Process automation tools automate manual and repetitive tasks inside a business process. But what distinguishes process automation tools, which may also be called business process automation (BPA) tools or hyperautomation tools, from other automation solutions is that they automate an entire business process, end to end. Some process automation examples can be found in banking customer onboarding processes and automated insurance underwriting.
Automating an end-to-end process is a thornier proposition than automating a discrete manual task or a handful of repetitive tasks—and it requires more than one automation technology. That’s why a modern platform for process automation brings together a wide variety of automation tools, including robotic process automation (RPA), intelligent document processing (IDP), workflow orchestration, artificial intelligence (AI), system integrations, and business rules. An important distinction here is that an RPA automation tool is just one part of a broader process automation approach.
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You can use an RPA bot to automate individual tasks within a process, replacing a person repeatedly clicking inside a software application. But many complex workflows demand more than robotic process automation can deliver on its own, such as content extraction from legacy documents. And RPA can’t orchestrate all the workflows involving people and automation within a complex business process like customer onboarding. This is why process automation proves crucial for so many companies doing digital transformation projects to improve time to market or customer experience.
How do you identify the right business process automation tools for your organization? Let’s explore some key questions to ask as you research and compare solutions.
Many organizations hit a point in their digital transformation and automation journeys where they’ve scored some automation wins in certain spots, eliminated some mundane tasks, then failed when they tried to scale the automation effort across the entire company.
Individual automation wins often disappoint both IT and business leaders. For example, these projects can saddle IT teams with high maintenance costs, integration and upgrade headaches, governance worries, and talent requirements for multiple automation vendors and tools. That’s a big consideration at a time when costs are under the microscope and governance and talent already present tremendous challenges for IT leaders.
Business leaders who want automated processes to enable speed and operational efficiency organization-wide will be disappointed when the speed stops at the department or team level. The ability to scale automation is one of the main reasons to consider a process automation platform.
Orchestration is a critical capability, yet it does not exist in all automation tools. Remember, your team doesn’t just need to automate tasks: It needs to orchestrate custom workflows, which will involve people, bots, and other automations. This is where orchestration technology earns its keep, connecting people, systems, bots, AI, business rules, and data in complete workflows.
Look for process orchestration technology that includes features like scheduling, error handling, routing, expression evaluations, and data transformation to help you build custom workflows.
Many IT and business leaders know the struggles associated with data silos all too well. Indeed, data silos can stop transformation and automation projects in their tracks. Process automation success will require the support of a strong data architecture.
Look for a process automation platform that gives people access to enterprise data throughout the automation process, regardless of where it lives, with well-defined structures and properly enforced security. The modern answer to this is a data fabric. A data fabric connects data sets across disparate software systems, whether they’re on-premises or in the cloud. Users interact with the fabric view; the data stays in its source systems. Data fabric centralizes data management for improved security and compliance as you scale automation, even for data silos associated with legacy systems.
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ChatGPT has only upped the hype level around AI tools. Sorting through that hype and the associated AI promises can be an arduous task. Focus on whether and how the tools actually break down or significantly reduce the barriers to AI adoption in your organization. Examine how well the specific AI tools align with your real-world use cases. AI-augmented tools can deliver powerful results for streamlining processes.
For example, AI-based intelligent document processing (IDP) can supercharge speed for companies that need to pull data from legacy documents. Many organizations can use IDP as they contend with large volumes of unstructured or semi-structured content, such as emails and documents, while working to automate a process.
[ How did commercial insurer CNA improve their underwriting processes and realize a 60% time savings? Get the case study. ]
All of these questions will help you identify a solution that is flexible enough to let you iterate on early wins and scale your automation success. A strong process automation platform should also empower your people to quickly adapt processes as business requirements and regulatory demands shift while staying compliant.
Stay practical about applying AI, tap into the power of data across the organization in new ways, and find tools that help you scale your automation efforts. Then your process automation work will pave the way for what CIOs and CEOs prize: innovation and competitive advantage.
Learn more about process automation strategies and tools. Get the Process Automation Guide.