IPsoft the company is an Artificial Intelligence specialist known for its enterprise-scale autonomic and cognitive software.
TechTarget defines Robotic Process Automation (RPA) is the use of software with Artificial Intelligence and Machine Learning capabilities to handle high-volume, repeatable tasks that previously required humans to perform — these tasks can include queries, calculations and maintenance of records and transactions.
Michael writes as follows…
Even the most basic RPA tools enable businesses to transfer many of the repetitive and mundane tasks that employees perform each day to software, freeing them up to handle more important and complex tasks.
But while RPA has been sold as a solution for every manual process out there, it only really excels in some of them.
In situations where rapidity is crucial and systems access and knowledge are slim, RPA shines – but scaling past this point has been a real challenge. Many RPA tools just aren’t capable of reading unstructured data, for example, or they require constant human oversight to fix any data entry mistakes. So, you’re returning many of those ‘saved’ workforce hours back to different basic and mundane processes. In problem solving terms, RPA is just a faster horse, rather than something representing true transformation.
Instead, we must view RPA as part of a solution.
If RPA is good at some automation approaches but bad at others, API automation and cognitive AI represent the other parts of the solution.
The dark (IT) side of RPA
Using RPA in a less siloed approach is not limited to its technological implementation, but also in its application. One of the more common issues we see is that singular RPA projects are not aligned with IT.
By and large, RPA represents dark IT – automation projects done piecemeal without being fully integrated into the IT strategy, which not only represents a risk, but means the wider problem won’t ever be solved.
By taking an integrated approach, businesses can use software for what its best at whilst still achieving the quick time to value and ease of use that RPA provides. It’s in this way that businesses can work towards a scaled vision that API automation & cognitive AI represent. If these elements can be made to work together, businesses can have an achievable automation goal that solves the scale problem, includes the IT team, and offers an opportunity for true enterprise change.
One large enterprise used this approach to radically transform their offboarding process, for example. The company typically offboards 200 workers each month, each of whom needs to be restricted from accessing applications immediately upon leaving the company. With employees having credentials for around 12 different applications, each offboarding procedure previously took 15 hours – which was a massive overhead for IT support staff every month.
Using a combination of RPA, an end-to-end autonomic backbone and a cognitive AI interface, staff were able to automate offboarding requests.
Integrating the RPA solutions with the existing IT systems and different subscription software was critical to achieving this and the impact has been monumental. The automated process is now virtually instantaneous. Indeed, the 81% reduction in Mean Time to Resolution (MTTR) has significantly improved both the experience of the HR and IT staff that previously implemented these mundane, repetitive requests and reduced the security risks involved with employees leaving the business.
While many businesses understand the immense opportunity that automation holds, in part driving the rapid adoption of RPA, what few understand is that it is just one part of the solution.
The aim should, instead, be to create an integrated digital automation platform incorporating API automation, cognitive AI & RPA. Breaking down the siloed approach to deploying this technology will in turn enable organisations to deliver a single integrated approach that covers the whole business.