Concept of Customer Relationship Management as an example of innovation in banking sector

Banks that has introduced CRM system, had to make some difficult changes in their organization in order to become more customer oriented. Beside the pure CRM banks try to adopt other innovative tools related with the core CRM. Some of these solutions are constructed in such a way so that ensured could be also access to the information beside to bank’s organization.

Partial utility-driven scheduling for flexible SLA and pricing arbitration in clouds

Cloud SLAs compensate customers with credits when average availability drops below certain levels. This is too inflexible because consumers lose non-measurable amounts of performance being only compensated later, in next charging cycles. We propose to schedule virtual machines (VMs), driven by range-based non-linear reductions of utility, different for classes of users and across different ranges of resource allocations: partial utility. This customer-defined metric, allows providers transferring resources between VMs in meaningful and economically efficient ways. We define a comprehensive cost model incorporating partial utility given by clients to a certain level of degradation, when VMs are allocated in overcommitted environments (Public, Private, Community Clouds). CloudSim was extended to support our scheduling model. Several simulation scenarios with synthetic and real workloads are presented, using datacenters with different dimensions regarding the number of servers and computational capacity. We show the partial utility-driven driven scheduling allows more VMs to be allocated. It brings benefits to providers, regarding revenue and resource utilization, allowing for more revenue per resource allocated and scaling well with the size of datacenters when comparing with an utility-oblivious redistribution of resources. Regarding clients, their workloads’ execution time is also improved, by incorporating an SLA-based redistribution of their VM’s computational power.

Automatização de testes à framework myMIS

Atualmente, verifica-se um aumento na necessidade de software feito à medida do cliente, que se consiga adaptar de forma rápida as constantes mudanças da sua área de negócio. Cada cliente tem os seus problemas concretos que precisa de resolver, não lhe sendo muitas vezes possível dispensar uma elevada quantidade de recursos para atingir os fins pretendidos. De forma a dar resposta a estes problemas surgiram várias arquiteturas e metodologias de desenvolvimento de software, que permitem o desenvolvimento ágil de aplicações altamente configuráveis, que podem ser personalizadas por qualquer utilizador das mesmas. Este dinamismo, trazido para as aplicações sobre a forma de modelos que são personalizados pelos utilizadores e interpretados por uma plataforma genérica, cria maiores desafios no momento de realizar testes, visto existir um número de variáveis consideravelmente maior que numa aplicação com uma arquitetura tradicional. É necessário, em todos os momentos, garantir a integridade de todos os modelos, bem como da plataforma responsável pela sua interpretação, sem ser necessário o desenvolvimento constante de aplicações para suportar os testes sobre os diferentes modelos. Esta tese debruça-se sobre uma aplicação, a plataforma myMIS, que permite a interpretação de modelos orientados à gestão, escritos numa linguagem específica de domínio, sendo realizada a avaliação do estado atual e definida uma proposta de práticas de testes a aplicar no desenvolvimento da mesma. A proposta resultante desta tese permitiu verificar que, apesar das dificuldades inerentes à arquitetura da aplicação, o desenvolvimento de testes de uma forma genérica é possível, podendo as mesmas lógicas ser utilizadas para o teste de diversos modelos distintos.

Determining the Adjustment Baseline Parameters to Define an Accurate Customer Baseline Load

Demand response is an energy resource that has gained increasing importance in the context of competitive electricity markets and of smart grids. New business models and methods designed to integrate demand response in electricity markets and of smart grids have been published, reporting the need of additional work in this field. In order to adequately remunerate the participation of the consumers in demand response programs, improved consumers’ performance evaluation methods are needed. The methodology proposed in the present paper determines the characterization of the baseline approach that better fits the consumer historic consumption, in order to determine the expected consumption in absent of participation in a demand response event and then determine the actual consumption reduction. The defined baseline can then be used to better determine the remuneration of the consumer. The paper includes a case study with real data to illustrate the application of the proposed methodology.

Question order and context effects on multi-items scales questions

Dissertação apresentada como requisito parcial para obtenção do grau de Mestre em Estatística e Gestão de Informação

Business planning in nonprofit: Laying the ground for customer relationship management in Instituto de Empreendedorismo Social

A Work Project, presented as part of the requirements for the Award of a Masters Degree in Management from the NOVA – School of Business and Economics

Customer Lifetime Value: a framework for application in the insurance industry - Building a Business Process to Generate and Maintain an Automatic Estimation Agent

Research Project submited as partial fulfilment for the Master Degree in Statistics and Information Management

Supply chain integration model: practices and customer values

Dissertation to obtain PhD in Industrial Engineering

Improving contact center cost efficiency and customer experience in a retail company

A Work Project, presented as part of the requirements for the Award of a Masters Degree in Management from the NOVA – School of Business and Economics

Internationalization Plan - How can UniPlaces improve its customer acquisition strategy in the London market?

A Work Project, presented as part of the requirements for the Award of a Masters Degree in Management from the NOVA – School of Business and Economics

Quality of process modeling using BPMN: a model-driven approach

Dissertação para obtenção do Grau de Doutor em Engenharia Informática

Strategic account management: the path to gain customer loyalty

The account management field works closely with the sales team, serving as the customer’s primary point of contact. This project’s purpose was to understand if shifting the account management from brand centric to customer centric, would be the best fit for a Portuguese Pharmaceutical company. This customer centric approach - Strategic Account Management (SAM) - was studied, understanding the implicated trade-offs to the company. The workforce was probed about the project and their comments were analyzed. The conclusion points to an implementation of SAM and proposes the adaptations to follow in order to smooth the change.

Customer relationship management at Siemens Healthcare – a diagnosis and proposal for strategy and market segmentation

Towards a holistic perspective of CRM, this project aims to diagnose and propose a strategy and market segmentation for Siemens Healthcare. The main underlying principle is to apply a full customer-centric outlook taking own business properties into consideration while preserving Siemens Healthcare’s culture and vision. Mainly focused on market segmentation, this project goes beyond established boundaries by employing an unbiased perspective of CRM while challenging current strategy, goals, processes, tools, initiatives and KPIs. In order to promote a sustainable business excellence strategy, this project aspires to streamline CRM strategic importance and driving the company one step forward.

Proving a market for a startup befor scaling using the hypothesis-driven entrepreneurship process

The year is 2015 and the startup and tech business ecosphere has never seen more activity. In New York City alone, the tech startup industry is on track to amass $8 billion dollars in total funding – the highest in 7 years (CB Insights, 2015). According to the Kauffman Index of Entrepreneurship (2015), this figure represents just 20% of the total funding in the United States. Thanks to platforms that link entrepreneurs with investors, there are simply more funding opportunities than ever, and funding can be initiated in a variety of ways (angel investors, venture capital firms, crowdfunding). And yet, in spite of all this, according to Forbes Magazine (2015), nine of ten startups will fail. Because of the unpredictable nature of the modern tech industry, it is difficult to pinpoint exactly why 90% of startups fail – but the general consensus amongst top tech executives is that “startups make products that no one wants” (Fortune, 2014). In 2011, author Eric Ries wrote a book called The Lean Startup in attempts to solve this all-too-familiar problem. It was in this book where he developed the framework for The Hypothesis-Driven Entrepreneurship Process, an iterative process that aims at proving a market before actually launching a product. Ries discusses concepts such as the Minimum Variable Product, the smallest set of activities necessary to disprove a hypothesis (or business model characteristic). Ries encourages acting briefly and often: if you are to fail, then fail fast. In today’s fast-moving economy, an entrepreneur cannot afford to waste his own time, nor his customer’s time. The purpose of this thesis is to conduct an in-depth of analysis of Hypothesis-Driven Entrepreneurship Process, in order to test market viability of a reallife startup idea, ShowMeAround. This analysis will follow the scientific Lean Startup approach; for the purpose of developing a functional business model and business plan. The objective is to conclude with an investment-ready startup idea, backed by rigorous entrepreneurial study.

Using customer lifetime value to improve the prediction of bank deposit subscription in telemarketing campaigns

Customer lifetime value (LTV) enables using client characteristics, such as recency, frequency and monetary (RFM) value, to describe the value of a client through time in terms of profitability. We present the concept of LTV applied to telemarketing for improving the return-on-investment, using a recent (from 2008 to 2013) and real case study of bank campaigns to sell long- term deposits. The goal was to benefit from past contacts history to extract additional knowledge. A total of twelve LTV input variables were tested, un- der a forward selection method and using a realistic rolling windows scheme, highlighting the validity of five new LTV features. The results achieved by our LTV data-driven approach using neural networks allowed an improvement up to 4 pp in the Lift cumulative curve for targeting the deposit subscribers when compared with a baseline model (with no history data). Explanatory knowledge was also extracted from the proposed model, revealing two highly relevant LTV features, the last result of the previous campaign to sell the same product and the frequency of past client successes. The obtained results are particularly valuable for contact center companies, which can improve pre- dictive performance without even having to ask for more information to the companies they serve.