Insights
AI Readiness
How to tell whether your operation is ready to hand work to AI, and how to find out rather than estimate. Covers what a readiness assessment should measure, how to decide what to automate first, and what a 90-day baseline gives you that a consulting study does not.
How to Prioritize AI Projects in Operations
Impact-versus-feasibility matrices fail because the impact numbers are guesses. Here's how to prioritize AI projects in operations using measured automation potential, not estimates.
How to Know What to Automate in Operations
The criteria for what to automate are easy. Finding where those tasks actually hide in your operation is the hard part. Here's how to identify real automation candidates...
An Alternative to McKinsey for AI Workforce Strategy
Looking for a McKinsey alternative for AI workforce strategy? Most "strategy" failures are really data failures. Here are the four categories of alternative and how to choose.
AI Deployment Roadmap for Operations: A Phased Plan That Survives Contact With Reality
Most operations AI roadmaps stall in pilot purgatory because they start with technology, not data. Here's a six-phase deployment roadmap that begins with ground truth and measures every...
The 90-Day AI Assessment vs. the 18-Month Consulting Engagement
A consulting firm samples your workforce over 12-18 months and hands you a deck. A ground-truth assessment captures the real work in 90 days. Here's how to choose.
AI Readiness Assessment for Operations: What It Is and How to Do It
Most AI readiness assessments check your infrastructure. The one that matters checks whether you know what your people actually do. Here's the five-pillar framework for operations.