Quality-as-Imagined versus Quality-as-Done

Assumptions about how work is carried out is often very different from the reality of the work. This is the difference between work-as-imagined and work-as-done. Assumptions about work as imagined often turn out to be wrong because they are based on a fundamental misunderstanding. Steven Shorrock on Humanistic Systems has been doing a great series on proxies for work-as-done that I recommend you read for more details.

The complexity of our organizations implies a certain level of inevitable unexpected variability and thus a gap between Work-as-Imagined and Work-as-Done. Work-as-Imagined reflects how work is understood by those who are separated from it by time or space; it is an over-simplified version of what is actually going on. Work-as-Done takes account of what it means to function effectively, despite resource-constrained circumstances. The analysis of the gap between Work-As-Imagined and Work-as-Done usually indicates that performance variability is present in both desired and undesired outcomes and, therefore, successful outcomes do not necessarily occur because people are behaving according to Work-as-Imagined.

The same concept applies to the nature and implications of the gap between the prescribed quality practices and policies, Quality-as-Imagined, and the way they are deployed in practice, Quality-as-Done.

This gap should be no surprise. Our organizations are complex systems, and complexity can give rise to unintended consequences.

The interesting thing is that quality can drive a reduction of that gap, solving for complexity.

	Dynamic Interactions	Wide Diversity	Unexpected Variability	Resilience
Social	Interactions between employees	Employees with varying skill levels Employee turnover Diversity of functions performed by employees (e.g. multiskilling)	Errors when operating equipment and tools Unexpected behaviors Absenteeism Variability in human labor demand Unexpected outcomes from social interactions (e.g. conflicts and alliances)	Employees’ ability to anticipate risks Critical analysis of data Informal agreements between workers to distribute the workload
Technical	Interactions between production resources Interactions due to tightly coupled operations (e.g. time constraints, low inventories, capacity constraints)	Product diversity Diversity of quality requirements Diversity of client requirements	Technical disruptions Resource availability (e.g. maintenance staff) Variability in production times (e.g. cycle time, lead time) Dimensional variability (e.g. potential for defects)	Inspection readiness Corrective, preventive and predictive measures
Work Organization	Interactions between information sources Interactions between functions Interactions between processes Interactions between performance indicators	Diversity in managerial controls Diversity in relationships with external agents Diversity of rules and procedures	Variability in the hiring of new workers Changing priorities (e.g. frequent rescheduling due to unexpected conditions) Variability in timing and accuracy of information	Negotiation, partnership and bargaining power with suppliers and clients Investments on new resources Multidisciplinary problem-solving meetings
External Environment	Interactions between the organization, suppliers, and clients Interactions with regulatory bodies	Diversity in suppliers Diversity in clients	Variability in Demand/Need Variability in logistics	Capacity and slack management