Inspiring Quality Solutions

We, on the other hand, focused on step 3, COA development. We investigated the use of GSS as an ideation technique to enhance the quality of COA generated. The results of our study demonstrate that the quality of COA produced during MDMP would be improved if the ideation techniques were revised. Rather than employ traditional brainstorming, MBW should be adopted. MBW (either manual or electronic) produces higher quality COA than traditional “free” brainstorming (MFB).

MBW produces COA that are more feasible than those of MFB. MBW creates COA that can better be accomplished given resources of people, money, time, and materiel. MBW produces COA that are more acceptable than those of MFB; the benefit justifies the costs. MBW produces COA that are more suitable; each COA agrees with the guidance received from the commander. MBW also produces COA that are more complete; they accomplish the mission.

Using MBW would significantly enhance the quality of COA available to commanders to meet mission requirements. With a superior tool in hand, rather than relying on intuition, commanders would be more inclined to use the analytic decisionmaking methodology that MDMP affords. MBW enhances MDMP, producing a tool of much greater facility to the commander of a military unit.

What benefits decisionmaking, benefits military operations. If leaders could use collaborative decisionmaking to formulate better COA, better OPORDs would result. Enhancing ideation would enhance the use of MDMP and ultimately improve operations.

Notes 1Adapted from Thomas P. Hanlon, Inspiring Creative Solutions: an Experimental Investigation of Three Ideation Methods in Generating Creative Product, doctoral dissertation, De Paul University, Chicago, IL, 2010. The dissertation attempted a broader scope than is reported here. Although the domain of the experiment was the military, we tried to generalize to a broader audience. The goal was creativity. A problem limiting creativity, cognitive inertia, was the focus. In this article, we have tailored back the scope. Rather than interpret FADS in terms of creativity, we have employed it as a measure of quality. Discussions of creativity (and cognitive inertia) have been omitted. 2 Chi M. Babcock, P. Reimann, and R. Glaser, “Self Explanation: How Students Study and Use Examples in Learning to Solve Problems,” Cognitive Science, Vol. 13, 1989, pp. 145-182.

3Headquarters, Department of the Army, U.S. Army Field Manual (FM) 5-0, The Operations Process, U.S. Government Printing Office (GPO), Washington, DC, 2010, p. B-3. 4Ibid., p. 2-12.

5Morgan M. Sheperd, Robert O. Briggs, Bruce Renig, Jerome Yen, and Jay F. Nunamaker Jr., “Invoking Social Comparison to Improve Electronic Brainstorming: Beyond Anonymity” Journal of Management Information Systems, Vol. 12, No. 3, 1995-1996, p. 156. 6George A. Miller, “The Magical Number Seven, Plus of Minus Two: Some Limits on our Capacity for Processing Information,” The Psychological Review, Vol. 63, No. 2, March 1956, pp. 81-97.

7Ibid.

8Ibid.

9David Schwartz, “Aristotelian View of Knowledge Management,” Encyclopedia of Knowledge Management, Idea Group Publishing, 2006.

10Gary R. Morrison, Steven M. Ross, Howard K. Kalman, and Jerrold E. Kemp, Designing Effective Instruction, 6th ed., John Wiley & Sons, Inc., Hoboken, New Jersey, 2011, p. 213.

11Ibid., p. 257.

12Ibid., p. 258.

13Miller, pp. 92-93.

14FM 5-0, p. B-16.

15A. F. Osborn, Applied Imagination: Principles and Procedures of Creative Thinking, 2d ed., Scribner, New York, 1957.

16Ibid., pp. 1-397.

17Michael Diehl and Wolfgang Stroebe, “Productivity Loss in Idea-Generating Groups Tracking Down the Blocking Effect,” Journal of Psychology and Social Psychology, Vol. 61, No. 3, 1991, pp. 392-403. 18Ibid., pp. 392-403; and Michael Diehl and Wolfgang Stroebe, “Productivity Loss in Brainstorming Groups: Towards the Solution of a Riddle,” Journal of Psychology and Social Psychology, Vol. 53, No. 3, 1987, pp. 497-509. 19Arthur B. Van Gundy, “Brain Writing for New Product Ideas: An Alternative to Brainstorming,” Journal of Consumer Marketing, Vol. 1, Issue 2, 1984, pp. 67-74; also Knut Holt, “Brainstorming — from Classics to Electronics,” Journal of Engineering Design, Vol. 7, Issue 1, 1966, pp. 77-82.

20In the dissertation, this procedure was labeled “carousel brainstorming,” and the commander’s guidance was described as “specification requirements.” The latter was used as a means of stimulating creativity. We now believe that it is more effective as a means of segmenting the information.

21We conducted the procedure synchronously; that is, all participants responded at the same time (and in the same place). But the procedure could as easily have been conducted asynchronously and from remote locations. 22Prashant Bordia, “Face-to-face versus Computer-mediated Communication: A Synthesis of the Experimental Literature,” Journal of Business Communication, Vol. 34, No. 1, January 1997, pp. 99-102. 23Poppy Lauretta McLeod, “An Assessment of the Experimental Literature on Electronic Support of Group Work: Results of Meta-analysis,” Human-Computer Interaction, Vol. 7, 1992, pp. 257-280.

24The GSS we chose for this study is the web-based software “ThinkTank ®,” produced and marketed by Groups Systems, Inc., Denver, Colorado. 25The majority of participants (76%) were undergraduate students in their fourth year of studies. Average age was

22. Seventy-eight percent were male and 22 percent female. Most (96%) had average to above average knowledge of computers. Ninety-two percent rated their knowledge of military tactics as average to above average. Their knowledge of decisionmaking, the majority rated as average to above average (88%). Collaboration techniques, on the other hand, they rated as only average (52%). Most (78%) rated their knowledge of group support systems as less than average.

26All evaluators were volunteer members of U.S. Army Reserve unit 3-75th Division (Training Support). One of the missions of the 3/75th Division is to train Army Reserve units in MDMP. Every officer of the panel had more than 6 years of service in the Army, and at least 1 year of service as a member of the 3/75th Division (Training Support). Accordingly, every panel member was an expert in the structure and use of MDMP.

27FM 5-0, p. 3-30.

28The FADS test is not used by the military as evaluation criteria for COA (that determination is left to later stages of the decisionmaking process and is specific to the mission at hand). The FADS test, rather, is an initial screening device that can be used during idea generation. For that reason, the military does not weigh FADS components as actual evaluation criteria would be so weighted. The test merely assays initial ideas to determine where to focus efforts.

29Statistical computations were done using Kwikstat for Windows ®, made by TaxaSoft, Cedar Hill, Texas. 30However, analysis of statistical significance is convoluted. Feasible, two statistically significant differences emerge: MBW differs from MFB and EBW differs from MFB, but MBW differs not from EBW. Acceptable, three statistically significant differences: MBW differs from MFB, EBW differs from MFB, and MBW differs from EBW. Distinguishable, no significant differences. Suitable, three statistically significant differences emerge: MBW differs from MFB, EBW differs from MFB, and MBW differs from EBW. Complete, three statistically significant differences: MBW differs from MFB, EBW differs from MFB, and MBW differs from EBW.

31Miller, pp. 83-84.

32Bordia, pp. 99-102; and McLeod, pp. 257-280. 33Howard C. Higley and Robert J. Harder, “Tailoring an Electronic Meeting System to Military Planning and Operations, A Case Study,” Proceedings of Hawaii International Conference on System Sciences, January 2003. Lieutenant Colonel Retired Thomas P. Hanlon is currently a visiting assistant professor, Southern Illinois University-Carbondale, Department of Workforce Education and Development, Off Campus Degree Program, Naval Station Great Lakes, Great Lakes, IL. He received a B.A. from the U.S. Military Academy, a M.A. from University of Illinois-Champaign, a M.S. from Northern Illinois University, a Ph.D. from Saint Louis University, and a Ph.D. from DePaul University. His military education includes U.S. Army Command and General Staff College, Combined Arms and Services Staff School, Adjutant General Officer Advanced Course, and Air Defense Artillery Officer Basic Course. He has served in various leader and staff positions, to include senior observer controller, 1st Battle Command Training Group, 3d Brigade, 75th Division (Training Support), Arlington Heights, IL; observer controller, 2d Simulations Group, 1st Brigade, 85th Division (TS), Fort Sheridan, IL; senior simulation coach, Battle Projection Group, 1st Brigade, 85th Division (TS), Fort Sheridan; automated data processing officer, TRADOC Combined Arms Testing Activity (TCATA), Fort Hood, TX; and commander, Headquarters and Headquarters Company, TCATA, Fort Hood.