For a processor (robot or human) productivity is best measured as a ratio of output:input. How much work did we get out for the amount of time we put in? For this to make sense we generally convert time into “capacity to do work” based on some idea of how much work could be done in a given time.
So if Person A completes 75 tasks in a day and they had capacity to complete 100 then their productivity was 75%. Similarly if Robot B completes 500 tasks in a day and had capacity to do 1,000 then their productivity would be 50%.
But why would Robot B only do 500 tasks? They wouldn’t dawdle because they didn’t like their boss. They wouldn’t spend hours on social media, and they would surely only be allocated tasks that they were 100% capable of processing. We wouldn’t give the robot a motivational pep talk, or offer it some incentive to “work harder” because the answer obviously lies in the system, not in the robot.
Maybe Robot B could only process 500 tasks because there were only 500 available to be done. Maybe the core system was running incredibly slowly that day, or there was so much network traffic that latency was affecting cycle times. Maybe someone changed a port on a firewall and the robot needed to be reset. Or there were hundreds of exceptions and the robot had to try them multiple times before rejecting them.