Upon entering the premises of an SME struggling with repetitive tasks, we see how every lost minute translates into costs and frustration. In our experience, automations and AI assistants can change that landscape, as long as we measure their impact rigorously.

The first step is to define what ROI means for the company. We work with our clients to agree on which indicators represent success: reduction of cycle times, increased delivery capacity without raising costs, and improved data quality.

Next, we identify costs and benefits. Costs may include licenses, implementation, integration, and training. Benefits should translate into economic values, such as savings in work hours, error reduction, and enhancement of user and customer satisfaction.

Next, we define key metrics for the trial period:

1. Hours saved per week or month
2. Reduction of errors in critical processes
3. Processing speed or delivery times
4. Adoption and usage rate by the team
5. Service level (SLA) and response times
6. Impact on customer and employee satisfaction

With these metrics in mind, we design the trial period. We establish a baseline, define representative test scenarios, and set up the automatic collection of data. We also assign responsible parties for monitoring and reporting to ensure that the information is comparable from day one to the end of the period.

To calculate ROI, we compare the estimated net benefit with the investment. A typical formula is ROI = (Net Benefit - Investment) / Investment, expressed as a percentage. In practice, we describe each term: net benefit as the economic value of savings and improvements, and investment as the costs associated during the trial period. The results must be interpreted in context and with due caution.

Finally, we interpret the results and outline an action plan. If the ROI is favorable, we move towards scalable implementation; if not, we review configuration, scenarios, or metrics. Our goal is that these metrics serve as a guide for informed decisions and for maximizing learning for the SME during the trial period.

With this approach, we strengthen confidence in AI tools to boost productivity without losing control, and together we build a clear path towards a more efficient operation.