Videos

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

How robust is your path to production? Can you own the end-to-end decision process? From handling input to removing hard-coded parameters, managing versions, and rollout testing, we’ll cover the top best practices for building, testing, and deploying decision models efficiently.

Switchback testing decision models: Demo using Nextmv

Use Nextmv to compare two decision models operating in production while accounting for network effects

What is switchback testing for decision models?

Switchback testing is a key part of the DecisionOps workflow. Get a quick primer on what it is and when to use it in this 2-minute video.

Build, test, and deploy an OR-Tools MIP model in Python

Learn how to solve mixed integer programming (MIP) problems with Google’s OR-Tools for use cases like scheduling, order fulfillment, packing and more. Then promote an updated model to production using CI/CD.

Forecast, schedule, route: 3 starter models for on-demand logistics

Automating on-demand logistics operations for scale, customization, and iteration is easier than you might think. Learn how to build, test, and deploy models for demand forecasting, shift scheduling, and route creation.

Operationalizing Google OR-Tools models

Learn how to integrate a new or existing OR-Tools model into production systems using Nextmv and its infrastructure, testing capabilities, and collaboration features to create a repeatable workflow to production.