Digital disruption is being embraced by businesses the world over. Chief among the core facets of this growing trend is RPA technology. With the ability to have a significant, quantifiable effect when planning and executing automation projects using best practices that help to clearly identify automation-friendly processes, RPA has much potential.

However, when you consider the additional impacts, such as helping businesses to clearly set ROI expectations, provide agile service delivery, or see the realized benefits of an improved customer journey, RPA becomes a very valuable asset.

In a nutshell, RPA offers the promise of an enhanced service, increased process accuracy, and sublime cost efficiencies. This is obviously the reason businesses have flocked to adopt the technology in droves.

The Manual Approach to End-to-End Process Execution

Businesses that adopt a manual approach to end-to-end process execution invest substantial amounts of time and money without reaping comprehensive rewards. The software utilized will generate immense amounts of process-related data. Only through analyzing and actioning that data can insights be uncovered. This is a very cumbersome process.

Why? When multiple systems execute different aspects of any process, it’s virtually impossible to recreate a single, usable perspective of how processes using old approaches operate. Not only that, analytics tools used to generate key metrics deliver just snapshots in time, rather than viewing how the overarching process works.

The only way to circumvent these drawbacks is to employ intelligent process mining. Cost-effective and easy to complete, intelligent process mining reconstructs RPA technology data as an interactive model that reflects the whole process execution interactive model.

Adding Value to RPA with Process Intelligence

RPA AI bots are increasingly being considered in processes with unstructured data, more complex environments which with manual intervention, or where a degree of cognitive reasoning is needed. This clearly demonstrates the value of RPA technology. As our digital processes become increasingly complex and sophisticated, deployment costs are increased. This means that businesses need to consider the potential value of initiating RPA.

However, the potential for intelligent data mining to be improved by employing RPA AI cannot be ignored. Accessing intelligent process intelligence is vital for both a physical workforce and a digital one as it allows businesses to:

  • Identify robotic process automation opportunities that can optimize digital workforce cycles, further increasing digital productivity
  • Locate and expose inefficiencies in the digital-human hand-offs or the human-digital hand-offs
  • Provide quantifiable data on the financial cost of a digital workforce by processes
  • Compare human and digital workforces by cost, accuracy, efficiency, and duration

The data gleaned by process intelligence is intrinsic to helping businesses optimize workflow processes and provide a better service to their clients.

Moreover, a process intelligence platform can complete a risk and compliance framework for your robotic operating model that monitors and assesses the automated process performance regularly. This will help to:

  • Establish a data-driven foundation for process governance, clearly documenting and automating the steps for process mitigation
  • Create an RPA center of excellence that captures, and exports processes using RPA technology or ranks processes based on their perceived value using multiple data touch points
  • Expand the scope of RPA by identifying process exceptions and launching automatic remedial action
  • Perform broader lifecycle management of both digital and human processes and their interactions

What’s clear is that to optimize RPA AI model within your workplace, process intelligence platforms are required.

Targeting the Right RPA Opportunities

Intelligent process mining is employed by a wealth of industries to automatically model and present workflow processes, exposing the inner workings of a single or multiple process structure in real-time using data-driven matrices. This is a staple of intelligent process mining.

The success that intelligent process mining is most aptly summarized in its ability to be a solution to these five RPA AI challenges, improving scalable sustainability whilst targeting processes with the greatest automation potential.

A single, end-to-end and comprehensive view of process execution that spans multiple business applications to uncover prime automation opportunities and potential side effects

  • Easily identify high-value automation candidates based on actual process execution data that displays cost implications, time taken and process variations
  • Provides a quantifiable, data-driven ROI calculations based on different variables, including number of transactions, number of process steps, and cost per transaction
  • Eliminates costly, arduous and error-prone process evaluation
  • Delivers 100% process visibility and helps identify high-risk and costly challenges

A process intelligence platform will help to improve every aspect of RPA technology process, regardless of system data. Businesses can gain actionable insights, more accurate, faster and cheaper automation results.

Intelligent process automation gives businesses the confidence of making data-driven decisions quicker and cheaper, having a sustainable impact on every aspect of your service delivery.


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