Contact us anytime to know more — Abhishek P., Founder & CFO CISIN
The RPA honeymoon is over, given the many automation programs that fall short of expectations and don't provide the promised ROI.
Automation teams' need for more attention to the proper metrics is one of the reasons why businesses aren't getting the most out of RPA.
Everyone tracks five standard intelligent automation key performance indicators. Even though each of those traditional metrics has a specific value, you will need more than just concentrating on them to provide your automation program with the crucial understanding required to increase ROI.
Automation journey leaders should be monitoring additional informative KPIs. These crucial RPA metrics, despite being less often used, offer far greater transparency into the state of your automation, the holes or weak points in your ecosystem, and the actions required to optimize RPA ROI.
How to Implement KPIs in your RPA Implementation
The final KPI is a business metric, and the previous six offer operational insights.
Implementation Costs
This indicator is critical to include in your success indicators because it has a big impact on your automation project's return on investment (ROI).
Compared to other IT infrastructure projects, the RPA implementation process usually requires a smaller budget and takes less time to complete (three months for a bot versus several years for IT infrastructure projects). Therefore, it is possible to clearly illustrate the financial benefits of RPA by focusing only on implementation costs.
Cycle Time
When performance is calculated based on the total amount of time needed to complete a task, RPA is also likely to appear favorable.
Because software robots can execute repetitive tasks faster and with less error, they shorten cycle times. Moreover, bots can run consistently and steadily because they are immune to fatigue or what's known as "holiday ideation."
Throughput
This measures the productivity of your company at a particular moment in time. Because cycle time is reduced with RPA deployment, this KPI, a gauge of deployment success, usually rises.
You should be aware of the potential side effect that increased throughput could cause workflow bottlenecks, even though it can't be processed any further.
To ensure that you can respond promptly in the event of congestion, you should thoroughly assess the end-to-end processes when organizing the RPA digitization of your business.
Accuracy
Enhanced precision is one of the principal advantages of automation solutions. It is contingent only on the software being correctly programmed.
Processes operate with a zero error rate whenever this is the case.
Compliance
RPA results in fewer compliance problems because of its higher accuracy. Data protection is made more accessible by the bots.
They also facilitate adhering to new regulations more easily; this benefit should be noticed, considering how frequently rules change. This point is aptly illustrated by adjusting to the latest European General Data Protection Regulation (GDPR) developments.
Moreover, when RPA supports checks and balances, compliance standards are reinforced more readily. This indicator can be quantified in two related ways: the quantity of compliance errors (if any) and the expense of correcting them.
Qualitative Indicators
These KPIs for robotic process automation need to be operationalized in terms of measurable attributes before they can be measured directly.
Examples include adaptability, scalability, or metrics about people, like staff morale or customer service satisfaction.
As an example of a qualitative metric for short-term employee engagement, consider employee morale. To evaluate it, staff members in the departments most affected by automation should be asked to fill out questionnaires describing how they feel about their workload and place in the organizational chart both before and after automation opportunities.
Process Outcomes
This metric is typically calculated by contrasting the process outcomes from before and after RPA deployment.
The result shows how much software robots have contributed to your company and, consequently, how much they help you reach your objectives.
The Five More Automation KPIs to Track to Maximize RPA ROI
Break-Fix Cycles
The number of times an automated process breaks and needs maintenance is called its "break-fix cycle."
This metric is directly responsible for many of the pain points RPA programs face, compounded by their incapacity to scale and optimize RPA ROI.
Monitoring Break-Fix Cycles reveals how robust or brittle the bots you've constructed, which is why it's so instructive. Bot malfunctions directly affect RPA ROI since they prevent the bot from decreasing expenses or improving operational efficiency while out of commission.
Break-Fix Person Hours
Automation teams can learn how long it takes to fix a bot that isn't working correctly and how much manual labor is involved by using Break-Fix Hours.
This RPA metric indicates the amount of time the bot's business processes value is idle, which reduces the expected RPA returns and raises the cost of hiring a full-time worker to investigate and repair the bot.
It takes an average of 120 hours to fix errors in bots, after which they are unable to operate again. This includes the time needed to identify the bot's issue, investigate its root cause, make the necessary repairs, retest, and redeploy.
Break Root Causes
Finding and keeping an eye on the underlying causes of bot malfunctions is crucial, especially since RPA programmes frequently involve continuous Break-Fix Cycles.
This RPA metric is crucial because it helps you identify gaps in your automation processes that prevent you from expanding and maximizing your RPA uptime for maximum returns.
It can assist you in observing how your Break-Fix Cycles have evolved, but it doesn't have to be restricted to a certain period of time. This could even be considered a living catalog.
Average Automation Uptime
Bot availability, sometimes called average processes for automation uptime, tells you how frequently your bots can perform the tasks they were intended for.
This is different from utilization because it measures a boat's capacity to contribute to the anticipated business value consistently.
All bots start with a maximum of 100% uptime. Uptime starts decreasing when they're pulled out of production because they've thrown errors or broken and require maintenance.
This metric should be tracked over a set period, but the longer, the better because the metrics will be more telling. A reasonably accurate average we've observed is 92% uptime, which, for one bot, seems reasonable. Still, for a sizable portfolio of one hundred bots, this can mean upwards of $2 million in lost business value as a direct result of downtime, leading to the next metric.
Business Value Lost in Downtime
Your bots' unavailability causes business value to be lost in downtime, which leaves money on the table and does not maximize returns.
It demonstrates the harm your Break-Fix Cycles are causing to your RPA program and the reasons you might not receive the returns you promised to your executive sponsors.
For this metric, the annual expected business value must be subtracted from the quantified downtime.
Are you curious to know more? View our webinar on demand and distribute it among your team members. During this webinar, we demonstrate:
- The most often tracked RPA metrics and the reasons behind their inability to offer the clarity and depth required to assess the state of your bot ecosystem
- The five KPIs that are important but little-known that you should start monitoring to get the most out of your cognitive automation anywhere.
- How to watch and assess these critical RPA metrics to observe long-term improvements
Conclusion
To effectively argue for business process automation, RPA performance metrics are crucial. It provides an open, measurable illustration of its financial and operational effects on the company.
One of the most important aspects of evaluating the success of your (RPA) deployment is performance measurement. One excellent way to make sure your project is on track and continuing to produce a successful solution is to identify and develop key performance indicators (KPIs).
