What input was used to run the model? What model version did it run on? Where are we tracking new model development? How long will it take to reproduce the experiment setup that generated the most recent test results? Is it safe to roll out the newest model iteration? And do we have a fallback model we can leverage just in case?
All of these questions are part of everyday decision model development. Answering them efficiently is critical to innovating within the discipline and driving sustained project success within teams and organizations. Too often teams rely on fragile or incomplete infrastructure to support these workflows, if they’re lucky to have them at all. Harness the DecisionOps habits that leading teams have used to drive greater and more sustained project success.
Join this session to learn about best practices for managing the full decision model lifecycle: from versioning, environment setup, CI/CD integration, model drift monitoring, rollout strategies, and more.
Related Domains:
Domain V – Model Building
Model verification and validation through testing, model reproducibility, model performance communication to stakeholders, and model integration.
Domain VI – Deployment
Infrastructure considerations for model deployment, online testing (shadow and switchback) for safer production rollouts, CI/CD workflows for collaboration with engineering processes.
Domain VII – Model Lifecycle Management
Observability and monitoring for model performance and health, model version management, model replay mode for troubleshooting, ongoing experimentation and reporting for model iteration and improvement to align with business requirements.
Relevant to:
- Essential (Early Career),
- Professional (Mid-Career), and
- Executive (Senior Level).
