Effective trending of human performance data

Abstract

In any labor-intensive industry there is a need to continuously improve performance of employees and the processes that guide them. One challenge in achieving this goal is the integration of human performance monitoring processes and the subsequent trend analysis of data collected. Such integration can be technically challenging if not incorporated in the processes prior to implementation. This is especially true with today's dynamic virtual organizations. The foundation of efforts to improve human performance is built upon trend analysis of documented errors and challenges, whether self-identified by the culpable individual or identified by the observation of others. Therefore, the trend evaluator must have the ability to analyze all human performance issues identified. Creating an atmosphere of self-critical behavior where employees proactively self-identify their errors is typically one of the most difficult challenges in the area of human performance improvement. Due to the difficulty in reaching this level of maturity, organizations often rely on various methods of observation, audits, reviews, and assessments. These various methods must be integrated such that value of information gather is utilized in all human performance monitoring processes. This document discusses an organized approach to human performance improvement through utilization of integrated processes aimed at recording human errors/challenges and subsequently trending this data to identify areas for improvement.