Working Model / v0.9

The Operating Layer

A working model for understanding the system between strategy and execution: direction, decisions, orchestration, content, intelligence, technology, governance and adoption.

01DirectionStrategy, priorities, outcomes, constraints
02DecisionsDecision rights, escalation, ownership
03OrchestrationIntake, planning, handoffs, execution
04ContentLifecycle, taxonomy, reuse, localization
05IntelligenceAI, agents, automation, decision support
06TechnologyInfrastructure, integration, constraints
07GovernanceStandards, controls, policy, accountability
08AdoptionEnablement, behavior, habits, capability

The layers are interdependent, not sequential. A change in governance changes decision flow. A change in adoption changes the value of technology. Outcomes feed back into direction.

01

Direction

Purpose

Clarifies what the organization is trying to achieve and which priorities should govern execution.

Failure signals

Everything becomes a priority; teams interpret strategy differently; work enters without strategic relevance; activity disconnects from outcomes; teams optimize locally against different definitions of success.

Design questions

What outcomes actually matter? Which priorities govern resource allocation? What should explicitly not be prioritized? How does strategic intent translate into operational choices? How are conflicting priorities resolved?

Useful signals

Proportion of work linked to defined priorities, unplanned work, prioritization changes, strategic alignment of active work, and work stopped or deprioritized.

Relationships

Strongly influences Decisions, Orchestration, Governance and Adoption.

02

Decisions

Purpose

Defines who decides what, at what level, using what information and within which boundaries.

Failure signals

Excessive escalation, unclear ownership, repeated approval loops, meetings substituting for decision rights, senior leaders making operational decisions unnecessarily, and decisions repeatedly reopening.

Design questions

Who should own this decision? Which decisions require escalation? What information is necessary? Which decisions can be standardized or AI-assisted? Where is ambiguity intentional versus accidental?

Useful signals

Decision latency, approval depth, escalation frequency, number of decision-makers, and the rate of reopened decisions.

Relationships

Strongly influences Orchestration, Governance, Intelligence and Adoption.

03

Orchestration

Purpose

Determines how work enters the system, gets prioritized, moves between actors and reaches completion.

Failure signals

Duplicate intake channels, excessive handoffs, manual coordination, invisible work, conflicting queues, meetings used to synchronize basic execution, and unclear ownership between stages.

Design questions

Where does work enter? Who owns it at each stage? Which handoffs are necessary? Which exist only because of legacy structure? Where does work wait? What information must travel with it? Which coordination work can disappear?

Useful signals

Cycle time, number of handoffs, work-in-progress, waiting time, rework, abandoned requests, and manual coordination effort.

Relationships

Strongly influences Decisions, Technology, Intelligence, Governance and Adoption.

04

Content

Purpose

Defines how content is created, structured, governed, reused, localized, maintained and delivered.

Failure signals

Repeated recreation, inconsistent metadata, weak reuse, late localization, fragmented ownership, governance at final approval, and assets becoming obsolete without clear lifecycle rules.

Design questions

What should be reusable? What information should be structured? Where should governance happen? How should localization enter the lifecycle? What is the canonical source? What should AI generate, transform or review? When should content be retired?

Useful signals

Content reuse, rework, localization turnaround, duplicate creation, lifecycle visibility, governance exceptions, and time-to-publish.

Relationships

Strongly influences Orchestration, Intelligence, Technology and Governance.

05

Intelligence

Purpose

Determines where data, analytics, automation and AI improve decisions or execution.

Failure signals

Isolated AI pilots, automation disconnected from workflows, humans repeatedly correcting machine output, low-value automation, excessive intervention, tools outside the system of work, and unclear escalation paths.

Design questions

Which decisions benefit from intelligence? Which tasks should disappear? Where must humans remain accountable? What triggers escalation? Which outputs require verification? Where does AI materially change cost, speed or quality?

Useful signals

Human intervention rate, AI escalation rate, automation coverage, exception rate, time saved, decision latency, and quality or error rates where measurable.

Relationships

Strongly influences Decisions, Orchestration, Governance and Technology.

06

Technology

Purpose

Provides the infrastructure through which the operating model executes.

Failure signals

Tools dictate process design, duplicate platforms, manual movement between systems, fragmented data, platform workarounds becoming permanent processes, and teams optimizing around tool limitations.

Design questions

What capabilities does the work actually require? Which systems should own which data? What should integrate or be removed? Which constraints are unavoidable, and which exist because nobody has challenged the architecture?

Useful signals

Manual system transfers, duplicate systems, integration failure rates, workflow coverage, manual reconciliation effort, and tool utilization versus business value.

Relationships

Strongly influences Orchestration, Content, Intelligence and Governance.

07

Governance

Purpose

Defines standards, boundaries and accountability so good decisions can happen safely and consistently.

Failure signals

Approval inflation, governance only at the end of work, central teams becoming bottlenecks, unclear accountability, normalised exceptions, and governance slowing decisions without improving quality.

Design questions

What actually needs control? Which decisions can be distributed? What should be standardized? Which risks justify approval? What can be governed by rules rather than review? How can governance increase decision velocity?

Useful signals

Approval depth, decision latency, exception rate, escalation frequency, rework after approval, and governance-related waiting time.

Relationships

Strongly influences Decisions, Orchestration, Intelligence and Adoption.

08

Adoption

Purpose

Turns system design into actual organizational behavior.

Failure signals

Licenses without meaningful usage, usage without measurable value, training without behavior change, parallel legacy processes, low trust, work outside the intended system, and teams reverting after launch.

Design questions

What behavior must change? Why should users change? What friction prevents adoption? What support is required? How is new behavior reinforced? What evidence shows sustained adoption? Which legacy behavior should disappear?

Useful signals

Sustained usage, intended workflow completion, reduction in shadow processes, adoption depth, support demand, repeat behavior, and measurable operational improvement.

Relationships

Strongly influences every other layer because design only creates value when behavior changes.

Model history

v0.9 — Initial public model.

An experience-derived, evolving model — not manufactured certainty.