Pondering on Data and CDO (Chief Data Officer)

A successful approach to organizing a business is to avoid overhead, i.e. to decentralize responsibilities as much as possible and to centralize as little as necessary. Having this in mind, I closed an earlier post "Close encounters with the 3rd resource" postulating that business departments take their ownership and responsibility to govern Data as assets.

Since governing the other two main resources, Finance and Human Resources, as assets were established early on and practices are not widely disputed, it should be deemed worthwhile to explore how Finance and Human Resources are fostered in a balanced approach between centralization and decentralization:

In medium or large enterprises, Finance and Human Resources are typically represented by central organizational units, headed by the CFO (Chief Financial Officer) and the CHRO (Chief Human Resources Officer), respectively, each of them directly reporting to the CEO. In their respective realm, Finance and Human Resources a.o.

• Develop corporate target scenarios and related strategies
• Ensure that the organization follows legal and regulatory obligations
• Advise business departments regarding strategic and legal aspects
• Perform tasks that are not assigned to the department level, but to the corporate level (e.g. declare taxes, report to regulatory authorities, compose the balance sheet, negotiate with the workers' union)
• Provide standard templates / procedures that operational departments can / must apply (e.g. standardize expense reports)

Any item of the above list is abstractly applicable to the resource Data, therefore, I suggest that medium and large enterprises implement a central unit headed by a CDO (Chief Data Officer) who directly reports to the CEO. 

More precisely, the Chief Data Office(r)'s tasks ought to include e.g.

• Develop a High-Level Enterprise Information Management Map (also see my post here)
• Ensure that the organization follows worldwide-applicable regulations such as the GDPR (General Data Protection Regulation) and industry-specific regulations such as HIPAA, Solvency II, Basel III etc.
• Derive measures that respond to international, national and corporate requirements of Data Governance and advise business areas accordingly
• Develop a detailed data model for the intersection of business areas (Master Data)
• Conceive standard interfaces for Master Data Management and related hubs
• Build a corporate Business Data Dictionary

Taking this approach, the enterprise will fulfill a crucial prerequisite to govern Data as an asset of the organization.