Move Over Flowcharts

Performance Improvement H. James Harrington
“Simulation modeling is a dynamic tool for improving systems”

During the 1980s using flowcharts was the “in thing” to do. Today, technology has provided us with a much more effective and useful tool: simulation modeling. If a picture is worth a thousand words, then one that logically simulates tasks and collects data has to be worth a million. Simulation models have the capability of considering complex interrelated tasks and structurally projected outcomes in a matter of seconds, providing users with validated, and usually quite reliable, results.

Author Charles R. Harrell defines simulation as “a means of experimenting with a detailed model of a real system to determine how the system will respond to changes in its structure, environment, or underlying assumptions.” It allows for a better understanding of processes with a goal of improving performance. Simulation modeling provides a means to evaluate, redesign, and measure or quantify customer satisfaction, resource utilization, process streamlining, and time spent.

Process simulation is a powerful means by which new or existing processes may be designed, evaluated, and visualized without running the risks associated with conducting tests on a real system. Dynamic process simulation allows organizations to study their processes from a system’s perspective, thereby gaining a better understanding of cause and effect in addition to predicting outcomes. Simulation’s strengths and capabilities make it an ideal tool in reengineering. It aids in evaluating, redesigning, and measuring:
  • Customer satisfaction and quantifying it for the new process or system
  • Resource use in the new redesigned process or system
  • Processes and how to streamline them
  • Time with a goal of minimizing it

During a reengineering effort, simulation can assist in the following areas:
  • Feasibility analyses. Examining the viability of new processes in the light of various constraints. Conducting a cost-benefit analysis or process evaluation.
  • Visioning. Exploring the possibilities for the system in the future state
  • Performance characteristics. Examining the performance metrics of a system either in its current or future state
  • Prototyping. Once a future-state vision for a reengineered process is generated, prototyping using simulation can help in implementation planning, risk assessment, and process design.
  • Communication. Disseminating information about the new reengineered process to the organization

Simulation can assist in creative problem solving, too. Fear of failure prevents people from coming up with ideas. Simulation allows for creative experimentation and testing, followed by selling the idea to management. It encourages an optimistic, “let’s try it” attitude.

Simulation can help predict outcomes. For example, it could help in predicting the response to market demands placed on a business system, analyzing whether the existing infrastructure can handle the new demand placed on it. Simulation can thus help determine how resources may be efficiently used.

Simulation can account for system variances. Conventional analytical methods, such as static mathematical models, don’t effectively address variance because calculations are derived from constant values. Simulation looks at system variances, taking into consideration interdependence, interaction among components, and time. It allows for a broader perspective.

Simulation promotes total solutions by modeling entire systems. It offers insight into a system’s capabilities, and the effect process changes will have on the system’s inputs and outputs. Additionally, simulation modeling allows for experimenting with system parameters without tampering with the real system. It provides more alternatives, lower risks, increases the probability of success, and generates information for decision support.

Simulation can be cost effective. As organizations try to respond quickly to changes in their markets, a validated simulation model can be an excellent tool for evaluating rapid responses. For example, a sudden change in market demand for a product can be modeled using a validated system model to determine whether the existing system can cater to this need.

Simulation can help quantify performance metrics. For example, the aim of a system may be to satisfy the customer. Using a simulation model, this requirement could be translated to the time required to respond to a customer’s request, which can then be designated as the performance measure for customer satisfaction. Simulation can help measure tradeoffs associated with process designs and allow for further analysis on parameters such as time to market, service levels, market requirements, carrying costs, SKU levels, and so forth. It thus provides a quantitative approach to measuring performance.

Simulation is an effective communication tool. It can be used to introduce a new reengineered process in a dynamic and animated fashion. This is a powerful means of explaining the function of various components to those who will use the new system, helping them understand how it works.

You don’t lose customers over averages; it’s the extremes that make them unhappy—e.g., you commit to a three-day delivery, and it takes two weeks. Simulation modeling is the only effective way to do Monte Carlo analysis of a total process.

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