When a client asks me "what's the ROI on your automation?", I ask them back: "ROI measured how?" The answer to that question determines whether the project succeeds or fails.
Most automation projects measure the wrong things in the first 90 days. They count tasks automated, hours theoretically saved, and errors reduced. These are leading indicators — they're not business outcomes.
**What to Track in Days 1–30** Process completion rate: Did the automation actually complete the task, or just partially? You want > 95% completion rate before calling it a success. Error rate comparison: What's the error rate now vs. before? Automation should reduce errors by at least 60% to be worth the switch cost. Human time to intervene: How often does a human have to manually fix something? This tells you how much training data you need.
**Days 31–60: Business Impact** Now start measuring outcomes. How has the automated process affected your conversion rate, response time, or customer satisfaction score? These are the numbers your CFO cares about. At Workcin, we measure a simple metric for every client: Revenue Per Human Hour. If an automation frees up 10 hours per week, and the team redirects that time to revenue-generating activities, does revenue per human hour go up? That's the real question.
**Days 61–90: Scale Readiness** By day 90, you should know: Can this automation handle 5x the volume it handles today? If the answer is no, you've built a fragile system, not a scalable one. This is where most DIY automations break.
The 90-day ROI framework isn't about proving automation works. It's about learning what the automation is actually telling you about your business. The data from a good automation is as valuable as the automation itself.
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