This post covers the same ground as the link in the papers section of the site, but I think it is worth dropping into a post as well.

Robotic Process Automation brings together classic Business Process Management (BPM) approaches, and macro or scripted automation, with a simpler approach to the automation development. In simple terms, RPA is about making the automation accessible without deep development-based integration.

RPA allows the replacement of repeatable human functions with automation, reducing both costs and time with the assumption that the process is clear, repeatable and well documented or articulated. In addition to simple replacement of human keyboard time, RPA facilitates bringing disparate systems together with minimal direct IT investment, or rigid development. This just touches on the capabilities made accessible by RPA, as it really becomes exponentially more valuable when paired with more advanced technologies such as NLP (Natural Language Processing) on the inbound size, ML (Machine Learning) and advanced analysis / rules engines on the processing side and NLG (Natural Language Generation) on the output side to mimic human to human interaction where that is needed. Think personalization without the cost of the person in the middle!

I drafted the included paper as a short reference on the lessons learned in an early implementation I was a part of, and these lessons continue to hold true as I dive deeper into this topic. I would welcome thoughts on the ideas outlined in the included paper.

Robotic Process Automation brings together classic Business Process Management (BPM) approaches, and macro or scripted automation, with a simpler approach to the automation development. In simple terms, RPA is about making the automation accessible without deep development-based integration.

RPA allows the replacement of repeatable human functions with automation, reducing both costs and time with the assumption that the process is clear, repeatable and well documented or articulated. In addition to simple replacement of human keyboard time, RPA facilitates bringing disparate systems together with minimal direct IT investment, or rigid development. This just touches on the capabilities made accessible by RPA, as it really becomes exponentially more valuable when paired with more advanced technologies such as NLP (Natural Language Processing) on the inbound size, ML (Machine Learning) and advanced analysis / rules engines on the processing side and NLG (Natural Language Generation) on the output side to mimic human to human interaction where that is needed. Think personalization without the cost of the person in the middle!

I drafted the included paper as a short reference on the lessons learned in an early implementation I was a part of, and these lessons continue to hold true as I dive deeper into this topic. I would welcome thoughts on the ideas outlined in the included paper. View the paper here.