Detecting your resiliency tipping point
Selecting which tasks to automate with AI based on procedure content alone may put a company at risk for reduced operational resiliency.
In a previous role, I supervised a loan servicing team that performed work using a library of mature standard operating procedures (SOPs). Each SOP provided step-by-step guidance for performing a task. More than fifty SOPs were required for my team alone. And each procedure was:
documented in a standard format
updated regularly
saved in a library on a shared drive
At first glance, it might seem these step-by-step SOPs would be candidates for AI automation.
But SOPs tell only part of the task-execution story. Human adaptive contributions, such as handling never-before-encountered system errors, must also be considered.
For instance, the people on my team regularly contributed the following adaptive value to tasks:
Handled exceptions, variability, and judgment calls
Made sense of unclear or shifting conditions
Used learned platform knowledge to problem solve
Fixed gaps between the SOP and real needs
Shared solutions and improvements
Coordinated with other teams and workflows
The more complex the task, the more often adaptive value was required. And without these human contributions, the company’s resiliency would have suffered.
Detecting your resiliency tipping point
A business is a Complex Adaptive System. Unpredictability is inherent in its operation, so it may be near-impossible to detect a resiliency tipping point. Even so, a deliberate assessment of human adaptive value will highlight where it contributes to a company’s resiliency.
A simple scoring method, such as the one shown below, could be used as a starting point. More robust and fine-tuned scoring could be developed over time. The important thing is to unearth this essential operations component before making AI automation decisions.
SAMPLE ADAPTIVE VALUE SCORING METHOD FOR TASKS
Adaptive Value Scoring Method - Sample
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This article was conceived, written, and edited by a human!