Symptoms
What are you seeing?
Start from the problem in front of you. Each symptom points to the models that best explain it, most useful first.
Delivery and change
“Every change touches several teams or services”
“Delivery keeps slowing down as the system grows”
“Adding people hasn't made us faster”
“Work piles up waiting for one team or one approval”
“Nobody dares change the old system”
“A rewrite is running late and over budget”
Systems and reliability
“One failure takes everything down”
“The system gets slower when we add servers”
“Queues and latency spike under load”
“Incidents keep happening in new ways”
“Consumers break whenever we change an API”
“Retries cause duplicate orders or payments”
People and decisions
“Every decision gets reopened”
“Meetings spend hours on trivia”
“Two experts disagree and neither will budge”
“Business and IT talk past each other”
“Executives don't read or fund our proposals”
“Nobody adopts the platform or standard”
“Teams hit their targets but outcomes get worse”
“We ship features nobody uses”
“Decisions stall because nobody knows who decides”
“We keep analysing instead of deciding”
“A sound decision gets blamed because it turned out badly”
Portfolio and strategy
“Several teams built the same thing”
“We run several systems that do the same job”
“The architecture board has become a bottleneck”
“Our best engineers work on commodity problems”
“We can't leave a vendor we're unhappy with”
“All the budget goes on keeping the lights on”
“Every team wants its own favourite technology”
“We can't tell whether to plan it or experiment”
“We have to integrate an acquired company”
“A new regulation has landed on our desk”
Data and AI
“The central data team can't keep up”
“Reports disagree about the same number”
“Moving the apps is easy, moving the data is not”
“Our AI feature works in demos but not in production”
“An AI agent can reach private data and the internet”
“Our hand-built rules keep losing to bigger models”
“Lots of AI pilots, but no measurable value”
“AI sped up one step, but nothing ships sooner”
“Agents can't reach the data or systems they need”
“Nobody can tell whether the AI is still right”
“People rubber-stamp whatever the AI produces”
“The AI hype keeps outrunning the results”