Intelligent process automation (IPA) refers to a collection of technologies meant to manage, optimize, and integrate digital processes. These days, it’s considered the tip of the spear for enterprise digital transformation, and it’s responsible for a wide variety of technological advancements from application integrations that improve the customer experience to autonomous cars.
Of course, automation in the workplace is nothing new. It’s been going on since the First Industrial Revolution, and thanks to bots and modern IoT devices, we’re currently in the midst of Industry 4.0, which looks set to improve intelligent automation to extents once believed to be science fiction. Benefits of intelligent process automation include freeing employees from repetitive tasks, agility in changing processes, better risk management, and much more.
If you’ve ever interacted with a bot on a company website and received all the information you needed without actually interacting with a human agent, then you’ve witnessed IPA at work. Here are the major components of intelligent process automation that make it all possible.
Digital Process Automation
Businesses these days deal with much larger volumes of data than they did in years past, and this rise of big data thanks to the widespread adoption of mobile devices and smart digital assistants has created the need to handle digital processes automatically.
This resulted in the use of event driven architecture (EDA) for business process management. Instead of using the legacy request/response architecture, which required computer systems to take breaks during each part of an event stream, digital process automation has given applications the ability to handle multiple complex events at once and without waiting for a response from separate functions.
DPA also resulted in the integration of once disparate data sources, which makes it easier for organizations to leverage all their data properly. When data sources can share information, it’s easier to analyze available data and detect patterns and trends. This ability makes it easier to detect inefficiencies in the workflow and improve business processes. It even lets businesses make more accurate predictions about future market activity, thanks to a combination of historical and current data trends.
Robotic Process Automation
RPA is the component that most people are likely to be familiar with. Everyone knows about the implementation of robots on factory floors and in warehouses, for example. RPA is great for mundane tasks and tasks that have a high chance to result in injury for humans. Eliminating such risks boosts operational efficiency, and taking advantage of RPA also lets engineers focus more on activities that can help facilitate business growth.
Practically every modern advancement in artificial intelligence is made possible thanks to machine learning (ML). Machine learning involves training computer algorithms to perform desired tasks based on structured data sets, unstructured data, or some combination of the two. ML is capable of more than simple, repetitive tasks as well. Modern computer algorithms are able to understand and respond intelligently to human speech, thanks to natural language processing (NLP). This is how digital assistants are able to provide intelligent responses to requests and filter background noise to detect human voices.
NLP is also used with text, and it allows chatbots and other computer systems to determine the intent behind why certain words are used. AI is also able to easily detect intricate data patterns and analyze big data sets far faster than the human mind ever could. Best of all, machine learning algorithms make all of this possible with no requirement for human intervention.
Businesses can use intelligent process automation solutions to gain insights and improve efficiency in any field. The more intelligent your processes, the easier it is to create lasting business improvements.