Software-Based Innovation

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A revolution is now underway. Most innovation occurs first in software.1 And software is the primary element in all aspects of innovation from basic research through product introduction:

  • Software provides the critical mechanism through which managers can lower the costs, compress the time cycles, and increase the value of innovations. It is also the heart of the learning and knowledge processes that give innovations their highest payoffs.
  • In many cases, software is the core element in process innovations or in creating the functionalities that make products valuable to customers. In others, software is the “product” or “service” the customer actually receives.
  • Software provides the central vehicle enabling the inventor-user interactions, rapid distribution of products, and market feedback that add most value to innovations. Consequently, customers — and the software itself — make many inventions that the company’s technologists, acting alone, could not conceive.

All this demands a basic shift in the way managers approach innovation, from strategic to detailed operational levels. Some portions of the innovation process may still require traditional physical manipulation, but leading companies have already shifted many steps to software. And those who do not will suffer. Managers can shorten innovation cycles through other means, but through properly developed software, they can change their entire innovation process, completely integrating, merging, or eliminating many formerly discrete innovation steps.2 In the process, they can dramatically lower innovation costs, decrease risks, shorten design and introduction cycle times, and increase the value of their innovations to customers.

Software Dominates All Innovation Steps

Innovation consists of the technological, managerial, and social processes through which a new idea or concept is first reduced to practice in a culture. Discovery is the initial observation of a new phenomenon. Invention provides the first verification that a real problem can be solved in a particular way. Diffusion spreads proved innovations broadly within an enterprise or society. All are necessary to create new value. Software dominates all aspects of the cycle from discovery to diffusion.

· Basic research.

Most literature searches, database inquiries, exchanges with other researchers, experimental designs, laboratory experiments, analyses of correlations and variances, hypothesis testing, modeling of complex phenomena, review of experimental results, first publication of results, enhancements to existing databases, and so on are performed through software. To a large extent, software search tools determine what data researchers see and what questions they ask.

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References

1. Software is a set of instructions designed to modify the behavior of another entity or system. Although one can code molecules to modify pharmaceutical or chemical systems in a predictable fashion, it is primarily information technology software that is changing innovation processes. We will direct our discussion to the latter.

2. For the best single source of the traditional analytics for doing this, see:

P. Smith and R. Reinertsen, Developing Products in Half the Time (New York: Van Nostrand, 1992).

3. D. Weingarter, “Quarks by Computer,” Scientific American, volume 274, February 1996, pp. 116–120.

4. For classic studies of the process, see:

J. Jewkes, D. Sawers, and R. Stillerman, The Sources of Invention (New York: St. Martins Press, 1958);

Battelle Memorial Laboratories, “Science Technology, and Innovation” (Columbus, Ohio: Report to the National Science Foundation, 1973); and

J. Diebold, The Innovators: The Discoveries, Inventions, and Breakthroughs of Our Times (New York: Dutton, 1990).

5. For many thoroughly explained examples, see:

T. Steiner and D. Teixeria, Technology in Banking (Homewood, Illinois: Dow Jones-Irwin, 1990); and

National Research Council, Computer Science and Telecommunications Board, Information Technology in the Service Society (Washington, D.C.: National Academy Press, 1994).

6. For examples and details, see:

“IBM Attacks Backlog,” Computerworld, 11 October 1993, pp. 1, 7;

J. McHugh, “Trilogy Development Group,” Forbes, volume 157, 3 June 1996, pp. 122–128;

“Boeing Overhaul Taking Flight,” Information Week, 26 September 1994, p. 18; and

P. Anderson, “Conquest,” (Hanover, New Hampshire: Amos Tuck School, case, 1996).

7. J.B. Quinn and F.G. Hilmer, “Strategic Outsourcing,” Sloan Management Review, volume 35, Summer 1994, pp. 43–55.

8. Details on numerous examples appear in:

J.B. Quinn, Intelligent Enterprise (New York: Free Press, 1992).

9. Many innovative new organization forms depend heavily on software for their implementation. See:

J.B. Quinn, P. Anderson, and S. Finkelstein, “Managing Professional Intellect: Getting the Most Out of the Best,” Harvard Business Review, volume 74, March–April 1996, pp. 71–80.

10. J. Moore, “The Death of Competition,” Fortune, 15 April 1996, pp. 142–144.

11. P. Roussel, K. Saad, and T. Erickson, Third-Generation R&D (Boston: Arthur D. Little, Harvard Business School Press, 1991).

12. K. Sabbagh, The Twenty-First Century Jet (New York: Scribner, 1996).

13. J. Main, “Betting on the Twenty-First Century Jet,” Fortune, 20 April 1992, pp. 102–104, 108, 112, 116–117.

14. For a description of the electronic processes and interactions with other fields that molecular designs in biotechnology require, see:

B. Werth, The Billion-Dollar Molecule (New York: Touchstone Books, 1995).

15. “Looking for the Evidence in Medicine” (News and Comment), Science, 5 April 1996, pp. 22–24.

16. E. von Hippel, Sources of Innovation (New York: Oxford University Press, 1988).

17. P. Senge, The Fifth Discipline: The Art and Practice of the Learning Organization (New York: Doubleday, 1994).

18. R. D’Aveni, Hypercompetition (New York: Free Press, 1994).

19. J.B. Quinn and M. Baily, “Information Technology: Increasing Productivity in Services,” Academy of Management Executive, volume 8, August 1994, pp. 28–51.

20. National Research Council found attempts to build such mega-systems among the most costly errors that large users had made in installing IT. See:

National Research Council (1994).

21. J. Pine, Mass Customization: The New Frontier in Business (Boston: Harvard Business School Press, 1993).

22. For an excellent overview of the generally available network software in early 1996, see:

“The Software Revolution,” Business Week, 4 December 1995, p. 78.

23. F. Brooks, The Mythical Man-Month (Reading, Massachusetts: Addison Wesley, 1975).

24. R. Moss Kanter, The Change Masters (New York: Simon & Schuster, 1983); and

J. Utterback, Mastering The Dynamics of Innovation (Boston: Harvard Business School Press, 1994).

25. J. Kotter and J. Heskett, Corporate Culture and Performance (New York: Free Press, 1992).

26. For a more detailed view of this process, see:

H. Mintzberg and J.B. Quinn, “Microsoft (B),” in The Strategy Process (New York: Prentice Hall, 1996).

27. For futher details on this process, see:

“Andersen Consulting (Europe),” in Mintzberg and Quinn (1996).

Reprint #:

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