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Motivating developer performance to improve project outcomes in a high maturity organization

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Abstract

In this paper we discuss the impact software developer performance has on project outcomes. Project performance remains unreliable in the software industry with many compromised software systems reported in the press. We investigate the impact that developer performance has on aspects of project success and explore how developer performance is motivated. We present interview, focus group and questionnaire data collected from a team of developers working in a software organization that has been assessed at CMM level 5. Our main findings are that developers value technical skills in their colleagues, but appreciate these especially when supplemented with good human skills. Software developers with a proactive, flexible, adaptable approach who are prepared to share knowledge and follow good practice are said to be the best developers. Motivators for these developers are pay and benefits, recognition and opportunities for achievement in their work. Overall, we found that technical competence, interpersonal skills and adherence to good practices are thought to have the biggest impact on software project success.

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Notes

  1. Laddering techniques are related to elements of Repertary Grid Technique (Bannister & Fransella, 1986).

References

  • Ahuja, S. (1999). Process improvement in a rapidly changing business and technical environment. Fourth annual European process group conference. Amsterdam, Holland. c303.

  • Baddoo, N., Hall, T., & Jagielska, D. (2005). Software developer motivation in a high maturity company: A case study. Proceedings of European software process improvement and innovation conference, 9–11 November 2005, Budapest, Hungary.

  • Baddoo, N., & Hall, T. (2002a). Motivators of software process improvement: An analysis of practitioners’ views. Journal of Systems & Software, 62(2), 85–96.

    Article  Google Scholar 

  • Baddoo, N., & Hall, T. (2002b). Practitioner roles in software process improvement: An analysis using grid technique. Journal of Software Process Improvement and Practice, 7(1), 17–31.

    Article  Google Scholar 

  • Bannister, D., & Fransella, F., (1986). Inquiring Man: The Psychology Of Personal Constructs (3rd ed.). London: Croom Helm

  • Bohem, B., & Papaccio, P. (1988). Understanding and controlling software costs. IEEE Transactions on Software Engineering, 14(10), 1462–1477.

    Article  Google Scholar 

  • Couger, J. D., & Adelsberger, H. (1988). Comparing motivation of programmers and analysts in different socio/political environments: Austria compared to the United States. Computer-Personnel, 11(4), 13–16.

    Article  Google Scholar 

  • Couger, J. D. (1988). Motivators and demotivators in the IS environment. Journal of Systems Management, 39(6), 36–41.

    Google Scholar 

  • Couger, J. D., & O’Callaghan, R. (1994). Comparing the motivators of Spanish and finish computer personnel with those of the United States. European Journal of Information Systems, 3(4), 258–291.

    Article  Google Scholar 

  • Denzin, N. (1989). The research act: A theoretical introduction to sociological methods. NJ, Prentice-Hall: Englewood Cliffs.

    Google Scholar 

  • Dyba, T., & Dyba, T. (1997). How software process improvement helped motorola. IEEE Software Archive, 14(5) 75–81.

    Article  Google Scholar 

  • Dyba, T. (2000). An instrument for measuring the key factors of success in software process improvement. Empirical Software Engineering, 5(4), 357–390.

    Article  MATH  Google Scholar 

  • El Emam, K., & Birk, A. (2000). Validating the ISO/IEC 15504 measure of software requirements analysis process capability. IEEE Trans on Software Engineering, 26(6), 541–566.

    Article  Google Scholar 

  • Fitz-Enz, J. (1978). Who is the DP professional? Datamation September:125–128.

  • Greene, J. C., Caracelli, V. J., & Graham, W. F. (1989). Towards a conceptual framework for mixed method evaluation designs. Education Evaluation and Policy Analysis, 11(3), 255–274.

    Google Scholar 

  • Goldenson, D. R., & Herbsleb, J. D., (1995). After The Appraisal: A Systematic Survey of Process Improvement, its Benefits and Factors that Influence Success, Software Engineering Institute, CMU/SEI-95-TR-009 ADA302225. http://www.sei.cmu.edu/publications/documents/95.reports/95.tr.009.html

  • Hall, T., & Wilson, D. (1997). Views of software quality: A field report. IEE Process on Software Engineering, Apr, 111–118.

  • Harrison, R., Baddoo, N., Barry, E., Biffl, S., Parra, A., Winter, B., & Wuest, J. (1999). Directions and methodologies for empirical software engineering research. Empirical Software Engineering, 4(4).

  • Hars, A., & Ou, S. (2001). Working for free?–motivations of participating in open source projects, Proceedings of the 34th Hawaii International Conference on System Sciences.

  • Hertel, G., Niedner, S., & Herrmann, S. (2003). Motivation of software developers in open source projects: An Internet-based survey of contributors to the Linux kernel. Research Policy, 32(7), 1159–1177.

    Article  Google Scholar 

  • Krippendorf, K. (2004). Content analysis, an introduction to its methodology. Thousand Oaks-London-New Delhi: SAGE Publication.

    Google Scholar 

  • Krueger, R. A., & Casey, M. A. (2000). Focus groups: A practical guide for applied research. Thousand Oaks,CA: Sage Publications.

    Google Scholar 

  • Mata Toledo, R. A., & Unger, E. A. (1985). Another look at motivating data processing professionals. Computer-Personnel, 10(1), 1–7.

    Article  Google Scholar 

  • McDermit, J. A., & Bennett, K. H. (1999). Software engineering research: A critical appraisal. IEEE Proceedings—Software, 146(4), 179–186.

    Article  Google Scholar 

  • Mellis, W. (1998). Software quality managment in turbulent times—are there alternatives to process oriented software quality management? Software Quality Journal 7, 277–295.

    Article  Google Scholar 

  • Morgan, D. L., & Krueger, R. A. (1993). When to use focus groups and why. In D. L. Morgan (Ed.), Successful focus groups: Advancing the state of the art. Newbury Park, CA: Sage.

    Google Scholar 

  • Pitterman, B. (2000). Telcordia technologies: The journey to high maturity. IEEE Software, 17(4), 89–96.

    Article  Google Scholar 

  • Preece, J., Rogers, Y., & Sharp, H. (2002). Interaction design, NY: John Wiley.

    Google Scholar 

  • Rainer, A., & Hall, T. (2002). Key success factors for implementing software process improvement: A maturity-based analysis. Journal of Systems & Software, 62(2), 71–84.

    Article  Google Scholar 

  • Seaman, C. (1999). Qualitative methods in empirical stuides of software engineering. IEEE Transactions of Software Engineering, 25(4).

  • Shah, M., Hall, T., Rainer, A., & Baddoo, N. (2003). Software engineering projects: How to evaluate success? University of Hertfordshire Technical Report, Faculty of Engineering & Information Science, number 394.

  • Shenhar, A., Tishler, A., Dvir, D., Lipovetsky, S, & Lechler T. (2002). Refining the search for project success factors: A multivariate, typological approach. Research & Development Management, 32(2), 111–126.

    Google Scholar 

  • The Standish Group International Inc. (Ed.), Chaos: Recipe for Success (1999), source: http://www.standishgroup.com.

  • Stewart, V., Stewart, A., & Fonda, N. (1981). Business applications of repertory grid. London: McGraw Hill.

    Google Scholar 

  • Turley, R. T., & Bieman, J. M. (1995). Competencies of exceptional and nonexceptional software engineers, Journal of Systems and Software, 28(2).

  • Warden, R., & Nicholson, I. (1995). IT quality initiatives at risk. Software Quality Management New Year, 24, 24–27.

    Google Scholar 

  • Willis, R. R., Rova, R. M., Scott, M. D., Johnson, M. I., Ryskowski, J. F., Moon, J. A., Shumate, K. C., & Winfield, T. O. (1998). Hughes aircraft’s widespread deployment of a continuously improving software process. Software Engineering Institute, Canergie Mellon University.

  • Wilson, D., & Hall, T. (1998). Perceptions of software quality: A pilot study. Software Quality Journal, 7(1), 67–75.

    Article  Google Scholar 

  • Wilson, D., Hall, T., & Baddoo, N. (2000). The software process improvement paradox. Approaches To Quality Management, Software Quality Management VIII:97–101.

    Google Scholar 

  • Verner, J., & Evanco, W. (2005). In-house software development: What project management practices lead to success?. IEEE Software, 22(1), 86–93.

    Article  Google Scholar 

  • Wohlin, C., & Andrews, A. (2002). Analysing primary and lower order project success drivers. Proceedings of International conference in Software Engineering and Knowledge Engineering, 393–400.

  • Wohlin, C., & Andrews, A. (2001). Assessing project success using subjective evaluation factors. Software Quality Journal, 9, 43–70.

    Article  Google Scholar 

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Author information

Authors and Affiliations

  1. Systems & Software Research Group, School of Computer Science, University of Hertfordshire, College Lane, Hatfield, AL10 9AB, UK

    Tracy Hall & Nathan Baddoo

  2. Department of Mental Health Sciences, University College London, 67-73 Riding House Street, London, W1W 7EJ, UK

    Dorota Jagielska

Authors
  1. Tracy Hall
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  2. Dorota Jagielska
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  3. Nathan Baddoo
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Corresponding author

Correspondence to Tracy Hall.

Appendix 1. Research instrument scripts

Appendix 1. Research instrument scripts

Individual interview script

  1. 1.

    Thinking about the best developer on this project….

    • What is the best thing about them?

    • What else is good about them?

    • Why do they have those good qualities?

    • How do they contribute well to the project?

  2. 2.

    Thinking about the worst developer on this project….

    • What is the worst thing about them?

    • What else is bad about them?

    • Why do they have those bad qualities?

    • How do they contribute badly to the project?

  3. 3.

    What is good about you as a developer?

    • What is the best thing you do?

    • What else do you do well?

    • Why do you have those good qualities?

    • How do those good qualities contribute to the project?

  4. 4.

    What is bad about you as a developer?

    • What is the thing you do least well?

    • What else do you not do so well?

    • Why do you have those bad qualities?

    • How do those bad qualities contribute to the project?

Focus group structure

  1. 1.

    Thinking about the project highs, what is working really well in this project….

    • What is this best thing about this project?

    • What are the other good things about this project?

    • Why are these so positive?

    • How have these positive aspects of the project been established?

    • How does this impact on project outcomes?

    • Who are the key players in this positive aspect of the project?

  2. 2.

    Thinking about the project lows, what is not working so well in this project….

    • What is this worst aspect of this project?

    • What else is negative about this project?

    • Why is this so negative?

    • How have these negative aspects of the project been established?

    • How do these impact on project outcomes?

    • Who are the key players in this negative aspect of the project?

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Hall, T., Jagielska, D. & Baddoo, N. Motivating developer performance to improve project outcomes in a high maturity organization. Software Qual J 15, 365–381 (2007). https://doi.org/10.1007/s11219-007-9028-1

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