Abstract
The goal of the present paper is to introduce a new model for estimating business function recovery complexity in order to predict reasonable recovery timeframes in case of an unexpected information system failure. The method has its roots in the Use Case Points approach, which is a broadly tested tool for software complexity estimation. The current paper illustrates the pure theoretical form of the new model as well as the mapping between software complexity and business function recovery complexity. The method includes 3 categories of factors which affect the recovery procedure and are weighted according to the Rank Order Centroid (ROC) approach of assigning weights. The method is entitled Business Continuity Points. The idea behind the development of the new method is the establishment of a standard approach for implementing efficient time management regarding business function recovery. The estimated recovery time depends on the impact of technical, environmental and unexpected factors. Each function’s Recovery Time should be compared with the Recovery Time Objective (RTO) and Maximum Accepted Outage (MAO) values as they are proposed by business continuity and IT experts.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
Notes
- 1.
Classification can also be performed for a single business process according to the number of Activities inside the process.
References
Martin, E.W., Brown, C.V., Hoffer, J.A., Perkins, W.C., Dehayes, D.W.: Managing Information Technology: What Managers Need to Know, 7th edn. Prentice Hall, Upper Saddle River (2011)
Rao, L., McNaughton, M., Osei-Bryson, K.-M., Haye, M.: The role of ontologies in disaster recovery planning. In: AMCIS 2009 Proceedings, Paper 713 (2009). http://aisel.aisnet.org/amcis2009/713
Miller, H.E., Engemann, K.J.: Using analytical methods in business continuity planning. In: Engemann, K.J., Gil-Lafuente, A.M., Merigó, J.M. (eds.) MS 2012. LNBIP, vol. 115, pp. 2–12. Springer, Heidelberg (2012)
Karner, G.: Resource estimation for objectory projects. In: Systems SF AB (1993)
Business Standard Institute: BS ISO 22301:2012 (2012)
Engemann, K.J., Henderson, D.M.: Business Continuity and Risk Management: Essentials of Organizational Resilience. Rothstein Associates, Brookfield (2012)
Information And Technology Services (ITS): Disaster Recovery/Business Continuity, University of Michigan (2014). http://www.mais.umich.edu
Gibson, D.: Managing Risks in Information Systems. Jones & Bartlett Learning, Burlington (2010)
National Institute of Standards and Technology-U.S. Department of Commerce: Contigency Planning Guide for Federal Information Systems, p. 16 (2010)
Snedaker, S.: Business Continuity and Disaster Recovery Planning for IT Professionals. Elsevier Inc., Burlington (2007)
Banerjee, G: Use Case Points -An Estimation Approach (2001)
Kusumoto, S., Matukawa, F., Inoue, K.: Estimating effort by use case points: method, tool and case study. In: 10th International Symposium on Software Metrics. IEEE Computer Society, Washington (2004)
Ochodek, M., Nawrocki, J., Kwarciak, K.: Simplifying effort estimation based on use case points. J. Inf. Softw. Technol. 53, 200–213 (2011). Elsevier
Barron, F.H., Barrett, B.E.: Decision quality using ranked attribute weights. Int. Manag. Sci. 42, 1515–1523 (1996)
Bagla, V., Gupta, A., Kukreja, D.: A qualitative assessment of educational software. Int. J. Comput. Appl. 36, 1–7 (2011)
Caelli, W.J., Kwok, L.-F., Longley, D.: A business continuity management simulator. In: Rannenberg, K., Varadharajan, V., Weber, C. (eds.) SEC 2010. IFIP AICT, vol. 330, pp. 9–18. Springer, Heidelberg (2010)
Laird, M.L., Brennan, M.C.: Software measurement and estimation- a practical approach. IEEE Computer Society, Hoboken (2006)
Gruhn, V., Laue R.: Complexity metrics for business process models. In: 9th International Conference on Business Information Systems
Ha, B.-H., Reijers, H.A., Bae, J., Bae, H.: An approximate analysis of expected cycle time in business process execution. In: Eder, J., Dustdar, S. (eds.) BPM Workshops 2006. LNCS, vol. 4103, pp. 65–74. Springer, Heidelberg (2006)
Acknowledgments
The current work is supported by the SGS Project with the Number 21079, from Technical University of Liberec.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2015 Springer International Publishing Switzerland
About this paper
Cite this paper
Podaras, A. (2015). A Non-arbitrary Method for Estimating IT Business Function Recovery Complexity via Software Complexity. In: Aveiro, D., Pergl, R., Valenta, M. (eds) Advances in Enterprise Engineering IX. EEWC 2015. Lecture Notes in Business Information Processing, vol 211. Springer, Cham. https://doi.org/10.1007/978-3-319-19297-0_10
Download citation
DOI: https://doi.org/10.1007/978-3-319-19297-0_10
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-19296-3
Online ISBN: 978-3-319-19297-0
eBook Packages: Computer ScienceComputer Science (R0)