Operations and AI Readiness: The Discipline You Can’t Skip
Operations brings the lean discipline that AI implementations desperately need. Waste elimination, metrics culture, and daily standups matter more than algorithms.
Operations brings the lean discipline that AI implementations desperately need. Waste elimination, metrics culture, and daily standups matter more than algorithms.
Product Development is the only team that can answer the question "what should AI do for our customers?" That conversation - from widgets to intelligence - is where new revenue lives.
Finance has been speaking in facts - insisting on data rigor, measuring value, building structures that survive turnover - since before AI was a boardroom topic. Those aren't peripheral skills for AI readiness. They're foundational.
The Data Value Chain was built for structured data. But 80% of what your organization knows is unstructured - and AI just cracked it open. This is the knowledge management breakthrough we've chased for 30 years.
AI compressed the technical middle of the Data Value Chain, shifting the bottleneck to the human bookends - Insight and Present. Most organizations haven't noticed.
A seven-step framework for turning raw data into business decisions. The Data Value Chain maps the distinct skills required at each stage - and explains why you need a team, not a unicorn.
IT, Marketing, and Operations can all claim ownership of your AI strategy. Committees claim nothing. The right owner is defined by what they can see, connect, and serve.
Most AI innovation programs produce demos, not results. The environment that actually ships sits between the sandbox and the cowboy - and it requires judgment, not just enthusiasm.
Most teams respond to AI with tactics - a demo here, a pilot there. Strategic thinking is a skill that can be taught, starting with three deceptively simple questions.
Experience replaces feelings with competence. That's its job - but it costs you the emotional memory your team needs you to have right now about AI.