Empirical validation of the Classic Change Curve on a software technology change project

  • Authors:

  • Uolevi Nikula;Christian Jurvanen;Orlena Gotel;Donald C Gause

  • Affiliations:

  • Department of Information Technology, Lappeenranta University of Technology, P.O. Box 20, FI-53851 Lappeenranta, Finland;Agricultural Data Processing Centre Ltd., P.O. Box 25, FI-01301 Vantaa, Finland;Independent Researcher, New York City, NY 10014, USA;Thomas J. Watson School of Engineering and Applied Science, Binghamton University, P.O. Box 6000, Binghamton, NY 13902-6000, USA

  • Venue:
  • Information and Software Technology
  • Year:
  • 2010

Quantified Score

Hi-index 0.00

Visualization

Abstract

Context: New processes, tools, and practices are being introduced into software companies at an increasing rate. With each new advance in technology, software managers need to consider not only whether it is time to change the technologies currently used, but also whether an evolutionary change is sufficient or a revolutionary change is required. Objective: In this paper, we approach this dilemma from the organizational and technology research points of view to see whether they can help software companies in initiating and managing technology change. In particular, we explore the fit of the technology S-curve, the Classic Change Curve, and a technological change framework to a software technology change project and examine the insights that such frameworks can bring. Method: The descriptive case study described in this paper summarizes a software technology change project in which a 30-year old legacy information system running on a mainframe was replaced by a network server system at the same time as the individual-centric development practices were replaced with organization-centric ones. The study is based on a review of the company's annual reports, in conjunction with other archival documents, five interviews and collaboration with a key stakeholder in the company. Results: Analyses of the collected data suggest that software technology change follows the general change research findings as characterized by the technology S-curve and the Classic Change Curve. Further, that such frameworks present critical questions for management to address when embarking on and then running such projects. Conclusions: We describe how understanding why a software technology change project is started, the way in which it unfolds, and how different factors affect it, are essential tools for project leaders in preparing for change projects and for keeping them under control. Moreover, we show how it is equally important to understand how software technology change can work as a catalyst in revitalizing a stagnated organization, facilitating other changes and thereby helping an organization to redefine its role in the marketplace.