Data Governance Structure and Ownership of the Data

On data governance structure the respondents had a shared view that the participation on the data governance work should be company-wide. It should be organized in the cooperation with the business units including participation from different business units, sales, customer communications, marketing, customer service and finance. The Senior Business Analysts brought up the importance of finance to be involved in data governance. They said it is important to ensure that the internal and external figures are matching.

About the ownership of the customer data and overall responsibility the views of the respondents were not as similar. Marketing Director thought that ownership should reside in her organization, which also has the overall responsibility of the customer communications. Director of Business Unit, Data Manager and Customer Data Analysts said that the ownership should not be within some business unit in order to avoid silos. Senior Business Analysts were only ones stating that ownership of customer data should reside within business units.

Support and commitment from top management was seen important in the interview of Data Manager and Customer Data Analysts. They said that it is needed to give authority to execute possible changes needed in for example CRM systems. Also, the characteristics of the person leading data governance activities were discussed in the interview of the Senior Business Analysts. According to them, the person should be interested and excited about the subject and have continuous drive to get things done. Also, in their opinion case company should avoid building too much hierarchy on data governance.

Previously it has been stated that data governance should create guidelines though whole company for data quality management, define roles and responsibilities and involve both business and IT stakeholders. (Weber & al, 2009) This case study shows that the selected members of the case company expect data governance to be organized in a way that the needs of different parts of the company are taken into account. All the respondents viewed this from business or marketing point of view, not from IT point of view. This could be because the respondents were from more business than IT related functions but it also tells that the respondents expect data governance especially benefit the case company in reaching business goals.

The involvement of the executive management is seen as important in organizing the data governance in the previous studies. Data governance organization should have an executive sponsor who provides sponsorship and sets strategic direction for data governance activities and is a member of the executive management of the organization. (Weber & al, 2009) There is no common view on this matter, but the locus of control should be located in both executive management and mid-level management. (Otto, 2011b) Korhonen & al (2013) goes further on stressing the importance of the involvement of the executive management. According to them, previously presented models for organizing data governance focus on the functional issues and operations are led several levels below top management.

Because of this, they fail to address data governance across the whole organization. (Korhonen & al, 2013) Contradictory to these theories, the studies among practitioners show that data governance activities are led several levels

below top management in practice. (Otto, 2011b; Pierce & al, 2008) In this case study the respondents looked the involvement of the top management in data governance from the practical point of view. If the top management does not support and authorize the data governance activities, it could be hard to get other parts of the organization to commit for these activities.

The characteristics of the persons in key positions of the data governance activities have been described in the previous studies. Executive sponsor should have high credibility within the organization and should have a drive and ability to achieve changes through data governance. Another important role, chief data steward, should have leadership and communication skills and ability to address business- and IT-related issues to make data governance effective. (Korhonen &

al, 2013) The respondents in this case study see that the success of data governance is depending the people and will. According to them, someone has to be responsible and excited about data governance in order it to succeed. Rather than hierarchical positioning or functional skills of a person, they see the personal characteristics important factor for success.

There is not available commonly agreed view on the balance between centralized and decentralized decision-making in data governance, it should be decided depending on the organization’s characteristics. (Otto, 2011b) In centralized data governance the decision authority is in one location and decisions are organization wide. If it is decentralized, the decisions are made in different functions and are not necessarily organization-wide. Also, there can be a mix of these two, meaning some decisions are made in a centralized manner and others in more decentralized manner. (Weber & al, 2009; Khatri & Brown, 2010) In this case study the respondents are not directly addressing this issue, but they indicated that they should avoid building too much hierarchy and bureaucracy in data governance processes. This is interpreted that the members of the case company expect the data governance to have straightforward decision-making processes.

6.1.5 Recapitulation of the Findings  

Table 5 presents the findings discussed previously in the same format as in Table 4 is presented six case studies where The Morphology of Data Governance was tested at the time. (Otto, 2011b) Similarly in this case study the two aspects of the concepts developed in the morphology of data governance, goals and structure, can be found. Formal goals in this case study are more concrete and have a direct relation to the case company’s strategy. Although the respondents did not explicitly state how to measure these goals, at least the improvement of the cross- and up-sales can be seen as quantified goal. This case study also shows that respondents expect significant improvement in operational efficiency. In the six case studies presented in table 4 none of the cases had quantified goals and improvement in operational efficiency is not as clearly present as in this case study. On formal goals respondents in this case study explicitly stated expectations for data governance to benefit to IT related issues such as CRM migration and continuous data quality improvements. Many of the functional goals are similar in this case study as in the six case studies the comparison is done. In this case study respondents expect data governance to improve knowledge sharing, increase general trust in the data and provide company-wide definition what is a customer. These aspects were not present in the six case studies.