The first question is not “Which AIs should I buy?” or “What training course?”, but “Which job consumes time and causes repeated remediation tasks. Or make the customer wait a long time? ”If this question is not answered, the project may seem busy at the start and become silent after the workshop.
1. Establish a baseline you can verify
Select a single process first and keep at least 4 values: number of tasks per month, time per piece, rate of erroneous or re-corrected tasks. And the quality perceived by the customer or user specifies the measured period and the data subject. If the data is not complete, be honest. It's a hypothesis, not a performance number.
The UK government's AI evaluation approach emphasises recording the baseline and traditional working conditions before starting. Because without a benchmark, it would be hard to know if the change actually improved the effect. Read the source guidelines ↗
2. Distinguish time freed up from cash saved
Hypothetical example: a team works on 600 items per month, if the pilot can reduce the time by 12 minutes per item, it will return 120 hours per month. If the value of labor is 350 baht per hour, the potential production capacity is 42,000 baht per month. But this is not yet the kind of cash that organizations can automatically save.
If the team takes the return time to work, the actual value is only half as high, the cautious value is 21,000. THB per month or THB 252,000 per year if the pilot spends an initial THB 90,000 and has a custodial cost of THB 5,000 per month. First year cost is 150,000 THB, hypothetical difference is 102,000 THB and simple ROI is 68%. These are all examples of how to think, not customer contributions or ThinkToFinish guarantees.
3. Include the full cost and side effects
Includes tooling, IT and team time, system integration, security monitoring, training, data stewardship, and review time. from humans. Do not combine “potentially extra” income with actual savings in one lump sum, and note risks such as: Quality, answers, privacy, and mistakes that could create new costs.
Australia's National AI Centre notes that AI's cost-effectiveness is not only financially rewarding, but also qualitative. Capacity, confidence and satisfaction by determining results and signals of progress before investing is critical. Read the source guidelines ↗
4. Run a pilot to test value—not to put on a show
Define the owner, experimental group, time interval, quality criteria and stop/extend conditions before starting, compare before with after. And if possible, compared to the team that still uses the same method, don't just measure the number of people who open the tool, but see that the work is done faster. Is it more accurate or does it help the team to take on more workload without compromising quality?
If the pilot result is still not worth it, then the decision to stop or change the problem is a valuable result. because it helps not to invest heavily on the wrong assumptions. If the results are really good, then talk about expanding and say that the pilot number may not be the same as when used throughout the organization
Begin with the free tools
For AI projects, use AI VALUE 360 To place use case, baseline, total cost and stage gate if the problem is user development. TRAINING ROI To connect learning with business behavior and results, download them without having to enter an email address and then replace the actual data of the organization with a sample value.
This article provides a practical framework for ThinkToFinish based on the evaluation principles from the above public bodies, not corporate-specific financial advice or guaranteed returns.