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Six Sigma, SPC and Business Management – UOP Simulates How to Manage Biz for Success

A University of Phoenix simulation shows how Six Sigma and SPC can be applied to almost any business situation. Looking at the number of inputs that were recorded with the help of the balanced scorecard template (two people vs. four people walking into a restaurant) can help provide insight into how a restaurant should be laid out.

In applying Learning Curve Theory to processing pizzas in the simulation entitled ‘Process Control and Problem Solving’ on the UOP Operations Management Materials website, students participate in a learning simulation that is designed to get them to visualize the restaurant process and then focus in on the sub-steps that are impacting the final outcome, which in business translates to profits and repeat business.

In this simulation, students look at several aspects of managing a business based upon understanding upper and lower control limits associated with operations costs.

They first look at the total value stream or the entire process of serving customers from the point of them walking into the store to the point of them walking out. They look at the costs associated with the seating arrangements, the staff in different jobs, and overall costs. Finally, students assess the equipment capabilities, the capacity of the restaurant as a whole, and then they look at the standard deviation of the process based upon adjusting the capacity of people and equipment in the subprocess steps.

In order to assess this process, a student must recognize first that there are two macro paths. The first being the one with customers choosing to stay and dine and the other with customers walking out. Many neophytes, when applying Six Sigma and SPC, fail to recognize that they need to look at the whole system to perfect it.

In this case, had a newbie looked at the restaurant process and failed to consider the fact that the restaurant was losing customers and only concentrated on the customers that stayed; they would be missing a critical outlet for more profits and more business.

By understanding the total picture, the owner rightly suggests within the simulation, to the student, ‘let’s focus on making sure customers stay when they come’. The data suggests that the customers enter the restaurant in a 2:1 ratio but the seating is the exact opposite. Further analysis shows that sometimes customers leave because it takes too long to wait for a table to accommodate them.

After taking this simulation the second time, the student recognizes their mistakes the first time and chooses a different seating arrangement that maximizes the capacity utilization of the restaurant.

By learning through their mistakes, as predicted in the Learning Curve Theory, the student chooses a better approach the second time they repeat the process of going through the learning simulation.

At some point, after going through this simulation a number of times, the student will no longer perfect their answers in the simulation because they have hit “near” perfect. This part of the equation is predicted in the Learning Curve Theory as well. It says, eventually when continuous improvement and six-sigma types of procedures are applied they will reach a point in time, where it is no longer cost-effective to try and continue improving a particular process.

Once a process is perfected, however, it doesn’t mean that a manager is done. Typically what happens is a control plan is put into place, and the process is continued to be monitored, and annually it is audited and compared to the customer feedback to make sure the process is still in line.

A business will then take the tools they used, and apply them elsewhere such as applying it to their vendor and procurement process.

Using data to manage a business is preferable over using subjective thinking, such as “we’ve always done it this way”, or selectively modifying the process in a trial and error type of method without data. The LCT suggests that repeatable processes can be improved, the process improvements can be measured, and at a certain point in time, these process improvements will no longer be cost-effective.