Businesses moving to cloud-based intelligent automation solutions — such as robotic process automation and artificial intelligence technology designed to transform businesses typically cite various reasons to adopt the latest technology. They focus on improving operational efficiency as well as a better customer experience. Others stress the need to enhance quality control and boost internal innovation.
Whatever goals are achieved, the two main driving forces are usually at the heart of their decision-making processes: Will this solution allows the company to increase its profits? Can the solution reduce the cost of existing ones? If one or both of the above questions is yes, the business will usually proceed with those solutions. Cutting costs and making more profit by automatizing manual tasks can positively impact the bottom line. It also allows the company to allocate resources (including human resources) to more valuable tasks.
How to Calculate Automation ROI
It’s all simple; however, the problem for many companies rises when they try to calculate the return on investment from intelligent automated solutions. Often, companies determine ROI by estimating the expense of creating an automation system and the ongoing cost of maintaining the automation, and the anticipated time savings by automating what was previously a manual process. Although this seems logical reasoning, many variables can alter the calculation and lead the company’s leadership to wonder if the decision to switch to intelligent automation is providing the type of ROI initially envisioned.
To accurately determine the ROI of intelligent automation, companies must consider the effects of redundant automated systems. Many businesses are caught up in the success of their automation, only focusing on a single bot and how much time and money one bot could be able to save an organization.
Unfortunately, this method lacks the need for a strong governance structure. A lack of governance could result in companies with inefficient or low-quality automations, as in a variety of other problems, all of which could cost them money that they were not planning to spend (and in some instances, they aren’t even conscious of). On average, 15-20% of the total automation infrastructure of most established companies is redundant.
Investigating the Real costs of Automation Projects
Businesses must begin an intelligent automation plan, knowing that, if they encounter errors or ceases to function, it’s not just the case of replacing the part. Complex automations can become costly quickly, given the advanced technical knowledge required to restore them to function with as little disruption to the process as possible.
The cost of technical expertise is also a factor in RPA design and compliance and, consequently, could dramatically impact the overall return on investment. Although most companies are aware and can easily estimate the costs for a developer to create an automated system, it’s more challenging to determine the expenses involved in studying the process that needs to be automated, creating the system and making any necessary changes as well as taking into account the security and risk of compliance, and evaluating the process with all the stakeholders to ensure that everyone is on board.
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Design and compliance are demanding and cost-effective. They can also quickly spiral out of control. In the end, businesses must obtain accurate cost estimates before starting any project and be aware of any additional costs. It will allow them to ensure that there aren’t unexpected costs, and will consider all charges in calculating ROI.
Application licensing fees are another expense that many businesses neglect or underestimate. This is because businesses tend to concentrate on the fee they pay for licensing the RPA platform they’re purchasing and forget that important expenses for any automation are the licensing costs for any software system the robot will have to connect to. If intelligent automation requires access to an ERP or billing system of a company, tools, for instance, should be prepared by the business for a monthly fee for licensing the various tools. Even when it costs minimal, annual fees could quickly add up for companies in the process of changing to multiple automations that require access to multiple software programs.
In addition, like any other industry, businesses that utilize intelligent automation tools should consider the increasing cost of business and the higher expenses related to RPA expansion when they make ROI estimations. Beginning with the first and continuing with the current wave of inflation is reflected in the more expensive cost of RPA charges all across the board. Consider an additional fact: RPA platforms are constantly getting new technologies, including process mining software, and the need to calculate intelligent automation ROI is apparent periodically.
In the same way, costs are expected to increase as an organization’s RPA practice expands. The development of new automated systems is likely accompanied by the need to hire new, more experienced RPA resources, increasing the overall cost. Many companies do not take into account the rising costs when determining ROI.
Be aware of costs
In the end, companies must consider these factors more when assessing whether their intelligent automation efforts result in the ROI they initially anticipated. Furthermore, they must be aware that, at a minimum, these expenses are not a fixed goal. This is why it’s crucial to consider these elements before making an automation change and periodically revisit the initial calculations to ensure they are still valid. This will result in an accurate ROI estimation and, ultimately, more precise information about whether the objectives associated with the move to automation are being achieved.