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Role for Design of Experiments in Financial Operations
B Most Master Black Belts would probably cite design of experiments (DOE) as the most underused statistical tool in financial services. Yet, designed experiments are a favorite tool of statisticians and Six Sigma practitioners working in general business environments because they are an extremely efficient way of identifying what matters in a process and what does not. That means businesses can focus their energies on the factors that really make a difference in effectiveness (quality, cost, customer satisfaction) and efficiency (speed). What distinguishes design of experiments is that:
The reason grade school science experiments were limited to only one variable at a time is because in those experiments there is no way to isolate the effects of one factor from those of another. DOE resolves that issue by using a particular kind of statistical analysis that allows differentiation among changes caused by different factors – even when all the factors are changed at the same time. A typical designed experiment will involve anywhere from three to eight factors, each of which are tested in a specific combination at two setting, or "levels." (Some designs allow more factors and more levels, but these are used less frequently.) Setting Up the ExperimentAs an example of DOE in use, here is how a designed experiment helped a financial services company improve its application process. The bank was experiencing a 60 percent reprocessing (rework) rate on applications due to incomplete information provided by the customer. The project team trying to solve this processing problem suspected that three factors might affect whether an application was complete:
The team decided to study the application process in two locations, so in all there were five factors included in the experiment, each of which had two levels:
The experiment involved 16 trials, or runs, each with a different combination of factor settings. As shown in the table below, for example, the first run tested Loan applications in the Midwest, with the current level of description and a negative example provided. The 12th run looked at Lease applications in the Northeast with the current level of description, additional examples, but not negative examples. The response (y) measured by the team was the percent complete of each application. The table shows both the experiment design and the results (the "Avg. % Complete" column).
Results of the ExperimentOf the five factors originally studied, only two of them proved to influence the percent complete:
What did not matter was Region (the completion rate was the same in both the Northeast and Midwest); Application Type (the completion rate was the same for both loans and leases); and Neg. Example (showing people what not to do did not affect completion rate). These results are captured in Figure 1, where the steepness of the lines indicates the strength of the relationship. The lines for Description and Example change a lot, while the lines for the other three factors are nearly flat.
As noted above, the DOE also reveals interactions between factors – that is, whether one factor affects another. Look at Figure 2, for example. What it shows is that having a negative example made things worse in the Midwest but improved rates in the Northeast. (In statistical terms, this means there is an interaction between Neg. Example and Region.)
From these results, the team concluded that for both types of applications:
By studying the results of the interactions closely, the team determined that negative examples did not help significantly when there were positive examples. And since the team had decided to use the positive examples, it would not pay to also develop negative examples. The new forms increased the application completeness from 60 percent to more than 95 percent, virtually eliminating reprocessing and significantly reducing the cycle time for the loan and lease application process. The additional capacity that was made available as a result of the improved process allowed the business to generate additional revenue without increasing headcount. Conclusion: Give DOE a TryMany companies avoid using design of experiments in part because it sounds complicated. Actually, the example shows that the basic setup is straightforward. All that is needed is to select the factors to test and identify different levels for those factors. It is advisable to work with a Black Belt or Master Black Belt trained in DOE to help pick out the factors and levels. That expertise will make sure the company gets the most from its investment of time and effort. A Black Belt also can help analyze and interpret the results – a process which can go quickly with statistical analysis software that is readily available. Most people who use DOE once become instant converts because the results usually have immediate practical application. It shows which process or design factors have the biggest impact on quality, speed, performance or delivery. That translates into better decisions. About the Authors: Kimberly Watson-Hemphill is a Master Black Belt with George Group and lead author of their Design for Lean Six Sigma curriculum. She has trained and coached hundreds of Black Belts and Master Black Belts throughout North America and Europe. She has a background in all areas of Lean Six Sigma, new product development and project management, and has worked with Fortune 500 companies in both service and manufacturing industries. She can be reached at kwatson@georgegroup.com. Bill Kastle is a vice president at George Group and has helped guide Lean Six Sigma initiatives at major corporations. He is co-author of the book What Is Lean Six Sigma? He has conducted executive training at Fortune 500 companies such as Alcan, Geico, Xerox, ITT Industries and DuPont-Merck. For more than 15 years, he has helped teams at all levels apply Lean and Six Sigma tools to respond to their customer needs. Mr. Kastle can be reached at bkastle@georgegroup.com. Reproduction Without Permission Is Strictly Prohibited – Copyright Requests Publish an Article: Do you have a Six Sigma tip, learning or case study? Share it with the largest community of Six Sigma professionals, and be recognized by your peers. It's a great way to promote your expertise and/or build your resume. Read more about submitting an article. "The Bottom Line" Links
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