The logic behind hyperautomation is clear: Automate everything that can be automated. The practicalities of that are far less clear. Consider, for example, the surge of interest over the past couple of years in task and process mining tools, which ostensibly enable you to automate more tasks and processes. This surge has, inadvertently perhaps, exposed many more challenges and, indeed, roadblocks, to automation than folks thought. In a real sense, task and process mining vendors are biting the hand that feeds them. Using these tools to understand how to automate a specific business process often exposes much more profound issues to be resolved. Furthermore, these same tools can suggest wrong paths to follow.
Pay attention to nuance
To dive a little deeper here, we are starting to see tightly defined automation projects stall, when the true chaos of what lies beneath the surface is exposed. Processes and business activities that management thought were solved problems in need of a bit of tidying up can turn out to be convoluted human work-arounds with a labyrinthian number of alternative options to reach business closure. Similarly, using task and process mining tools to contrast ‘best practices’ is sometimes misused by enterprises under the impression that the fast route is the best route. For example, Worker A takes 20 steps and 4 hours to complete a task, whereas worker B takes 12 steps and ends the same task in 30 minutes. Often, worker B is designated the one to model and for everyone (bot or human) in the future to take this route. But common sense, which is not, in reality, all that common, tells us that worker B may well be cutting corners and potentially doing a poor and incomplete job.