Why Measuring Tech ROI Can Be Complicated and How to Simplify It

For a multitude of reasons, organizations may find it challenging to calculate their actual earnings from technological investments.

These investments include the implementation of AI and other automation technologies to make daily work operations more efficient. To understand the true ROI of AI, organizations must ask themselves three key questions.

The task of accurately evaluating the returns on the implementation of AI and other automation technologies is different from calculating the ROI in other areas such as material procurement and packaging. Firstly, AI and other technologies are present in several areas of an organization (even the lesser-known ones), so it is hard to get a measure of their actual scope. Additionally, organizations need to decide the type of returns (monetary, qualitative or efficiency-based) they are trying to note down.

Why Measuring Technological ROI Is Complicated

There are some issues that may prompt organizations to second-guess themselves while measuring the ROI of AI and other IT systems. These issues can be:

a) No ‘Correct’ Starting Point

There are no fixed points while calculating the IT ROI of your organization. As stated earlier, AI may be present in so many aspects of your organization that it is hard to keep track of its true influence on your revenues.

b) Intangible Qualities

There are certain things that cannot be measured. For example, how AI gives you a head start for your business operations. This is an attribute that can be measured in time, not money. As a result, there are no fixed yardsticks with which the ROI of AI can be measured.

c) Too Many Variables

As we know, the calculation of ROI involves the subtraction of the costs from the earnings gained from a particular investment. However, once again, the time spent on sourcing AI datasets and the money and time spent on upskilling each employee may not be comparatively measurable while calculating the ROI of AI. The presence of several such variables makes it hard to maintain records of costs and earnings in a traditional balance sheet format.

How businesses can simplify the measurement of AI’s ROI

You can make the process simpler by considering these factors:

a) Avenues of Earning

One of the questions that you must ask yourself is whether the introduction of AI and other automation technologies has increased revenue streams in the form of diversified product lines or improved product quality. If yes, those revenues can be included while calculating the ROI of AI.

b) Change in Operational Costs

The second question that you must answer is whether AI makes certain operations unnecessary and, if yes, whether spending money in those operations (on wages, maintenance) can be avoided.

c) Change in Capital Expenditure

Another important thing to consider is whether AI makes certain capital investments redundant and unnecessary. If yes, those investments can be sold to raise money for other purposes. The savings made on capital and operational expenditure can be added as a component in the ROI of AI.

Apart from this, organizations can also measure the surplus profit earned after the implementation of AI and other technologies in their workplace. The calculation of ROI of AI is not hard if expenses and earnings from every area of your organization are factored into the measurement process and the true value of AI applications is understood and appreciated.