Many organizations are struggling to improve customer-focused quality in today's highly competitive domestic and global markets. At the same time, these organizations have failed to implement the Six Sigma methodology into their daily control and strategic planning processes. Six Sigma deployment failures have been categorized as coming from many sources, both management related and person related. Some of the key management related Six Sigma project failures have been identified and discussed in this research work. For continuous improvement to truly take root, organizations must realize that just successfully applying quality tools on any process will not necessarily provide dramatic results, unless the concepts of policy management and deployment are institutionalized. A model called "Six Sigma Policy Deployment" was developed and has been proposed which may help mitigate Six Sigma project failures that are presently attributed to management and organizational issues. By integrating Policy Deployment, the Six Sigma DMAIC (Define-Measure-Analyze-Improve-Control) problem solving approach, and the classic PDCA (Plan-Do-Check-Act) Cycle, the potential for breakthrough improvements in any organization can be enhanced. The model was contrasted against a list of 30 sources of failure in typical Six Sigma projects in order to validate its applicability to mitigate these failures. Furthermore these failures were matched with the work of recent quality theorists in order to validate their occurrence and relevance. A case study section is presented to illustrate FPL's Quality Improvement Program and the Six Sigma Lifecycle, which are bases for the new model. This section also highlights how the use of the proposed Six Sigma Policy Deployment model could help to mitigate potential Six Sigma project failures.

Goal of the thesis is a detail description of the project methodology within the Telecommunication Company and pointing out the differences between current existing methodology and methodology standards. The thesis is not just simple description of the project methodology but addition to that it tries to (in given time & material framework) design new solutions for the project process optimalization. The aim of the proposed solutions is to increase competitiveness of the company on the market in current dynamic environment. Thesis has two main parts, theoretical and practical one. Theoretic part deals with general project methodologies and compares theirs main features and characteristics. One of the chapters is also describing Six Sigma process methodology, that will play a major role in the practical part of the thesis. In practical part, first of all I am introducing the company Vodafone Czech republic which allowed me the creation of the diploma thesis. Following chapter is focused on existing project methodology, project life-cycle and tools that the company uses in day-to-day practice. Next chapter deals with the detail analysis of the project process and by using of real samples of the company projects I try to find the optimalization of the project process in order to speed up the time to market and thus provide faster reaction to the market conditions and needs. Final chapter provides a summary and conclusion of the work done. Benefits of the diploma thesis should be following: 1)Detail mapping of the project methodology in mobile operator environment 2)Analysis of the current existing project process and project lifecycle 3)Possibility to get greater knowledge about the work of the Project management office 4)Design a possible solution that would help to increase competitiveness on the market

Made available in DSpace on 2016-06-02T19:51:53Z (GMT). No. of bitstreams: 1 4153.pdf: 2182125 bytes, checksum: a074f91bda22478d2c98528b9d3de6ff (MD5) Previous issue date: 2012-02-27 / Financiadora de Estudos e Projetos / The organizations face problematic situations that involve the analysis of a significant number of correlated variables to reduce the variability of production processes. There are many approaches, methods and techniques to support problem solving, however has achieved distinction in literature and adopted by Six Sigma companies, one of whose goals is to identify and eliminate the causes of variation in product and process through the use of techniques statistics. The Multivariate Data Analysis (MDAs) belongs to a set of techniques that examine both the relationship between several variables, have not been included in intensive training programs in Six Sigma. This research is qualitative and descriptive, whose purpose is to confirm the dimensions criticism from Firka (2011) and Montgomery (2010) agree that the use of statistical methods to problems of manufacturing in the context of Six Sigma programs, through the study of multiple cases. These research findings confirm the association between the use of technical barriers in the MDAs to factors of management and sociology, such as the lack of management support, focus on short-term results, the methodological factors (selection and validation of variables and results) and the statistical assumptions (multivariate normality, multicollinearity and homoscedasticity). / As organizações enfrentam situações problemáticas que envolvem a análise de um conjunto significativo de variáveis correlacionadas para reduzir a variabilidade dos processos produtivos. Há muitas abordagens, métodos e técnicas de apoio à solução de problemas; entretanto tem obtido destaque na literatura e adotado pelas empresas o Seis Sigma, cujo um dos objetivos é identificar e eliminar as causas de variação do produto e processo por meio do uso de técnicas estatísticas. A Análise de Dados Multivariados (MDAs) pertencem a um conjunto de técnicas que analisam simultaneamente a relação existente entre diversas variáveis, ainda pouco difundidas nos programas de treinamento em Seis Sigma. Esta pesquisa tem caráter qualitativo-descritivo, cujo objetivo é confirmar as dimensões críticas apontadas por Firka (2011) e Montgomery (2010) que comprometem o uso de métodos estatísticos em problemas da manufatura no contexto dos programas Seis Sigma, por meio do estudo de casos. Os resultados desta pesquisa confirmam a associação entre as barreiras no uso de técnicas MDAs a fatores de ordem gerencial e sociológica, tais como, a falta de suporte gerencial, foco em resultados de curto prazo, fatores de ordem metodológica (seleção e validação das variáveis e dos resultados) e aos pressupostos estatísticos (Normalidade Multivariada, Multicolinearidade e Homocedasticidade). Palavras chaves: Analise de Dados Multivariados (MDAs). Fatores Críticos. Melhoria Contínua (MC). Projetos Seis Sigma.