While it is true that the concept of operational efficiency was previously associated with doing things faster, at a lower cost and with fewer mistakes, this is no longer the only thing that matters. For today’s successful companies, operational efficiency is now about how the work is accomplished – end to end, as opposed to simply speeding up individual steps or tasks.
Unlike traditional automation which does exactly what is instructed and follows the “playbook,” Intelligent Automation combines automated technology with the ability to make decisions based on a variety of factors including data interpretation and determining when an action should be taken – all with little to no human involvement. While this will continue to drive productivity, it also provides other benefits such as shorter cycle times, increased compliance and an enhanced customer experience as well as free time for team members to perform tasks of greater value.
What Is Intelligent Automation?
Intelligent Automation is defined as the use of technologies that provide automation of tasks, but also allow for the automation of variability and decision making logic in the course of completing those tasks. It is commonly achieved through the combination of several types of technologies including:
- robotic process automation (RPA) to perform repetitive, rules-based tasks
- the application of artificial intelligence (AI) and machine learning to identify patterns and predict future outcomes
- workflow orchestration to tie together multiple tasks and/or departments and/or systems
- document intelligence to obtain data from emails, invoices, forms and/or pdf files
- analytics and performance monitoring to measure and evaluate performance of automated workflows and continually improve them
Unlike traditional automation, Intelligent Automation does not only follow the playbook; instead, it deals with the complexities of real world situations (e.g., unstructured data, exceptions, variable conditions).
1. Acceleration of Cycle Time Across Key Processes
Cycle time is typically a function of the amount of time that work takes to move from one process step to the next. In addition to accelerating cycle time, Intelligent Automation can also accelerate the movement of work through a given process by automating tasks that are required in each subsequent process step, prefiling data, validating input data, and triggering downstream actions to accelerate the process.
Examples of this include:
- approval and payment of invoices in purchase-to-pay and procurement processes
- workflows in the order-to-cash process that generate bills and trigger payments
- onboarding new employees, vendors and/or customers
- processing claims and managing cases
Improved cycle times, in turn, typically lead to improved cash flow, reduced escalation levels, and higher customer satisfaction.
2. Reduced Errors and Rework
Manual work is inherently less consistent than automated work. Even the most diligent and effective teams are subject to error when there is a reliance on manual copying and pasting, manual spreadsheet tracking, and repeated data entry. Intelligent Automation provides consistency by enforcing rules, validating field entries, flagging potential anomalies, and creating standardized output documents.
As a result of this consistency, organizations that implement Intelligent Automation tend to experience:
- reduced costs related to correcting errors
- reduced instances of compliance failures
- reduced customer-facing errors
- reduced time spent performing quality checks
Ultimately, the reduction in errors results in less rework, and less rework represents one of the most direct ways to achieve efficiency.
3. Improved Exception Handling (Not Just the “Happy Path”)
Most automation efforts fall short because they only address the “happy path” of process execution and ignore the exceptions that inevitably arise in all real-world processes (e.g., missing data, unusual transactions, conflicting policies, duplicate records, edge cases).
Intelligent Automation improves exception handling by:
- early identification of potential anomalies
- routing the issue to the appropriate party with relevant context
- providing suggestions for the next best action
- continually learning from resolution activity
As a result, Intelligent Automation enables the uninterrupted movement of workflows, eliminating the need for teams to manually restart the workflow after encountering an exception.
4. Improved Visibility and Control Over Processes
Operational efficiency cannot be improved if the organization cannot see where the work is getting stuck. Many Intelligent Automation platforms provide performance monitoring tools (dashboards, audit logs, performance analytics), enabling leaders to ask critical questions regarding their business processes such as:
where are the greatest delays occurring in my process?
- what steps are causing the most rework?
- how long are approvals really taking?
- where are compliance exceptions arising?
By providing clarity around their processes, organizations can optimize their processes continuously as opposed to periodically.
5. Continuously Measure and Improve Performance
Establish metrics to define success (e.g., cycle time, cost per transaction, error rate, rework rate, customer satisfaction). Regularly review performance and view automation as a living system.
Common Mistakes to Avoid When Implementing Intelligent Automation
automating broken processes that have not been redesigned
- only focusing on cost reductions and ignoring the customer experience implications
- underestimating data quality and integration issues
- not planning for change management and training for teams
- not planning for exceptions and human interactions
Conclusion
Intelligent automation is transforming the way we think about operational efficiency by focusing on workflow improvement from start to finish versus improving individual tasks. It can accelerate cycle times, reduce errors, improve visibility and allow teams to focus on more valuable activities. Organizations that treat intelligent automation as a strategic capability (versus a single project) are much more likely to realize sustainable efficiency improvements.