{"id":{"repo_id":"mit","oai_identifier":"oai:dspace.mit.edu:1721.1/8067"},"canonical_url":"https://search.dev.ndltd.org/etd/mit/oai:dspace.mit.edu:1721.1/8067","repository":{"repo_id":"mit","name":"MIT","base_url":"https://dspace.mit.edu/oai/request"},"display":{"title":"Evaluating the implementation of new services models in the financial advisory industry : a statistical data mining and system dynamics approach","abstract":"Program Alpha is a new business practice model designed to increase service quality and productivity of one of the world's largest financial services organizations, by implementing structured time management and a disciplined client and prospect contract process. This thesis quantitatively and qualitatively evaluates business impact of this program, by developing and applying two analytical frameworks. We first present and develop a System Dynamics framework for interpretation of qualitative information collected through interviews, focus groups and surveys, which measure the impact of Program Alpha from operational, organizational and behavioral perspectives. Secondly, we present a Statistical Data Mining framework for interpretation of quantitative financial and customer preference information. Using this framework, we generate a preliminary set of algorithmic guidelines for improvement of Program Alpha in future deployment stages. Such guidelines, based on statistical learning algorithms applied to historical data, aim to streamline the client segmentation process at the core of Program Alpha.","abstract_html":"Program Alpha is a new business practice model designed to increase service quality and productivity of one of the world's largest financial services organizations, by implementing structured time management and a disciplined client and prospect contract process. This thesis quantitatively and qualitatively evaluates business impact of this program, by developing and applying two analytical frameworks. We first present and develop a System Dynamics framework for interpretation of qualitative information collected through interviews, focus groups and surveys, which measure the impact of Program Alpha from operational, organizational and behavioral perspectives. Secondly, we present a Statistical Data Mining framework for interpretation of quantitative financial and customer preference information. Using this framework, we generate a preliminary set of algorithmic guidelines for improvement of Program Alpha in future deployment stages. Such guidelines, based on statistical learning algorithms applied to historical data, aim to streamline the client segmentation process at the core of Program Alpha.","abstract_has_math":false,"creators":["Barra, Hugo Botelho, 1976-"],"institution":"Massachusetts Institute of Technology","degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":"Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science.","school":null,"contributors":[],"advisors":["Gabriel R. Bitran."],"committee_chairs":[],"committee_members":[],"year":2002,"date_issued":"2002","date_published":"2002","updated_at":"2026-07-22T22:21:10Z","subjects":["Electrical Engineering and Computer Science."],"languages":["eng"],"rights":["M.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. 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