Andre de Godoy Nunes

  Artificial intelligence (AI) is becoming an indispensable tool in numerous industries, and project management is no exception. With the dynamic nature of managing projects, spanning from planning and execution to stakeholder communication and risk management, AI’s ability to analyse data, automate tasks, and provide predictive insights is revolutionising how project managers work.  The application of AI in project management is not only optimising efficiency but also reshaping the skill set required for success in the role. This article delves into the primary benefits AI brings to project management, explores use cases where AI proves invaluable, and offers tips on developing the necessary skills to embrace AI fully in the project management field. The Benefits of AI in Project Management Improving Communication with Stakeholders is one of the main benefits brough to project management. AI’s ability to streamline communication is one of its most immediate and impactful ben...

In today's dynamic business landscape, the concept of the "project economy" has become increasingly prominent. As organisations seek to innovate and adapt to rapid changes, project-based work has emerged as a critical component of strategic success. This article explores the project economy, its significance, and the key factors driving its adoption. What is Project Economy? The project economy refers to an organisational approach where projects are the primary unit of work and value creation. Unlike traditional operational models that emphasise ongoing, routine activities, the project economy focuses on temporary, goal-oriented efforts that deliver specific outcomes. This shift reflects a broader trend towards agility, innovation, and adaptability in business. Project economy is a very well know term in the United States as well as the use of this approach in small, medium and large organisations to deliver value not just to their customers but also to themselves. In its...

Agile methodologies have gained immense popularity over the past few decades due to their versatility, flexibility, adaptability, and focus on customer satisfaction. However, still today when I talk to people from different industries a common misconception persists that Agile methodologies eschew planning altogether as people believe that you can adapt and change your path as you move toward the project lifecycle and learn by gaining quicker feedback.   In reality, planning is a crucial component of Agile practices, while in a different form than traditional project management approaches.  I’ve been using agile practices since 2014 when I was first introduced to this new approach and mindset, so in this article I would like to share what I learned and the practices that I usually apply in my way of working, aiming to clarify the significance and relevance of planning within Agile project management, demonstrating how it contributes to the success of projects. Understanding Ag...

In my previous article, I discussed a methodology designed to mitigate investment risks, particularly beneficial when contemplating a new business venture or embarking on a project to develop a product or technology amid uncertainty. The methodology in question is Discovery Driven Planning (DDP), developed by Rita Gunther McGrath of Columbia University and Ian MacMillan of Wharton Business Schools. If you haven't had the chance to read my article titled " Mitigate Investment Risks with Discovery-Driven Planning ," I encourage you to do so. Originally crafted in the mid-1990s, DDP primarily targeted large enterprises. McGrath and MacMillan examined past product launches by major corporations, including notable failures like Disney's Euro Disney theme park. Despite being more than 25 years old, DDP remains relatively underutilised as a business management tool, notwithstanding its numerous benefits. Initially tailored for senior managers making critical decisions in g...

  Discovery-driven planning (DDP), or Discovery-Driven Growth, is a strategic methodology designed to manage uncertainty and foster innovation. It shifts the focus from traditional detailed forecasts and linear execution plans to a more flexible, learning-based approach. DDP emphasises experimentation, validation of assumptions, and iterative learning, making it particularly useful in environments where the path to success is not clearly defined, such as new markets or innovative product development. I was first introduced to DDP in 2020 when I helped deliver a digital strategy and a technology capability roadmap for a digital transformation program. At the time, we lacked certainty about our technology choices. DDP provided us with a plan that could be executed in parallel with the delivery projects, allowing us to track our progress toward the business goals, change direction or pivot all together when needed. Since there I became a fan of the approach and applied DDP in other si...