Application of Lean Management Principles To

Lean was first adopted as a management technique for improving results in manufacturing environments. It is based on the 5 principles of identifying the Value to be created, mapping the Value-Stream (incremental addition of value), ensuring process Flow, orienting the process towards the Pull of the customer and finally eliminating all Waste through a process of continuous improvement. This framework is highly adaptable, and has been applied in recent years to non-manufacturing efforts, such as product development and the retail and service industries. We explore the application of Lean to voting. Applications can be found in the phases of technology development, production, deployment, poll management and more. By following a structured approach based on Lean, the efforts to advance voting solutions in the US can gain in efficiency, security, privacy and credibility over their current state. These will be adapted to deal with the voting environment, which imposes a unique set of challenges and follows priorities different from normal corporations. Additional Lean elements, such as eliminating irregularities through standardization, improved training and process transparency will be reviewed. The development and deployment of Brazilian voting system will be presented as an example of how Lean elements can be used in the voting setting. While not intentionally created by the Lean model, the design, deployment and current use of the Brazilian system is highly complimentary to this model. Finally, we suggest ways in which such an approach can be applied to the U.S. voting system. With a theoretical structure in place, specific improvement efforts can be devised and applied in the field. This study, therefore, is intended as a preliminary effort of identifying a problem and modeling it. It hopes to induce a commitment to Lean which will put in motion a cycle of implementation, elaboration and continuous improvement. Thesis Advisor: Ted Selker Title: Associate Professor, Media Lab, MIT Thesis Supervisor: Thomas B. Sheridan Title: Professor of Mechanical Engineering, MIT