Selling software that bases its potential on Artificial Intelligence since a few years, we have learned to cope with the most popular questions from our potential customers, which usually concern the design phase needed to ground pricing, forecasting or segmentation solution such as those offered by Premoneo’s platform.
Projects based on the use of AI, in fact, especially when it’s the first time the company is dealing with the in-depth use of data, promise to improve performance, but involve a non-negligible investment in time and resources. For this reason, it is essential to be ready to calculate, together with the client, the return on investment (ROI): the most significant KPI of all, these days, to convince the client to invest in the technology we propose.
ROI, how it is calculated
The return on investment (ROI) is an indicator that evaluates the ratio between invested capital and realized profit. The ROI can also be seen, by a company, as the objective in terms of profits given a certain investment (Economic return of a single investment in a given period).
ROI, the main aspects to consider
There are mainly three aspects to consider before determining the ROI of an innovation project involving the adoption of new technology:
- The problem. An AI-based solution is often identified with the goal of solving a problem, making a process more efficient, or improving some performance. Sometimes these areas of focus involve multiple divisions of the company and different operational teams, making the project startup more complex. Where it is possible to circumscribe a problem that can be addressed with the proposed technology, then we always advise clients to start with a pilot project that involves a few resources and can provide rapid feedback on the goodness of the action. This solution has a twofold advantage: that of making technology adoption faster, quickly achieving a measurable result (on which to calculate ROI), and that of training internal resources who will lead the way, internally within the company, when the solution is scaled to more processes, involving more operational teams.
- Competitive advantage. The time and resources invested in an innovation project must materialize in a competitive advantage, measurable and demonstrable to the entire supply chain. However, it is not always easy to measure the advantage of an AI project. For this reason, one of the key points to be unpacked together with the client is how to calculate the competitive advantage. Often a benchmark or a shared calculation model will suffice, and then speak the same language when it comes time to verify the results and the extent of the project’s impact.
- Cost impact. An artificial intelligence application may impact not so much business outcomes as it saves the company time and resources. Cost savings can then become a significant KPI that should always be placed on the scale in the overall project evaluation. At Premoneo, we often ask clients to measure the number of hours resources spend performing a certain type of task whose use will be lowered by our technology. Putting a price on that labour cost will allow us to put that advantage on the right side of the scale as well.
With these few premises, it’s possible to better evaluate the scale of the pilot project and identify a shared method to calculate the ROI, the key to convincing any CEO to invest in a project like the ones we propose at Premoneo.