CRISIS VERSUS NON-CRISIS SIMULATION GAMING Simulation Games and Experiential Learning in Action, Volume 2, 1975 245 CRISIS VERSUS NON-CRISIS SIMULATION GAMING Sam Barone Jack R. Dauner Jonathon S. Rakich INTRODUCTION The widespread use of simulation models is an outgrowth of the Operations Research and/or Management Science eras. Simulation has widespread application in business, education, health-care, government, and many other organizations. The process of objective and quantitative decision making, the representation of endogenous and exogenous variables, and the ability to allocate resources toward the accomplishment of specific objectives would not be developed to the degree that it is today without simulation techniques and simulation learning tools. Without simulation, the space program would not have been possible and man would not have landed on the moon. Nor would scientific research have progressed as rapidly as it has. Furthermore, the education and training of people such as airline pilots, engineers, medical students, and business students [1, pp. 26-27], to name a few, has reached a higher plateau due to simulation. Simulations, as educational tools, can range from highly sophisticated and complex multi-variable computer simulation models to those that are relatively simplistic, to non- computer simulations such as role-playing. Computer simulations can assist in the accomplishment of many educational objectives such as: (1) developing an understanding of the decision making process [5, p. 3]; (2) putting into practice the theoretical concepts of dynamic group and firm interaction; (3) emphasizing and sharpening the student’s skills in the various functional areas of business; (4) requiring the use of those forecasting tools which will aid in effective strategy formulation; (5) encouraging advance planning to improve the coordination of activities; and (6) offering a dynamic setting in which students can more fully understand the interdisciplinary mix which is required to successfully operate a profitable business organization [3, pp. 2-5]. PURPOSE Although much debate has existed pertaining to the sophistication level of business simulation models, our purpose is to report on the use of two computer oriented simulations in different decision-making settings. Simulation A involved decision- making under crisis conditions while simulation B was used under non-crisis conditions. Simulation Games and Experiential Learning in Action, Volume 2, 1975 246 Simulation A (Crisis) Simulation A was a multi-variable multiple firm simulation which involved decision making relative to the production, pricing, and marketing of a particular product in four market areas [4]. The reports available to the participants were (1) a cash flow statement, (2) an income statement, (3) a decision worksheet, and (4) a forecasting form. The variables involved were (a) the unit selling price of the product, (b) marketing expenditures, (c) the research and development expenditures, and (d) the production levels and depreciation coverage. Simulation B (Non-Crisis) Simulation B was more complex. It was a multi-variable multiple firm simulation which involved the manufacturing and selling of a product in three market areas [2]. The reports available to the participants were (1) a warehouse operations report, (2) a manufacturing report, (3) a balance sheet, (4) an income statement, (5) a cash flow statement, (6) a selling expense report, (7) the sales activity report, and (8) an over-all industry report. The variables involved were (a) independent pricing in three market areas, (b) the determination of advertising expenditures by market areas, (c) the determination and allocation of salesmen, and (d) the expenditures of R & D funds. In addition, (e) production options consisted of straight and overtime production along with increasing the efficiency of existing plant. Further, variables such as (f) the selling of stock, (g) the issuance of bonds, and (h) labor contract negotiations were present. IMPLEMENTATION Simulation A (Crisis) Simulation A was implemented at Saint Louis University by two of the writers. It was also used by one of the writers at The University of Akron in both undergraduate and graduate courses. In both instances experiments were conducted using the simulation as an exercise in decision making under crisis. Students who were pre-oriented toward simulation A generated eight sets of decisions (each representing one business quarter), during an eight hour period on a given day. Decision time was ½ hour with ½ hour turn around time from the computer center. In that only one half hour was allowed for the evaluation of data, observation of competing firms, and the actual decision- making, this simulation represented decision-making under crisis without the ability to derive as “full information” through data analysis as would otherwise be possible under normal circumstances. Simulation Games and Experiential Learning in Action, Volume 2, 1975 247 Simulation B (Non-Crisis) Simulation B was implemented by one of the writers at The University of Detroit and also at The University of Akron for use in both undergraduate and graduate Business Policy courses. The primary objective of this business simulation was to foster the integration of the business functional areas. Additional objectives were to force the establishment of objectives and strategies. APL computer terminals were made available to the students so that they could analyze their output reports in detail through the use of canned statistical packages. A sales forecast was provided giving the students rather full information of the future. The logistics consisted of each firm’s decision being submitted on Friday during each week of the term with output being distributed the following Monday morning. As a result, a four day interval was available for the data analysis and evaluation. OBSERVATIONS There are several observations that were made from the use of business simulation models under crisis and non-crisis conditions. Under “crisis conditions” some observable effects were (1) participant frustration, (2) clerical errors, (3) lack of clear objective formulation, (4) inconsistent strategies within individual firms, and (5) reactive decision-making versus overt well planned decision-making based upon data analysis. Observations made of the simulation under “non-crisis conditions” were (1) initial participant frustration which eventually channeled itself to intense competition, (2) specific delineation of objectives and strategies along with using the appropriate decision variables to implement strategy, (3) extensive data analysis with canned statistical packages, (4) team member cohesiveness and knowledge dissemination, and (5) overt versus reactive decision- making. IMPLICATIONS The implications drawn from comparing Simulation A (Crisis) with Simulation B (Non- Crisis) were varied. As pedagogical tools both Simulation A (Crisis) and B (Non-Crisis) had advantages and disadvantages. Advantages of Crisis Condition 1. Forces teams to use their time and talents efficiently 2. Forces rapid decision making within an atmosphere of crisis with no time for “dilly dallying” 3. Encourages team members to compromise or “go along” with decisions--i.e., forces consensus 4. Creates a strongly competitive atmosphere internal to the firm 5. Virtually no logistical problems relative to group meetings. Simulation Games and Experiential Learning in Action, Volume 2, 1975 248 Disadvantages of Crisis Condition 1. Does not allow sufficient time for calm and rational data analysis to determine effectiveness of strategies and whether or not changes in strategy are in order 2. Artificially or falsely represents the normal pace of real world decision making processes--i.e., emphasis is on acceleration or speed of decision making 3. Tends to lead to hastily developed reactive decisions unsupported by objective analysis and evaluation--i.e., tends to be mechanical rather than interactive 4. The integrative process is almost totally internal to the firm to the general exclusion of competing firms-- i.e., tends to be internalyzed to the team efforts with little concern for external factors in the overall market 5. Results in intense anxiety and frustration of team participants who lean toward “seat of the pants” hunches in making decisions in haste 6. Does not allow participants sufficient time to reflect upon their individual and team behavior (or to synthesize their experience) as they progress through the simulation from quarter to quarter. Advantages of Non-Crisis Condition 1. There is sufficient time to evaluate internal and external data and, if necessary, re- formulate strategy 2. Integration of functional areas appeared to be deeply reinforced 3. Full discussion of options discussed by team members and less pressure to make a quick decision or go along because of time constraints 4. Frustration appeared to be relatively low. Disadvantages of Non-Crisis Condition 1. Time and talents not always efficiently utilized 2. Interest in the last several weeks appeared to diminish. It is conceivable that the conditions of Simulation A (Crisis) would sharpen the acuity of some team participants by accelerating the decision or strategy formulation process. And it is arguable that the above average or “better” student may benefit from experience under crisis conditions. But, by and large, the crisis approach exaggerates actual business practice and to this extent distorts rather than depicts reality. Furthermore, if this goal of business simulation is to simulate the real world and to provide a vehicle for integrative learning, our experience indicates that the crisis approach as used, leaves much to be desired. Simulation Games and Experiential Learning in Action, Volume 2, 1975 249 REFERENCES 1. Babb, E. M. and Eisgruber, L. M., Management Games for Teaching and Research, (Chicago: Educational Methods, Inc., 1966). 2. Brett, Frederic A. and Scott, Charles R., “Simulett” in Hargrove, Merwin N., Harrison, Ike H., and Swearingen, Eugene L., Business Policy Cases, (Homewood, Illinois: Richard D. Irwin, 1966), pp. 613-642. 3. Carlson, John G. H. and Misshauk, Michael J., Introduction to Gaming: Management Decision Simulations, (New York: John Wiley and Sons, 1972). 4. IBM Management Decision Making Model, No. 1, International Business Machines Corporation. 5. McKenney, James L., Simulation Gaming for Management Development, (Boston: Harvard University Press, 1967). Table of Contents Volume 2, 1975 ABSEL Research - From Adolescence to Adulthood, Framing the Future of Business Simulation and Experiential Learning Inventory Simulation - A Time Sharing Television Output Simulation OMSIM: An Operations Management Game An Experiential-Cognitive Methodology in the First Course in Management: Some Preliminary Results Experiential Training Methodology, Traditional Training Methodology, and Perceived Opportunity to Satisfy Human Needs Operational Problems and Solutions of Business Gaming: A Primer One Experience with the V. K. Gadget Company - An Introduction to Managerial Accounting A conversational Marketing Mix Exercise The Use of Program BAYES in the Teaching of Sample Size Determination in Survey Research An Experiential Study of Performance in a Basic Management Course Using Student Opinions in Evaluation Results with a Business Game Some Impacts of Varying Amounts of Information on Frustration and Attitudes in a Finance Games Player Performance under Differing Player Configurations in the Investment Game: Some Preliminary Observations Integrating Across Functional Areas with a Computer-Assisted Case Using Computer Assisted Cases for Marketing Research Instruction ACQUIRES: ACcounting QUick Information REtrieval System A Simulation Approach to Data Processing Controls Motivating Simulation Game Performance and Satisfaction with Group Performance-Contingent Consequences The Educational Impact of Supplementary Personal Interaction in Computerized Business Games The Minnesota Manpower Management Simulation Games RAISE II, A Personal Simulation Management in a Test Tube: A Small Group Laboratory Simulation A Methodology for Measuring Decision Making in a Business Game A Case Study of a Capital Investment Simulation Combining Experiential and Clinical Methodologies in a Small Business Management Program Results of Using Gaming to Teach Ethics and Social Responsibility Business and Society: An In-Basket Simulation Crisis versus Non-Crisis Simulation Gaming Warm-up Company: A Business Simulation Business Simulations: Competition or Learning A Computerized Management Training System for Franchized Dealers Mode I Stores, Inc.: Computer Supported Cases on the Marketing Research and Problem Solving Process Experiential Learning in Statistics Through the Computer The COMPUSTAT Analysis System as an Instructional Resource Research on Experiential Learning: Enhancing the Process A Comparison of Lecture-Case Study and Lecture-Computer Simulation Teaching Methodologies in Teaching Minority Students Basic Marketing Student Evaluation of Reaction to a Marketing Simulation Game Under Varying Circumstances The Validity and Usefulness of Packaged Models in Game Play The Effectiveness of Experiential Methods in Training and Education: A Review Guidelines for the Future Development of Business Games The Future Potential of Structures Learning Exercises Turning Them on to Management by Turning Them Out to Managers with Video Tape Recorders