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Metrics for success with RPA
The collection of RPA success metrics listed below should be considered from both a technical and business project management standpoint. From both a technical and business project management perspective, the group of RPA success measures given below should be taken into account.
All of them should be recognizable to you?
Yes. All of the metrics given below should be familiarized with in order to better grasp what and how you may measure in connection to RPA activities.
Are all of these intended for use?
No. Over Measuring is far worse than performing no measurements at all. When you follow too many signs, you become overloaded with information and lose sight of what is really important. Choosing a modest number of steps and sticking with them over time is the best course of action.
Following are the enterprise metrics to measure the success of an RPA −
Time gains' value (TGV)− Time gains' value(TGV) compares the costs of processes carried out by humans with RPA bots. This equation may be used to calculate it.
TGV= (EC − AC)/AC x 100%
EC is the costs of processes performed by employees, including wages (including leaves and vacations), taxes, and office and workplace expenses (rent, utilities, etc).
AC stands for the expenses associated with the services provided by bots, including license fees, development costs, virtual machine/hosting costs, and maintenance costs.
Your baseline metric for determining RPA ROI is TGV.
RPA Return on Investment(ROI) − Processes Robotics Automated A key business metric called return on investment (ROI) should demonstrate how much money your organisation was able to make (or save) as a result of using RPA.
To determine the RPA ROI, consider the Value of Time Gains (above point). In order to fully understand RPA ROI, two more factors must be considered −
Process speedup A−Value − A−The value of process acceleration reveals how much actual money was earned by using automation. This may be shown, for instance, by how expediting the customer onboarding process affects the number of customers handled before and after automation, multiplied by the average benefit per client.
B−Value of error reduction − Value of error reduction− This measure shows how much money can be saved by eliminating mistakes. It should correspond to the priorities of your company.
It could, for instance, represent the total cost of business deals lost as a result of errors or protracted processing, the cost of manually correcting errors (represented by payroll costs, such as 30% of 1 FTE), the rise in the proportion of cases that meet SLAs, the improvement in data quality, or anything else that is essential for a specific process or organization.
Once VoPA, VoER, and VTG have been calculated, we may calculate the RPA ROI as follows.
[(TGV*AC + Value of Process Acceleration + Value of Error Reduction) − AC]/AC x 100%
Business Value Assumed − The RPA indicator called as Expected Business Value compiles all extra business−related KPIs connected to RPA. It is calculated by multiplying the overall cost savings (achieved through greater performance, better resource usage, and fewer errors) by the average FTE costs during a certain time frame.
Rise in productivity − The "gained productivity" metric is one of the most often utilized by enterprises to assess the performance of RPA. It demonstrates how many FTEs were added as a result of automating a certain operation. For instance, if automation replaced the manual labour of 4 people who would normally spend 2 hours per day doing the activity, the productivity gain would be 1 FTE/month.
Cost per Error − The cost of an error that occurred during a specific automation is disclosed by this measure. It should include the cost of the labour hours needed to fix the problem as well as the total value lost due to downtime.
Utilization of License − License utilization gauges how much the business uses their RPA provider license. If your UiPath−based bots are using the license to the greatest degree possible but are unavailable for 10% of the time over a given period due to maintenance or downtime, your license utilization will be at 90% in this case.
Following are the technical metrics to measure the success of an RPA −
Speed of Process Automation − When using an automated process, you may look at the process velocity to determine the typical time needed to finish one case or project.
Average Automation Development Time − These statistics show how long it typically takes to create and set up one RPA bot, as well as how many hours an RPA developer works on it, in terms of FTEs or the number of hours they work on it.
Bot Success Rate − Bot Success Rate/Bot Accuracy Rate shows the proportion of cases handled by the bot for a certain operation. RPA success rates of 80% or more are considered ideal. An RPA bot with a 99% accuracy rate is definitely possible to build.
Scalable automation − This statistic shows how easy it is to scale a certain method. The time and cost to install a new machine or reproduce the bot should be compared to the time and cost to hire and onboard a human processor to carry out the same tasks, including the payroll costs (for instance, 30% FTE).
In general, if the RPA bots are developed following all other best practices, they should grow pretty quickly.
Scalability in development − Demonstrates the portion of the old automation code that can be applied to the new automation. Since they can be created by re−constructing the existing ones, adding a new bot typically gets easier and takes less time as the amount of automation produced for one business increases.
Failure Rate − The proportion of time that your bot may be completing a task but isn't due to a problem or maintenance is known as the downtime rate.
Person Hours for Break−Fix − Data on the amount of time needed to resolve a specific problem is available in the Break−Solve Person Hours metric. The quantity of FTEs or man−hours required to correct the automation and bring it back on track should be specified.
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