Sorting the myth from the magic when it comes to Robotic Process Automation
These days it can be hard to sort the myth from the magic and easy to get confused when it comes to Robotic Process Automation (RPA), and Machine Learning (ML).
A general rule of thumb is to understand that RPA systems ‘do’ things, while Machine Learning systems ‘think’ and ‘learn’. RPA is rules based and can easily work alongside other automated approaches such as Machine Learning and workflow
RPA isn’t the stuff of science fiction but is ‘the use of sophisticated computer software that automates rule-based processes without the need for constant human supervision’¹. It’s being hailed by many as the breakthrough platform for modern enterprises, so it would be easy to imagine that jumping on board this freight train will keep you ahead of the competition.
While RPA clearly has enormous potential, right now companies may come unstuck in the rush to implement this technology in their desire to lower costs and increase efficiency. That’s because they are investing in RPA driven by budget holder’s needs, without identifying economies of scale. Pockets of RPA knowledge grow through uncoordinated experimentation, and success can be largely invisible as process metrics are unmeasured.
End to end processes must be assessed
RPA is simple and quick to implement compared with other automation technologies. It can decrease per-transaction costs and reduce cycle times for specific types of business process – e.g. high-volume, highly rules-based processes (see our RPA readiness questionnaire for an example). But it needs to be part of a wider process of evaluation to identify inefficiencies and pain points. It should complement your existing technology infrastructure not be considered in isolation. Without this approach, the value of RPA will be quickly eroded.
With so much uncertainty, what’s the solution?
RPA promises a great deal but only if the right end to end business processes are in place will you gain the advantages of it, so using an Agile approach will reduce delivery risk and increases ROI.
Look for an organisation with the experience to perform the analysis, build the business case and manage the implementation in an agile way (from the perspective of technology, process and people). Agile methodology is designed to reduce risk and allow continuous improvements as ways of working are refined.
The next step? Talk to an expert
If RPA is on your radar, the next step is to talk to an expert in how to make it work appropriately for your organisation and see how to intelligently automate processes end-to-end with solutions that free you to focus on running your business. Clarasys holds free Proof of Concept (PoC) workshops and with early Proof of Concept, you have a fact-based foundation for the appraisal of future RPA business cases.
Get in touch with Philip Richardson to find out more.
¹Source: https://www.uipath.com/automate/robotic-process-automation
This post was originally written by:Philip Richardson
