Submitted by Maicon Juliano Schmidt (maicons) on 2015-06-05T17:13:04Z No. of bitstreams: 1 Daniel Burin Chu.pdf: 1313899 bytes, checksum: 1d5a23ac357f108c3b3a1a678db082e1 (MD5) / Made available in DSpace on 2015-06-05T17:13:04Z (GMT). No. of bitstreams: 1 Daniel Burin Chu.pdf: 1313899 bytes, checksum: 1d5a23ac357f108c3b3a1a678db082e1 (MD5) Previous issue date: 2015-04-24 / Nenhuma / O texto propõe uma análise da ambiência que configura o telemarketing na sociedade brasileira. Para isso foi realizada uma observação minuciosa de uma Central de Relacionamento (Call Center), em Porto Alegre. Procuramos verificar as lógicas comunicacionais e as constantes principais no trabalho realizado por operadores de telemarketing. A dissertação procura verificar os dois lados do processo: produtores (atendentes de telemarketing), e receptores (consumidores de telemarketing). No ambiente da circulação, e da Midiatização, oferecemos ao leitor uma pesquisa, um método, e um panorama da situação da questão Call Center-Telemarketing, no mundo da mídia. Isso se fez, principalmente, pela análise do site “Reclame Aqui” (reclameaqui.com.br), e do Canal do Youtube, “Porta dos Fundos”. Realizamos 11 entrevistas com produtores, e 11 entrevistas com receptores. Para tanto foi utilizado o “método clínico” de Piaget, via Delval (2002), para conhecer o pensamento dos sujeitos envolvidos nos processos. Propomos um modelo triádico de análise, a partir da observação do universo dos Call Centers. Esta tríade é formada pelas seguintes categorias: “estranhamento”; “incomunicabilidade”; “ancestralidade”. Este é o motor da pesquisa, e é por esta tríade que caminha toda a nossa dissertação. O método do trabalho é preferencialmente marcado por inferências abdutivas, e é preciso notar que, as três categorias elencadas, fazem parte de um processo altamente inferencial e hipotético, tentando dar as devidas respostas ao fenômeno. / The paper presents an analysis of the environment that sets the telemarketing in Brazilian society. For this a thorough observation of a Customer Service ( Call Center ) was held in Porto Alegre. Tried to verify the communication logic, and the main work done by telemarketers. The dissertation tries to verify both sides of the case: producers (telemarketing operators) and receivers (telemarketing consumers). In circulation environment, and Mediazation, offer the reader a search, a method, and the present situation of the matter Call Center-Telemarketing, in the media world. This was done mainly by the analysis of site “Here Claim” ( reclameaqui.com.br ), and the Youtube Channel, “The Funds Door”. We conducted 11 interviews with producers, and 11 interviews with recipients. For this we used the “clinical method” of Piaget , via Delval (2002 ), to know the thoughts of those involved in the processes. We propose a triadic model of analysis, from the observation of Call Centers universe. This triad is formed by the following categories: “strangeness”; “incommunicado” ; “ancestry”. This is the engine of research, and it is for this triad walks throughout our dissertation. The working method is preferably marked by abductive inferences, and it should be noted that the three categories listed, are part of a highly hypothetical and inferential process, trying to give appropriate answers to the phenomenon.

Made available in DSpace on 2016-04-25T16:45:16Z (GMT). No. of bitstreams: 1 Sandra Gentil Di Dario.pdf: 3990902 bytes, checksum: 449a1afac524dd8c2b678106308a06c2 (MD5) Previous issue date: 2009-05-29 / This research focuses on labour issues of an In-house Call Center of a bank, located in the State of São Paulo, which was chosen for being an enterprise of a growing service sector as well as an expressive sector regarding the hiring of workers in Brazil. The research is based on a case study whose participants are two groups of In-house Call Center employees: the employees who have a leading position (supervisor, coordinator and manager) and the ones that do not have a leading position (agents and analysts). The aim of this study is to know the meaning of work attributed by the workers to their own work as well as to the three dimensions of the research instrument: conditional variables, central variables and future consequences. The methodological foundation was based on the dimensions presented in the methodology Meaning of Working (MOW, 1987) adapted to the theoretical foundation of Morin (2004). The research was based in a sample of an In-house Call Center, totalizing 170 questionnaires responded. The data analysis shows the employees opinions regarding the dimensions of the research structure, organized by gender and group of workers of leading and non-leading positions, in the following way: (1) conditional variables: professional and personal situation; nature of the work; organizational structure - management practices; and work conditions; (2) central variables: know the opinion of the employees as to the rank of importance of the work in their professional and personal lives as well as to when an activity means work; relative and objective centrality of work; and finally, with regard to the institutional norms: know the perception of the workers towards their rights, obligations and ethical behavior. Our findings, on the one hand, show that the workers of the In-house Call Center are satisfied with their work conditions as well as with the management style of their employer, the bank; on the other hand, however, the results show that the characteristics of the In-house Call Center sector are low autonomy and high monitoring. Concluding, we consider relevant that the organizations pay attention to the opinion of their employees in order to the quality of professional relationships at workplace / Esta pesquisa está centrada nas questões do trabalho em serviços, em uma central de atendimento própria de um Banco do Estado de São Paulo, por tratar-se tanto de uma empresa do setor de serviços em expansão como por ser um setor expressivo em relação à contratação de pessoas no cenário brasileiro. A pesquisa parte do estudo de caso, cujo objeto de estudo são os profissionais ocupantes do cargo de liderança (supervisor, coordenador e gerente) e não-liderança (operadores e analistas) de uma central de atendimento própria. O objetivo desta dissertação é conhecer o significado do trabalho atribuído pelos profissionais ao próprio trabalho bem como às dimensões do instrumento de pesquisa: variáveis condicionais, variáveis centrais e conseqüências futuras. O embasamento metodológico baseou-se nas dimensões apresentadas na metodologia de pesquisa Meaning of Working (MOW, 1987), adaptada à fundamentação teórica de Morin (2004). A pesquisa partiu da amostra de uma central de atendimento própria, totalizando 170 questionários respondidos. A análise dos dados permite apresentar as opiniões dos profissionais em relação às dimensões da estrutura da pesquisa, por gênero e grupo de cargos classificados como líderes e não líderes, a saber: (1) variáveis condicionais: situação pessoal e profissional; natureza do trabalho; estrutura organizacional - práticas de gestão; condições de trabalho; (2) variáveis centrais: conhecer a opinião dos profissionais quanto ao grau de importância do trabalho em sua vida pessoal e profissional e quando uma atividade significa trabalho; centralidade objetiva e relativa do trabalho; e (3) normas societais: conhecer a percepção dos profissionais com relação aos direitos, aos deveres e à ética. Os resultados de nosso estudo, por um lado, mostram que os profissionais da central de atendimento própria estão satisfeitos com as condições de trabalho bem como com o estilo de gestão de pessoas; no entanto, por outro lado, mostram que as características do setor da central de atendimento própria são confirmadas como baixa autonomia e alto monitoramento. Concluindo, acreditamos ser relevante que as organizações se ocupem das opiniões dos profissionais de modo a possibilitar-lhes aprimorar a qualidade das relações profissionais no local de trabalho

Scripting, defined as the mechanization of business processes through automated tools or orchestrated responses, has played a significant role in shaping call center activities and the resultant customer relationship. However, findings of industry research have shown that the use of scripting to maximize operational efficiency has had a disempowering effect on call center employees by lowering their job-skill and knowledge requirements. Grounded in the concepts of knowledge management and knowledge transfer, this study explored the experiences of frontline call center employees on the effects of scripting on customer problem solving. A single-case study design with semistructured interviews was used with a population of 20 frontline employees in a North American call center to gather insights. Thematic analysis was applied to the interview data using nodes to identify emerging themes and insights. Three major themes emerged: First, although scripting had contributed to improved service quality and operational efficiency, scripted practices undermined the use of team knowledge and limited the amount of shared information. Second, the employees requested that call center scripted solutions be more intuitive and better aligned to knowledge requirements. Third, the employees suggested that an object-oriented approach to solution management be used, one that could better leverage communities of practices and collective team knowledge sharing within the organization. This object-oriented approach to solution management may promote virtual knowledge flow and the building of subject matter expertise that could elicit higher agent engagement and problem ownership. The proposed object-oriented approach to knowledge sharing is important to management, as it could help facilitate knowledge reuse and improved organizational performance.

Zugl.: Köln, Universiẗat, Diss., 2007.

Call centers are an important function of most companies’ day to day business activities. They are often the link between a company and its customers and hugely impact the customer’s perspective or point of view (POV) of a company. A call center in the most general sense is a place, representing a business, which receives inbound calls from customers and/or makes outbound calls to customers, the latter being most commonly referred to as telemarketing. There was a time when a typical call center strictly consisted of agents who handled inbound/outbound calls; these agents are considered specialized agents. Generally speaking, a specialized agent is one trained, in-depth, in a particular area of knowledge. Most businesses have transgressed from your typical call center into contact centers. Contact centers operate essentially the same as a call center but interact with the customer in a variety of ways including, but not limited to: Phone, Mail, Fax, Email, and Internet (via online chat and instant messaging applications). The dynamics of these kinds of call centers has caused an increase in the need for agents to become more diverse in their talents and abilities to handle different types of calls. This has lead to specialized agents becoming general or “cross-trained” agents in which they are trained, broadly, over several areas of knowledge. The purpose of this thesis is to compare specialized agents to cross-trained agents and through the use of simulation, determine which of the two are more efficient and reliable in their ability to service the customer. This thesis has three major components: Simulation, Reliability Analysis, and Comparison. The results indicate that a cross-trained model is more reliable and efficient than a specialized model. Performance metrics common to call center literature, simulation, and Lean reliability systems were used to determine the effectiveness and reliability of the two models.

Call centers are an important function of most companies’ day to day business activities. They are often the link between a company and its customers and hugely impact the customer’s perspective or point of view (POV) of a company. A call center in the most general sense is a place, representing a business, which receives inbound calls from customers and/or makes outbound calls to customers, the latter being most commonly referred to as telemarketing. There was a time when a typical call center strictly consisted of agents who handled inbound/outbound calls; these agents are considered specialized agents. Generally speaking, a specialized agent is one trained, in-depth, in a particular area of knowledge.Most businesses have transgressed from your typical call center into contact centers. Contact centers operate essentially the same as a call center but interact with the customer in a variety of ways including, but not limited to: Phone, Mail, Fax, Email, and Internet (via online chat and instant messaging applications). The dynamics of these kinds of call centers has caused an increase in the need for agents to become more diverse in their talents and abilities to handle different types of calls. This has lead to specialized agents becoming general or “cross-trained” agents in which they are trained, broadly, over several areas of knowledge.The purpose of this thesis is to compare specialized agents to cross-trained agents and through the use of simulation, determine which of the two are more efficient and reliable in their ability to service the customer. This thesis has three major components: Simulation, Reliability Analysis, and Comparison. The results indicate that a cross-trained model is more reliable and efficient than a specialized model. Performance metrics common to call center literature, simulation, and Lean reliability systems were used to determine the effectiveness and reliability of the two models.

Thesis (Ph. D.)--Rutgers University, 2009. / "Graduate Program in Communication, Information and Library Studies." Includes bibliographical references (p. 185-193).

We consider the problem of staffing large-scale service centers with multiple customer classes and agent types operating under quality-of-service (QoS) constraints. We introduce formulations for a class of staffing problems, minimizing the cost of staffing while requiring that the long-run average QoS achieves a certain pre-specified level. The queueing models we use to define such service center staffing problems have random inter-arrival times and random service times. The models we study differ with respect to whether the arrival rates are deterministic or stochastic. In the deterministic version of the service center staffing problem, we assume that the customer arrival rates are known deterministically. It is computationally challenging to solve our service center staffing problem with deterministic arrival rates. Thus, we provide an approximation and prove that the solution of our approximation is asymptotically optimal in the sense that the gap between the optimal value of the exact model and the objective function value of the approximate solution shrinks to zero as the size of the system grows large. In our work, we also focus on doubly stochastic service center systems; that is, we focus on solving large-scale service center staffing problems when the arrival rates are uncertain in addition to the inherent randomness of the system's inter-arrival times and service times. This brings the modeling closer to reality. In solving the service center staffing problems with deterministic arrival rates, we provide a solution procedure for solving staffing problems for doubly stochastic service center systems. We consider a decision making scheme in which we must select staffing levels before observing the arrival rates. We assume that the decision maker has distributional information about the arrival rates at the time of decision making. In the presence of arrival-rate uncertainty, the decision maker's goal is to minimize the staffing cost, while ensuring the QoS achieves a given level. We show that as the system scales large in size, there is at most one key scenario under which the probability of waiting converges to a non-trivial value, i.e., a value strictly between 0 and 1. That is, the system is either over- or under-loaded in any other scenario as the size of the system grows to infinity. Exploiting this result, we propose a two-step solution procedure for the staffing problem with random arrival rates. In the first step, we use the desired QoS level to identify the key scenario corresponding to the optimal staffing level. After finding the key scenario, the random arrival-rate model reduces to a deterministic arrival-rate model. In the second step, we solve the resulting model, with deterministic arrival rate, by using the approximation model we point to above. The approximate optimal staffing level obtained in this procedure asymptotically converges to the true optimal staffing level for the random arrival-rate problem. The decision making scheme we sketch above, assumes that the distribution of the random arrival rates is known at the time of decision making. In reality this distribution must be estimated based on historical data and experience, and needs to be updated as new observations arrive. Another important issue that arises in service center management is that in the daily operation in service centers, the daily operational period is split into small decision time periods, for example, hourly periods, and then the staffing decisions need to be made for all such time periods. Thus, to achieve an overall optimal daily staffing policy, one must deal with the interaction among staffing decisions over adjacent time periods. In our work, we also build a model that handles the above two issues. We build a two-stage stochastic model with recourse that provides the staffing decisions over two adjacent decision time periods, i.e., two adjacent decision stages. The model minimizes the first stage staffing cost and the expected second stage staffing cost while satisfying a service quality constraint on the second stage operation. A Bayesian update is used to obtain the second-stage arrival-rate distribution based on the first-stage arrival-rate distribution and the arrival observations in the first stage. The second-stage distribution is used in the constraint on the second stage service quality. After reformulation, we show that our two-stage model can be expressed as a newsvendor model, albeit with a demand that is derived from the first stage decision. We provide an algorithm that can solve the two-stage staffing problem under the most commonly used QoS constraints. This work uses stochastic programming methods to solve problems arising in queueing networks. We hope that the ideas that we put forward in this dissertation lead to other attempts to deal with decision making under uncertainty for queueing systems that combine techniques from stochastic programming and analysis tools from queueing theory. / text

Tese (doutorado) - Universidade Federal de Santa Catarina, Centro Tecnológico, Programa de Pós-Graduação em Engenharia de Produção, Florianópolis, 2010 / Made available in DSpace on 2012-10-25T00:12:52Z (GMT). No. of bitstreams: 1 288536.pdf: 5124186 bytes, checksum: ba691ecfa89934c98178be2cdddd6c7c (MD5) / Os problemas de otimização das escalas de trabalho e o dimensionamento do número de atendentes vêm sendo abordados em diversas pesquisas devido à complexidade das operações de funcionamento nos Call Centers. Com o objetivo de resolver esses problemas, foram desenvolvidos neste trabalho dois modelos: o primeiro utilizou a Simulação para obtenção do número de atendentes necessários para cada hora do dia e a análise do desempenho das operações do Call Center; o segundo tratou do problema da programação das jornadas dos atendentes. O simulador foi construído para imitar o funcionamento de um Call Center receptivo (inbound). Os dados da simulação para tempo de atendimento das ligações, tempo que um cliente está disposto a esperar o atendimento sem que abandone a chamada, número de pausas técnicas dos atendentes, duração dessas pausas e taxa de rejeição das chamadas foram gerados seguindo estudos estatísticos dos dados reais. Os resultados encontrados ao final da simulação em relação aos clientes foram: o tempo de espera até ser atendido; o tempo de abandono para chamadas em que o cliente desistiu; número de chamadas atendidas, abandonadas e rejeitadas; tempo do cliente no sistema; e tempo de atendimento. Com relação aos atendentes, o simulador fornece ao final da execução, o tempo total de ocupação de cada atendente, o número de chamadas atendidas e o número total de atendentes necessários para cada hora do dia. Já o segundo modelo, que trata do problema da programação das jornadas dos atendentes, visa determinar um conjunto de jornadas de trabalho para os atendentes com menor custo de salários para o Call Center. Na resolução desse problema desenvolveu-se primeiramente, um #Gerador de Escalas# com o objetivo de gerar as combinações de jornadas considerando as restrições operacionais. Para a resolução do referido modelo, foi desenvolvido um aplicativo computacional que escreve o modelo em PLI na linguagem GAMS. Este modelo é então resolvido com os aplicativos MOSEK e XPRESS, ambos disponíveis online no site NEOS SERVER. Os dados com relação a número de atendentes necessários para cada hora do dia foram os obtidos através do simulador. A validade e a eficiência do modelo apresentado são comprovadas por intermédio de um exemplo de aplicação em um Call Center real. Os resultados foram satisfatórios quando da comparação das escalas otimizadas com as escalas do Call Center em estudo. Ainda com relação aos resultados, pode-se observar, através de várias simulações, que o simulador retrata de forma eficiente o funcionamento do Call Center analisado. Os modelos obtiveram os resultados em tempo computacional aceitável na sua resolução. Ainda, esses, podem ser facilmente adaptados e aplicados a outros Call Centers desde que possuam características semelhantes. / The optimization of work schedules and scaling of the number of attendants has been a challenge for the Call Centers. These problems have been addressed in several researches due to the complexity of the operations and functioning of Call Centers. Aiming to solve these problems, two models were developed in this study: the first model used the Simulation in order to obtain the number of required agents for each day time and the performance analysis of their Call Center operations and; the second model has handled the problem of the agents# schedule. The simulator was built up to imitate the running of an inbound Call Center. The simulation data for time to answer calls, time which a customer is willing to hold on without hanging up, number of technical pauses of agents' terminals, length of these pauses and rate of rejected calls were generated following statistical studies of actual data. The results regarding the customers, which were found at the end of the simulation, were: hold-off time until being serviced; the abandon time calls in which the customer gave up; number of answered, abandon and rejected calls; customer#s length of time in system; and servicing time. Regarding the agents, the simulator provides at the end of the running, the total time of each agent#s work, the number of answered calls and the total number of agents required for each time of day. As for the second model, which deals with the problem of the agents' schedule of a Call Center, aims to determine a set of working time for the agents with lower cost wages for the Call Centers. By solving this problem a "Shift Generator# was developed with the objective of generating working time bonds, considering the operational restrictions. For the resolution of the aforementioned model, a computational application, which writes the model in ILP in the GAMS anguage, was developed. This model is then solved with the tools MOSEK and XPRESS, both available on NEOS SERVER web site. The data regarding the number of agents required for each time were obtained through the simulator. The validity and efficiency of the model presented are proofed by means of an application example in a real Call Center. The results were satisfactory when comparing the optimized scales to Call Center scales being studied. Yet regarding the results, it is possible to observe, through several simulations, the simulator reflects efficiently the running of the analyzed Call Center. The models obtained the results in acceptable computational time in their resolution. Yet, these models may be easily adapted and applied to other Call Centers, since they have similar features.

O Risco Operacional nas instituições financeiras foi normatizado com a Resolução nº 3.380 em 29 de junho de 2006, emitida pelo Conselho Monetário Nacional. Desde então, entidades autorizadas a funcionar pelo Banco Central do Brasil tiveram de adequar suas estruturas e procedimentos com o intuito de aumentar os controles sobre eventos internos e externos à instituição, com a finalidade de reduzir perdas financeiras a partir da mitigação deste tipo de risco. Dessa forma, a presente dissertação tem como objetivo apresentar como um banco comercial precisa agir para adequar seus processos às novas exigências legais diante de um assunto com uma importância tão significativa. Este trabalho, além de apresentar os procedimentos de gestão de riscos em uma entidade, procura também elucidar como o risco operacional, no departamento de Call Center da instituição financeira escolhida, pode afetá-la, no caso da inobservância dos procedimentos a serem adotados com vistas à mitigação das falhas já identificadas e de possíveis ocorrências que possam comprometer a continuidade da organização. Os resultados obtidos na pesquisa mostram que o banco em estudo, em relação a outras instituições financeiras pesquisadas, ainda apresenta-se em uma etapa de desenvolvimento da sua área de gestão de riscos, trabalhando em conformidade com a legislação vigente e buscando aperfeiçoar suas técnicas de identificação e mensuração dos riscos operacionais. / Operational risk in financial institutions was normalized with Resolution No. 3380 on June 29, 2006, issued by the National Monetary Council. Since then, entities authorized to operate by the Central Bank of Brazil had to adapt its structures and procedures in order to tighten controls on internal and external events to the institution, in order to reduce financial losses from this type of risk mitigation. Thus, this paper aims to present as a commercial bank must act to adjust its processes to the new legal requirements before a subject with a very significant importance. This paper, besides presenting the procedures for managing risks in an entity, also seeks to clarify how operational risk, the department's Call Center financial institution chosen may affect it, in the case of a failure of procedures to be adopted in order mitigating the flaws already identified and possible events that could endanger the continuity of the organization. The results obtained from the survey show that the bank under study in relation to other financial institutions surveyed, still comes in a stage of development of their area of risk management, working in accordance with current legislation and seeking to improve their techniques identification and measurement of operational risks.