1,324 research outputs found

    Profiling Essential Professional Skills of Chief Data Officers Through Topical Modeling Algorithms

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    Today enterprises are increasingly dependent on data to keep their business competitive and successful. To better harness values of data, more and more organizations are establishing Chief Data Officer (CDO) position. The professional skills of CDOs are rather diverse because CDOs are expected to undertake a variety of roles in their companies including enterprise data architect, data quality and governance manager, business strategy leader, business regulation compliance officer, etc. CDO is an emerging research field, few studies have been done on CDO. This paper tries to profile what are the key professional skills and education background that current CDOs have by studying their resumes on LinkedIn using topic modeling technique. This work is a step forward towards understanding the roles of CDOs in organizations and what are the professional skills and experience they may need have in order to undertake their responsibilities of managing data and realizing its true values for their organizations

    Design Dimensions for Enterprise-Wide Data Management: A Chief Data Officer’s Journey

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    To unlock additional business value, most enterprises are intensifying their enterprise-wide data management. In the case of the globally operating bank, we base this article on, a Chief Data Officer (CDO) organization is established for providing data governance and, in a second step, pushing data driven innovation forward. As many employees of the bank were not yet familiar with (or did not acknowledge) the need for enterprise-wide data management, this evolution exhibits characteristics of an organizational learning process. CDOs may want to actively steer this learning process by purposefully designing and adjusting their data management approach over time. Based on the major controversies the CDO has been confronted with, we propose four design dimensions for enterprise-wide data management and discuss the considerations for their configuration: (I) objective, (II) governance, (III) organization of data analytics, and (IV) expertise

    Automatic definition of engineer archetypes: A text mining approach

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    With the rapid and continuous advancements in technology, as well as the constantly evolving competences required in the field of engineering, there is a critical need for the harmonization and unification of engineering professional figures or archetypes. The current limitations in tymely defining and updating engineers' archetypes are attributed to the absence of a structured and automated approach for processing educational and occupational data sources that evolve over time. This study aims to enhance the definition of professional figures in engineering by automating archetype definitions through text mining and adopting a more objective and structured methodology based on topic modeling. This will expand the use of archetypes as a common language, bridging the gap between educational and occupational frameworks by providing a unified and up-to-date engineering professional figure tailored to a specific period, specialization type, and level. We validate the automatically defined industrial engineer archetype against our previously manually defined profile

    CDO Positions: A Study on the Impact of Chief Data Officers on Organizational Performance

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    Purpose – The purpose of this paper is to employ a strategic change view, with the appointing of a CDO, to develop theoretical links and empirically examine the association between the CDO’s presence and organizational performance utilizing accounting measures. Design/methodology/approach – Adopted for this study is the “matched sample comparison group” methodology, also known as the matched pair analysis, to empirically test the hypotheses, compare the performance of the treatment sample group with CDOs and the control sample group without CDOs, and assess the relationship between CDO presence and firm performance. The financial data for treatment firms with CDOs and control firms without CDOs was collected from the Compustat database. The Wilcoxon signed-rank test and regression analysis were used to analyze the performances for the treatment and control sample groups. Findings – Overall, the results indicate that firms that have lower performance will be more likely to appoint a CDO and still maintain a competitive cost structure relative to firms without CDOs. Even though the cost ratios of firms with CDOs were not lower after the appointment of the CDO than before the appointment, CDOs promptly improve their profitability relative to peers who do not have CDOs, without significantly increasing cost. Finally, prior year financial performance has very great impact on current year financial performance. Practical implications – With limited statistical confidence, due to a small sample and short period of performance measurements to analyze, as the CDO position is a quite new to Canada, the conclusion can still be made that: CDOs are hired when performance is low and excel at solutions, which they seem to bring swiftly, by improving revenues and profitability without significantly increasing costs. This research further addresses both the academic and business communities emphasizing that, in this moment in big data history, the position of the CDO is not to be ignored or disregarded, as this role may prove to appreciably advance and elevate corporate Canada. Originality/value – The study explores the relationship between the CDO’s presence and firm performance. It is the first attempt to explore the CDO’s impact on the profit and cost performances from a purely Canadian perspective, evaluating only firms listed on the Toronto Stock Exchange – TSX. Prior studies have been from a global standpoint and heavily focused on the United States of America

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