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dc.contributor.advisorMort Webster and Georgia Perakis.en_US
dc.contributor.authorOgura, Norien_US
dc.contributor.otherLeaders for Global Operations Program.en_US
dc.date.accessioned2013-09-24T19:36:47Z
dc.date.available2013-09-24T19:36:47Z
dc.date.copyright2013en_US
dc.date.issued2013en_US
dc.identifier.urihttp://hdl.handle.net/1721.1/81010
dc.descriptionThesis (M.B.A.)--Massachusetts Institute of Technology, Sloan School of Management; and, (S.M.)--Massachusetts Institute of Technology, Engineering Systems Division; in conjunction with the Leaders for Global Operations Program at MIT, 2013.en_US
dc.descriptionCataloged from PDF version of thesis.en_US
dc.descriptionIncludes bibliographical references (p. 63-64).en_US
dc.description.abstractMany methods for analyzing the possibility of errors are practiced by organizations who are concerned about safety and error prevention. However, in situations where the error occurrence is random and difficult to track, the rate of errors at a particular instant in time is not a practical metric of hazardous conditions (or whether a system may be vulnerable to errors). Qualitative indicators (such as stress levels) that are easier to observe, but difficult to measure, may be linked to the dynamic behavior of quantitative indicators that are easier to measure using System Dynamics models. In this work, we propose a method to find an appropriate metric for error analysis, by determining the direct quantitative triggers associated with the qualitative indicators of hazardous conditions. A System Dynamics model is generated for determining the measurable quantitative indicator behaviors linked to more apparent qualitative factors for determining the health of a system. Used in concert with other system methodologies, it gives insight into triggers and policies for developing and implementing improvement processes. The context of this research is in reducing billing errors at a utility company which for confidentiality reasons we refer to as United Energy. We use several system methodologies including System Dynamics and Safety System Analysis, to assess the billing operation system and process, to develop a project management plan for the development and implementation of a tool to reduce billing errors.en_US
dc.description.statementofresponsibilityby Nori Ogura.en_US
dc.format.extent64 p.en_US
dc.language.isoengen_US
dc.publisherMassachusetts Institute of Technologyen_US
dc.rightsM.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.en_US
dc.rights.urihttp://dspace.mit.edu/handle/1721.1/7582en_US
dc.subjectSloan School of Management.en_US
dc.subjectEngineering Systems Division.en_US
dc.subjectLeaders for Global Operations Program.en_US
dc.titleA systems approach to reducing utility billing errorsen_US
dc.typeThesisen_US
dc.description.degreeS.M.en_US
dc.description.degreeM.B.A.en_US
dc.contributor.departmentLeaders for Global Operations Program at MITen_US
dc.contributor.departmentMassachusetts Institute of Technology. Engineering Systems Division
dc.contributor.departmentSloan School of Management
dc.identifier.oclc857790055en_US


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