Local government improves the lives of its citizens with Six Sigma and MINITAB

by Minitab on 21st October 2008

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Minitab

The city of Fort Wayne, USA has famously - and successfully - applied Six Sigma principles to its government systems. This case study shows some examples of how this was done.

Introduction

All city governments strive to give their citizens a safe and healthy place to live while offering businesses an attractive location to develop and prosper. As material and service costs rise, however, municipalities ﬁnd it increasingly difﬁcult to provide public safety and quality services within the constraints of a limited budget. To face this challenge, Graham Richard, mayor of Fort Wayne, Indiana, implemented an innovative solution that borrows techniques from industry and applies them to his city’s government.

Before becoming mayor, Graham Richard participated in a number of government-business partnerships. In these he witnessed industry in the Fort Wayne area use a MINITAB-driven Six Sigma program to improve efficiency and offer customers better goods and services. Impressed with the results, he believed Fort Wayne’s government and its citizens also could benefit from the same comprehensive approach. After his election in 2000, he introduced a Six Sigma program to the city, with the goals of improving services and making government more efficient and responsive.

Shortly after taking ofﬁce, Mayor Richard laid the foundation for the city’s Six Sigma effort – believed to be the ﬁrst in municipal government – by forming the Executive Quality Council and appointing former corporate executive Michele Hill to the newly created position of Quality Manager. To gain public support for the program, Mayor Richard wanted the initial Six Sigma projects to focus on services that were highly visible and of greatest concern to residents. With this in mind, the Executive Quality Council selected pothole repair and garbage collection as 2 of the ﬁrst 15 processes to improve.

Smoothing the Road – The Pothole Project

Spring is pothole season across the northern Midwest. As the ice and snow melt and refreeze, the resulting potholes damage cars and cause accidents, costing the city thousands of dollars. Bob Kennedy, Associate Director of Public Works and Utilities, led a Six Sigma project to reduce the city’s response time to pothole complaints. At the start of the project, the city repaired 77% of the potholes within 24 hours of receiving the complaint. Kennedy’s goal was to repair 97% of the potholes within 24 hours.

Because Six Sigma projects use data to uncover the roots of the problem, they often challenge commonly held beliefs, and the pothole project was no exception. Before the data were collected, many long-time employees of the department believed that most potholes occurred in the southeast quadrant of the city. Yet the project’s data showed the northeast quadrant actually had the most potholes – 8% more than the southeast quadrant (Figure 1). The project team clearly demonstrated the facts to the department, using MINITAB to transform the collected raw data into easily understood graphs. Kennedy says, “The workers and middle managers understand a graph more easily than simply looking at data. Our graphs had a wide effect through the whole organization.”

Figure 2

Armed with a better understanding of the problem, the project team analyzed their collected data to identify ways to reduce future response times. Again, MINITAB proved invaluable, helping the team to explore possible solutions. The team created a main effects plot (Figure 2) – measuring response time by quadrant – which showed the southwest had the quickest response, by far. Upon investigation, the team discovered that the southwest quadrant’s foreman relayed complaints to his workers faster, personally picking up new complaints from the central dispatch ofﬁce on his lunch break. Seeing that quick communication signiﬁcantly reduced the response time, the team reﬁned the process further. Now, the central dispatch ofﬁce immediately radios complaints directly to the work crews.

Figure 3