Creating the position of a chief data officer is rapidly coming into vogue in both the private and public sectors....
But what are the responsibilities of a CDO that aren't already covered in an organization? First, let's consider a definition of the role, such as the one provided by Wikipedia -- it says a CDO is "a corporate officer responsible for enterprise-wide governance and utilization of information as an asset." Meanwhile, TechTarget's chief data officer definition says a CDO's "main purpose is maximizing the value the company can realize from the increasing amount of data it generates and maintains."
You might think that a CIO, already in place, would be accountable for overseeing the data governance process and leading efforts to reap business value from corporate information. But in many organizations, the CIO role has been transformed over time into one dedicated more to deploying and managing data processing systems, networking equipment and other IT platforms. As a result, their emphasis on data governance has diminished -- or completely fallen by the wayside.
For the CDO role to be relevant, it must balance ensuring data usability from all perspectives with developing polices and processes for oversight and governance of a company's data assets. To accomplish that, there must be up-front clarity about three key facets of the job: developing an enterprise data strategy, instituting data stewardship and governance processes, and defining quantifiable measures of success. Each of those is vital to an effective data governance framework, which will become apparent as we examine them in more detail.
Get into the data flow
From the simplest perspective, an enterprise data strategy combines documentation of how data is currently being used with a vision of how information optimally should flow into and around an organization to best enable it to achieve corporate business objectives. From a practical standpoint, it should start with developing an inventory of data assets, identifying which business units "own" them and acquiring knowledge about the operational uses of individual data sets. You also need to catalog how data sets are formatted and managed -- for example, structured transaction data stored in relational databases versus unstructured documents kept in file systems.
Another key foundational element is documenting the data lifecycle: how data sets are created, captured, modified and used, including policies and processes on data retention, archiving and deletion. In addition, an enterprise data strategy should encompass data integration and data quality processes, metadata management and the development of a business glossary with standardized data definitions designed to increase the usability of information -- and reduce the likelihood of end-user confusion. Once all of that is in place, looking for ways to improve data flows and usage can help sharpen the strategy and increase organizational performance.
Effectively governing data means going beyond the creation of a data governance council -- especially if it ends up being neutered by scope limitations that hamper its effectiveness. To make the data governance process work, a CDO should ensure that an operating model for data stewardship and governance is developed with defined roles, responsibilities and levels of escalation to enforce compliance with rules for using business data. An approach that isn't accompanied by such a framework is bound to miss the mark.
Data governance by the numbers
Lastly, if a C-level position lacks quantifiable goals, the executive filling it is doomed to failure. Anyone taking on the CDO role should insist that performance measures for enterprise information management be clearly specified. If they aren't already defined, a CDO's first task should be to provide proposed metrics to the rest of the management team. Having tangible goals not only provides a means for monitoring progress, it also shields the CDO from being blamed for issues beyond his control.
Basic operational metrics can be included, such as the number of data sets cataloged and the number of business terms added to the glossary. But the real performance measures should reflect efficient and consistent use of enterprise data assets -- for example, broader adoption of self-service business intelligence and analytics tools, cost savings from eliminating duplicate data storage and a reduction in data errors and other quality issues.
Instituting governance policies and procedures with tangible business goals while also developing an overarching data strategy for an organization requires an individual with the proper skills, knowledge and characteristics. To be taken seriously, the CDO must rise above corporate politics, effectively communicate the value of data governance and take the right steps to engage both data practitioners and data users, creating a collaborative environment for managing and governing data.
The ultimate goal is to facilitate the optimal use of corporate data and the adoption of standardized reference data and common tools for data management, integration, reporting and analytics. And that shouldn't be done in a vacuum: The CDO must be held accountable by the senior management team to ensure that those objectives are being met successfully, and in a timely manner.
About the author:
David Loshin is president of Knowledge Integrity Inc., a consulting and development services company that works with clients on big data, business intelligence and data management projects. He also is the author or co-author of various books, including Using Information to Develop a Culture of Customer Centricity. Email him at firstname.lastname@example.org.
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