CLARIFYING AND SUPPORTING ROOT CAUSES IN ORGANIZATION BEHAVIOUR: TOWARD A SCIENCE OF SOCIAL SYSTEMS

Abstract

The aim of this paper is to identify root causes in human social system behaviour then discuss implications of these causes for understanding, designing, and managing large organizations. The need for clarifying root causes is clear. Science offers useful laws for how things behave, or the hard sciences, such as chemistry, physics, math and engineering. In contrast, science offers few and conflicting models for how people behave. Thus, there are the soft sciences, such as psychology, management, education, sociology, and economics.  And there are the soft social systems such as schools and workplaces. Our current knowledge of soft social systems lies in many disciplines, and the knowledge within each discipline resides in silos, resulting in Tower-of-Babel communication across disciplines. Unintended, undesired, even harmful outcomes are frequent, especially in large organizations. The approach used in this investigation is narrative path analysis. Beginning with large social system outcomes as the unit of focus and dependent variable, a systems science explanatory lens is developed, and the path lands at the individual human system member as root cause, unit of focus and independent variable. The narrative path then proceeds back up to the large social system, with implications at multiple levels/sizes of system-- the pair, the room, small building, and then the multisite organization. The investigation gathers details via key concepts, literature, and evidence from relevant disciplines, including management, control systems engineering, psychology, adult learning theory, plus examples from large urban schools and workplaces. Metaphors and images are included to clarify the narrative with the goal of making sense to a wide diverse audience—including leaders, learners, workers, theorists, researchers, engineers, and policy-makers.  Updated theory is that cause/agency of organization behaviour is not solely in the leader, nor the worker, but in both. Each system member, from janitor to CEO, from student to superintendent, learns and performs according to his/her own willingness and ability, resulting in almost infinite variability. A new provide-pickup relationship emerges. That is: The leader’s role is to provide input, resources and tasks; the learner/worker role is pickup of input, each at his/her own rate. In spite of infinite variability, there is predictability.  We can predict, with certainty, that each system member will pick up, learn and complete tasks, as he/she is willing and able.  The nature of pickup described, a new issue emerges, span of pickup, at the level of the large social system-- adding an important new dimension to the concept of span of control.  Namely, in large social systems, important input is beyond the pickup span of individuals.  For example, it is easier for CEOs to care more about their children’s college tuition than their employees’ salaries.  And, it is easier for front-line employees to care more about their weekly paycheck than the big picture goals of the organization, or for a cattle herder to care about the profit gained by adding a new animal to his herd than the big picture of overgrazing. Ideal-based user-designed automated social control systems (IBUDASCS) are proposed to allow organizations and system members to flourish.  The cumulative meaning of IBUDASCS is constructed using the following examples:  Control Systems-- When the temperature turns 65, the heater turns on; plus Social—When an employee is late, he/she makes up the time (Honor system, or superviser controlled); plus Automated – When an employee is late, the information automatically goes to the time clock and payroll; plus User-designed-- People at each system level decide together their automated consequences (in alignment with suprasystem policy); plus Ideal-based-- The consequence is automated not to berate or punish, but to free up everyone’s time for more important matters.