Developing a Machine Learning Strategy
Challenge
A global health program office leads efforts to combat a global epidemic, but in recent years, has seen outcomes stall with target demographics and geographies. The client sought our support to design a strategy for how machine learning can be used to accelerate progress and improve healthcare outcomes.
Discovery & Design
Our team engaged more than 40 healthcare experts, implementation partners, and technology leaders to gain an understanding of the organization’s capabilities and how machine learning might help the organization meet its goals. We synthesized best practices from 70+ pieces of literature, and facilitated multiple working sessions to help decision makers align on opportunities and challenges related to deploying and scaling machine learning. We aggregated findings into a visual roadmap that could guide interested users in setting up a machine learning project, and help senior leaders shepherd the organization towards smart, sustainable, and responsible deployment of machine learning.
Driving Impact
Developed a toolkit for leaders and program staff to assess and accelerate machine learning. The toolkit includes 1) frameworks to inform whether machine learning is a good-fit solution, 2) case studies to demonstrate machine learning impact, and 3) references to open-source data that could be used for machine learning projects
Prioritized action steps program office leaders should take to set up, deploy, and scale machine learning across multiple domains including private partnerships, data & IT, and people