As Alexandra Kate Hak once said:
"The most expensive failure is inaction."
This has become a guiding principle for how we think about lab automation.
The Pattern We See Over and Over
Budgets get approved. Vendors are selected. Plans are established.
And then... nothing happens.
Labs enter extended periods of inactivity. Systems are technically "in progress," but nothing tangibly advances:
- Instruments remain on order
- Integration is months away
- Progress is perpetually deferred
Meanwhile, science keeps evolving. Assays change. SOPs shift. Scientists adapt manually out of necessity.
The Costly Result
By the time automation finally deploys, it addresses outdated problems.
- Late modifications increase costs
- Delays erode confidence in the project
- The original champions have moved on
Why Projects Really Fail
When I first entered lab automation, I questioned why the industry didn't mirror software development's agile approach.
The answer I received was revealing:
Most automation projects survive only one to two years. Not because science failed, but because the world transformed before deployment completed.
Scientists relocated. Leadership priorities shifted. Momentum evaporated.
How Lab Donkey Does It Differently
We rejected this outcome.
We adopted a software-first approach, delivering measurable progress within weeks rather than years.
Our philosophy:
- Early iteration — Start seeing value immediately
- Expected changes — The world will change, so plan for it
- Rapid learning — Fail fast, learn faster
This is how software works. Why shouldn't automation work the same way?
What This Means in Practice
- Immediate software tools you can use today
- Labs own their workflows from day one
- Platform consistency across projects
- No proprietary hardware mandates
The Real Cost
Automation is failing science. Not the other way around.
The costliest outcome isn't a failed project—it's extended waiting that prevents projects from genuinely starting.
Stop waiting. Start iterating.