Nothing Special   »   [go: up one dir, main page]
Skip to main content

Advertisement

Springer Nature Link
Log in

A socio-technical approach to improving the systems development process

  • Published:
Information Systems Frontiers Aims and scope Submit manuscript

Abstract

Research on improving the systems development processes has primarily focused on mechanisms such as tools, software development methodologies, knowledge sharing and process capabilities. This research has yielded considerable insights into improving the systems development process, but the large majority of information systems development projects still continue to be over budget, late, and ineffective in meeting user needs. Together with the advent of software development moving offshore, or consisting of offshore team members, a more holistic approach is appropriate. Approached from a socio-technical perspective the software development process is viewed as a process embedded in a social and a technical subsystem. Drawing upon socio-technical work design principles, this paper suggests how capabilities of the development process can be improved. Data collected from a survey of software development practices in organizations indicates that organizations at different levels of process capabilities differ in work system characteristics as well as process performance. For example, the use of multi-skilled teams was found to be significantly related to the systems development process maturity level as well as significantly related to all the performance measures studied. This paper provides empirical support for the socio-technical approach and provides a theoretical foundation for designing software process initiatives in organizations.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6

Similar content being viewed by others

Notes

  1. CMM, or Capability Maturity Model has been replaced by the Software Engineering Institute by Capability Maturity Model Integration (CMMI). However, on their website they state: “Many of the skills used in applying the Software CMM are useful in implementing a CMMI-based process improvement program, since many of the best practices, issues, and improvement approaches are essentially the same.” Since our study primarily uses CMM as an indicator of process capabilities, the results are applicable across both models proposed by SEI.

References

  • Aladwani, A. M. (2002). An empirical examination of the role of social integration in systems development projects. Information Systems Journal, 12, 339–353.

    Article  Google Scholar 

  • Alter, S. (1999). A general, yet useful theory of information systems. Communications of the AIS, 1, 1–70.

    Article  Google Scholar 

  • Alter, S. (2001). Which life cycle—Work, information, or software? Communications of the AIS, 7, 1–54.

    Google Scholar 

  • Agrawal, M., & Chari, K. (2007). Software effort, quality and cycle time: A study of CMM Level 5 Projects. IEEE Transactions on Software Engineering, 33, 145–156.

    Article  Google Scholar 

  • Anonymous (2002). Q&A: James Rumbaugh, a modeling champion. Application Development Trends, 6, 2.

  • Avgerou, C. (2001). The significance of context in information systems and organizational change. Information Systems Journal, 11, 43–63.

    Article  Google Scholar 

  • Bahrami, H. (1992). The emerging flexible organization: Perspectives from Silicon Valley. California Management Review, 34, 33–52.

    Google Scholar 

  • Banker, R. D., & Kauffman, R. J. (1991). Reuse and productivity in integrated computer-aided software engineering: An empirical study. MIS Quarterly, 15, 375–401.

    Article  Google Scholar 

  • Bansler, J. P., & Bodker, K. (1993). A reappraisal of structured analysis: Design in organizational context. ACM Transactions on Information Systems, 11, 165–193.

    Article  Google Scholar 

  • Benko, C., & McFarlan, W. (2003). Connecting the dots: Aligning projects with objectives in unpredictable times. Boston: Harvard Business School Press.

    Google Scholar 

  • Booch, G. (1999). UML in action. Communications of the ACM, 42, 26–28.

    Article  Google Scholar 

  • Brooks, F. P. (1987). No silver bullet: Essence and accidents of software engineering. IEEE Computer, 20, 10–19.

    Google Scholar 

  • Brown, J. S., & Duguid, P. (2001). Knowledge and organizations: A social-practice perspective. Organization Science, 12, 198–213.

    Article  Google Scholar 

  • Burns, T., & Stalker, G. M. (1961). The management of innovation. London, UK: Tavistock Publications.

    Google Scholar 

  • Card, D. N., Mcgarry, F. E., & Page, G. T. (1987). Evaluating software engineering technologies. IEEE Transactions on Software Engineering, 13, 845–851.

    Article  Google Scholar 

  • Cherns, A. (1987). The principles of sociotechnical design. Human Relations, 40, 45–51.

    Article  Google Scholar 

  • Daft, R. L., & Lengel, R. H. (1986). Organizational information requirements, media richness and structural design. Management Science, 32, 554–571.

    Article  Google Scholar 

  • Dayan, R., & Evans, S. (2006). KM your way to CMMI. Journal of Knowledge Management, 10, 69–80.

    Article  Google Scholar 

  • Diaz, M., & Sligo, J. (1997). How software process improvement helped Motorola. IEEE Software, 14, 75–81.

    Article  Google Scholar 

  • Fichman, R. G., & Kemerer, C. F. (1997). The assimilation of software process innovations: An organizational learning perspective. Management Science, 43, 1345–1363.

    Article  Google Scholar 

  • Fichman, R. G., & Moses, S. A. (1999). An incremental process for software implementation,. Sloan Management Review, 40, 39–52.

    Google Scholar 

  • Fidler, L. A., & Johnson, J. D. (1984). Communication and innovation implementation. Academy of Management Review, 9, 704–711.

    Article  Google Scholar 

  • Finlay, P. N., & Mitchell, A. C. (1994). Perceptions of benefits from the introduction of case: An empirical study. MIS Quarterly, 18, 353–370.

    Article  Google Scholar 

  • Greenwood, R. H., & Hinnings, C. R. (1993). Understanding strategic change: The contribution of archetypes. Academy of Management Journal, 36, 1052.

    Article  Google Scholar 

  • Grover, V., Jeong, S. R., & Segars, A. H. (1996). Information system effectiveness: The construct space and patterns of application. Information and Management, 31, 177–191.

    Article  Google Scholar 

  • Hammer, M. (1990). Reengineering work: Don’t automate, obliterate. Harvard Business Review, 68, 104–102.

    Google Scholar 

  • Harter, D. E., Krishnan, M. S., & Slaughter, S. A. (2000). Effects of process maturity on quality, cycle time and effort in software product development. Management Science, 46, 451–466.

    Article  Google Scholar 

  • Herbsleb, J., & Zubrow, D. (1997). Software quality and the capability maturity model. Communications of the ACM, 40, 30–40.

    Article  Google Scholar 

  • Herbsleb, J., Zubrow, D., Goldenson, D., Hayes, W. & Paulk, M. C. (1997). Software quality and the capability maturity model. CACM, 4, 31–40.

  • Hollenbach, C., Young, R., Pflugrad, A., & Smith, D. (1997). Combining quality and software process improvement. Communications of the ACM, 30, 41–45.

    Article  Google Scholar 

  • Humphrey, W. S., & Curtis, B. (1991). Comments on ‘a critical look’. IEEE Software, 8, 42–46.

    Article  Google Scholar 

  • Ivari, J., Hirscheim, R., & Klien, H. K. (2001). A dynamic framework for classifying information systems development methodologies and approaches. Journal of Management Information Systems, 17, 179–218.

    Google Scholar 

  • Iversen, J., & Mathiassen, L. (2003). Cultivation and engineering of a software metrics program. Information Systems Journal, 13, 3–19.

    Article  Google Scholar 

  • Keil, M., Mann, J., & Rai, A. (2000). Why software projects escalate: An empirical analysis and test of four theoretical models. MIS Quarterly, 24, 631–664.

    Article  Google Scholar 

  • King, W. R. (2005). Outsourcing becomes more complex. Information Systems Management, 22, 89–90.

    Article  Google Scholar 

  • Leonard-Barton, D. (1991). The role of process innovation and adaptation in attaining strategic technology capability. International Journal of Technology Management, 6, 303–320.

    Google Scholar 

  • Levinson, M. (2001). Let’s stop wasting $78 billion a year. CIO, 78–83.

  • Lyytinen, K., & Robey, D. (1999). Learning failure in information systems development. Information Systems Journal, 9, 85–101.

    Article  Google Scholar 

  • Markus, M. L., & Benjamin, R. I. (1997). Magic bullet theory in IT-enabled transformation. Sloan Management Review, 38, 55–68.

    Google Scholar 

  • Markus, M. L., & Robey, D. (1988). Information technology and organizational change: Causal structure in theory and research. Management Science, 15, 583–598.

    Article  Google Scholar 

  • Martin, J. (1986). Information engineering. Camforth: Savant.

    Google Scholar 

  • Mathiessen, L. (1998). Reflective systems development. Scandinavian Journal of Information Science, 10, 67–117.

    Google Scholar 

  • Melcher, A., Acar, W., Dumont, P., & Khouja, M. (1990). Standard-maintaining and continuous-improvement systems: Experiences and comparisons. Interfaces, 20, 24–41.

    Article  Google Scholar 

  • Mi, P., & Scacchi, W. (1992). Process integration in case environments. IEEE Software, 9, 45.

    Article  Google Scholar 

  • Mumford, E. (1995). Creative chaos or constructive change: Business process re-engineering versus socio-technical design. In G. Burke & J. Peppard (Eds.), Examining business process re-engineering (pp. 192–216). London, UK: Kogan Page.

    Google Scholar 

  • Mumford, E. (2003). Redesigning human systems. Hershey, PA: Idea Group.

    Google Scholar 

  • Niazi, M., Wilson, D., & Zowghi, D. (2005). A Maturity model for the implementation of software process improvement: an empirical study. The Journal of Systems and Software, 74, 155.

    Article  Google Scholar 

  • Okhuysen, G. A., & Eisenhardt, K. M. (2002). Integrating knowledge in groups: How formal interventions enable flexibility. Organization Science, 13, 370–386.

    Article  Google Scholar 

  • Orlikowski, W. J. (2002). Knowing in practice: Enacting a collective capability in distributed organizing. Organization Science, 13, 249.

    Article  Google Scholar 

  • Parthasarthy, R. S., & Prakash, S. (1993). Relating strategy and structure to flexible automation: A test of fit and performance implications. Strategic Management Journal, 14, 529.

    Article  Google Scholar 

  • Pasmore, W. A. (1998). Designing effective organizations: The sociotechnical system perspective. New York, NY: Wiley.

    Google Scholar 

  • Patnayakuni, R., & Rai, A. (2002). Development infrastructure capabilities and process maturity. Communications of the ACM, 45, 201–210.

    Article  Google Scholar 

  • Patnayakuni, R., Rai, A., & Tiwana, A. (2007). Systems development process improvement: A knowledge integration perspective. IEEE Transactions on Engineering Management, 54(2), 286–300.

    Article  Google Scholar 

  • Patnayakuni, R., Ruppel, C., & Rai, A. (2006). Managing the complementarity of knowledge integration and process formalization for systems development performance. Journal of Association of Information Systems, 7(8), 545–567.

    Google Scholar 

  • Pfleeger, S. L. (1996). Realities and rewards of software process improvement. IEEE Software, 13, 99–101.

    Article  Google Scholar 

  • Pfleeger, S. L. (2001). Software engineering: Theory and practice. Upper Saddle River, NJ: Prentice Hall.

    Google Scholar 

  • Pinsonneault, A., & Kraemer, K. L. (1993). Survey research methodology in management information systems: An assessment. Journal of Management Information Systems, 10, 75–105.

    Google Scholar 

  • Purvis, R. L., Sambamurthy, V., & Zmud, R. W. (2001). The assimilation of knowledge platforms in organizations: An empirical investigation. Organization Science, 12, 117–135.

    Article  Google Scholar 

  • Rai, A., & Howard, G. (1994). Propagating CASE usage for software development: An empirical investigation of key organizational correlates. Omega, 22, 133–147.

    Article  Google Scholar 

  • Ravichandran, T., & Rai, A. (2002). Quality management in systems development: An organizational systems perspective. MIS Quarterly, 24, 381–415.

    Article  Google Scholar 

  • Rose, J. (2002). Interaction, transformation and informations systems development—An extended application of soft systems methodology. Information Technology & People, 15, 242–258.

    Article  Google Scholar 

  • Sarbaugh-Thompson, M., & Feldman, M. S. (1998). Electronic mail and organizational science: Does saying “hi” really matter? Organization Science, 9, 685–698.

    Article  Google Scholar 

  • Schmidt, R., Lyytinen, K., Keil, M., & Cule, P. (2001). Identifying software project risks: An intenational Delphi study. Journal of Management Information Systems, 17, 5–36.

    Google Scholar 

  • Shani, A. B., Grant, R. M., Krishnan, R., & Thompson, E. (1992). Advanced manufacturing systems and organizational choice: Sociotechnical systems approach. California Management Review, 34, 91–111.

    Google Scholar 

  • Souder, W. (1987). Managing new product innovations. Lexington, MA: Lexington Books.

    Google Scholar 

  • Staples, M., Niazi, M., Ross, J., & Abrahams, A. (2007). An exploratory study of why organizations do not adopt CMMI. The Journal of Systems and Software, 80, 883.

    Article  Google Scholar 

  • Tate, G., Verner, J., & Jeffery, R. (1992). Case: A testbed for modeling, measurement, and management. Communications of the ACM, 35, 65–72.

    Article  Google Scholar 

  • Trienekens, J., Kusters, R., vanGenuchten, M., & Aerts, H. (2007). Targets, drivers and metrics in software process improvement: Results of a survey in a multinational organization. Software Quality Journal, 15, 135–153.

    Article  Google Scholar 

  • Unhelkar, B., & Mamdapur, G. (1995). Practical aspects of using a methodology: A road map approach. Report on Object Analysis and Design, 2, 34–36.

    Google Scholar 

  • Wynekoop, J. L. (1993). Strategies for implementation research: Combining research methods. International Conference on Information Systems, Dallas, TX, pp 185–193.

  • Yu, J., & Cooper, H. (1983). A quantitative review of research design effects on response rates to questionnaires. Journal of Marketing Research, 20, 36–44.

    Article  Google Scholar 

  • Zanzi, A. (1987). How organic is your organization? Journal of Management Studies, 24, 125.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Economics and Information Systems, University of Alabama in Huntsville, 301 Sparkman Drive, Huntsville, AL, 35899, USA

    Ravi Patnayakuni

  2. Huizenga School of Business and Entrepreneurship, Nova Southeastern University, 3301 College Ave., Davie, FL, 33314, USA

    Cynthia P. Ruppel

Authors
  1. Ravi Patnayakuni
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Cynthia P. Ruppel
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Ravi Patnayakuni.

Appendices

Appendix 1

Unless otherwise specified, respondents were required to indicate their agreement or disagreement on a seven-point Likert-type scale (strongly disagree, disagree, slightly disagree, neutral, agree slightly, agree, strongly agree).

Table 6 Analysis of reliability and unidimensionality
Full size table

Appendix 2

Process capability descriptions

Level 1: Ad hoc, without formalized procedures, cost estimates and project plans.

Level 2: Stable and repeatable process based on accumulated experience of individuals, some project controls and metrics, but no process framework used.

Level 3: A defined process that is consistently implemented across projects. Sufficient data is collected to analyze process efficiency

Level 4: A managed process with comprehensive and defined process measurements. Systematic record of process performance measures is maintained.

Level 5: In a continuous improvement mode for optimizing the process.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Patnayakuni, R., Ruppel, C.P. A socio-technical approach to improving the systems development process. Inf Syst Front 12, 219–234 (2010). https://doi.org/10.1007/s10796-008-9093-4

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10796-008-9093-4

Keywords

Search

Navigation