Updated: Mar 29
Automation is good for business. Teams are freed from mundane, repetitive, rules-based tasks, and can spend time on more value-added activities. The thing is, automating tasks in isolation is just the tip of the iceberg.
The Structured World
We deliver RPA systems that can respond to triggers, use OCR technology to read images or hand-writing and process data to present analysis. We also work towards developing an attitudinal shift in the workforce where automation is embraced as a means to drive the business forward. Our “automate in 28” service will solve such problems and we’re so confident that you will make use of our bots that we offer “free for 3” pricing.
Most data is unstructured
However, that isn’t where the story of automation ends. For example, many organisations dedicate much of their workflow to document processing and data extraction. In such cases, the output could be unstructured, and it is here that a more intelligent approach is required.
Reliable data is critical in decision making, whether it be mortgage approvals, new client on-boarding or providing support through automated, natural language chat-bots. In such circumstances, RPA is not suitable as it simply replicates existing processes by reproducing human behaviour. Yes, RPA provides efficiency gains, but it isn’t intelligent.
Intelligent automation takes automation techniques and adds artificial intelligence and machine learning to streamline complex processes. The system continues to learn and improve outcomes every time it is operated leading to improved process efficiency and more nimble operational performance.
The future is intelligent
Unattended intelligent bots can fully automate business processes without the need for human intervention. This is the next stage in the evolution of automation, and it is happening now.
Consider the example of an accountancy practice. On-boarding a new client can be completely automated with the customer starting the journey with a chatbot. The chatbot sends the client the correct forms and ensures that anti-money laundering checks are properly conducted. The bot then ensures that all systems, from filing deadlines, invoicing through to tax production are all updated and ready. Where exceptions occur, such as when a client uses a nickname such as Nick instead of Nicholas, the system can pass the query to a human operator and learn from their actions.
As this very simple example illustrates, intelligent automation can create greater efficiency which allows employees to focus on relationship-building, getting to know the client and helping them to achieve their goals, instead of processing data.
RPA is great for gaining efficiencies by automating repetitive, rules, based tasks. It is often the first step towards digital transformation.
Intelligent automation automates workflows with unstructured data using AI and machine learning. It can handle complex tasks and learns over time. It is the next stage in the evolution of automation.
Please note, intelligent automation is often referred to as Intelligent Process Automation (IPA), hyperautomation and digital process automation.