Intelligent process automation is evolving with transparency and an end-to-end view of processes at its core as enterprises mix and match technologies. Here’s a look at intelligent process automation and where Process Mining fits.
Intelligent Process Automation refers to the use of advanced technologies such as Process Mining, artificial intelligence, machine learning and robotic process automation to automate complex business processes end-to-end.
With intelligent automation, companies can not only automate repetitive tasks and provide analytics but provide decision-making capabilities efficiently. By automating routine tasks and workflow with real-time insights, intelligent process automation can improve productivity, reduce errors, optimize resources and drive business outcomes.
Intelligent digital process automation starts with the process at the core of the technology stack. For instance, automation by itself is not an end goal. Automating inefficient processes and tasks only increases the speed of inefficiency.
Process Mining allows enterprises to understand the challenges and resolve them before automating and scaling other technologies such as robotic process automation (RPA).
While traditional enterprise automation focuses on automating repetitive and rule-based tasks, intelligent automation adds a layer of intelligence that enables better execution for complex business processes. This layer of intelligence is often augmented with various technologies including machine learning, artificial intelligence and robotic process automation.
Celonis CIO Jon Dack said CIOs and their organizations are among the few across a company that can see and understand a full process. "In any particular part of the organization, people don't truly understand the full process," said Dack. "They understand they're part of a process, but there are a lot of dependencies across the organization.”
With a more holistic view of automation, enterprises can deploy platforms such as Celonis Execution Management System (EMS), which connects multiple applications with pre-built, process specific connectors. This intelligent process automation approach allows companies to focus on business outcomes such as working capital, customer satisfaction and sustainability over automation KPIs such as labor productivity and automation rates.
Transparency via Process Mining sits at the core of intelligent business process automation. Without a complete view of processes, data and systems, it's difficult to optimize processes and automate them. Intelligent process automation shouldn't be confined to one system or technology.
Process Mining works by extracting knowledge from event logs readily available in today’s information systems, in order to visualize business processes — and their every variation — as they run. With data-driven insights, enterprises will have a better view of what to automate with Celonis EMS.
Here are a few ways how Process Mining helps improve digital process automation:
Process Mining can help organizations identify business processes that are suitable for automation.
Process Mining can be used to optimize automated processes as well as the intersection with manual tasks. By analyzing process data and identifying inefficiencies, organizations can improve the performance of their automated processes and eliminate bottlenecks and inefficiencies.
Process Mining can monitor and maintain automated processes. By continuously analyzing process data, enterprises can ensure automated processes are functioning well and improving productivity.
Object Centric Process Mining (OCPM), which is a novel approach to Process Mining that overcomes the limitations of traditional techniques and allows organizations to better visualize and analyze the complexity and interconnectedness of modern business operations, will play a role in the intelligent process automation stack. Celonis was the first technology provider to fully embrace object-centric Process Mining with the release of Process Sphere™, a capability of Celonis EMS unveiled at Celosphere 2022.
OCPM can give enterprises a holistic view of processes to discover opportunities for automation, find issues and fix them.
Intelligent Process Automation can be used in a wide range of industries and applications. Specific processes include Accounts Receivable, Accounts Payable, Procurement, Supply Chain and customer experience to name a few.
Today, intelligent process automation is being driven by departments such as Finance and Accounting, IT and supply chain, but other functions are also providing use cases.
What steps are required for intelligent process automation?
There are multiple steps to deploy intelligent process automation and every company will have its unique approach. That said, there are some common steps to consider:
Identify business processes: Identify the business processes that are suitable for automation. Look for tasks that bog down processes and are repetitive, time-consuming or error-prone.
Map the processes: Once the processes have been identified, they need to be mapped out in detail. This involves creating a visual representation of the process end-to-end ideally with interdependencies. Object-centric Process Mining can provide this end-to-end visibility.
Define automation goals: Determine what business goals such as reducing costs, improving operational efficiency or increasing accuracy you’re trying to achieve with automation.
Identify the automation technology, including machine learning and artificial intelligence, needed to improve the business process.
Look for quick wins and scale: Automate processes that will provide the most business value and then scale across the organization.
Intelligent process automation has a wide range of use cases across industries and functions. Here are a few:
Finance and accounting: Intelligent process automation can be used for everything from financial reporting to invoice processing and accounts payable processes. Seventy-nine percent of CFOs said their companies plan to embed more automation and digital transformation into operations as they manage through higher costs and concerns about the economy, according to a survey from Deloitte.
IT: Companies can leverage intelligent process automation for systems transformation as well as manage IT processes.
Customer service: Intelligent process automation can be used to automate customer service processes such as responding to customer inquiries, routing calls and collecting feedback.
Supply chain management: Companies can automate supply chain processes such as order processing, inventory management and shipment tracking as well as improve logistics processes.
Human resources: Intelligent process automation can be used to automate repetitive HR tasks such as employee onboarding, performance evaluations, and benefits administration.