Challenges to Adopting Hybrid Methodology: Addressing Organizational Culture and Change Control Problems in Enterprise IT Infrastructure Projects

IT infrastructure projects have long been an overlooked field superseded by the more popular software development silos and cross-functional project teams when it comes to enterprise Agile transformations. This paper presents a systematic literature review by leveraging a qualitative research methodology based on empirical evidence provided in contemporary scholarly research articles to explore how certain variables such as organizational culture- including team structure, leadership hierarchy, geolocation, etc. along with an organization’s change management processes affect the adoption of a Hybrid/Agile project management methodology, focusing on reported challenges and critical success factors that define such large-scale enterprise transformations. The salient features from the conclusion of this preliminary research endeavor point to a direct relationship between certain aspects such as the size of the organization, stakeholder buy-in, and inherent resistance to change playing pivotal roles that define success within IT infrastructure teams and associated projects. This research endeavor and literature review also identifies a plethora of opportunities within IT infrastructure project management practices for future research based on the gaps that have been identified in contemporary literature

Improving the management of an IT department by using a new developed computer application

This work has been developed outside of office hours, in combination with the work of IT Analyst and Project Manager in Philip Morris SA (Switzerland). The dissertation seeks solutions to real-life problems, specifically associated with the daily challenges faced by the managers and team members of the Information Technology department. It was acknowledged the need to enhance the management and assignment of tasks and projects to the team members, where the major issue resided on the understanding of the constraints affecting the work allocation and workload management. To solve the mentioned hurdles, it was needed to develop an appropriate tool, matching the specific needs while being economically efficient and easy to operate. The management was involved in various sharing sessions, allowing the work to be developed in line with the genuine pain-points and to be built accordingly to the needs and expectations of the end-users. The SWOT analysis and the Ishikawa diagram played an important role in the delimitation of the challenges and on documenting the improvement possibilities. Firstly, the problem assessment was done, then it was time to review the literature, searching for the core values and best practices in Project Management. Later, there was an extensive review of the Resources Allocation subject, by concept and objectives, and as a tool to efficiently merging the specificities of the resources and activities while considering an extensive group of constraints. Then, it was done a broad attempt to combine the concepts of the Manager as a human and a servant leader with a focus on team success, with the usage of Resources Allocation tools as indispensable instruments for the success of any Project. Later, the work arrives at its core, with the development of the Allocation Algorithm and the MS Excel® program that allows the Managers to properly register and assign the Projects and Tasks, considering the specificities and constraints in place. The developed tools have been validated and utilized by Managers while performing their daily management routines. The most relevant improvements indicated by the end-users have been, the centralization and availability of the information, the rapidity of new activities’ assignment, and the benefit of having a unified status tool that takes into consideration the team specificities. In the literature, there are different approaches related to the resources’ allocation and project management issues and challenges. However, many of the Researchers never left the concept development stage and several of them have only proposed theoretical approaches. In this work, more than build an algorithm and a program with a straightforward approach to the management challenges, it was prioritized the practicality of the model and the development of a purposeful tool – allowing the ideas to get off paper, implementing the tool and as result, effectively improving the management of activities and the human resources allocation.Este trabalho foi desenvolvido fora do horário de trabalho, em harmonia com o trabalho de Analista IT e Gestor de Projeto na Philip Morris SA (Suíça). Esta dissertação procura encontrar soluções para problemas de gestão, especificamente para os desafios relativos ao trabalho diário dos gestores e membros de equipa do Departamento de Tecnologias da Informação. Assim, foi considerada a necessidade de melhorar o sistema de gestão de tarefas e projetos. Um dos desafios foi compreender as restrições que afetam uma boa gestão e alocação de tarefas, sendo necessário desenvolver uma ferramenta que seja economicamente eficiente e fácil de utilizar. Os gestores foram envolvidos em várias sessões de partilha, permitindo que o trabalho fosse desenvolvido em linha com as necessidades reais e tendo em conta as expetativas dos utilizadores finais da ferramenta. A utilização da análise SWOT e do diagrama de Ishikawa foram muito importantes para delimitar o problema e para definir as oportunidades de melhoria. Primeiramente foi definido o problema, depois foi feita uma revisão da literatura, investigando os valores e os bons princípios da Gestão de Projetos. Seguidamente, foi feita uma revisão sobre a Alocação de Recursos, considerando a base teórica e a aplicabilidade na gestão e alocação de tarefas e de recursos humanos. Paralelamente foi feita uma análise sobre como conjugar o conceito do gestor como humano e líder, e o seu papel no sucesso dos projetos. Foi também analisada a importância das ferramentas na gestão de qualquer projeto. Mais tarde, o trabalho chega ao seu âmago, com o desenvolvimento do Algoritmo de Alocação e do programa MS Excel®, ambos permitindo uma fácil e eficiente alocação de projetos e tarefas por parte dos responsáveis, considerando as restrições e as necessidades da empresa. O desenvolvimento do algoritmo e do programa foi feito em concordância com a gestão, garantindo dessa forma o alinhamento ideal entre o desenvolvimento e as necessidades reais. Os gestores indicaram como benefícios, a forma correta e fácil de associar atividades aos colaboradores, a centralização e qualidade da informação disponibilizada, e ainda a garantia de usar uma ferramenta que considera as especificidades da equipa e os projetos do departamento. Na literatura existem várias abordagens relativas aos desafios da alocação de recursos e da gestão de projetos. Contudo, muitos dos investigadores ficam apenas pela fase do conceito, e muitos apresentam apenas hipóteses e soluções teóricas. Neste trabalho, procurou-se desenvolver um algoritmo e um programa de utilização simples, colocando o funcionalismo e aplicabilidade como prioridades – permitindo que as ideias saíssem do papel, garantindo a implementação da solução e criando melhorias reais em termos de gestão de atividades e gestão de recursos humanos

Aplicação de SAFe® a um Projecto de Manutenção de Aviões

Maintenance, repair and overhaul (MRO) operations have a great impact on the life cycle of an aircraft (A/C). MROs organizations address various challenges on planning activities to ensure the maximum reliability of an A/C, given the amount of unscheduled maintenance. Subcontracting MRO activities by airline companies, has been continuously increasing as an alternative of performing the heavy maintenance themselves, adding a constraint on this type of industries which is to manage the customer demands. Considering the main issues, it is required to select the most suitable approach to plan and manage A/C maintenance projects. Agile Project Management (PM) could be a solution to overcome the main difficulties in this sector, managing the uncertainty throughout the project, providing customer visibility and control over the service. This work arises in a real-life case of a subcontracted MRO program in a multinational A/C manufacture enterprise, which also suffers from significant challenges of planning and managing maintenance activities throughout the project life cycle. The program has experimented agile methodologies that revealed a positive impact. In order to the whole program embrace agility and overcome the identified main problems, it was proposed the usage of an elaborate and well-defined agile framework. Scaled Agile Framework for enterprises (SAFe®) is an online knowledge base that implements diverse agile techniques to support businesses, develop and deliver solutions, achieving business agility. As SAFe® was mainly developed for software industries, due to the characteristics of the project and the type of industry where it is inserted, the application of this framework needed to be customized. Accordingly to the particularities of the project, the most suitable PM approach is a hybrid approach, where initially the scope of the project is delineated, with a contingency plan, supported by SAFe® to manage the issues that arise throughout the project. The agile methodologies allow customer centred attention, more communication channels, and by iterating over the product, planning the unscheduled work focusing on high priority tasks. Lastly, a framework in the core of the appearance of the issues was developed, to define the interconnection between the whole SAFe® concepts and to provide an extended view of how the project will progress with the new approach.As operações de manutenção, reparação e revisão produzem grande impacto no ciclo de vida de uma aeronave. As organizações que operam neste setor enfrentam vários desafios no planeamento das atividades que garantem a máxima confiabilidade de uma aeronave, dada a quantidade de manutenção não programada. A subcontratação deste tipo de atividades, por parte das companhias aéreas, tem crescido continuamente como uma alternativa à realização da própria manutenção pesada, adicionando um constrangimento para este tipo de indústrias: gerir as exigências dos clientes. Considerando os principais problemas, é necessário selecionar a abordagem mais adequada para planear e gerir projetos de manutenção de aviões. A gestão ágil de projetos poderá ser uma solução para superar as principais dificuldades deste setor, gerindo as incertezas ao longo do projeto, proporcionando visibilidade ao cliente e controlo sobre o serviço. Este trabalho surge num caso real de um programa subcontratado numa empresa multinacional de fabrico de aviões, que também sofre de desafios significativos no planeamento e gestão de atividades de manutenção ao longo do ciclo de vida do projeto. O programa experienciou metodologias ágeis que revelaram um impacto positivo. Para que todo o programa adote a agilidade e supere os principais problemas identificados, foi proposto o uso de uma elaborada e bem definida estrutura ágil. O Scaled Agile Framework para empresas é uma base de conhecimento online que implementa diversas técnicas ágeis para apoiar as empresas no desenvolvimento e entrega de soluções, alcançando a agilidade nos negócios. O SAFe® foi desenvolvido principalmente para indústrias de software, devido às características do projeto e ao tipo de indústria em que está inserido, a aplicação desta estrutura necessitou de ser personalizada. De acordo com as particularidades do projeto, a abordagem de gestão de projetos mais adequada é uma abordagem híbrida, onde inicialmente o projeto é delineado, com um plano de contingência, apoiado pelo SAFe® para gerenciar os problemas que surgem ao longo do projeto. As metodologias ágeis permitem centrar a atenção no cliente, mais canais de comunicação e, ao iterar sobre o produto, planear o trabalho não programado com foco em tarefas de alta prioridade. Por fim, foi desenvolvido um framework no cerne do surgimento dos problemas, de forma a definir as interligações entre todos os conceitos do SAFe® e fornecer uma visão ampliada de como o projeto irá progredir com a nova abordagem

IoT analytics and agile optimization for solving dynamic team orienteering problems with mandatory visits

Transport activities and citizen mobility have a deep impact on enlarged smart cities. By analyzing Big Data streams generated through Internet of Things (IoT) devices, this paper aims to show the efficiency of using IoT analytics, as an agile optimization input for solving real-time problems in smart cities. IoT analytics has become the main core of large-scale Internet applications, however, its utilization in optimization approaches for real-time configuration and dynamic conditions of a smart city has been less discussed. The challenging research topic is how to reach real-time IoT analytics for use in optimization approaches. In this paper, we consider integrating IoT analytics into agile optimization problems. A realistic waste collection problem is modeled as a dynamic team orienteering problem with mandatory visits. Open data repositories from smart cities are used for extracting the IoT analytics to achieve maximum advantage under the city environment condition. Our developed methodology allows us to process real-time information gathered from IoT systems in order to optimize the vehicle routing decision under dynamic changes of the traffic environments. A series of computational experiments is provided in order to illustrate our approach and discuss its effectiveness. In these experiments, a traditional static approach is compared against a dynamic one. In the former, the solution is calculated only once at the beginning, while in the latter, the solution is re-calculated periodically as new data are obtained. The results of the experiments clearly show that our proposed dynamic approach outperforms the static one in terms of rewardsThis project has received the support of the Ajuntament of Barcelona and the Fundació “la Caixa” under the framework of the Barcelona Science Plan 2020-2023 (grant 21S09355-001)Peer ReviewedPostprint (published version

Applications of biased-randomized algorithms and simheuristics in integrated logistics

Transportation and logistics (T&L) activities play a vital role in the development of many businesses from different industries. With the increasing number of people living in urban areas, the expansion of on-demand economy and e-commerce activities, the number of services from transportation and delivery has considerably increased. Consequently, several urban problems have been potentialized, such as traffic congestion and pollution. Several related problems can be formulated as a combinatorial optimization problem (COP). Since most of them are NP-Hard, the finding of optimal solutions through exact solution methods is often impractical in a reasonable amount of time. In realistic settings, the increasing need for 'instant' decision-making further refutes their use in real life. Under these circumstances, this thesis aims at: (i) identifying realistic COPs from different industries; (ii) developing different classes of approximate solution approaches to solve the identified T&L problems; (iii) conducting a series of computational experiments to validate and measure the performance of the developed approaches. The novel concept of 'agile optimization' is introduced, which refers to the combination of biased-randomized heuristics with parallel computing to deal with real-time decision-making.Las actividades de transporte y logística (T&L) juegan un papel vital en el desarrollo de muchas empresas de diferentes industrias. Con el creciente número de personas que viven en áreas urbanas, la expansión de la economía a lacarta y las actividades de comercio electrónico, el número de servicios de transporte y entrega ha aumentado considerablemente. En consecuencia, se han potencializado varios problemas urbanos, como la congestión del tráfico y la contaminación. Varios problemas relacionados pueden formularse como un problema de optimización combinatoria (COP). Dado que la mayoría de ellos son NP-Hard, la búsqueda de soluciones óptimas a través de métodos de solución exactos a menudo no es práctico en un período de tiempo razonable. En entornos realistas, la creciente necesidad de una toma de decisiones "instantánea" refuta aún más su uso en la vida real. En estas circunstancias, esta tesis tiene como objetivo: (i) identificar COP realistas de diferentes industrias; (ii) desarrollar diferentes clases de enfoques de solución aproximada para resolver los problemas de T&L identificados; (iii) realizar una serie de experimentos computacionales para validar y medir el desempeño de los enfoques desarrollados. Se introduce el nuevo concepto de optimización ágil, que se refiere a la combinación de heurísticas aleatorias sesgadas con computación paralela para hacer frente a la toma de decisiones en tiempo real.Les activitats de transport i logística (T&L) tenen un paper vital en el desenvolupament de moltes empreses de diferents indústries. Amb l'augment del nombre de persones que viuen a les zones urbanes, l'expansió de l'economia a la carta i les activitats de comerç electrònic, el nombre de serveis del transport i el lliurament ha augmentat considerablement. En conseqüència, s'han potencialitzat diversos problemes urbans, com ara la congestió del trànsit i la contaminació. Es poden formular diversos problemes relacionats com a problema d'optimització combinatòria (COP). Com que la majoria són NP-Hard, la recerca de solucions òptimes mitjançant mètodes de solució exactes sovint no és pràctica en un temps raonable. En entorns realistes, la creixent necessitat de prendre decisions "instantànies" refuta encara més el seu ús a la vida real. En aquestes circumstàncies, aquesta tesi té com a objectiu: (i) identificar COP realistes de diferents indústries; (ii) desenvolupar diferents classes d'aproximacions aproximades a la solució per resoldre els problemes identificats de T&L; (iii) la realització d'una sèrie d'experiments computacionals per validar i mesurar el rendiment dels enfocaments desenvolupats. S'introdueix el nou concepte d'optimització àgil, que fa referència a la combinació d'heurístiques esbiaixades i aleatòries amb informàtica paral·lela per fer front a la presa de decisions en temps real.Tecnologies de la informació i de xarxe

Applying autonomy to distributed satellite systems: Trends, challenges, and future prospects

While monolithic satellite missions still pose significant advantages in terms of accuracy and operations, novel distributed architectures are promising improved flexibility, responsiveness, and adaptability to structural and functional changes. Large satellite swarms, opportunistic satellite networks or heterogeneous constellations hybridizing small-spacecraft nodes with highperformance satellites are becoming feasible and advantageous alternatives requiring the adoption of new operation paradigms that enhance their autonomy. While autonomy is a notion that is gaining acceptance in monolithic satellite missions, it can also be deemed an integral characteristic in Distributed Satellite Systems (DSS). In this context, this paper focuses on the motivations for system-level autonomy in DSS and justifies its need as an enabler of system qualities. Autonomy is also presented as a necessary feature to bring new distributed Earth observation functions (which require coordination and collaboration mechanisms) and to allow for novel structural functions (e.g., opportunistic coalitions, exchange of resources, or in-orbit data services). Mission Planning and Scheduling (MPS) frameworks are then presented as a key component to implement autonomous operations in satellite missions. An exhaustive knowledge classification explores the design aspects of MPS for DSS, and conceptually groups them into: components and organizational paradigms; problem modeling and representation; optimization techniques and metaheuristics; execution and runtime characteristics and the notions of tasks, resources, and constraints. This paper concludes by proposing future strands of work devoted to study the trade-offs of autonomy in large-scale, highly dynamic and heterogeneous networks through frameworks that consider some of the limitations of small spacecraft technologies.Postprint (author's final draft

Dependency Management in Large-Scale Agile: A Case Study of DevOps Teams

Managing dependencies between teams and within teams is critical when running large-scale agile projects. In large-scale software development, work is carried out simultaneously by many developers and development teams. Results are delivered frequently and iteratively, which requires management of dependencies on both the project and team level. This study explores coordination mechanisms in agile DevOps teams in a large-scale project and how the mechanisms address different types of dependencies. We conducted a case study where we observed 38 scheduled meetings and interviewed members of five DevOps teams and two teams supporting the DevOps teams. By using a dependency taxonomy, we identified 20 coordination mechanisms (eleven synchronization activities and nine synchronization artifacts). Eight of these mechanisms seem essential for coordination in large-scale projects because they addressed more than four types of dependencies. The main implication is that project management needs to combine many practices handling all the dependencies in large-scale projects

A Process Development Project For A Case Company

This paper presents a case study on a process improvement project undertaken by a company in the sustainable energy industry. The project aimed to optimize the gate model for new product development, implement a hybrid-gate model, develop a gate checklist, and create an R&D process flow chart to better manage the R&D process. The study began with a thorough analysis of the existing gate model, which revealed several bottlenecks and inefficiencies. These were addressed through a series of process improvements, including better definition of gate criteria, improved cross-functional collaboration, and enhanced communication with stakeholders. To further improve the R&D process, the company implemented a hybrid-gate model, which integrated elements of both the stage-gate and agile development methodologies. This approach enabled the company to be more responsive to changes in the market and customer needs while maintaining the discipline and rigor of the stage-gate model. In addition, the project team developed a gate checklist, which provided a standardized set of criteria to evaluate project progress at each gate. This allowed the team to identify and address potential issues early in the development process. To provide greater visibility and understanding of the R&D process, the team also created an R&D process flow chart, which outlined the steps involved in new product development and the flow of information and decision-making. The project was successful in improving the efficiency and effectiveness of the R&D process, resulting in faster time-to-market for new products and increased customer satisfaction. The gate checklist and R&D process flow chart provided greater transparency and accountability, helping to ensure that projects were delivered on time and within budget. Overall, this case study demonstrates the importance of continuous process improvement in the sustainable energy industry and highlights the potential benefits of a hybrid-gate model, gate checklist, and R&D process flow chart for managing complex development projects

Optimizing transportation systems and logistics network configurations : From biased-randomized algorithms to fuzzy simheuristics

242 páginasTransportation and logistics (T&L) are currently highly relevant functions in any competitive industry. Locating facilities or distributing goods to hundreds or thousands of customers are activities with a high degree of complexity, regardless of whether facilities and customers are placed all over the globe or in the same city. A countless number of alternative strategic, tactical, and operational decisions can be made in T&L systems; hence, reaching an optimal solution –e.g., a solution with the minimum cost or the maximum profit– is a really difficult challenge, even by the most powerful existing computers. Approximate methods, such as heuristics, metaheuristics, and simheuristics, are then proposed to solve T&L problems. They do not guarantee optimal results, but they yield good solutions in short computational times. These characteristics become even more important when considering uncertainty conditions, since they increase T&L problems’ complexity. Modeling uncertainty implies to introduce complex mathematical formulas and procedures, however, the model realism increases and, therefore, also its reliability to represent real world situations. Stochastic approaches, which require the use of probability distributions, are one of the most employed approaches to model uncertain parameters. Alternatively, if the real world does not provide enough information to reliably estimate a probability distribution, then fuzzy logic approaches become an alternative to model uncertainty. Hence, the main objective of this thesis is to design hybrid algorithms that combine fuzzy and stochastic simulation with approximate and exact methods to solve T&L problems considering operational, tactical, and strategic decision levels. This thesis is organized following a layered structure, in which each introduced layer enriches the previous one.El transporte y la logística (T&L) son actualmente funciones de gran relevancia en cual quier industria competitiva. La localización de instalaciones o la distribución de mercancías a cientos o miles de clientes son actividades con un alto grado de complejidad, indepen dientemente de si las instalaciones y los clientes se encuentran en todo el mundo o en la misma ciudad. En los sistemas de T&L se pueden tomar un sinnúmero de decisiones al ternativas estratégicas, tácticas y operativas; por lo tanto, llegar a una solución óptima –por ejemplo, una solución con el mínimo costo o la máxima utilidad– es un desafío realmente di fícil, incluso para las computadoras más potentes que existen hoy en día. Así pues, métodos aproximados, tales como heurísticas, metaheurísticas y simheurísticas, son propuestos para resolver problemas de T&L. Estos métodos no garantizan resultados óptimos, pero ofrecen buenas soluciones en tiempos computacionales cortos. Estas características se vuelven aún más importantes cuando se consideran condiciones de incertidumbre, ya que estas aumen tan la complejidad de los problemas de T&L. Modelar la incertidumbre implica introducir fórmulas y procedimientos matemáticos complejos, sin embargo, el realismo del modelo aumenta y, por lo tanto, también su confiabilidad para representar situaciones del mundo real. Los enfoques estocásticos, que requieren el uso de distribuciones de probabilidad, son uno de los enfoques más empleados para modelar parámetros inciertos. Alternativamente, si el mundo real no proporciona suficiente información para estimar de manera confiable una distribución de probabilidad, los enfoques que hacen uso de lógica difusa se convier ten en una alternativa para modelar la incertidumbre. Así pues, el objetivo principal de esta tesis es diseñar algoritmos híbridos que combinen simulación difusa y estocástica con métodos aproximados y exactos para resolver problemas de T&L considerando niveles de decisión operativos, tácticos y estratégicos. Esta tesis se organiza siguiendo una estructura por capas, en la que cada capa introducida enriquece a la anterior. Por lo tanto, en primer lugar se exponen heurísticas y metaheurísticas sesgadas-aleatorizadas para resolver proble mas de T&L que solo incluyen parámetros determinísticos. Posteriormente, la simulación Monte Carlo se agrega a estos enfoques para modelar parámetros estocásticos. Por último, se emplean simheurísticas difusas para abordar simultáneamente la incertidumbre difusa y estocástica. Una serie de experimentos numéricos es diseñada para probar los algoritmos propuestos, utilizando instancias de referencia, instancias nuevas e instancias del mundo real. Los resultados obtenidos demuestran la eficiencia de los algoritmos diseñados, tanto en costo como en tiempo, así como su confiabilidad para resolver problemas realistas que incluyen incertidumbre y múltiples restricciones y condiciones que enriquecen todos los problemas abordados.Doctorado en Logística y Gestión de Cadenas de SuministrosDoctor en Logística y Gestión de Cadenas de Suministro