise Wide. Staff have been trained …Pilots have been run…Evidence: Programme Infrastructure document / Utility user manuals.|
|6. Governance in place||Governance is in place to ensure that the defined policy is implemented in accordance with the defined process.E.g. The stakeholders are…The Data Steering Enterprise includes the CIO and ….The reporting process is….. The following controls are in place….Evidence: Programme Governance document / Education / completed sign-offs|
How do you assess Data Governance within your organisation, or that of a client? Please share your experience by posting a comment – Thank you – Ken.