While companies have traditionally operated under the assumption that it makes sense to improve processes before automating them, the advent of robotic process automation (RPA) technology may be turning that conventional wisdom on its head.
RPA, or software “robots,” use business rules logic to automate repetitive, time-consuming tasks previously conducted by people. The technology reduces cost and enhances speed, accuracy, availability and auditability, and is being applied to tasks such as data entry, claims processing and access management in industries as diverse as insurance, retail and financial services. It’s relatively quick to implement – RPA systems can be deployed in a matter of weeks. They also can, cost as little as $10,000 a year to implement and maintain, and replace three to 10 human administrators. Considering, moreover, that robots can work 24/7 without vacation and sick days, the efficiency gains are significant.
Since the cost and effort to implement RPA is relatively low, and the efficiencies are immediate and significant, the traditional order of optimizing processes prior to automating is becoming less relevant. While automating broken processes is never a good idea, spending too much time over-thinking a working process up front can be counter-productive, given the quick results RPA can deliver.
Moreover, data analysis and incremental process improvement can always be applied after deploying an RPA solution. By alleviating immediate “symptoms” and reducing customer pain points, businesses can lay the groundwork for end-to-end process redesign and implement a smoother long-term transformation to a digital operating model that delivers even greater ROI and business value.
One reason RPA systems are so easy to implement is because they don’t require much coding and instead are taught specific, repeatable tasks. While traditional automation software interacts with other applications on multiple levels, RPA is implemented at the user interface level, requiring minimal IT involvement. The technology is also more configurable, and systems can be can easily be updated and modified, which is critical in industries with continually changing regulations and requirements.
RPA best practices
So how can businesses determine an effective process optimization and automation approach for their organizations? Here are some best practices:
- Collaborate early and often. Engagement between IT and business stakeholders provides insight into current and future business requirements and helps determine the types of technology solutions and deployment strategies that will best support business requirements.
- Identify the processes that can be automated through RPA. Look for routine, repeatable and rules-based processes where automation can drive efficiency gains. RPA systems will need to offload exceptions to rules-based operations to human operators. In addition, by providing immediate efficiency and accuracy results, RPA can avoid or postpone the need to engage in expensive and time-consuming re-engineering projects.
- Work closely with human workers to collect key information about how the task is typically completed so it can be “taught” to the software robots.
- Be prepared to redeploy and potentially retrain workers in the new environment. In many cases, RPA will allow people to spend more time using their existing skills and experience, thereby adding value to the business. In other instances, acquisition of new skills may be needed.
- Analyze data to improve. RPA tools provide clean and accurate data that can be applied to drive higher rates of automation. By assessing operations to identify root causes of exceptions, businesses can in many cases eliminate those causes to enhance efficiency. Analysis is also essential to keeping up with changing business environments. As systems change and industry regulations evolve, RPA systems must adapt to new requirements.
Rod Dunlap is a director at Alsbridge, a global sourcing advisory and consulting firm.