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The Calculus of Reengineering

Author

Listed:
  • Anitesh Barua

    (Department of Management Science and Information Systems, Graduate School of Business, The University of Texas at Austin, Austin, Texas 78712)

  • C. H. Sophie Lee

    (Management Information Systems, College of Management, University of Massachusetts at Boston, Boston, Massachusetts 02125)

  • Andrew B. Whinston

    (Department of Management Science and Information Systems, Graduate School of Business, The University of Texas at Austin, Austin, Texas 78712)

Abstract

Advances in new Information Technologies (IT) and changes in the business environment such as globalization and competitive pressure have prompted organizations to embark on reengineering projects involving significant investments in IT and business process redesign. However, the evidence of payoff from such investments can be classified as mixed as best, a problem we partly attribute to the absence of a strong theoretical foundation to assess and analyze reengineering projects. We seek to apply complementarity theory and a business value modeling approach to address some questions involving what, when, and how much to reengineer. Complementarity theory is based on the notion that the value of having more of one factor increases by having more of another complementary factor. Further, related developments in the optimization of “supermodular” functions provide a useful way to maximize net benefits by exploiting complementary relationships between variables of interest. Combining this theory with a multi-level business value model showing relationships between key performance measures and their drivers, we argue that organizational payoff is maximized when several factors relating to IT, decision authority, business processes and incentives are changed in a coordinated manner in the right directions by the right magnitude to move toward an ideal design configuration. Our analysis further shows that when a complementary reengineering variable is left unchanged either due to myopic vision or self-interest, the organization will not be able to obtain the full benefits of reengineering due to smaller optimal changes in the other variables. We also show that by increasing the cost of changing the levels of design variables, unfavorable pre-existing conditions (e.g., too much heterogeneity in the computing environment) can lead to reengineering changes of smaller magnitude than in a setting with favorable conditions.

Suggested Citation

  • Anitesh Barua & C. H. Sophie Lee & Andrew B. Whinston, 1996. "The Calculus of Reengineering," Information Systems Research, INFORMS, vol. 7(4), pages 409-428, December.
  • Handle: RePEc:inm:orisre:v:7:y:1996:i:4:p:409-428
    DOI: 10.1287/isre.7.4.409
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    Citations

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    Cited by:

    1. Rajiv Kohli & Sarv Devaraj, 2003. "Measuring Information Technology Payoff: A Meta-Analysis of Structural Variables in Firm-Level Empirical Research," Information Systems Research, INFORMS, vol. 14(2), pages 127-145, June.
    2. Thomas W. Ferratt & Ritu Agarwal & Carol V. Brown & Jo Ellen Moore, 2005. "IT Human Resource Management Configurations and IT Turnover: Theoretical Synthesis and Empirical Analysis," Information Systems Research, INFORMS, vol. 16(3), pages 237-255, September.
    3. Anitesh Barua & Deepa Mani, 2018. "Reexamining the Market Value of Information Technology Events," Information Systems Research, INFORMS, vol. 29(1), pages 225-240, March.
    4. Amit Basu & Robert W. Blanning, 2000. "A Formal Approach to Workflow Analysis," Information Systems Research, INFORMS, vol. 11(1), pages 17-36, March.
    5. Francis Kofi Andoh-Baidoo & Kweku-Muata Osei-Bryson & Kwasi Amoako-Gyampah, 2012. "Effects of firm and IT characteristics on the value of e-commerce initiatives: An inductive theoretical framework," Information Systems Frontiers, Springer, vol. 14(2), pages 237-259, April.
    6. Li-Ren Yang & Jieh-Haur Chen & Huan-Hsun Li, 2016. "Validating a model for assessing the association among green innovation, project success and firm benefit," Quality & Quantity: International Journal of Methodology, Springer, vol. 50(2), pages 885-899, March.
    7. Ravi Aron & Shantanu Dutta & Ramkumar Janakiraman & Praveen A. Pathak, 2011. "The Impact of Automation of Systems on Medical Errors: Evidence from Field Research," Information Systems Research, INFORMS, vol. 22(3), pages 429-446, September.
    8. Bernal-Jurado, Enrique & Mozas-Moral, Adoración & Fernández-Uclés, Domingo & Medina-Viruel, Miguel Jesús, 2021. "Online popularity as a development factor for cooperatives in the winegrowing sector," Journal of Business Research, Elsevier, vol. 123(C), pages 79-85.
    9. Susan A. Sherer & Rajiv Kohli & Ayelet Baron, 2003. "Complementary Investment in Change Management and IT Investment Payoff," Information Systems Frontiers, Springer, vol. 5(3), pages 321-333, September.
    10. Prasad, Acklesh & Heales, Jon, 2010. "On IT and business value in developing countries: A complementarities-based approach," International Journal of Accounting Information Systems, Elsevier, vol. 11(4), pages 314-335.
    11. Murali D. R. Chari & Sarv Devaraj & Parthiban David, 2008. "Research Note--The Impact of Information Technology Investments and Diversification Strategies on Firm Performance," Management Science, INFORMS, vol. 54(1), pages 224-234, January.
    12. Galang, Roberto Martin N., 2014. "Divergent diffusion: Understanding the interaction between institutions, firms, networks and knowledge in the international adoption of technology," Journal of World Business, Elsevier, vol. 49(4), pages 512-521.
    13. Sundar Bharadwaj & Anandhi Bharadwaj & Elliot Bendoly, 2007. "The Performance Effects of Complementarities Between Information Systems, Marketing, Manufacturing, and Supply Chain Processes," Information Systems Research, INFORMS, vol. 18(4), pages 437-453, December.
    14. Justin T. Kistler & Ramkumar Janakiraman & Subodha Kumar & Vikram Tiwari, 2021. "The Effect of Operational Process Changes on Preoperative Patient Flow: Evidence from Field Research," Production and Operations Management, Production and Operations Management Society, vol. 30(6), pages 1647-1667, June.

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