13.6 Other Simulation Issues
Simulation is one of the most widely used tools in business. As we have seen in the earlier parts of this chapter, applications abound, as we are not restricted by the assumptions in some of the mathematical models discussed in earlier chapters. In this section, we look at a few other issues related to simulation, including some of the software tools available.
Two Other Types of Simulation Models
Simulation models are often broken into three categories. The first, the Monte Carlo method just discussed, uses the concepts of probability distribution and random numbers to evaluate system responses to various policies. The other two categories are operational gaming and systems simulation. Although in theory the three methods are distinctly different, the growth of computerized simulation has tended to create a common basis in procedures and blur these differences.3
Operational Gaming
Operational gaming refers to simulation involving two or more competing players. The best examples are military games and business games. Both allow participants to match their management and decision-making skills in hypothetical situations of conflict.
Military games are used worldwide to train a nation’s top military officers, to test offensive and defensive strategies, and to examine the effectiveness of equipment and armies. Business games, first developed by the firm Booz Allen Hamilton in the 1950s, are popular with both executives and business students. They provide an opportunity to test business skills and decision-making ability in a competitive environment. The person or team that performs best in the simulated environment is rewarded by knowing that his or her company has been most successful in earning the largest profit, grabbing a high market share, or perhaps increasing the firm’s trading value on the stock exchange.
During each period of competition, be it a week, month, or quarter, teams respond to market conditions by coding their latest management decisions with respect to inventory, production, financing, investment, marketing, and research. The competitive business environment is simulated by computer, and a new printout summarizing current market conditions is presented to the players. This allows teams to simulate years of operating conditions in a matter of days, weeks, or a semester.
Systems Simulation
Systems simulation is similar to business gaming in that it allows users to test various managerial policies and decisions to evaluate their effect on the operating environment. This variation of simulation models the dynamics of large systems. Such systems include corporate operations,4 the national economy, a hospital, or a city government system.
In a corporate operating system, sales, production levels, marketing policies, investments, union contracts, utility rates, financing, and other factors are all related in a series of mathematical equations that are examined by simulation. In a simulation of an urban government, systems simulation can be employed to evaluate the impact of tax increases, capital expenditures for roads and buildings, housing availability, new garbage routes, immigration and out-migration, locations of new schools or senior citizen centers, birth and death rates, and many more vital issues. Simulations of economic systems, often called econometric models, are used by government agencies, bankers, and large organizations to predict inflation rates, domestic and foreign money supplies, and unemployment levels. Inputs and outputs of a typical economic system simulation are illustrated in Figure 13.5.
The value of systems simulation lies in its allowance of what-if questions to test the effects of various policies. A corporate planning group, for example, can change the value of any input, such as an advertising budget, and examine the impact on sales, market share, or short-term costs. Simulation can also be used to evaluate different research and development projects or to determine long-range planning horizons.
Verification and Validation
In the development of a simulation model, it is important that the model be checked to see that it is working properly and providing a good representation of the real-world situation. The verification process involves determining that the computer model is internally consistent and following the logic of the conceptual model.
Validation is the process of comparing a model to the real system that it represents to make sure that it is accurate. The assumptions of the model should be checked to see that the appropriate probability distribution is being used. An analysis of the inputs and outputs should be made to see that the results are reasonable. If we know what the actual outputs are for a specific set of inputs, we could use those inputs in the computer model to see that the outputs of the simulation are consistent with the real-world system.
It has been said that verification answers the question “Did we build the model right?” On the other hand, validation answers the question “Did we build the right model?” Only after we are convinced that the model is good should we feel comfortable in using the results.
Role of Computers in Simulation
We recognize that computers are critical in simulating complex tasks. They can generate random numbers, simulate thousands of time periods in a matter of seconds or minutes, and provide management with reports that make decision making easier. As a matter of fact, a computer approach is almost a necessity for us to draw valid conclusions from a simulation. Because we require a very large number of simulations, it would be a real burden to rely on pencil and paper alone.
While general-purpose programming languages can be used for simulation, some special simulation software tools have been developed that make the simulation process much easier. Among the numerous tools available are Arena, ProModel, SIMUL8, ExtendSim, and Proof 5.5 In addition to these stand-alone tools, there are several Excel add-ins, such as @Risk, Crystal Ball, RiskSim, and XLSim, which can make simulating with Excel very easy.
