When heading to a destination, we don’t just jump into a vehicle, hit the gas and cross our fingers for the best. Ideally, we bring out the map, set a route and get all the snacks and music in order to make it a journey worth remembering. So why should reaching your business goals be any different?
Some companies are eager to dive headfirst into solutions like robotic process automation (RPA) without sparing a moment’s thought about where they’re going or how to best get there. Success demands a game plan, a steady pace and a healthy splash of motivation. The fix? Using process mining technology with your RPA.
What is RPA in Process Mining?
Before we jump into all the details, let’s establish some foundations:
Process mining tools help you discover and extract data from your systems to monitor, understand and improve real processes. It uses event log data like a trail of breadcrumbs to uncover how specific processes are executed and compares them to how they should run. These insights allow you to spot the process flow of activities, deviations and variations. Read our full guide on process mining for more information.
Robotic process automation
RPA, or robotic process automation, uses software robots (also known as ‘digital workers’ or ‘RPA bots’) to automate low-value repetitive jobs that are usually performed by a human worker. You provide them with step-by-step, rule-based instructions, and they mimic actions and perform tasks.
Before undertaking RPA, many companies are turning to process mining technology to help them plan their next steps.
How do you use RPA and process mining together?
You can say that process mining and RPA are like a well-mapped route and a trusty car for driving. They are the perfect pair when implementing transformative intelligent automation (IA) in your organization.
Intelligent automation (IA) combines cognitive technologies that can streamline and optimize business processes and decision-making. It includes RPA, artificial intelligence (AI), machine learning (ML), natural language processing (NLP) and other advanced technologies to increase productivity and scale success.
Just as a GPS needs to know your set destination and preferred routes, RPA can only really get going with a good stock of processes that are ready to automate. How do you know which processes are the ones? Process mining helps you get insights and highlight opportunities that are the perfect candidates for RPA.
How are RPA and Process Mining Different?
RPA and process mining work to serve different purposes and goals.
Process mining is about analyzing and visualizing existing processes based on your data. It lets you know just how your processes are actually happening, revealing everything from bottlenecks to opportunities for more informed decision-making.
The next step would be implementing those opportunities through RPA. RPA aims to automate manual tasks and replicate human actions to reduce human intervention within digital systems.
Why Do You Need Process Mining in Your RPA Strategy?
Implementing process mining in your RPA strategy is like having a seasoned navigator on your road trip. Here are a few convincing reasons why you need it:
- Creates a route: Process mining helps chart the best route by identifying automation opportunities through process mapping. Instead of blindly creating an RPA strategy, you can pinpoint exact areas for improvement.
- Ensures a smooth journey: Process mining optimizes your journey as it pre-highlights the bottlenecks and inefficiencies in your process. This ensures your RPA strategy doesn’t replicate existing errors but enhances your workflow for smoother operations.
- Minimizes stops: As process mining identifies your automation priorities, you can avoid unnecessary distractions. You’re also able to identify and address any process issues prior to automation for the best business outcomes.
- Provides data-driven insights: For an informed RPA strategy, process mining provides quantifiable and accurate insights for you to make informed decisions. This data is also valuable for demonstrating return on investment (ROI) and getting senior leadership buy-in.
- Continuous improvement: Process mining isn’t just a static map; it provides ongoing visibility into your process performance. You can adjust your RPA strategy accordingly and successfully steer towards success.
How Process Mining Improves RPA
If you’re not convinced about why you need process mining in your RPA strategy. Here are a few more benefits about how it can ultimately improve your RPA:
- Quality assurance
- Cost reduction
- Scalability and adaptability
- Boosted innovation
- Enhanced employee experience
- Improved customer experience
Get full details about the benefits here.
RPA and process mining examples
Healthcare data has a significant digital footprint. Records include information about patient health, appointment systems, booking systems, payment schemes and monitoring and follow-up information.
In this intricate web of data, process mining paints a clearer picture of how these elements work and interconnect, revealing potential inefficiencies, siloes, bottlenecks and opportunities for improvement through RPA. For example, process mining can pinpoint appointment booking (often involving manual input) as an automation candidate.
Learn more about process mining in healthcare.
Through process mining, financial services can get greater visibility into their many processes. It can help leaders better understand activities in transactions, customer interactions, customer pain points, risk assessment and compliance.
By using process mining to compare against best practices, it makes it easier to see which processes need optimizing so decision-makers can make critical choices faster and more accurately. Consider transactions: process mining can help identify this area for RPA improvement due to its heavy manual intervention that hinders efficient working.
Learn more about process mining in financial services.
Navigating the insurance industry involves addressing several intricacies in claims processing, data entry, validation, approvals and communication. The interconnectedness of these steps is key for the insurance industry to deliver efficient services.
Insurers can use process mining to see how well business processes are running in their operations. They can look at how their people and systems manage real workloads and understand how they can improve through RPA. For example, you can figure out how many processes are involved in claims management and whether they're manually done. Then identify if they can be fully automated.
Learn more about process mining in insurance.
Manufacturers are embracing digital transformation to address ever-evolving environmental, social and governance (ESG) challenges. Adopting IA and RPA forms part of this change, and many have already begun with process mining to get visibility in their operations to see where these changes can have the most positive impact.
For example, process mining can help spotlight the assembly process in a car manufacturing plant. It can highlight where the delays occur so manufacturers can optimize their workflows and judge whether RPA can enhance efficiency.
Learn more about process mining in manufacturing.
It doesn't just stop there. Process mining can continue to benefit your processes by monitoring and measuring your newly automated processes. It helps you assess the impacts and ensures you're not missing out on any other opportunities to better integrate, train and maximize the efficiency of both digital and human workers.
Elevating Your Strategy With Process Intelligence
Building an intelligent business means increasing capability and clarity. Adding process mining to RPA planning can lay the groundwork, but how businesses truly flourish is through Process Intelligence.
From start to finish, SS&C |Blue Prismâ Process Intelligence Powered by ABBYY Timeline builds more functionality. In addition to process mining, it also deeply integrates task mining with intelligent automation and business process management (BPM) to facilitate decision-making and deliver a unified workforce.
Process Intelligence for RPA and IA
Process Intelligence is a numerical deep-dive analysis of all types of processes and tasks, no matter how many data sources are involved or how complex a process may be. Unlike other tools, Process intelligence can monitor in real-time, making it extremely valuable for the sustained success of RPA. Other benefits of using Process Intelligence for RPA include:
- Valuable insights into where automation can deliver the best outcomes.
- Full visibility to processes in different dimensions.
- Reduces the time for process discovery to accelerate automation initiatives.
- Identifies opportunities for continuous optimization in a single view.
- A straightforward way to define and track process rules that align with governance.
Now you can achieve end-to-end intelligence, not just of your processes, but every detail, to continuously optimize your automations, predict business performance and respond to changing business conditions.