The Path of Intended Motion
Data science has the potential to fundamentally change the value of a company. However often to fully embrace this path, a company must be willing to rethink their technologies, processes, and culture. Our goal is to guide our clients down this path to fundamentally change how they think and operate in order to fully realize the value within the data they hold.
In the Navy, the Captain is responsible for the success of the fleet. The geography it will travel, the enemy’s resources, and the fleet’s capabilities must all be evaluated. This data is compiled together to produce what is called the Path of Intended Motion: the strategy and direction the fleet must follow to be successful.
The same also applies to companies. Leadership must evaluate a similar landscape of data: market dynamics, the competition, and their own resources to plot out successful solutions. Intended Motion helps companies navigate this landscape with data science business advisory services, experienced analytics project leadership, and the design and implementation of predictive solutions.
John Conwell, aka “Turbo”, is co-founder and CEO of Intended Motion, a data science consulting and leadership firm in Seattle. From his over 10 years’ experience in data science and machine learning, he has come to understand the key to delivering actionable data science solutions is deeply intertwined in organizational, operational, and cultural forces within a company. Turbo is dedicated to helping organizations discover and deliver disruptive and actionable value from their data, while using his experience and leadership to help them navigate internal and external forces that threaten to derail the project. After serving 4 years in the Navy, Turbo earned a BA in MIS from Tulsa University. In his free time he grows over 20 different varieties of hot peppers and makes his own hot sauces.
Sean M. McNee has a Ph.D. in Computer and Information Sciences from the University of Minnesota. His research and business efforts focus on the creation of actionable insights in support of critical decision-making through the use of new technologies and workflows. Specifically, he studies visual analytics, information filtering/retrieval, personalization & recommender systems, data mining, user modeling, computer-supported cooperative work, and human-computer interaction in a legal and business contexts to improve the productivity, increase profitability, and strengthen culture in organizations. When not geeking out, Sean enjoys film, sunshine, and macaroni & cheese.