Sales coverage vs payroll cost
A commercial team wants broader pipeline coverage, but extra headcount raises fixed cost and pressure on margin.
TRIZ mini appStart building
ITB Contradiction Builder
ITB stands for IF → THEN → BUT. It helps teams state a contradiction cleanly: if we make a change, we gain a benefit, but we worsen something else. That clarity is the starting point for solving the problem without settling for a weak compromise.
Method in one line
If we increase inspection intensity, then we detect more issues before they escape downstream, but we reduce throughput and create bottlenecks.
Example: if we add more review gates, then quality improves, but delivery slows. The contradiction becomes clear: we need higher quality without longer lead time.
What you get
A contradiction statement you can use in a workshop, brief, or review.
- Main IF → THEN → BUT statement
- Reverse statement that exposes the cost of inaction
- Contradiction card, challenge question, and export-ready summary
Builder
Structured inputs
Generated outputs
Editable statements
Idea triggers
Prompts, not fake automation
Can the benefit be achieved without adding this cost?
Can the function be automated?
Can the effect be achieved through a partner, proxy, or different mechanism?
Can the action be delayed, divided, or shifted?
Live diagram
Diamond contradiction view
Action
increase inspection intensity
Desired effect
we detect more issues before they escape downstream
Undesired effect
we reduce throughput and create bottlenecks
Reverse condition
If we do not increase inspection intensity, then we avoid we reduce throughput and create bottlenecks, but we lose we detect more issues before they escape downstream.
Summary card
Raise control quality without lowering throughput
Problem
Raise control quality without lowering throughput
Action
increase inspection intensity
Domain
Operations
Desired effect
we detect more issues before they escape downstream
Undesired effect
we reduce throughput and create bottlenecks
Contradiction
The contradiction is: we need we detect more issues before they escape downstream without we reduce throughput and create bottlenecks.
Next question
How can we achieve we detect more issues before they escape downstream without causing we reduce throughput and create bottlenecks?
Example library
Built-in contradictions
Review depth vs delivery speed
A delivery team wants fewer mistakes, but each extra approval step slows release flow and increases wait time.
Inspection intensity vs throughput
An operations function wants tighter control, but more intensive inspection reduces throughput and creates bottlenecks.