Estimating cost & ROI realistically

Try it yourself: when does it pay off?

The four factors of a realistic ROI estimate

Frequency & rule stability: How often does the process run, and how stable are the rules behind it? The less stable the rules, the more rework shows up later. Exception rate: How many cases deviate from the standard case? A high exception rate eats into the planned time savings. Ongoing maintenance cost: Realistically 10 to 40% of the original implementation cost per year – almost always missing from the first calculation. A named owner: Without clear ownership, an automation's value demonstrably erodes faster – nobody notices in time when the underlying rules have changed.

Why this matters for you as a decision-maker

A realistic ROI estimate accounts for more than day one – it accounts for maintenance and value erosion over time. That's why Beyond Prompt's AI Opportunity Scan calculates with maintenance cost and a named owner from the start, instead of only showing the day-one number.

Key takeaways

• ✓ROI math that only looks at day one is almost always too optimistic.
• ✓Ongoing maintenance cost (realistically 10-40% of implementation cost per year) belongs in the calculation from the start.
• ✓Frequency, rule stability, exception rate, and a named owner together decide whether a process is really worth automating.
• ✓Without a named owner, an automation's value demonstrably erodes faster.
• ✓Realistic payback periods are often several years, not a few months.