Robotic Process Automation matured into a mature technology capability around 2012 to 2014, though easy-to-use automation tools, especially screen-scraping versions, existed 10 and 20 years prior. In the early part of this decade, RPA tools truly matured into an alternative to traditional IT and software programming. RPA has been a rapidly growing technology in the past 5 years, and the forecasts are for even more rapid growth over the next 5 years. RPAs are the use of software ‘robots’ to do repetitive tasks that a human typically does when interfacing with a software application. A good example is where incoming mail that previously was sorted by a person for the right specialist to answer is handled by a robot that analyzes the email and looking at key words and phrases, then sorts the email or responds directly. Another example is to assist a financial advisor where previously they would have to cut and paste (or re-enter) data from one system to others to complete process steps that can now be accomplished automatically by a robot (or if desired, the robot is triggered by the advisor and the work is then completed) thus freeing up advisor time from repetitive typing tasks. This is particularly valuable for example when sitting with a customer and taking a request for a new service or product. At Danske Bank, since our initial implementation in 2014 (yes, 2014), we have implemented over 300 robots leveraging the Blue Prism toolset (which is now owned by IBM). Each robot that was built was typically completed in a 2 to 6 week cycle where the automation suggestion was initially analyzed, reviewed for business return, and prioritized. Once a robotic team freed up to work on the next suggestion, the idea was then jointly analyzed and built and delivered into production (in two to six weeks). The robot could save anywhere from a third of an FTE to 30 FTEs or even more. And the automation typically increased quality (no typos) and improved cycle time as well.
One could consider RPAs almost as a ‘poor man’s API’, especially where the robots copy data from one system and then deliver it into another system which is the next step in the process. Of course, if it had been properly architected originally, this robot would not be required and it instead would have been handled by direct application to application communications. Further, many processes were previously automated by building systems to handle the steps of a process in a certain department, with a human handoff still existing between the departments. By using RPAs, organizations can quickly automate the handoffs, overcome the lack of APIs in legacy systems, and reap the cycle time and efficiency benefits. Later, when the applications are updated, many of these robots will not be needed, but they serve a good purpose until then.
One can view RPA and Business Process Management (BPM) or workflow/case handling tools in the following diagram which includes traditional 3rd Generation Language solutions (3GL) as well as new artificial intelligence tools:
One can expect these toolsets to advance further in the coming years as there is tremendous investment in this space both from enterprises leveraging the technologies and suppliers increasing their capability. Both integration among toolsets and better interfaces back to traditional applications and common software (Outlook, SAP, etc) are occurring as shown below:
For additional information on RPAs:
- best RPAs on the market, though I would recommend Blue Prism
- further definition of RPA