Because of the rapid growth and increased competition in information technology (IT), business process outsourcing (BPO) and other service sector industries in India, quality and cost of operations have become the major distinguishing factors among such companies. Survival, growth and profits depend on how an organization controls its costs and satisfies its clients or customers.
Many organizations have adopted quality improvement programs, the important ones being Six Sigma and Kaizen. They also have modified the techniques of these programs to best suit the organization’s needs. To generalize, the choice of the quality philosophy has been made on such factors as scope and duration of the projects, the organization’s product or processes, and the statistical intensity required to analyze and improve.
Irrespective of the quality program used, many organizations have found limitations in some of the quality improvement tools they use. At the same time, they are discovering the advantages of using simulation modeling and analysis as a problem-solving tool.
The reasons why companies are finding that some analysis methodologies provide sub-optimal results include:
These limitations of quality processes can be dealt with by implementing an operations research technique called simulation modeling and analysis.
Discrete Event System Simulation by Jerry Banks, John S. Carson II, Barry L. Nelson and David M. Nicol, (third edition) Pearson Education.
System Simulation by Geoffrey Gordon, (second edition) Prentice Hall.
“Simulation as a Tool for Continuous Process Improvement” by Mel Adams, Paul Componation, Hank Czarnecki and Bernard J. Schroer in Proceedings of the 1999 Winter Simulation Conference, IEEE Press.
Simulation is imitation of the operations of a real world process or system over time. It involves the generation of artificial history of the system and the observation of that artificial history to draw inferences concerning the operating characteristics of the real system.
Operations research and simulation modeling have been used in the past by upper management for decision-making in various areas, including supply chain management, manufacturing applications, semiconductor manufacturing, construction engineering and military applications.
Simulation is now in use in service industries to model and analyze call flows, human resource management and forecasting. Usage had generally been a one-time effort due to various disadvantages of the simulation concept, but current technology and development have actually converted these disadvantages into advantages. Some of the important ones are:
Most organizations have modified the quality techniques to suit their requirements, but the basic project methodology for continuous quality improvement remains. The projects would follow the basic outline as shown in Figure 1.
Simulation modeling and analysis as a tool can be best used in Steps 2 and 3 in the framework above. It is most useful when studying the system, designing the system, evaluating alternatives and backing up the results of the improved process.
A typical example of how it can be done is shown in Figure 2 for a Six Sigma DMAIC (Define, Measure, Analyze, Improve, Control) process. DMAIC applies to an existing process that needs improvement. It is best applicable to continuous defect reduction in a cross-functional/uni-functional environment.
Simulation modeling and analysis can be used in a quality improvement framework as an enhancement to current methods. Some key points to remember when deciding to use simulation are:
Simulation modeling as a tool currently is the best addition for a continuous improvement process. Organizations have a lot of new challenges when it comes to quality of service. These new challenges can only be dealt with by taking it up with newer ways of finding solutions. The quality framework needs to be upgraded as the situation demands.