We live in an increasingly digitized world. The depth of customer data grows every day as businesses strive to understand and predict their customers’ behavior and expectations. However, this expanse of information comes with a responsibility to respect and protect customer data by enhancing information governance policies and practices.
Digital adtech data is creating new opportunities for marketing organizations to gather a more holistic view of their customers’ and prospects’ behavior in the online space, but these new sources and uses of digital data create privacy and security challenges. Marketing organizations will need to determine how they define, create, control, and use this data.
Internal policies and external regulations on the collection and use of this data should be a part of an organization’s information governance process. Information governance orchestrates people, processes, and technology to leverage data as an enterprise asset by establishing policies for the creation and usage of data within an organization. As marketing departments and the data they use continue to become a more central focus within the broader organization, the controls of that data will be under greater scrutiny, especially from a security and privacy perspective.
To properly address these privacy and security concerns, one must thoroughly consider several components of information governance: information governance organization, data stewardship, data quality management, metadata management, information lifecycle management, security and privacy.
While the “who and how” of traditional and digital customer data usage are functions of the privacy and security components, all the other information components, such as data stewardship, ownership, and data retention, are core aspects of the information governance responsibilities for using this data.
Each type of marketing customer needs to have a different set of discovery, control, and usage patterns in the organization that will have significant information governance impacts on data ownership, data stewardship, and privacy and security.
Digital data analytics is defined as the research and analysis of new sources of digital customer data for the marketing organization that can provide a richer set of understandings in marketing spend. One of the important themes of digital data analytics is that it does not replace traditional transactional sources of customer data (despite much of the hype surrounding digital data), but rather it augments traditional customer data by providing a broader view of the behaviors of a prospect or customer. Additionally, it challenges the marketing department to think more deeply about questions of identity and identity management, particularly as access to and the joining of first and third-party data along with second-party data increases in scope and scale.
To evaluate and answer the question of whether or not the data is safe would be to apply a series of tests to the use case(s) to determine the associated risk level. These tests can be organized into a simple framework that can help to drive clarity as well as identify areas of potential risk so that appropriate risk mitigation steps can be taken.
One of the key information governance themes in this text is that of data ownership. Typically, a data owner is that business or domain executive that generates and analyzes the data for a particular function of the organization. For example, the chief marketing officer is characteristically responsible for the sales and marketing transactional and analytics data. Their definitions and business rules are easily created, operationalized, and enforced in internal structured data. The question remains, however: how would an information governance process enforce the data ownership standards for unstructured external data such as Twitter and Facebook? Better still: who owns this data and how can it be safely used within the organization?
Digital data has raised many different organizational questions for both the marketing department and information governance that have not had to be considered in the past. Digital data control can be best defined as the information governance approach to integrating digital data for use into the organization in a secure manner that will ensure maximum benefit without undue risk. It determines how to best integrate digital data into the organization, both from technical and security perspective. The four types of digital data all raise the following questions “Who owns the data?” and “How is it managed?”
The challenge for information governance is to ensure that once digital data is discovered and determined to be of value for the organization, it will be defined, qualified, and controlled, not unlike other organizational data. Two risks need to be mitigated. One risk is that the digital data that is targeted for use is not authorized for organizational use (e.g., customer information gleaned without permission from social networks or that has security issues such as viruses). The second risk is that vast amounts of digital data are staged and integrated only to not be used, thus creating unneeded operational and maintenance costs.
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