Data Governance Maturity Model for Micro Financial Organizations in Peru

Stephanie Rivera, Nataly Loarte, Carlos Raymundo, Francisco Dominguez

Abstract

Micro finance organizations play an important role since they facilitate integration of all social classes to sustained economic growth. Against this background, exponential growth of data, resulting from transactions and operations carried out with these companies on a daily basis, becomes imminent. Appropriate management of this data is therefore necessary because, otherwise, it will result in a competitive disadvantage due to the lack of valuable and quality information for decision-making and process improvement. Data Governance provides a different approach to data management, as seen from the perspective of business assets. In this regard, it is necessary that the organization have the ability to assess the extent to which that management is correct or is generating expected results. This paper proposes a data governance maturity model for micro finance organizations, which frames a series of formal requirements and criteria providing an objective diagnosis. This model was implemented based on the information of a Peruvian micro finance organization. Four domains, out of the seven listed in the model, were evaluated. Finally, after validation of the proposed model, it was evidenced that it serves as a means for identifying the gap between data management and objectives set.

References

  1. Soares, S. (2010). The IBM Data Governance Unified Process: Driving Business Value with IBM Software and Best Practices.1st edition. Ketchum: MC Press.
  2. World Vision (2014). Economic Development. [Online]. Available at: http://m.worldvision.org/content/economicdevelopment?&origin=www.worldvision.org%2Fourimpact%2Feconomic-development [Accessed 16 July 2016].
  3. EY (2014). Big Data Changing the way businesses compete and operate. [Online]. Available at: http://www.ey.com/ Publication/vwLUAssets/EY_- _Big_data:_changing_the_way_businesses_operate/%24FI LE/EY-Insights-on-GRC-Big-data.pdf [Accessed 19 July 2016].
  4. The Guardian (2014). New Digital Universe Study Reveals Big Data Gap. [Online]. Available at: http://www.emc.com/ about/news/press/2012/20121211-01.htm [Accessed 20 July 2016].
  5. Ponemon Institute and IBM. (2015). The cost of data breach study: Global Analysis. [Online]. Available at: http://www01.ibm.com/common/ssi/cgibin/ssialias?subtype=WH&infotype=SA&htmlfid=SEW03 053WWEN&attachment=SEW03053WWEN.PDF [Accessed 22 July 2016].
  6. Aiken, P., Allen, D., Parker, B., and Mattia, A. (2007). Measuring Data Management Practice Maturity. IEEE Computer Society, 42, pp. 43-50.
  7. Spruit, M. and Pietzka, K. (2015). MD3M: The master data management maturity model. Computers in Human Behavior, 51, pp. 1068-1076.
  8. IBM (2007). Data Governance Council Maturity Model: Building a roadmap for effective data governance. [Online]. Available at: https://www-935.ibm.com/services/uk/ cio/pdf/leverage_wp_data_gov_council_maturity_model.p df [Accessed 24 July 2016].
  9. Informatica (2015). Transforming financial institutions through data governance. [Online]. Available at: https://now.informatica.com/en_transforming-financialinstitutions-through-data-governance_whitepaper_2882.html#fbid=gt6PYccHzOO [Accessed 26 July 2016].
  10. Wende. K. (2007). A model for data governance - organizing accountabilities for Data Quality Management. ACIS Proceedings, 19, pp. 417-425.
  11. Weber, K., Otto, B. and Osterle, H. (2009). One size does not fill all: A contingency approach to data governance. ACM Journal of Data and Information Quality, 1(4), pp. 1-27.
  12. Vijay K. and Brown, C. (2010). Designing Data Governance. Communication of the ACM, 53, pp. 148-152.
  13. Malik, P. (2015). Governing Big Data: Principles and practices. IBM Research Journal, 57(3), pp.1-20.
  14. Zhu, H., Madnick, S., Lee, Y., Wang, R. (2014). Data and Information Quality Research: Its Evolution and Future. Computing Han book: Information Systems and Information Technology, 3, pp. 16.1-16.20.
  15. Gestion (2015). Microfinance and its decentralization role. [Online]. Available at: http://gestion.pe/mercados/ microfinancieras-y-su-rol-descentralizador-2138997 [Accessed 22 July 2016].
  16. Deloitte. (2014). Personal Data Protection Law: Practical Approach. [Online]. Available at: https://www2.deloitte.com/content/dam/Deloitte/pe/Docum ents/risk/ley_n29733_la_experiencia_implementacion.pdf [Accessed 20 March 2016].
  17. Arnold, M. (2016). Insurance broker warns on financial groups' cyber-attack cover. Financial Times. [Online]. Available at: https://www.ft.com/content/93b7eabc-1bb4-11e6-8fa5- 44094f6d9c46 [Accessed 20 April 2016].
  18. KPMG (2014). Governing Strategies for managing data lifecycles. [Online]. Available at: https://www.kpmg.com/ ES/es/ActualidadyNovedades/ArticulosyPublicaciones/Do cuments/frontiers-finance-governance-strategies-managingdata-lifecicle.pdf [Accessed 18 June 2016]
  19. EY (2011). Data Loss Prevention Keeping your sensitive data out of public domain. [Online]. Available at: http://www.ey.com/Publication/vwLUAssets/EY_Data_Lo ss_Prevention/$FILE/EY_Data_Loss_Prevention.pdf [Accessed 18 June 2016].
  20. Oracle (2011). Enterprise Information Management: Best Practices in Data Governance. [Online]. Available at: http://www.oracle.com/technetwork/articles/entarch/oeabest-practices-data-gov-400760.pdf [Accessed 16 June 2016].
  21. DataFlux Company (2010). Data Governance Maturity Model. [Online]. Available at: http://www.fstech.co.uk/fst/ whitepapers/The_Data_Governance_Maturity_Model.pdf [Accessed 10 June 2016].
  22. CMMI Institute (2014). Data Governance Maturity Model. [Online]. Available at: http://www.fstech.co.uk/fst/ whitepapers/The_Data_Governance_Maturity_Model.pdf [Accessed 9 June 2016].
  23. Kalido (2010). Kalido Data Governance Maturity Model. [Online]. Available at: http://docplayer.net/2788287- Kalido-data-governance-maturity-model.html [Accessed 15 June 2016].
  24. ECM (2009). Enterprise Content Management Maturity Model - ECM3. [Online]. Available at: http://mike2. openmethodology.org/wiki/ECM_Maturity_Model_(ecm3 )#_note-ftn3 [Accessed 12 June 2016].
Download


Paper Citation


in Harvard Style

Rivera S., Loarte N., Raymundo C. and Dominguez F. (2017). Data Governance Maturity Model for Micro Financial Organizations in Peru . In Proceedings of the 19th International Conference on Enterprise Information Systems - Volume 3: ICEIS, ISBN 978-989-758-249-3, pages 203-214. DOI: 10.5220/0006149202030214


in Bibtex Style

@conference{iceis17,
author={Stephanie Rivera and Nataly Loarte and Carlos Raymundo and Francisco Dominguez},
title={Data Governance Maturity Model for Micro Financial Organizations in Peru},
booktitle={Proceedings of the 19th International Conference on Enterprise Information Systems - Volume 3: ICEIS,},
year={2017},
pages={203-214},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006149202030214},
isbn={978-989-758-249-3},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 19th International Conference on Enterprise Information Systems - Volume 3: ICEIS,
TI - Data Governance Maturity Model for Micro Financial Organizations in Peru
SN - 978-989-758-249-3
AU - Rivera S.
AU - Loarte N.
AU - Raymundo C.
AU - Dominguez F.
PY - 2017
SP - 203
EP - 214
DO - 10.5220/0006149202030214