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While RPA technology is already well established, many companies are still not ripe to take advantage of its full benefits. Monotonous, repetitive processes are prime candidates for automation because they prevent employees from focusing on more important tasks, which ultimately leads to errors.
This is where you start your RPA implementation. However, as technology becomes more prevalent in organizations, there are many aspects to consider in order to manage the automation pipeline and get the most out of robots.
A quick guide to identifying suitable processes for automation
Let’s start with the basics of RPA before we start measuring the parameters of successful implementation. RPA and calculating its ROI. So what processes can be automated? Below are some tips.
See if the process consists of well-defined stages, is there even the slightest room for interpretation and exception? When there are too many stages, and a person needs to decide what to do next, then the process should be automated. You can also find ways to refine the process so that the automated portion of it runs several times a month. These and other reasons will help determine that the investment will not pay off.
2. Labor intensity of the processes.
Automation includes some administrative tasks that take up a lot of time from employees and distract from their main responsibilities. Obviously, this is a process where savings are calculated based on the hours freed up. Practice shows that for an automated process to be beneficial, it must free at least two full-time employees.
3. The readability of the input data.
RPA works with any application or environment, but requires highly recognizable data such as text, user interface actions (such as keyboard bumps or mouse clicks), optical character recognition (OCR) data, and green screen. But RPA does not recognize non-OCR images and non-digital formats.
4. Data structuredness.
Structured data is composed of well-defined data types, so it’s easy to find it in searches. For example, a specific term in a data entry field in an application refers to a specific action in a process. Unstructured data is all other data that is harder to find using search and includes audio, video, and free-recorded formats.
It is often possible to overcome the limitations of RPA thanks to advanced tools based on artificial intelligence – picture and voice recognition, natural language processing (NLP) and others.
Automation is the essence of ROI
Automation is at the heart of ROI. RPA is easy to implement, doesn’t need to change existing systems, and is cheap enough by itself. Especially when cloud RPA is provided as a service, it can be turned on and off like tap water without a fixed technology cost. On a turnkey basis, cost is directly related to usage, not performance. Investments consist of development costs and per-minute calculation of payment for maintenance of robots.
The basic formula for calculating ROI RPA:
Automation cost – (hours spent doing the task manually × manual labor cost).
Whether you are implementing RPA as a service or licensed, ROI should not be measured in years, but in months and weeks. Usually RPA projects pay off within 3-9 months. When RPA is purchased as a service, the payback period is usually shorter than under a license due to the lack of flexibility in tuning performance for the required tasks.
The company’s other costs for RPA relate to training and recruiting specialists, organizing project management, and launching automation. Consider carefully evaluating your internal resources, calculate the development cost, and determine which areas to focus on when setting up and running an RPA program. For example, should you focus on creating high-quality reporting and analysis of automation stages or assemble a team to develop and support automation.
Why is ROI calculation the key to success?
The use of RPA, like any other significant business tool, must be guided by the company’s strategy. For example, if your goal is to be the best in delivering quality service and outperform the competition, first of all, automate the processes that will help you achieve that goal. Simple, right? This is still the first step.
The RPA strategy is based on the company’s overall strategy, but it requires certainty: clearly articulated responsibilities are required when starting the program, and key performance indicators (KPIs) are selected based on the goals you want to achieve.
There are many cases where the development of adequate RPA success metrics has been ignored. There are two reasons for this: it is difficult to effectively manage and maintain the program in the company.
It is critically important to show clear results when the program is attempted to scale and involve stakeholders at various levels of the organization. The lack of systematic accountability creates a problem in a situation where the people managing the program change jobs, and it is difficult to track whether the results will be passed on to the successor in this position, since the attitude to the program depends on this employee.
Finally, the results suggest how the RPA program should be further developed. By monitoring what works, you can make informed decisions and improve, for example, the automation pipeline or prioritization.
What should be measured?
Choosing the most appropriate KPIs depends on the strategic goals of your automation program and the automation process itself. Below are a few general RPA success metrics to consider when calculating ROI.
Full Time Equivalent – FTE
This is the most obvious metric to consider when calculating ROI. Full-time equivalent is the number of hours one employee works full-time for a fixed time, such as one month or a year. The cost of automating a process is compared to the cost of manually performing the same process. FTE measures for calculating direct savings are used when the alternative to automation is hiring a large number of temporary employees to manually move data from the old system to the new one, or hiring an external provider to run the process outside of business hours.
Saved working hours
Automation rarely results in layoffs. In fact, the processes that are planned to be automated prevent workers from performing their basic responsibilities. For example, a doctor spends time entering data into the system instead of treating patients. Stored hours are calculated by assigning the cost of the hours freed up for more productive work, or by adjusting the FTE to reflect the cost of returned work hours.
To reallocate the freed hours, change management skill is required. If the task no longer exists, what will happen to the time that was spent on it?
Reduced error correction costs
This metric reflects the extent to which process automation contributes to the correction or elimination of process errors. The cost of fixing bugs is tools to prevent, detect and correct problems. If automation can improve the quality of the process, you should know how much the error will cost. For example, getting rid of the constant small typos in the purchasing process can save you money by eliminating the need for cross-checking and reducing the number of order forms to fill out.
Process optimization and timing
The lead time for a process is how long the process takes from start to finish. This period also includes a certain amount of waiting time. Automation allows you to streamline the process, for example, by running preparatory activities at night or on weekends to reduce downtime during business hours.
Accelerating lead times can also increase productivity and, in some cases, profit. For example, thanks to the round-the-clock preprocessing by RPA, bank employees will be able to handle a large number of loan applications.
Service availability and customer satisfaction
One of the simplest ways to measure service availability is with two numbers. This is the agreed service time when the service is available during the reporting period and any downtime during that period.
In manual work, service levels can change as a result, for example, depending on a key employee or overloading requests. Automation solves the performance issue that leads to increased throughput and shorter queues.
Automation also allows the company to significantly expand service hours and provide services around the clock. Over the past few years, digitalization has contributed to the development of customer service. People expect that access to online services is unlimited by the time of day. A service powered by RPA 24/7 creates a strong competitive advantage whose business impact should be measured. In addition, the question may arise how to measure the value of having improved service availability through customer service metrics.
It seems difficult to incorporate service availability and customer satisfaction metrics into ROI calculations. But there are several ways to solve this problem: 1) calculate the opportunity cost of offering the same level of service without automation, or 2) evaluate how valuable it is to the business that service availability and customer satisfaction are improved by X%.
Increased business agility
Increased business agility is a very important indicator of RPA success. Lack of available human resources and technological sluggishness hinder business development. RPA is being used to bring flexibility to these two areas: freeing up employee time and increasing technology agility through integration. Business agility counts when calculating ROI by measuring the number of new strategic initiatives and determining their value.
Business Continuity Measures
There is much more awareness of the value of business continuity today. Reducing reliance on employees for mission-critical processes often equals lower risks to business continuity. RPA is a great tool to achieve this goal. Calculate the cost of downtime and assess the risk. How much can it cost to reduce or eliminate these risks?
Employee satisfaction is an uncertain indicator, but it is nevertheless very important. Overwork does not make employees happy, so if automation solves this problem, it can be measured.
Employee satisfaction metrics can be used to calculate ROI by reducing employee retention, improving productivity and employer image making it easier to develop new skills.
There are other metrics that are appropriate for specific tasks, but in our experience, the above can be used in many scenarios when calculating RPA ROI, KPI performance and prioritizing automation stages.
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