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Towards Information Governance of Data Value Chains: Balancing the Value and Risks of Data Within a Financial Services Company

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Knowledge Management in Organizations (KMO 2017)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 731))

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Abstract

Data is emerging as a key asset of value to organizations. Unlike the traditional concept of a business value chain, or an information value chain, the concept of a data value chain has less currency and is still under-researched. This article reports on the findings of a survey of employees of a financial services company who use a range of data to support their financial analyses, and investment decisions. The purpose of the survey was: to test out the idea of the data value chain as an abstract model useful for organizing the different discrete processes involved in data gathering, data analysis, and decision-making; and to further identify issues, and suggest improvements. While data and its analysis is clearly a tool for supporting the delivery of financial services, there are also a number of risks to its value being realized, most prominently data quality, along with some reservations as to the relative advantages of data-driven over intuitive decision-making. The findings also raise further data and information governance concerns. If implemented these programmes can aid in the realization of value from data, while also mitigating the risks of value not being realized.

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References

  1. Blake, R., Mangiameli, P.: The effects and interactions of data quality and problem complexity on classification. Assoc. Comput. Mach. Comput. Surv. 41(3), 1–52 (2011)

    Google Scholar 

  2. Foster, J.: Towards an understanding of data work in context: issues of economy, governance and ethics. Libr. Hi-Tech 34(2), 182–196 (2016)

    Article  Google Scholar 

  3. Gartner: Governance of master data starts with the master data life cycle. Stamford CT, Gartner Research (2008)

    Google Scholar 

  4. Jorge, M., Ismael, C., Bibiano, R.: A data quality in use model for big data. Future Gener. Comput. Syst. 63, 1–8 (2015)

    Google Scholar 

  5. Kasim, H., Hung, T., Li, X.: Data value chain as a service framework: for enabling data handling, data security and data analysis in the cloud. In: International Conference on Parallel and Distributed Systems, vol. 18, pp. 804–809 (2012)

    Google Scholar 

  6. Khatri, V., Brown, C.V.: Designing data governance. Commun. ACM 53(1), 148–152 (2010)

    Article  Google Scholar 

  7. Liu, J., Li, J., Wu, J.: Rethinking big data: a review on the data quality and usage issues. J. Photogram. Remote Sens. 115, 1–9 (2015)

    Article  Google Scholar 

  8. Miller, H., Mork, P.: From data to decisions: a value chain for big data. IEEE Comput. Soc. 15, 57–59 (2013)

    Google Scholar 

  9. OECD: Data-driven innovation: big data for growth and well-being (2015). http://www.oecd.org/sti/data-driven-innovation-9789264229358-en.htm Accessed 30 April 2017

  10. Ofner, M., Straub, K., Otto, B., Oesterle, H.: Management of the master data lifecycle: a framework for analysis. J. Enterp. Inf. Manage. 26(4), 472–491 (2013)

    Article  Google Scholar 

  11. Pipino, L.L., Lee, Y.W., Wang, R.Y.: Data quality assessment. Commun. ACM 45(4), 211–218 (2002)

    Article  Google Scholar 

  12. Tallon, P.P., Ramirez, R.V., Short, J.E.: The information artifact in IT governance: toward a theory of information governance. J. Manage. Inf. Syst. 30(3), 145–181 (2013)

    Article  Google Scholar 

  13. Vera-Baquero, A., Colomo-Palacios, R., Molloy, O.: Real-time business activity monitoring and analysis of process performance on big-data domains. Telematics Inf. 33, 793–807 (2016)

    Article  Google Scholar 

  14. Wand, Y., Wang, R.Y.: Anchoring data quality dimensions in ontological foundations. Commun. ACM 39(11), 86–95 (1996)

    Article  Google Scholar 

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Author information

Authors and Affiliations

  1. Information School, University of Sheffield, Regents Court, 211 Portobello Street, Sheffield, S1 4DP, UK

    Haifangming Yu & Jonathan Foster

Authors
  1. Haifangming Yu
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  2. Jonathan Foster
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Correspondence to Jonathan Foster .

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Editors and Affiliations

  1. University of Staffordshire, Stoke-on-Trent, Staffordshire, United Kingdom

    Lorna Uden

  2. Bei**g Jiaotong University, Bei**g, China

    Wei Lu

  3. Department of Information Management, University of Kaohsiung, Kaohsiung, Taiwan

    I-Hsien Ting

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Yu, H., Foster, J. (2017). Towards Information Governance of Data Value Chains: Balancing the Value and Risks of Data Within a Financial Services Company. In: Uden, L., Lu, W., Ting, IH. (eds) Knowledge Management in Organizations. KMO 2017. Communications in Computer and Information Science, vol 731. Springer, Cham. https://doi.org/10.1007/978-3-319-62698-7_28

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  • DOI: https://doi.org/10.1007/978-3-319-62698-7_28

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-62697-0

  • Online ISBN: 978-3-319-62698-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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