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This paper presents an application of the Lean Six Sigma DMAIC model. It is used to improve a plastic cup manufacturing process. The Improve Phase of the DMAIC model utilizes the amazingly simple, and yet effective, Japanese 5S techniques to achieve a dramatic improvement in the process.

The purpose of this paper is to present a new look at solving the national nursing shortage problem by discussing new approaches to minimize the impact of nursing miss‐utilization and or miss‐allocation.

Among the approaches explored is the well‐known financial engineering derivative interest rate swap as well as new scheduling applications including inventory management and queuing models.

The study found that there is great interest in the field of the nurse scheduling and staffing problem. The problems are, however, studied in isolation from one another, while their respective nature is inter‐related: staffing policies impact nursing problem model constraints. This gap may be one of the contributing factors to a well‐known gap between industry application and academic literature. Industry solutions focus encouraging the growth of nurses in the field, most of which result in a financial paradox due to increasing rate capitation for health service facilities, which began in the mid‐1990s.

Possible limitations include a resistance to application from industry, as it has not been possible to minimize the application gap.

This paper introduces a swap model that satisfies the key problems resulting from the shortage: increasing costs and gap needs. The additional approaches offer a new look from outside industry application that have yielded solutions needed in the nurse scheduling problem.

This paper aims to resolve a staffing solution for a purchasing department at the University of Miami to expand a service request bulk purchasing program that generates savings for the university and respective departments.

The well‐known lean Six Sigma methodology is applied to yield consistent results and eliminate unnecessary actions (steps/tasks) by the staff.

The university is able to reduce processing time for a service request from 168 hours to 2.27 by streamlining communication and service request and automating lengthy process steps using a proprietary built workflow intelligence system.

There are limited publications in the field of lean Six Sigma as an approach to staffing solutions.

This paper provides an unexplored practical application of lean Six Sigma to yield a staffing solution.