WORKFLOW EVIDENCE
Evidence about what improved, for whom and under what conditions within the tested workflow.
Human Contribution Work Redesign Lab
Redesign one workflow that matters.
A focused engagement that brings an accountable outcome owner together with the people closest to the work. Together, they redesign and test one consequential workflow, learn what improves the outcome and build the capacity to repeat the process.
- Frame
- Discover
- Map
- Redesign
- Test
One workflow. One cross-functional team. One bounded test.
Why the Lab
Improve the work. Build the capacity to adapt.
ADAPTIVE CAPACITY
Participants learn a repeatable way to examine, redesign and test consequential work.
ORGANIZATIONAL LEARNING
Learning is tracked across workflows to identify recurring patterns in what enables or constrains change.
Where to begin
Choose a workflow where value is at stake.
The Lab begins with a strategic outcome that matters, not a generic AI use case.
- What strategic outcome needs to improve, and who should benefit?
- Where is value being lost, delayed or left unrealized?
- Which shared workflow most influences that outcome?
- What in the work would need to change for that outcome to improve?
What the engagement requires
Conditions for testing.
A viable Lab needs an accountable outcome owner, the people closest to the work and permission to test under real conditions.
OUTCOME OWNERSHIP
One person is answerable for the outcome and can mobilize the people, data and bounded resources the test requires.
PARTICIPATION
A cross-functional group includes people who perform, receive, enable, govern or are affected by the work.
PERMISSION TO TEST
The team can establish a baseline, test a changed workflow and act on what the evidence reveals.
The Lab flow
From current work to evidence, learning and the next test.
Frame
Clarify the strategic outcome, who should benefit, how value is expected to be created, the current baseline and the conditions under which the workflow must perform.
Discover
Examine how work actually happens, including exceptions and workarounds.
Map
Make visible the tasks, decisions, relationships, learning and accountability that shape the outcome.
Redesign
Use the Contribution Design Tests to create the future-state workflow.
Test
Test the redesigned workflow under real conditions. Measure business, human, adoption and governance outcomes.
What we make visible
Work is more than tasks.
A responsible redesign examines the full system of work.
The formal process is only one version of the work. The Lab also captures informal judgment, tacit knowledge and the work people do to hold the system together.
WHEN AI ACTS ACROSS THE WORKFLOW
The system matters more than any single agent.
The Lab maps how people, AI agents and organizational systems interact across the workflow, including authority, human checkpoints, exceptions, escalation and recovery. It tests the system as a whole, not a single tool or agent.
What enables or constrains the redesign
A redesigned workflow may not hold inside an unchanged system.
The Lab records which surrounding conditions appear to enable or constrain the redesigned work. These observations become questions to examine within this workflow and, where relevant, across future tests.
- Outcome ownership and priorities
- Roles, decision rights and accountability
- Capacity and resource allocation
- Capabilities and learning
- Measures and incentives
- Data, knowledge, technology and governance
- Leadership practices
- Trust, voice and participation
Core outputs
A tested redesign, documented learning and a clear next test.
01Lab Charter, Value Hypothesis and Test Conditions
02Current-State Blueprint
03Human Contribution Point Map
04Contribution Architecture
05Future-State Workflow and Authority Map
06Role, Workforce and Capability Implications
07Enablers, Constraints and Questions for Further Testing
08Bounded-Test Scorecard
09Evidence and Learning Record
10Scale, Revise or Stop Recommendation and Next Test
How we evaluate the bounded test
A faster workflow is not automatically a better system.
Strategic, financial and operational value, quality, capacity, speed, service and client outcomes
Workload, judgment, learning, agency, trust and meaningful contribution
Appropriate use and reliance, proficiency and workflow integration
Errors, bias, overrides, incidents, accountability and recovery
From local learning to organizational learning
Learning accumulates across workflows.
One test does not explain the organization. Tracking evidence across workflows helps leaders distinguish what is local, what recurs and what may justify broader change. Each redesign also strengthens the organization’s capacity to learn, adapt and redesign work again.