Preparing for production: Best practices for OR and decision science teams

How robust is your path to production? Too often algorithms designed to deliver millions of dollars (or more) in ROI are inefficiently developed and often dependent upon high-friction development workflows. The tools and practices exist to systematically test, manage, monitor, and orchestrate decision workflows in a way that builds trust with business users, seamlessly integrates with engineering stacks, and provides decision modeling teams the agency to innovate and deliver business value faster. 

Join Carolyn Mooney, Nextmv CEO, and Tiffany Bogich, Nextmv Head of Product, as they discuss their observations from lived experiences and a broad swath of industry use cases. From handling input to removing hard-coded parameters, version control, CI/CD, and rollout testing, they’ll cover their top best practices for building and deploying decision models efficiently.

Key segments

• Common patterns, observations, and lessons learned
• Best practices and new habits to adopt for success
• Utilizing a DecisionOps scorecard