## 4 Discussion, Limitations, and Conclusions
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\begin{tabular}{p{142.3 pt} p{142.3 pt}} \hline \hline
**Nr.** & **Question** & **Possible Answers** \\ \hline \multirow{8}{*}{1} & Pharma \\ \cline{3-3}  & Manufacturing \\ \cline{3-3}  & Automotive \\ \cline{3-3}  & Before we start your assessment, we want to know one detail: In which industry are you working? & Consumer products and goods \\ \cline{3-3}  & Life sciences \\ \cline{3-3}  & Energy \\ \cline{3-3}  & Chemicals \\ \cline{3-3}  & Other \\ \hline
2 & Day you want a benchmark with some recommendation for action? & Open text answer \\ \cline{3-3}  & Please let us know your mail address below. & 1. Incomplete: no data strategy in place or planned \\ \cline{3-3}  & & 2. Performed: initiative for establishing a data strategy is planned \\ \cline{3-3}  & & 3. Managed: initiative for a data strategy roadmap started by assessing the current status quo \\ \cline{3-3}  & How would you describe your data strategy? & 4. Established: a holistic data strategy is defined and communicated—for example: a roadmap and defined working packages \\ \cline{3-3}  & & 5. Predictable: the profound data strategy is integrated into the yearly overarching company strategy process \\ \cline{3-3}  & & 6. Innovating: the data strategy is continuously updated regarding trends/innovations and has a lasting influence for the whole company in terms of value creation \\ \hline \multirow{8}{*}{4} & 1. Incomplete: no established lifecycle or maintenance processes; no integration into an end-to-end approach \\ \cline{3-3}  & 2. Performed: processes exist, but only minimal end-to-end process integration \\ \cline{3-3}  & How do you rule your organization’s data management processes (data lifecycle, data maintenance, etc.)? & 4. Established: some established processes are partially integrated into the end-to-end approach \\ \cline{3-3}  & 5. Predictable: processes are very well established and almost fully integrated into the end-to-end approach \\ \cline{3-3}  & 6. Innovating: data processes are not only well defined but actively managed and refined as well as fully integrated into the end-to-end approach, resulting in efficient overall process execution \\ \hline \multirow{8}{*}{5} & 1. Incomplete: no data roles/committees or anything else; no willingness to invest in data resources \\ \cline{3-3}  & 2. Performed: a first step into a data organization is planned; some distributed knowledge exists within company & 2. Performed: a first step into a data organization (roles, committees, incl. enablement and training) is conceptualized \\ \cline{3-3}  & How mature is your data organization and data literacy skills? & 4. Established: data organization is implemented and communicated; most important stakeholders are enabled \\ \cline{3-3}  & 5. Predictable: an overarching data organization is in place, the needed enablement is done; a data culture is established \\ \cline{3-3}  & 6. Innovating: the established data organization is reviewed and adapted continuously; data competencies are spread all over; a data culture is well established and lived within the company \\ \hline \multirow{8}{*}{6} & 1. Incomplete: no approach \\ \cline{3-3}  & 2. Performed: data has been mapped across key systems \\ \cline{3-3}  & 3. Managed: initial successful attempts at harmonizing data across some systems \\ \cline{3-3}  & and normalization? & 4. Established: confirmed process to unify data has tackled main key data objects \\ \cline{3-3}  & 5. Predictable: advanced process has standardized and harmonized the majority of data across key systems \\ \cline{3-3}  & 6. Innovating: transparent cross-system data model including standards and guidelines at attribute level \\ \hline \multirow{8}{*}{7} & 1. Incomplete: no standardized approach \\ \cline{3-3}  & 2. Performed: some occasional initiatives were/are started to improve data and its quality, but no systematic approach \\ \cline{3-3}  & 3. Managed: standardized data quality management process and data improvement process are planned and conceptualized \\ \cline{3-3}  & 4. Established: settled approach with some ongoing data quality management and improvement \\ \cline{3-3}  & 5. Predictable: data quality management and continuous data improvement are actively managed and standardized enterprise-wide \\ \cline{3-3}  & 6. Innovating: data quality management and continuous data improvement is used to gain a huge competitive advantage \\ \hline \hline \end{tabular}
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