What intelligent workload balancing means for RPA

The relatively new concept of intelligent workload balancing is an important one to consider when operating RPA, because it determines whether tasks are more suitable for human employees or their digital colleagues.

With this in mind, five industry experts identify particular ways in which this can be applied to this space.

Firstly, intelligent workload balancing can be used to check that bots can adhere to rules set up by the company.

“The ability to automatically decide if an activity requires human intervention or if it can be performed by a bot is usually called ‘intelligent workload balancing’,” said Sathya Srinivasan, vice-president, solutions consulting (Partners) at Appian. “The intelligence comes from the business rules that determine who is the best candidate to complete the work – human or bot. If human, which department, group, experience level or management is best to handle this case, and if bot, what does it take to bring a bot in, how flexible can a bot cater to different types of requests.

“To be truly effective, a bot must be able to work across a wide set of parameters. Let’s say, for example, a rule involves a bot to complete work for goods returned that are less than $100 in value, but during peak times when returns are high, the rules may dynamically change the threshold to a higher number. The bot should still be able to perform all the necessary steps for that amount of approval without having to be reconfigured every time.”

Gopal Ramasubramanian, senior director, intelligent automation & technology at Cognizant, added: “If there are 100,000 transactions that need to be performed and instead of manually assigning transactions to different robots, the intelligent workload balancing feature of the RPA platform will automatically distribute the 100,000 transactions across different robots and ensure transactions are completed as soon as possible.

“If a service level agreement (SLA) is tied to the completion of these transactions and the robots will not be able to meet the SLA, intelligent workload balancing can also commission additional robots on demand to distribute the workload and ensure any given task is completed on time.”

Neil Murphy, global vice-president at ABBYY, explained how process intelligence solutions can be incorporated in order to get a better of perspective of which areas need to be optimised.

“In RPA, repeating a high volume number of processes can be challenging if the processes are broken or not fully understood – as this leads to frequent human intervention,” said Murphy. “As such, there is definitely a case to apply intelligent workload balancing to RPA.

“This is why we have seen process intelligence solutions emerging. This helps businesses better identify which processes are best to optimise for RPA, and ensures they fully understand a process by detecting bottlenecks that might be causing errors or increasing lead times.