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.

The Influence of Complexity on Quality
Dynamic InteractionsWide DiversityUnexpected VariabilityResilience
SocialInteractions between employeesEmployees with varying skill levels
Employee turnover
Diversity of functions performed by employees
(e.g. multiskilling)
Errors when operating equipment and tools
Unexpected behaviors
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
TechnicalInteractions 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 OrganizationInteractions 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 EnvironmentInteractions 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
Examples of Complexity Impact

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