What If M&A Diligence Was Designed Like Chaos Engineering?
Article summary
Picture this: You’re about to acquire a fast-growing SaaS startup. Their architecture diagram is clean, the uptime metrics look solid, and the CTO delivers confident, well-rehearsed answers in every Zoom call. So the diligence team signs off. The deal closes. And three weeks later, the system falls over during a traffic spike. Turns out the billing service was built by an intern two summers ago and never touched since. The monitoring stack covers less than half the real traffic. And the only person who understood the deployment pipeline is now off the grid in Bali. What happened? You tested the surface, not the substance. Which brings us to chaos engineering. Chaos engineering is the practice of injecting controlled failure into a system to test its resilience. Netflix pioneered it with Chaos Monkey, intentionally crashing services in production to see how systems recovered.
Read Full Article on MediumPractical takeaway
The main idea behind What If M&A Diligence Was Designed Like Chaos Engineering? is to help teams move from broad theory to clear, repeatable decision making. When teams apply this thinking, they reduce ambiguity and focus on improvements that deliver measurable momentum.
Example scenario
Imagine a team facing competing priorities. By applying the ideas in What If M&A Diligence Was Designed Like Chaos Engineering?, they can map dependencies, identify risks and choose the next move that produces progress without destabilizing their system.
Common mistakes to avoid
- Trying to redesign everything instead of taking small steps.
- Ignoring real constraints like incentives, ownership or legacy systems.
- Creating documents that do not lead to any change in code or decisions.
How to apply this in real work
Start by identifying where What If M&A Diligence Was Designed Like Chaos Engineering? already shows up in your architecture or delivery flow. Then pick one area where clarity would reduce friction. Apply the idea, measure its effect and share the learning.
Signs you are doing it correctly
- Teams make decisions faster and with fewer disagreements.
- Architectural conversations become clearer and less abstract.
- Changes land safely with fewer surprises or rework cycles.