BUS631: Brand Management

In this part we show the characteristics of the selected studies and give an overview of the interest in the chosen topic over the years and the distribution of publications in different journals.

Overview

For a first overview, this study summarized the relevant papers (n=21) by source and document type, territory, source title, subject area, year of publication, key components (layer) and fields of action of Data Governance. Most of the papers published in (classical scientific and trade) journals, followed by conference proceedings and reviews. Books are source type "underdogs" (Table 2).

Table 2. Source and Document Type

Abbreviation(s): A = Article; CP = Conference Paper; R = Review; BC = Book Chapter; N = Note; Limitation(s): no multiple assignments

In terms of the territorial distribution of articles, the global camp is very dispersed (Table 3). The leading regions are Europe (e.g., UK, Finland, Sweden, France, Czech Republic) and North America (US), followed by Asia (e.g. India), Australia and South America (e.g. Brazil). All research papers provide a good insight into the topic. The African region is not covered, which certainly has potential for future research. Of critical importance is that collaboration between the regions as a whole is strengthened.

Table 3. Territory

Abbreviation(s): Qty = Quantity; Limitation(s): multiple assignments

Regarding the sources (Table 4), the articles can be found in various journals, which mostly address topics of Marketing, e-Business and Business Intelligence and Analytics. The conferences are predominantly conferences with focus on "Information Systems".

Table 4. Source Title

Abbreviation(s): J = Journal | TJ = Trade Journal | CP = Conference Proceedings | CS = CiteScore at Scopus for 2021 | Qty = Quantity; Limitation(s): no multiple assignments

The Scopus CiteScore 2021 counts the citations received in 2018-2021 to articles, reviews, conference papers, book chapters and data papers published in 2018-2021, and divides this by the number of publications published in 2018-2021. The distribution of articles within the scientific disciplines (Table 5) is balanced between "Science, Technology, Engineering, and Mathematics (STEM)" and "Business Administration" (which includes Economics, Finance and Accounting). This reflects the integrated view in terms of Business-IT-Alignment in the Marketing field.

Table 5. Subject Area

Abbreviation(s): Qty = Quantity; Limitation(s): multiple assignments

Looking at the years in which the above-mentioned articles were published, there is an increasing trend, although in the years themselves the numbers sometimes vary considerably (Table 6, Figure 4).

Table 6. Year of Publishing

Abbreviation(s): Qty = Quantity; Limitation(s): multiple assignments

Figure 4: Year of Publishing

This also correlates with Jagels et al. (2021), saying that publications concerning DG actually started in 2005 and has increased ever since. Nevertheless, the topic enjoys a constant attention in the academic world. The upward trend should continue in the future as a result of an increasingly data-driven world. According the defined term of Data Governance described above, the studies focus on all Data Governance key components (layer), primarily on processes and resources, but crossover aspects, like ethical considerations (known as data ethics), are applied (Table 7).

Table 7. Focused Data Governance Layer

Abbreviation(s): Qty = Quantity; Limitation(s): multiple assignments

In terms of fields of action of Data Governance (Table 8), the studies focus primarily on Data Protection, Security and Compliance (from the author's point of view as a consequence of the introduction of the GDPR in May 2018 and their implementation), Data Management (because of getting customer insights for decision-making) and Data Quality (because Marketing needs accurate and timely information to manage Marketing service effectiveness and to prioritize and ensure the best use of resources). Because of missing other action fields, like Data Scope, Data Catalogue or Data Lineage, research potential is given.

Table 8. Focused Action field of Data Governance

Abbreviation(s): Qty = Quantity; Limitation(s): multiple assignments

Content and Trending Topics

This chapter analyses the results of the review according to the theoretical introductions presented at the beginning of the systematic review. Recall that Data Governance is an enterprise-wide concept encompasses the strategy, processes and resources (people, ICT) needed to manage, protect and enhance an organisation's data capital (e.g. Marketing) in order to guarantee universally understandable, accurate, complete, trustworthy, secure and discoverable data. For this we systemized the results on the three levels - the key components of Data Governance, also on cross-over aspects and trending topics.

Strategy: Establishing Data Governance in Marketing requires direction to bring it into a "lived Framework" of an Organisation. This direction is provided by the Data Governance Strategy (Vision) with the goal of actively shaping and empowering the Marketing organisation to make the best use of its data capital as well as to manage the increasingly complex compliance requirements in a low-risk manner. This includes active responsibility at top management level, e.g. by a Board Member/Executive Director, as well as taking into account the peculiarities of the industry and operational organisation. Furthermore, this must be aligned with the corporate strategy.

Process(es): Furthermore, the results of the studies underline that Data Governance processes must be established, documented and lived in order to (a) minimise data silos, inconsistent data and incorrect classifications through establishing rules to reduce semantic and syntactic variability in data and data management, (b) permanently increase data quality by checking and measuring it - at least on a legal and regular basis and (c) restrict access to critical and sensitive data in order to meet data protection, data security and compliance requirements. In particular, compliance with regulatory requirements, such as the GDPR, are crucial for the acceptance of Data Governance. Such regulations are important because they can be helpful in clarifying grey areas. For example, the GDPR attempted to clarify what constitutes a high-risk use case and what is expected in these use cases (confirmatory test assessments, audits and the like). This kind of clarification increases process understanding and reduces risks. Company size also influences the process organizational form of data governance in a balance of automation and non-automation.

Resource(s): The competence of (Marketing) staff to understand the possibilities of data and the use of technology, as well as the understanding of software and computer skills are important skills for digital marketing organisations. In many companies, the role of "Chief Data Officer (CDO)" has been established to reflect the increasing importance of data (Earley, 2019). Its tasks and responsibilities must not collide with those of the "Chief Marketing Officer (CMO)", but a partnership of both is required: the CDO focuses on providing fully integrated information sources of sufficient quality, the CMO focuses on brand, communication and business strategy, as well as analytics, data, customer segmentation and social media. According data quality this activity is not an IT activity alone. It should by start in the IT, but it must be follow in business involving all business areas that create, utilize or report on business information. And all activities should be supported by the right ICT.

Cross-Over Aspects: Throughout all phases of Data Governance, ethical considerations must be integrated into the aspects of data collection, data security and data protection. In this respect, Data ethics is not primarily a privacy and security compliance exercise. It is also not about bias or fairness, but about the whole managing process: if, for example, rules for handling and protecting critical or sensitive data are not implemented or not implemented correctly, this can have an impact on people. This also applies to consent to the processing of data (e.g. in the context of a marketing campaign, as an active act by users of information systems (IS), whether digital or not. Users of IS must be able to determine with what content (that is, the information generated and exchanged within the IS) and under what perspective and what purposes the consent was given.

Trending topics: One of the emerging trends in Marketing is the introduction of AI methods. Data and its management are the most important resource for the successful implementation of an AI development project in Digital Marketing. However, not only the data itself, but also the performance of the learning algorithms influence the success and acceptance of AI in the marketing field.

Future Research and Limitations

The selected studies give a good first impression of Data Governance research in the Marketing field. Nevertheless, recommendations for further research are given here and limitations are pointed out.

Future research recommendations: The starting point of a Data Governance initiative is to measure the maturity of the Marketing organization , the ability or maturity level with respect to the asset data. Due this fact a specifically Data Governance Maturity Model for Marketing should be developed. This model helps the Marketing organization pass in its quest to achieve a fully developed data management program.

Further investigation on other fields of action of Data Governance should be done. This concerns (a) data catalogues providing a central view on meta data of Marketing data, (b) data lineage providing the information about the use, processing, quality and performance of Marketing data throughout its lifecycle, from original creation to deletion, (c) data ownership having legal rights and complete control over all Marketing data elements and (d) data scope establishing principles and procedures for the evaluation and prioritisation of high-value and high-risk Marketing data.

The Marketing organization and its changing role - in more and more digitalized companies as the customer journey becomes more complex - are another research object. At its core, it is about hiring and developing analytical skills while maintaining a culture of creativity, collaboration in hybrid work environments, and increasing competition for talent.

Another research aspect of particular importance is the question of sponsorship at management level or the organizational integration of the topic of Data Governance into corporate organization. The focus is on differentiating the Marketing function, especially the Chief Marketing Officer, from earlier established roles, e.g., the Chief Information Officer or Chief Technology Officer, and roles that have emerged more recently, e.g., the Chief Data Officer and Chief Digital Officer.

And last but not least, it is also a question of differentiating Data Governance from other Governance areas (e.g., knowledge governance and information governance), taking industry and company peculiarities into account.

Limitations of the study: With regard to the review conducted, some limitations should be noted. Firstly, the scope of the studies was not as large as the author had expected due to the current hype around the topic of Data Governance. Further studies using other types of research methods may provide additional information. Secondly, only one database (Scopus) was retrieved. Extending the search to other common libraries may also provide additional information. In addition, only articles written in English were considered. Furthermore, only the information contained in the selected studies was assessed and merged; therefore, some publication error cannot be completely excluded.