Podcasts about capm

In this episode, Ricardo presents Chesterton's Fence, a principle that warns against removing rules, controls, or processes before understanding why they were created. Although simplifying bureaucracy can improve agility, eliminating safeguards without investigating their purpose may revive risks they were designed to prevent. Ricardo recommends four steps: identify who created the process and why; determine which risk it controls; when its purpose remains unclear, test its removal through a reversible pilot; and document why controls exist for future teams. He also encourages humility when judging decisions made by previous teams, since they may have faced unknown constraints. His challenge is: before eliminating anything from a project, ask why it is there. If nobody knows, investigate before tearing down the fence. Listen to the podcast to learn more!

Neste episódio, Ricardo apresenta a Cerca de Chesterton, princípio que alerta contra a remoção de regras, controles ou processos antes de compreender por que foram criados. Embora reduzir a burocracia possa aumentar a agilidade, eliminar salvaguardas sem investigar sua finalidade pode reativar riscos que deveriam evitar. Ricardo recomenda quatro passos: identificar quem criou o processo e por quê; descobrir qual risco ele controla; quando sua finalidade permanecer incerta, testar sua remoção por meio de um projeto-piloto reversível; e registrar por que os controles existem. Ele aconselha humildade ao avaliar decisões de equipes anteriores, pois podem ter enfrentado restrições desconhecidas. O desafio é: antes de eliminar algo, pergunte por que está ali. Se ninguém souber, investigue antes de derrubar a cerca. Escute o podcast para saber mais!

In this podcast, Ricardo explains the normalization of deviance: repeated small failures that, because they cause no immediate consequences, become accepted as normal. Drawing on Diane Vaughan's studies of the Challenger disaster, he shows how delays, skipped tests, recurring risks, and postponed meetings can make problems invisible. To avoid this trap, he recommends examining trends instead of isolated events, establishing rules before pressure arises, and documenting exceptions with an owner and an end date. He also stresses the importance of protecting people who challenge improper practices and listening to outsiders or newcomers, who can notice deviations the team has normalized. Ricardo invites listeners to review their status report and ask when a problem became considered normal within the project team. Listen to the podcast to learn more!

Neste podcast Ricardo explica a normalização do desvio: pequenas falhas repetidas que, por não causarem consequências imediatas, passam a ser aceitas como normais. Inspirado nos estudos de Diane Vaughan sobre o acidente do Challenger, ele mostra como atrasos, testes ignorados, riscos recorrentes e reuniões adiadas podem tornar problemas invisíveis nos projetos. Para evitar essa armadilha, recomenda-se observar tendências e não apenas ocorrências isoladas; definir regras antes que surjam pressões; e registrar exceções com responsável e prazo. Também destaca a importância de proteger quem questiona práticas inadequadas e ouvir pessoas externas ou recém-chegadas, capazes de perceber desvios já naturalizados pela equipe. Ricardo propõe revisar o último relatório de status e perguntar quando uma situação incorreta passou a ser considerada normal pela equipe. Escute o podcast para saber mais!

In this podcast, Ricardo explores what makes people irreplaceable in an age of artificial intelligence. Rather than asking which tasks AI cannot perform, he suggests asking what AI does not have: desire, responsibility, and something at stake. AI can analyze risks, prepare schedules, summarize contracts, and recommend decisions, but it does not care whether a project succeeds or fails. People give projects purpose because they want outcomes and accept responsibility for the consequences. Drawing on his humanitarian work at the UN, Ricardo explains that legitimate decisions require someone willing to face the affected community afterward. He concludes that professionals become difficult to replace when they care, question incorrect recommendations, defend outcomes, and put their names and reputations behind those choices. Listen to the podcast to learn more!

Neste podcast, Ricardo explora o que torna as pessoas insubstituíveis na era da inteligência artificial. Em vez de perguntar quais tarefas a IA não consegue realizar, ele sugere questionar o que a IA não possui: desejo, responsabilidade e algo em jogo. A IA pode analisar riscos, elaborar cronogramas, resumir contratos e recomendar decisões, mas não se importa se um projeto terá sucesso ou fracassará. As pessoas conferem propósito aos projetos porque desejam resultados e assumem a responsabilidade pelas consequências. Com base em sua experiência humanitária na ONU, Ricardo explica que decisões legítimas exigem alguém disposto a enfrentar a comunidade afetada posteriormente. Ele conclui que os profissionais se tornam difíceis de substituir quando se importam, questionam recomendações incorretas, defendem resultados e assumem a responsabilidade por essas escolhas, colocando nelas seus nomes e reputações. Ouça o podcast para saber mais!

In this episode, Ricardo warns that artificial intelligence is often approved as a project cost, but after implementation, it becomes an ongoing operational expense. Unlike traditional licenses, its cost varies according to consumption: the greater the adoption, the higher the bill. He also highlights frequently ignored expenses such as data preparation, systems integration, human review, price changes, model replacement, and new testing. Ricardo recommends presenting recurring costs per unit, projecting growth scenarios, identifying who will assume the expense after the project ends, and proactively assessing exit costs. For him, advancing with AI is essential, but it requires financial discipline. Without knowing the cost, the responsible party, and the value generated, there is no complete and sustainable business case. Listen to the podcast to learn more!

Neste episódio, Ricardo alerta que a inteligência artificial costuma ser aprovada como custo de projeto, mas, após a implantação, transforma-se em despesa operacional contínua. Diferentemente das licenças tradicionais, seu custo varia conforme o consumo: quanto maior a adoção, maior a fatura. Ele destaca também despesas frequentemente ignoradas, como preparação de dados, integração de sistemas, revisão humana, alterações de preços, substituição de modelos e novos testes. Ricardo recomenda apresentar custos recorrentes por unidade, projetar cenários de crescimento, identificar quem assumirá a despesa após o encerramento do projeto e avaliar antecipadamente os custos de saída. Para ele, avançar com IA é essencial, mas exige disciplina financeira. Sem conhecer custo, responsável e valor gerado, não existe caso de negócio completo e sustentável. Ouça o podcast para saber mais!

In this episode, Ricardo warns about the risk of resuming January's projects at midyear. According to him, the context has changed: budgets, suppliers, technology, markets, regulations, and priorities may now be different. Before following the original plan, he recommends three actions: recalculate the project using current information, assess external changes, and reevaluate the portfolio, prioritizing what truly matters. Ricardo emphasizes that replanning does not represent failure; instead, it shows awareness of the transformations that have occurred. He suggests setting aside two hours, gathering people who understand the project's reality, and asking whether it would still be approved today with the same structure, scope, team, and cost. This reflection reveals whether the project will meet the organization's needs in December. Listen to the podcast to learn more!

Neste episódio, Ricardo alerta para o risco de retomar, no segundo semestre, os projetos planejados em janeiro. Segundo ele, o cenário mudou: orçamento, fornecedores, tecnologia, mercado, regulamentações e prioridades podem ser diferentes. Por isso, antes de seguir o plano original, recomenda três ações: recalcular o projeto com base nas informações atuais, analisar as mudanças externas e reavaliar o portfólio, priorizando o que importa. Ricardo destaca que replanejar não representa fracasso, mas demonstra atenção às transformações ocorridas. Ele sugere reservar duas horas, reunir pessoas que conheçam a realidade do projeto e questionar se ele seria aprovado hoje com o mesmo formato, escopo, equipe e custo. A reflexão permite verificar se o projeto ainda atenderá às necessidades da organização em dezembro. Ouça o podcast para saber mais

In this episode, Ricardo explains that modern projects depend heavily on external suppliers, contractors, partners, and AI vendors whose teams do not report directly to the project manager. He argues that leading these people has become a core project management skill. He emphasizes that contracts and service-level agreements define obligations and penalties but do not create trust, commitment, or guarantee success. Ricardo also warns that supplier risk should be treated as a major project risk. He recommends involving partners in planning, explaining the project's purpose, addressing problems early, and speaking directly with leaders who can reallocate resources. Finally, he encourages managers to identify their three most critical external organizations and build genuine relationships with their senior decision-makers. Listen to the podcast to learn more!

Neste episódio, Ricardo explica que os projetos modernos dependem fortemente de fornecedores externos, contratados, parceiros e provedores de IA, cujas equipes não se reportam diretamente ao gerente do projeto. Ele argumenta que liderar essas pessoas tornou-se uma competência essencial de gestão de projetos. Ele ressalta que contratos e acordos de nível de serviço definem obrigações e penalidades, mas não geram confiança ou comprometimento, nem garantem o sucesso. Ricardo também alerta que o risco relacionado a fornecedores deve ser tratado como um risco importante do projeto. Ele recomenda envolver os parceiros no planejamento, explicar o propósito do projeto, abordar problemas precocemente e dialogar diretamente com líderes capazes de realocar recursos. Por fim, ele incentiva os gerentes a identificar as três organizações externas mais críticas e a construir relacionamentos genuínos com seus principais tomadores de decisão. Escute o podcast para saber mais!

In this episode, Ricardo discusses the common rush to start acting before fully understanding a project's problem. Action creates a sense of progress, while thinking may seem like wasted time. However, teams can work intensely and still move quickly in the wrong direction. Ricardo emphasizes that speed should not be confused with impulsiveness. Asking simple questions about the problem, missing information, potential consequences, urgency, and reversibility can prevent weeks of unnecessary rework. Even during crises or emergencies, acting quickly does not mean abandoning reflection. Planning often appears expensive because it happens before execution, while the cost of correcting poor decisions remains hidden. Before saying there is no time to think, teams should ask whether they have time to do the work twice. Want to know more? Tune in to the podcast!

Neste episódio, Ricardo reflete sobre a pressa de iniciar ações em projetos sem compreender o problema. Ele explica que agir transmite sensação de progresso, enquanto pensar pode parecer perda de tempo, embora decisões precipitadas gerem reuniões, retrabalho, atrasos e desperdício. Ricardo ressalta que velocidade não deve ser confundida com impulsividade: equipes podem trabalhar intensamente e, ainda assim, avançar na direção errada. Antes de agir, recomenda perguntas sobre o problema, as informações, os impactos, a urgência e a possibilidade de reverter decisões. Mesmo em crises, oportunidades ou emergências, instantes de reflexão continuam essenciais. Para ele, o planejamento parece caro porque ocorre antes, enquanto o retrabalho permanece escondido. Às vezes, parar por poucos minutos permite chegar mais rápido ao destino certo. Mergulhe no assunto e ouça o episódio completo!

In this episode, Ricardo discusses rework, one of the most damaging yet invisible costs in projects. Rework occurs when presentations, software, proposals, plans, or decisions must be redone because expectations, requirements, or responsibilities were unclear. Although teams appear busy, they may simply be returning to a point they believed they had already reached—paying multiple times for a result. The later an error is discovered, the greater its impact, which shows that speed does not always mean efficiency. Ricardo highlights avoidable rework caused by haste, poor communication, ambiguous decisions, weak planning, and unvalidated requirements. He suggests measuring not only completed work, but also how much had to be repeated. True efficiency means transforming effort into results with minimal waste. Want to know more? Tune in to the podcast!

Neste episódio, Ricardo aborda o retrabalho, um dos custos mais prejudiciais e, ao mesmo tempo, invisíveis em projetos. O retrabalho ocorre quando apresentações, softwares, propostas, planos ou decisões precisam ser refeitos porque expectativas, requisitos ou responsabilidades não estavam claros. Embora as equipes pareçam ocupadas, elas podem estar simplesmente retornando a um ponto que acreditavam já ter alcançado — pagando várias vezes pelo mesmo resultado. Quanto mais tarde um erro é descoberto, maior é o seu impacto, o que demonstra que velocidade nem sempre significa eficiência. Ricardo destaca o retrabalho evitável causado por pressa, comunicação deficiente, decisões ambíguas, planejamento fraco e requisitos não validados. Ele sugere medir não apenas o trabalho concluído, mas também a quantidade de trabalho que precisou ser repetida. A verdadeira eficiência consiste em transformar esforço em resultados com o mínimo de desperdício. Mergulhe no assunto e ouça o episódio completo!

In this episode, Ricardo explains that projects are promises about a future often experienced by people other than those who originally approved or delivered them. He argues that organizations tend to exaggerate benefits, minimize long-term costs, and focus on schedules, budgets, scope, and acceptance instead of verifying whether promised outcomes materialize. Ricardo highlights the imbalance between those who gain visibility by making promises, those pressured to execute them, and those left to operate solutions and face their consequences. He offers three recommendations: involve the people who will inherit the project from the beginning, document promised benefits as carefully as deliverables, and extend accountability beyond project closure. Ultimately, he says projects must create the future used to justify their existence. Listen to the podcast to learn more!

Neste episódio, Ricardo explica que projetos são promessas sobre um futuro frequentemente vivenciado por pessoas diferentes daquelas que os aprovaram ou entregaram originalmente. Ele argumenta que as organizações tendem a exagerar nos benefícios, minimizar os custos de longo prazo e concentrar-se em cronogramas, orçamentos, escopo e aceitação, em vez de verificar se os resultados prometidos realmente se concretizam. Ricardo destaca o desequilíbrio entre aqueles que ganham visibilidade ao fazer promessas, aqueles pressionados a executá-las e aqueles que ficam responsáveis ​​por operar as soluções e arcar com suas consequências. Ele apresenta três recomendações: envolver desde o início as pessoas que herdarão o projeto, documentar os benefícios prometidos com o mesmo cuidado dedicado às entregas e estender a responsabilidade para além do encerramento do projeto. Em suma, ele afirma que os projetos devem criar o futuro usado para justificar a sua própria existência. Escute o podcast para saber mais!

In this episode, Ricardo reflects on reactions to his newsletter about project management in the age of AI. He stresses that he is not predicting the future but encouraging professionals to question assumptions and prepare for rapid change. Although some readers considered his views alarmist, he argues that learning AI carries little downside: even if its impact is smaller than expected, new skills remain valuable. However, ignoring AI could be risky if organizations continue redesigning structures, PMOs, governance, roles, and teams. Ricardo believes project management will not disappear, but it will evolve significantly. His central concern is helping younger professionals remain relevant, adaptable, and responsible for their choices in a world changing faster than ever before through continuous learning and reflection. Listen to the podcast to learn more!

Neste episódio, Ricardo reflete sobre as reações à sua newsletter sobre o gerenciamento de projetos na era da inteligência artificial. Ele ressalta que não pretende prever o futuro, mas incentivar os profissionais a questionarem certezas e se prepararem para mudanças rápidas. Embora alguns leitores tenham considerado suas opiniões alarmistas, ele argumenta que aprender sobre IA apresenta poucas desvantagens: mesmo que seu impacto seja menor do que o esperado, as novas competências continuarão valiosas. Entretanto, ignorar a IA pode ser arriscado se as organizações continuarem reformulando estruturas, PMOs, governança, funções e equipes. Ricardo acredita que o gerenciamento de projetos não desaparecerá, mas evoluirá significativamente. Sua principal preocupação é ajudar profissionais mais jovens a permanecerem relevantes, adaptáveis e responsáveis por suas escolhas. Escute o podcast para saber mais!

In this episode, Ricardo reflects on how many project managers have shifted from managing projects to merely reacting to urgent matters. Their daily routines are consumed by meetings, messages, emails, and immediate issues, creating a sense of heavy workload but little actual progress. According to him, managing projects means reducing uncertainty, whereas managing anxiety amounts to nothing more than reacting to chaos. Artificial intelligence has accelerated operational tasks but also raised expectations for instant responses, thereby intensifying anxiety within organizations. In this context, the project manager's role becomes even more critical: establishing priorities, shielding the team from false urgencies, creating predictability, making decisions, and instilling confidence. Listen to the podcast to learn more about!

Neste episódio, Ricardo reflete sobre como muitos gerentes de projetos deixaram de gerenciar projetos para apenas reagir a urgências. A rotina é consumida por reuniões, mensagens, e-mails e problemas imediatos, gerando a sensação de muito trabalho, mas pouco progresso real. Segundo ele, gerenciar projetos significa reduzir incertezas, enquanto gerenciar ansiedade significa apenas reagir ao caos. A inteligência artificial acelerou tarefas operacionais, mas também aumentou a expectativa por respostas instantâneas, intensificando a ansiedade nas organizações. Nesse contexto, o papel do gerente de projetos torna-se ainda mais importante: estabelecer prioridades, proteger a equipe de falsas urgências, criar previsibilidade, tomar decisões e transmitir confiança. Escute o podcast para saber mais!

In this episode, Ricardo discusses the new PMP certification exam. He explains that updating the exam is a natural progression, as project management has evolved with artificial intelligence, agile methods, distributed teams, and new challenges. He highlights that the PMP exam has always prioritized the ability to analyze situations, make decisions, lead teams, and deliver value, rather than simply memorizing concepts. Ricardo also emphasizes that previous versions of the PMBOK® remain relevant because project management fundamentals stay the same, while only the context and tools evolve. His recommendation is to stay up to date without believing that all prior knowledge has lost its value. Listen to the podcast to learn more about!

Neste episódio, Ricardo fala sobre o novo exame para a certificação PMP. Ele explica que a atualização do exame é natural, pois a gestão de projetos evoluiu com inteligência artificial, métodos ágeis, equipes distribuídas e novos desafios. Destaca que o exame PMP sempre valorizou a capacidade de analisar situações, tomar decisões, liderar equipes e gerar valor, e não apenas memorizar conceitos. Ricardo também reforça que as versões anteriores do PMBOK continuam relevantes, pois os fundamentos da gestão de projetos permanecem os mesmos, enquanto apenas o contexto e as ferramentas evoluem. Sua recomendação é manter-se atualizado, sem acreditar que todo o conhecimento anterior perdeu valor. Escute o podcast para saber mais!

Laurel Donnellan sits down with David Cumberbatch, newly appointed Managing Director of North America for the Project Management Institute (PMI), for a wide-ranging conversation on education, career readiness, and leadership in a rapidly changing world of work.David traces his path from a childhood in Trinidad and Tobago — shaped by a grandfather who ran the country's largest orphanage — through Oxford as a Rhodes Scholar, to formative years at Procter & Gamble and Microsoft, and now to leading PMI's 800,000-member global community. Along the way, he and Laurel compare the British and American education systems, unpack why generation beta may hold 18 to 30 jobs across 7 to 10 career chapters, and discuss the delicate balance of introducing technology and AI to young learners.The conversation turns to PMI's own AI transformation — including its new CPM AI credential, the PMI Infinity AI companion platform, and an updated PMP exam that now includes AI and sustainability content. David makes the case that durable "power skills" like critical thinking and interpersonal communication matter more, not less, as AI reshapes project work, and shares how PMI is building accessible pathways (like the CAPM certification) for people without a four-year degree to reach six-figure project management careers.The episode closes with David's reflections on leadership: the foundational role of safety and trust in lasting relationships, the lesson he carried from PNG's promotion-from-within culture versus Microsoft's "up or out" model, and his belief that compassionate leadership and competitive excellence aren't in tension — they're the same thing.Guest BioDavid Cumberbatch is the Managing Director of North America for the Project Management Institute (PMI), overseeing the U.S., Canada, and the Caribbean. Raised in Trinidad and Tobago, David earned a double honors degree in computer science and economics from the University of Kent at Canterbury, then studied at Oxford as a Rhodes Scholar. His career spans Procter & Gamble, Microsoft, the Gates Foundation, and ACT, with the last 20 years focused on the intersection of education, technology, and workforce readiness.Resources & Links Mentioned PMI website: pmi.org PMI job board (for certified members) PMI Infinity (PMI's AI companion platform) CPM AI Certification and CAPM/PMP certification pathways PM Ready certificate (high school level) University of Pennsylvania high school internship training program Crimson Global Academy (referenced re: UK/US K-12 comparison — see Laurel's earlier interview) Opportunity@Work (referenced re: non-degree career pathways) Resources & Links Mentioned PMI website: pmi.org PMI job board (for certified members) PMI Infinity (PMI's AI companion platform) CPM AI Certification and CAPM/PMP certification pathways PM Ready certificate (high school level) University of Pennsylvania high school internship training program Crimson Global Academy (referenced re: UK/US K-12 comparison — see Laurel's earlier interview) Opportunity@Work (referenced re: non-degree career pathways

In this podcast, Ricardo argues that many projects are not actually late; instead, their schedules were unrealistic from the beginning. He explains that organizations often approve aggressive timelines to satisfy executives, budgets, or customer expectations, only to blame the project team when those plans fail. Ricardo emphasizes that early estimates are always surrounded by uncertainty, making unrealistic forecasts a planning problem rather than an execution issue. While artificial intelligence can quickly generate detailed schedules, its results are only as reliable as the assumptions behind them. Therefore, project managers must challenge deadlines and question key assumptions before approval. Effective planning requires honesty about risks, constraints, capacity, and uncertainty, because expectations alone do not deliver projects—people executing realistic plans do.

Neste podcast, Ricardo questiona uma crença comum no gerenciamento de projetos: nem todo projeto está atrasado; muitas vezes, o cronograma era inviável desde o início. Ele explica que organizações frequentemente aprovam prazos irreais para atender expectativas, orçamentos ou pressões políticas, transferindo depois a responsabilidade para a equipe. Ricardo destaca que previsões iniciais sempre envolvem incertezas e que culpar a execução por falhas de planejamento é um erro. Embora a inteligência artificial ajude a criar cronogramas, ela depende de premissas realistas. Por isso, o gerente de projetos deve desafiar prazos e questionar hipóteses antes da aprovação. Planejar exige honestidade sobre riscos, restrições, capacidade e incertezas, pois expectativas não entregam projetos; pessoas, trabalhando com planos realistas, sim.

In this episode, Ricardo challenges whether traditional two-week Agile sprints still make sense in an era where AI agents can develop, test, review, and improve software in minutes. While Agile principles such as collaboration, adaptability, and customer focus remain essential, their execution may need to evolve. As AI dramatically accelerates software development, the main bottleneck shifts from execution to human decision-making, including prioritization, validation, quality assurance, and risk management. This transformation questions the relevance of fixed sprints, story points, and traditional Agile ceremonies. Ricardo suggests that project managers will increasingly orchestrate AI-driven workflows instead of managing tasks, arguing that human judgment will remain the key competitive advantage in teams where people and AI agents work together. Listen to the podcast to learn more!

Neste episódio, Ricardo questiona se os tradicionais sprints de duas semanas ainda fazem sentido em um cenário em que agentes de inteligência artificial desenvolvem, testam e corrigem software em minutos. Embora os princípios do Agile permaneçam essenciais, sua execução pode precisar ser reinventada. Com a IA acelerando a implementação, o principal desafio deixa de ser a execução e passa a ser a tomada de decisões, como definir prioridades, validar resultados, garantir qualidade e gerenciar riscos. Nesse novo modelo de desenvolvimento contínuo, o gerente de projetos deixa de controlar tarefas e passa a orquestrar agentes e fluxos de trabalho. O julgamento humano continua sendo o principal diferencial para gerar valor. Escute o podcast para saber mais!

In this episode, Ricardo presents three practical applications of AI agents in project management. Unlike tools that only answer questions, these agents act autonomously, monitoring information and executing tasks. The first example is the risk agent, capable of identifying problems in messages, classifying their severity, updating records, and suggesting responses. The second is the status and reporting agent, which collects data from various sources, updates indicators, and automatically generates reports, allowing the manager to focus on analysis. The third is the planning and forecasting agent, which tracks project progress, identifies trends, performs simulations, and anticipates problems. Ricardo concludes that these agents not only automate tasks but transform the nature of project management work. Listen to the podcast to learn more!

Neste episódio, Ricardo apresenta três aplicações práticas de agentes de IA no gerenciamento de projetos. Diferentemente de ferramentas que apenas respondem a perguntas, os agentes atuam de forma autônoma, monitorando informações e executando tarefas. O primeiro exemplo é o agente de riscos, capaz de identificar problemas em mensagens, classificar sua gravidade, atualizar registros e sugerir respostas. O segundo é o agente de status e relatórios, que coleta dados de diversas fontes, atualiza indicadores e gera relatórios automaticamente, permitindo que o gerente foque na análise. O terceiro é o agente de planejamento e previsão, que acompanha o progresso do projeto, identifica tendências, realiza simulações e antecipa problemas. Ricardo conclui que os agentes não apenas automatizam tarefas, mas transformam a natureza do trabalho do gerenciamento de projetos. Escute o podcast para saber mais!

In this episode, Ricardo compares a project to a disorganized email inbox, full of messages, decisions, and pending tasks without proper handling. He explains that many projects don't face difficulties due to a lack of resources or schedule flaws, but because of the accumulation of actions, risks, requests, and decisions without follow-up. To deal with this problem, he presents the principles of the GTD (Getting Things Done) methodology, created by David Allen, which is based on the idea that the human mind should generate ideas, not store them. Ricardo highlights five fundamental steps: capturing information, clarifying necessary actions, organizing responsibilities, regularly reviewing records, and executing priorities. Applied to projects, these principles help reduce chaos, increase productivity, and improve decision-making. Listen to the podcast to learn more!

Neste episódio, Ricardo compara um projeto a uma caixa de e-mails desorganizada, repleta de mensagens, decisões e pendências sem tratamento adequado. Ele explica que muitos projetos não enfrentam dificuldades por falta de recursos ou por falhas no cronograma, mas pelo acúmulo de ações, riscos, solicitações e decisões sem acompanhamento. Para lidar com esse problema, apresenta os princípios da metodologia GTD (Getting Things Done), criada por David Allen, que parte da ideia de que a mente humana deve gerar ideias, e não armazená-las. Ricardo destaca cinco etapas fundamentais: capturar informações, esclarecer ações necessárias, organizar responsabilidades, revisar regularmente os registros e executar as prioridades. Aplicados aos projetos, esses princípios ajudam a reduzir o caos, aumentar a produtividade e melhorar a tomada de decisões. Escute o podcast para saber mais!

In this podcast, Ricardo explores the emerging concept of the “one-person project,” made possible by advances in artificial intelligence, automation, and digital platforms. He challenges the traditional belief that complex projects require large teams, noting that bigger teams also increase coordination efforts, communication overhead, and dependencies. Drawing on Brooks' Law, he explains that adding more people does not always improve productivity. Today, a single professional can perform tasks that once required entire teams, raising the question of whether projects should be delivered by the smallest effective team possible. However, he also highlights risks such as knowledge concentration and reduced diversity of perspectives. Finally, Ricardo expands the discussion to the future of work, questioning how society will adapt if fewer people are needed to achieve greater results. Listen to the podcast to learn more about!

Neste episódio, Ricardo reflete sobre a crescente possibilidade de projetos serem executados por uma única pessoa graças ao avanço da inteligência artificial, da automação e das plataformas digitais. Ele destaca que, tradicionalmente, projetos complexos exigiam grandes equipes, mas que o aumento do número de pessoas também amplia os esforços de coordenação, comunicação e alinhamento. Com as novas tecnologias, um profissional pode realizar atividades que antes demandavam equipes inteiras, tornando possível reduzir o tamanho dos times sem comprometer os resultados. Contudo, esse modelo traz riscos, como a concentração de conhecimento e a redução da diversidade de perspectivas. Ricardo amplia a discussão para o futuro do trabalho, questionando os impactos sociais e econômicos de um cenário em que cada vez menos pessoas sejam necessárias para produzir mais resultados. Escute o podcast para saber mais!

In this episode, Ricardo presents Brooks' Law, created over 50 years ago and still very relevant. The law states that adding people to a software project that is behind schedule tends to delay it even further. This is because new members need to be trained and mentored by more experienced members, reducing team productivity. Furthermore, increasing the number of people makes communication, coordination, and integration of deliverables more complex. Ricardo emphasizes that this concept remains valid in the age of artificial intelligence, as adding more tools, agents, or automations does not solve problems of priorities, processes, or governance. Often, the solution lies in removing obstacles, simplifying decisions, and improving work coordination. Listen to the podcast to learn more about!

Neste episódio, Ricardo apresenta a Lei de Brooks, criada há mais de 50 anos e ainda muito relevante. A lei afirma que adicionar pessoas a um projeto de software, que está atrasado, tende a atrasá-lo ainda mais. Isso ocorre porque os novos integrantes precisam ser treinados e orientados pelos membros mais experientes, reduzindo a produtividade da equipe. Além disso, o aumento do número de pessoas torna a comunicação, a coordenação e a integração das entregas mais complexas. Ricardo destaca que esse conceito continua válido na era da inteligência artificial, pois adicionar mais ferramentas, agentes ou automações não resolve problemas de prioridades, processos ou governança. Muitas vezes, a solução está em remover obstáculos, simplificar decisões e melhorar a coordenação do trabalho. Escute o podcast para saber mais!

In this episode, Ricardo discusses the main misunderstandings about the eighth edition of the PMBOK Guide. He explains that the PMI has not abandoned traditional management nor transformed everything into agile, but has begun to integrate predictive, hybrid, and adaptive approaches in a more intelligent way. Ricardo emphasizes that governance, cost control, scheduling, and leadership remain essential, but are now applied in more complex and dynamic environments. He also clarifies that artificial intelligence appears as a support tool, not as a replacement for human leadership. Another important point is that no framework solves cultural problems or management failures on its own. According to Ricardo, the new PMBOK seeks to connect execution and value creation, reducing conflict between methodologies and encouraging adaptation to the real context of projects. Listen to the podcast to learn more about! * The opinions presented in this podcast reflect solely the personal views of Ricardo and do not necessarily represent the position of PMI. This episode has no sponsorship, support, or institutional affiliation with any organization.

Neste episódio, Ricardo comenta os principais mal-entendidos sobre a oitava edição do PMBOK Guide. Ele explica que o PMI não abandonou a gestão tradicional nem transformou tudo em ágil, mas passou a integrar abordagens preditivas, híbridas e adaptativas de forma mais inteligente. Ricardo destaca que governança, controle de custos, cronograma e liderança continuam essenciais, porém agora aplicados em ambientes mais complexos e dinâmicos. Ele também esclarece que a inteligência artificial aparece como ferramenta de apoio, não como substituição da liderança humana. Outro ponto importante é que nenhum framework resolve problemas culturais ou falhas de gestão sozinho. Segundo Ricardo, o novo PMBOK busca conectar execução e geração de valor, reduzindo o conflito entre metodologias e incentivando adaptação ao contexto real dos projetos. Escute o podcast para saber mais! * As opiniões apresentadas neste podcast refletem exclusivamente a visão pessoal de Ricardo e não representam, necessariamente, o posicionamento do PMI. Este episódio não possui patrocínio, apoio ou vínculo institucional com qualquer organização.

In this episode, Ricardo explains that career growth in project management is not defined only by technical skills, certifications, or tools. Often, the most important moments are brief, unexpected interactions during crises or difficult conversations. In these situations, leaders observe who remains calm, simplifies chaos, communicates clearly, takes responsibility, and helps others make decisions. While technical competence is essential, trust, confidence, and leadership under pressure become the true differentiators as careers evolve. With artificial intelligence automating many technical tasks, human abilities such as judgment, communication, and decision-making in uncertain situations are becoming even more valuable. Sometimes, a career-changing moment may last only a few minutes. Listen to the podcast to learn more about!

Neste episódio, Ricardo explica que o crescimento na carreira de gestão de projetos não se define apenas por habilidades técnicas, certificações ou ferramentas. Muitas vezes, os momentos mais importantes são interações breves e inesperadas durante crises ou conversas difíceis. Nessas situações, os líderes observam quem mantém a calma, simplifica o caos, comunica-se com clareza, assume a responsabilidade e ajuda os outros a tomar decisões. Embora a competência técnica seja essencial, a confiança e a liderança sob pressão tornam-se os verdadeiros diferenciais à medida que as carreiras evoluem. Com a inteligência artificial automatizando muitas tarefas técnicas, habilidades humanas como julgamento, comunicação e tomada de decisão em situações incertas tornam-se ainda mais valiosas. Às vezes, um momento que pode mudar a carreira dura apenas alguns minutos. Escute o podcast pra saber mais!

In this episode, Ricardo Vargas discusses "Watermelon Projects": projects that appear healthy on dashboards but face serious internal problems. He explains that often, indicators remain green for fear of exposing difficulties, disappointing sponsors, or suffering punishment in corporate cultures that associate problems with personal failure. Thus, delays, risks, and scope cuts end up being masked. Ricardo warns that the greatest danger is not a red project, but an artificially green one, as problems grow silently until they become critical. He emphasizes that dashboards reflect organizational behaviors and culture. For him, healthy projects are not those without problems, but those where the team feels safe to discuss difficulties early, transparently, and without fear. Listen to the podcast to learn more about!

Neste episódio, Ricardo fala sobre os “Watermelon Projects”: projetos que parecem saudáveis nos dashboards, mas enfrentam sérios problemas internamente. Ele explica que, muitas vezes, os indicadores permanecem verdes por medo de expor dificuldades, decepcionar patrocinadores ou sofrer punições em culturas corporativas que associam problemas ao fracasso pessoal. Assim, atrasos, riscos e cortes de escopo acabam sendo mascarados. Ricardo alerta que o maior perigo não é um projeto vermelho, mas sim um projeto artificialmente verde, pois os problemas crescem silenciosamente até se tornarem críticos. Ele destaca que dashboards refletem comportamentos e cultura organizacional. Para ele, projetos saudáveis não são os que não possuem problemas, mas aqueles onde a equipe tem segurança para discutir dificuldades cedo, com transparência e sem medo. Escute o podcast pra saber mais!

In this episode, Ricardo questions the effectiveness of traditional project planning tools, based on static plans. Although fundamental for decades, these plans quickly become obsolete in dynamic environments. He highlights that Artificial Intelligence transforms this scenario by allowing continuous forecasting and real-time adjustments, replacing fixed estimates with dynamic, data-driven analyses. With this, the focus shifts from following a plan to adapting to change. Current tools still lack this predictive intelligence, which can compromise their relevance. The role of the project manager also changes: from planner to critical and strategic analyst. Despite the benefits, there are risks, such as excessive reliance on AI and decisions based on inaccurate data. Listen to the podcast to learn more about!

Neste episódio, Ricardo questiona a eficácia das ferramentas tradicionais de planejamento de projetos, baseadas em planos estáticos. Embora tenham sido fundamentais por décadas, esses planos rapidamente se tornam obsoletos em ambientes dinâmicos. Ele destaca que a Inteligência Artificial transforma esse cenário ao permitir previsões contínuas e ajustes em tempo real, substituindo estimativas fixas por análises dinâmicas baseadas em dados. Com isso, o foco deixa de ser seguir um plano e passa a ser adaptar-se às mudanças. As ferramentas atuais ainda carecem dessa inteligência preditiva, o que pode comprometer sua relevância. O papel do gerente de projetos também muda: de planejador para analista crítico e estratégico. Apesar dos benefícios, há riscos, como dependência excessiva da IA e decisões baseadas em dados imprecisos. Escute o podcast para saber mais!

In this episode, Ricardo discusses KPIs (Key Performance Indicators). He explains that KPIs are essential metrics that support decision-making in projects, unlike general metrics that only report data. Effective KPIs help anticipate problems, expedite decisions, and align teams and stakeholders. Examples for schedule performance include the percentage of tasks completed on time, the planned versus scheduled duration, the SPI (Schedule Performance Index), and the average delay per delivery. For cost, the CPI (Cost Performance Index) and cost variance measure efficiency. Beyond schedule and cost, strategic KPIs are essential, such as rework rate, value delivered, adherence to the business plan, and stakeholder satisfaction, as projects can meet time and budget targets and still fail. Ricardo recommends using a few meaningful KPIs, tracking trends, updating them frequently, and avoiding superficial metrics that don't guide decisions. Tune in to the podcast to learn more!

Neste episódio, Ricardo fala sobre KPIs (Key Performance Indicators - Indicadores-Chave de Desempenho). Ele explica que os KPIs são métricas essenciais que apoiam a tomada de decisões em projetos, ao contrário das métricas gerais que apenas reportam dados. KPIs eficazes ajudam a antecipar problemas, agilizar decisões e alinhar equipes e stakeholders. Exemplos para desempenho de cronograma incluem a porcentagem de tarefas concluídas no prazo, a duração prevista versus a duração programada, o SPI (Índice de Desempenho do Cronograma) e o atraso médio por entrega. Para custo, o CPI (Índice de Desempenho de Custo) e a variação de custo medem a eficiência. Além de cronograma e custo, KPIs estratégicos são essenciais, como taxa de retrabalho, valor entregue, aderência ao plano de negócios e satisfação dos stakeholders, pois os projetos podem atingir as metas de tempo e orçamento e ainda assim falhar. Ricardo recomenda usar alguns KPIs significativos, acompanhar tendências, atualizá-los frequentemente e evitar métricas superficiais que não orientam as decisões. Escute o podcast para saber mais!

In this episode, Ricardo explains that rework is an invisible yet highly destructive problem in projects. Although organizations measure schedule, cost, and scope, they rarely monitor rework, the effort spent correcting already completed work. This lack of measurement obscures the project's true efficiency. Rework often stems from deeper problems, such as unclear requirements, misalignment among stakeholders, late decisions, or low initial quality. Its impact is significant: delays increase, costs rise, teams become exhausted, and client confidence decreases. Ricardo argues that rework should be treated as a key performance indicator, continuously monitored to assess the project's health. When measured, it drives better behaviors, improving quality, decision-making, and alignment. Ultimately, projects fail not only due to delays but also due to wasted effort, with rework being one of the main hidden factors contributing to this failure. Tune in to the podcast to learn more!

In this episode, Ricardo discusses how artificial intelligence is transforming project management by moving beyond being just a tool and becoming an active agent in decision-making and execution. He highlights the emergence of new, unpredictable, and difficult-to-control risks that can arise from the interaction between systems. He also emphasizes concerns about manipulation and cybersecurity, since AI can both protect and attack. This scenario challenges traditional risk management practices. In response, he suggests continuous monitoring, controls focused on detection and rapid response, and reinforcing human responsibility. Despite the benefits, understanding these new risks has become essential. Tune in to the podcast to learn more!

What if the way we think about investing—and expected returns—was fundamentally incomplete? In this episode, Ben Felix and Dan Bortolotti take a deep dive into one of the most influential papers in financial economics: Fama and French (1993). With nearly 15,000 citations, this research reshaped how we understand asset pricing by showing that market beta alone isn't enough to explain returns. Instead, multiple factors—specifically size and value—play a critical role. Ben and Dan unpack how this paper challenged the dominance of CAPM, introduced the now-famous Three-Factor Model, and laid the foundation for decades of empirical asset pricing research. They explore how factor investing evolved, why anomalies may not be anomalies at all, and what this means for evaluating portfolios and active managers today. The conversation also connects theory to practice—highlighting how modern fund providers implement factor strategies and what it means for investors trying to improve expected returns without abandoning diversification.     Key Points From This Episode: (0:00:00)  Introduction to the episode and why this is a long-awaited deep dive into factor investing. (0:01:12) Overview of Fama and French (1993) and its massive impact on finance and portfolio management. (0:03:55) Origins of factor investing and how it connects to index investing and academic research. (0:04:46) Core premise: multiple factors drive expected returns and asset prices. (0:06:08) He explains why different assets can have different expected returns, and why that matters for investors. (0:07:24) Ben introduces the CAPM as the dominant model that linked expected return to market beta. (0:08:53) Dan reflects on how revolutionary CAPM and portfolio theory were when they were first introduced. (0:10:51) Ben describes today as a "golden age of investing," where theory and implementation tools are widely accessible. (0:11:17) He explains how anomalies emerged that CAPM could not explain. (0:12:10) Ben introduces the joint hypothesis problem: we cannot cleanly separate market efficiency from model accuracy. (0:13:47) He identifies the three big issues with CAPM: size, value, and the weak relationship between beta and returns. (0:15:29) Ben introduces the three-factor model: market, size (SMB), and value (HML). (0:17:37) He explains that these factors are built as long-short portfolios designed to capture systematic return variation. (0:18:02) Dan notes that the model did not really address the low-volatility anomaly. (0:18:36) Ben agrees and explains that later work, including the five-factor model, went further on that front. (0:19:03) Ben describes how Fama and French formed 25 portfolios sorted by size and book-to-market. (0:20:00) He explains their use of time-series regression to test how well the model explained portfolio returns. (0:21:12) Ben walks through factor loadings, alpha, and R-squared, and why those outputs matter. (0:23:31) He highlights the model's strong explanatory power, with average R-squared around 0.93 across test portfolios. (0:25:00) Dan clarifies that unexplained return could reflect skill, luck, or another missing factor. (0:25:27) Ben emphasizes how dramatic the jump was from CAPM's explanatory power to the three-factor model's. (0:26:11) He points to small-cap growth as the major area the model struggled to explain. (0:27:09) Ben explains how the model also absorbed dividend-to-price and earnings-to-price "anomalies." (0:28:01) Dan discusses why dividend strategies may simply act as rough value screens rather than offering something unique. (0:28:52) Ben expands on how later research, especially profitability, sharpened value investing implementation. (0:30:37) He notes the unresolved debate over whether factors are true risk exposures or persistent mispricing. (0:32:16) Ben explains how factor models changed the way investors evaluate active managers and fees. (0:33:16) Dan raises the possibility that some early active managers may have intuitively identified factor opportunities before the research formalized them. (0:34:09) Ben discusses whether factor premiums have shrunk after publication and why the evidence is still noisy. (0:34:59) He describes how the paper helped launch the boom in empirical asset pricing research. (0:35:35) Ben introduces the "factor zoo" problem and the explosion of published factors. (0:36:49) He explains the five-factor model and the addition of profitability and investment. (0:38:21) Dan asks about the intuition behind profitability and investment, especially why profitable firms might have higher expected returns. (0:39:38) Ben explains profitability through a multi-factor lens and inferred discount rates. (0:42:15) He argues that combining factors matters because single-factor portfolios can have offsetting exposures. (0:44:05) Dan points out that layering too many factors naively can just bring you back toward the market portfolio. (0:44:56) Ben discusses the tradeoff between diversified tilts and concentrated factor bets. (0:46:29) Dan describes factor tilting as a subtle adjustment around a diversified core portfolio. (0:46:47) Ben cites Fama's idea that investors need to "talk themselves out of the market portfolio." (0:47:16) He notes that there is still active debate over which factors and models truly make sense. (0:48:31) Dan explains why momentum is harder to implement in practice because of turnover, taxes, and trading costs. (0:49:23) Ben says even simple-sounding factors like value and profitability remain heavily debated in academia. (0:50:20) He brings the discussion back to practical relevance: how investors can access factor exposure through funds. (0:51:06) Ben explains Dimensional's roots in academic research and its long history of implementation. (0:52:48) He introduces Avantis as a newer competitor with similar academic foundations and newly launched Canadian ETFs. (0:53:42) Ben discloses that PWL uses Dimensional extensively, while noting they are not paid to mention Dimensional or Avantis. (0:54:09) He summarizes what factor investing means for investors seeking higher expected returns through systematic tilts. (0:55:47) Dan reflects on how early PWL's adoption of index and factor-based investing was in the Canadian market. (0:57:07) Ben invites listeners to learn more about how PWL applies this thinking in client portfolios. (0:57:41) The episode moves to the after show and review section. (0:58:21) Dan reads a listener review focused on evidence-based investing, planning, and disciplined saving. (1:00:23) Ben notes that they never actually named the paper during the main episode. (1:00:32) Dan closes with: the paper is Common Risk Factors in the Returns on Stocks and Bonds.     Links: Patrick Adams – MIT PhD Candidate: https://patrick-adams.com/  Meet with PWL Capital: https://calendly.com/d/3vm-t2j-h3p Rational Reminder on iTunes — https://itunes.apple.com/ca/podcast/the-rational-reminder-podcast/id1426530582. Rational Reminder on Instagram — https://www.instagram.com/rationalreminder/ Rational Reminder on YouTube — https://www.youtube.com/channel/ Benjamin Felix — https://pwlcapital.com/our-team/ Benjamin on X — https://x.com/benjaminwfelix Benjamin on LinkedIn — https://www.linkedin.com/in/benjaminwfelix/ Cameron Passmore — https://pwlcapital.com/our-team/ Cameron on X — https://x.com/CameronPassmore Editing and post-production work for this episode was provided by The Podcast Consultant (https://thepodcastconsultant.com)