Tommi kramer 2013-06-21-caise-re2-kramer

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Tommi kramer 2013-06-21-caise-re2-kramer

  1. 1. Department of General Management and Information Systems Prof. Dr. Armin Heinzl Software Outsourcing Decision Aid (SODA): A Requirements based Decision Support Method and Tool Authors: Tommi Kramer & Michael Eschweiler CAISE - June 21, 2013
  2. 2. Outline • Problem Domain & Motivation • Research Design • SODA – A Decision Support Method – Model Creation Phase – Model Clustering Phase – Structural Analysis Phase • Evaluation • Summary 2
  3. 3. Problem Domain • SMEs are inexperienced in software development outsourcing Where / what / how to outsource? (Klimpke et al. 2011) • Behavior patterns: – Decisions on a gut level – Decisions are subjective in nature and people centric • But, SMEs want to be successful in SDO 3
  4. 4. Objective Research objective: Definition of a decision making approach for selective software development outsourcing based on software requirements delivering: • Good clustering quality • Good scalability (low setup costs) • outsourcing success 4
  5. 5. Research Domain • Applying systems theory and graph theory to existing approaches • Facing multi-dimensional decision problem with including decision rationales from SE principles (Dibbern et al. 2004, Kramer et al. 2011) • Focus on selective sourcing of application systems by supporting decision making on component level 5
  6. 6. Research Methodology • Design Science Research (Hevner et al. 2004, Peffers et al. 2007) – Graph theory and systems theory deliver requirements for artifact design – Definition and implementation of a new decision making approach in IS outsourcing as artifact development – Software development projects with students used for artifact evaluation 6
  7. 7. SODA (1) • SODA: Software Outsourcing Decision Aid - A decision making method and tool supporting IT project teams in selecting components suitable for outsourcing • Phase 1: Graph Model Creation – Representing requirements in a graph – Nodes: Requirements – Edge: „similar_to“ or „requires“ relationships 7
  8. 8. SODA (2) • Phase 2: Graph Model Clustering – Finding cohesive groups of requirements – Neither the number of clusters nor the clusters‘ size is known a priori – Newman algorithm for “community structure detection” (Newman 2006) 8
  9. 9. SODA (3) • Phase 3: Structural Analysis of requirements – Modularity – Coupling and Cohesion – Requirements Centrality – Rule-based recommendations 9
  10. 10. SODA 10 PHASE 2 PHASE 1 PHASE 3 Resulting Decision Determinants: • Modularity • Cluster Coupling and Cohesion • Requirements Centrality
  11. 11. Evaluation • Simulation by using data from four master team projects developing a software application • Clustering quality: More interdependencies lead to more coarse- grained partitioning of graph. But cluster quality remains stable! • Scalability: Higher effort in interdependency definition is not delivering better modularity or clustering quality! • SDO success: ? 11 Project Require ments Interdepen- dencies Achievable Modularity No. of Clusters in Optimal Partition Rand Index A 45 61 0.71 10 0.80 B 45 43 0.67 8 0.84 C 45 181 0.54 6 0.77 D 46 49 0.65 8 0.82
  12. 12. Conclusion/Contribution • We apply modularity, clustering & cohesion as well as centrality techniques for requirements analysis to support outsourcing decision making • Design and development of an appropriate method and tool (scalable and good clustering) • Contribution to practice – Facilitate decision making for managers in SMEs when it comes to the question what to outsource and what to realize in-house – Provide a repeatable and precise method for SDO in order to store decision information 12
  13. 13. Thank you for your attention! 13 Tommi Kramer * kramer@uni-mannheim.de
  14. 14. References • Dibbern, J., Goles, T., Hirschheim, R., & Jayatilaka, B. (2004). Information Systems Outsourcing: A Survey and Analysis of the Literature. Communications of the ACM, 35(4), 6-102. • Hevner, A. R., March, S. T., Park, J., & Sudha, R. (2004). Design Science in Information Systems Research. Management Information Systems Quarterly 28 (1), 75 – 105. • Klimpke, L., Kramer, T., Betz, S., & Nordheimer, K. Globally Distributed Software Development in Small and Medium-Sized Enterprises in Germany: Reasons, Locations, and Obstacles. In Proceedings of the 19th European Conference on Information Systems (ECIS2011), Helsinki, Finland, 2011 • Kramer, T., Heinzl, A., & Spohrer, K. (2011). Should this Software Component be Developed Inside or Outside our Firm? - A Design Science Perspective on the Sourcing of Application Systems. In J. Kotlarsky, L. P. Willcocks, & O. Ilan (Eds.), New Studies in Global IT and Business Service Outsourcing: 5th Global Scourcing Workshop 2011, Courchevel, France, March 14-17, 2011, Revised Selected Papers (pp. 115-132). Heidelberg, Dordrecht, London, New York: Springer. • Newman, M. E. J. Modularity and Community Structure in Networks. In Proceedings of the National Academy of Sciences of the United States of America, 2006 (pp. 8577-8582) • Peffers, K., Tuunanen, T., Rothenberger, M. A., & Chatterjee, S. (2007). A Design Science Research Methodology for Information Systems Research. Journal of Management Information Systems, 24(3), 45 - 78. 14

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