Data Governance Issues in Digital Marketing

Conclusion

This paper presents the topic of Data Governance in the Marketing environment. From the analysis of the study results, the author concludes that Data Governance has a great potential to develop a systematic and integrative view of (relevant) data in Marketing. For this approach theoretical aspects and practical implications are marked out.

Theoretical Aspects

The aim of this work was to promote a better understanding of the extent to which Data Governance in the Marketing environment can support the targeted maximization of the value of Marketing data. This study makes an important contribution to the Marketing literature by presenting current studies from the fields of action of Data Governance and summarizing their results. It thus presents an overview of the current state of assimilation of Data Governance in the Marketing field.

The research addresses all three levels of Data Governance for the marketing division - strategy, processes, resources. This is a clear reflection of the fact that Data Governance is seen as an integrative approach. A well-designed strategy supports uniform, standard processes as well as responsibilities and shows which data - from the point of view of data security and data protection - require careful control and how support (human, IT) can be provided in a way that makes sense in terms of resources. Customer-oriented business units can benefit from a homogeneous data infrastructure if it bundles standardized data and databases in a socio-technical structure. This applies in particular to standardization of the way master data is collected, stored and maintained, the quality of which increases customer satisfaction.

Data governance helps in overcoming various challenges in complying with data protection and data security regulations. Providing transparency in data processing can be a competitive advantage for customer-facing businesses. In more and more digitalized and thus data-driven companies, the topic needs to be anchored organizationally at the highest management level. It is advantageous to have a high-level sponsor within the company.

Practical Implications

In addition to the theoretical insights, this study also offers a number of implications for marketing practitioners. First and foremost, practitioners must recognize that Data Governance does not exist "out-of-the-box". It has to be developed individually for the respective company. Since the know-how for handling data is usually already available in the company, it is not necessary to reinvent everything.

This study has confirmed that Data Governance must have a clear strategy from which concrete goals can be derived, which in turn are concretized in a concrete governance plan. Such a plan includes not only the procedure for how decisions are made when processing data, but also the documentation of data protection and data security principles, ownership and responsibilities. It should be noted that the organization of decisions as well as the principles of data protection and data security are not the same for all data and it is therefore advisable to group data semantically, i.e., with the same requirements. This facilitates the definition of rules.

From this point, Data Governance processes need to be defined, described and established. When designing and implementing Data Governance, the specifics of the operational organization and the respective industry must be taken into account. This has an influence on the concrete organizational structure and process organization and the use of people and machines in a sensible combination as a socio-technical system.

Furthermore, Data Governance must be understood as a continuous (improvement) process. The results achieved must be continuously compared with the defined goals in order to correct the measures and, if necessary, the goals. For this purpose, metrics that are as measurable as possible are already defined in the data governance strategy. Suitable tools for collecting values for the defined metrics are interviews or anonymous surveys.