Guest Forwards

Forward by Tom Davenport

Many things are changing in the worlds of systems engineering, analytics, and AI. With generative AI, for example, we now have the ability to create extensive programming or data analysis with only a short prompt. Nontechnical users can also employ "low code/no code" tools to create departmental-level applications with only a few clicks. Automated machine learning systems can evaluate multiple algorithms within seconds. What has not changed, however, is the importance of understanding the problem that needs to be solved. The ultimate objective of the program or analysis that one is trying to create is not something that an AI system can determine; that requires context, consultation, communications, and clear thinking by humans. These topics are the focus of this book. The OUtCoMES cycle it describes is key to solving the right problem for the organization. In an era when it is becoming much easier to solve data-oriented problems, it is even more important to ensure that engineers, analysts and data scientists are working on the issues and solutions that matter most.

Thomas H. Davenport

Distinguished Professor, Babson College

Fellow, MIT Initiative on the Digital Economy

Senior Advisor, Deloitte AI Practice

Forward by Jack Phillips

If you’re reading this book, then most likely you’ve spent your fair share of time in and around analytics and engineering projects, either as a member of a project team or as a team leader, or more than likely both at various points in your career. One of the things that you’ve probably seen too often, as I have, are lost opportunities to generate a conclusive win. And you’ve probably seen these even when wins seem like they are well within reach. Why is that? Success in engineering and analytics projects often boils down to some really not-immediately-obvious elements that tend to lurk around the edges of every project’s day-to-day focus.  Is the team working on the most important problem?  How can you generate evidence and confidence that the team is working on the most important problem, from a set of given alternatives?  Can the project teams that follow in the wake of this current project find specific ways to accelerate their own success by building directly or indirectly from the prior team’s work? These are important questions that all analytics and engineering projects have to find answers to in order to build and to maintain a culture of project team success. As the CEO and Co-founder of the International Institute for Analytics (IAA), I regularly see first-hand the tremendous value that’s created when organizations have a culture that emphasizes and systematically focuses on process and execution excellence in analytics and engineering projects. On the flip side, I also see the tremendous waste of effort, and the enormous opportunity costs when they don’t approach project execution with this kind of systematic, focused discipline.

One of the topics that has tended to come up the most frequently in and around the analytics and engineering projects that I’ve had both direct and indirect exposure to throughout my career is the question of identifying the most effective applied frameworks for consistently driving project excellence, project after project. Now for the first time in Mastering Project Discovery (MPD), this book introduces a critical, encompassing framework, what’s called the OUtCoMES Cycle (The Cycle), that is specifically designed to minimize wasted effort and the risk of project failure. The “Cycle” provides project leaders and members tasked with project co-leadership with a straightforward, easy to implement, structured project discovery and development process that is tied directly to objectives that maximize project value and practical impact. The sum total of project value across an enterprise, of course, is the key to industry differentiation and generating sustainable competitive advantage.  With the Cycle, MPD offers a timely, practical, and easy-to-implement approach for project leaders tasked with solving the right problem in the right way, and generating value from analytics and engineering projects. Importantly, the Cycle also creates an organizational record of process considerations and decisions, providing a systematic guide and source of problem insight for use by subsequent project teams operating in the same or adjacent spaces.

In developing the Cycle, the author team draws from decades of practical experience in the field of analytics and engineering in both academia and in industry. The OUtCoMES Cycle was developed through systematic academic study of best practices in project management, combined with practical application across a wide range of different industry settings. In addition, the cases, exercises and practitioner summaries provided in each chapter offer clear examples of how and where The Cycle can help to predictably reduce risk and to create value. After reading Mastering Project Discovery, I am excited to see how organizations apply these principles to improve their project outcomes. Whether you’re a student, project team member or leader, or executive responsible for continuous innovation and value creation, I have every confidence that you’ll find value in applying the approach described in The Cycle to your organization’s analytics and engineering projects.

Jack Phillips

CEO & Co-Founder of International Institute for Analytics (IIA)