The title slide is titled "Intelligent Governance: A Scientific Approach to Service Strategy," presenting a framework for public sector service planning. Its subtitle elaborates on synthesizing adaptation economics, stochastic dynamics, and holistic design to achieve this approach.

Intelligent Governance: A Scientific Approach to Service Strategy

Synthesizing Adaptation Economics, Stochastic Dynamics, and Holistic Design for the Public Sector

Source: Appendix A: Presentation Framework

The slide critiques the NPM model for failing in volatile environments by outsourcing everything, treating citizens as customers, and optimizing for averages, advocating a shift to Intelligent Governance for adaptive public service strategies. It introduces key concepts like Dynamic Sourcing via Adaptation Cost Theory to balance market and internal options, Co-Production Operations using Hawkes Processes for bursty collaboration, and Variance-Aware Design through Holistic Coupling for integrating interdependent service steps.

The Strategic Imperative

• NPM model fails in volatile world: outsources everything, treats citizens as customers, optimizes for average.
• Shift to Intelligent Governance for adaptive public service strategy.
• Dynamic Sourcing: Adaptation Cost Theory balances market vs. internal specialization.
• Co-Production Operations: Hawkes Processes model bursty, collaborative service delivery.
• Variance-Aware Design: Holistic Coupling integrates interdependent service steps.

Source: Appendix A: Presentation Framework

The slide explores the Adaptation Cost Theory, which weighs the trade-off between market-based functional specialization for general efficiency and internal firm-specific specialization for tailored adaptation, balancing external expertise with internal control in dynamic settings. It pivots to adjustment frequency, noting that high volatility exponentially raises contracting costs from frequent renegotiations, making insourcing preferable for stable internal governance in uncertain environments.

Sourcing Strategy - When to Insource?

Source: Wernerfelt et al. (2021)

The slide "Operations - The Myth of 'Lightest Load'" debunks the idea of routing work to the least busy agents, highlighting key stats from operations data. It shows increased wait times over 10% compared to predictive routing, 70% of workloads being bursty and overloading agents, and a 40% risk of cognitive overload from mismatched assignments.

Operations - The Myth of 'Lightest Load'

• >10%: Increased Wait Times

vs. predictive routing

• 70%: Bursty Workload

peaks overload agents

• 40%: Cognitive Overload Risk

from mismatched routing Source: Daw et al. (2025)

Bellos and Kavadias (2021) outline a process framework for service design that contrasts routine steps, where increased effort boosts value while reducing variance (e.g., ID checks), with nonroutine steps, where effort enhances value but increases variance (e.g., crisis assessments). The recommended strategy is to differentiate processes by investing in routine steps to achieve greater consistency.

Designing the Journey - Routine vs. Nonroutine

• Bellos & Kavadias (2021): Process Framework for Service Design
• Routine Steps: ↑ Effort → ↑ Value, ↓ Variance (e.g., ID Check)
• Nonroutine Steps: ↑ Effort → ↑ Value, ↑ Variance (e.g., Crisis Assessment)
• Strategy: Differentiate; Invest in Routine for Consistency

Source: Bellos & Kavadias (2021)

In the 'Impact Zone,' service steps interconnect such that errors propagate and bad starts amplify issues across phases. To address this, designs should be modular, optimizing each step based on variances from adjacent ones, while holistically coupling elements like the Digital Portal and Physical Interview.

The 'Impact Zone' and Holistic Coupling

• Service steps interact in an 'Impact Zone' where errors propagate.
• Bad starts amplify issues across interconnected service phases.
• Design modularly: Optimize Step N using variances of N-1 and N+1.
• Couple Digital Portal with Physical Interview for holistic design.

The slide challenges the false premise that simply adding more channels resolves service issues, emphasizing instead that high-variance, rigid processes amplify failures during scaling. It advocates integrating Baron Omnichannel and Rai Relational solutions to build relational value, using trust as the key currency.

Moving Beyond False Premises

• False Premise: Adding channels fixes service issues.
• Reality: High-variance rigid processes scale failures.
• Integration: Combine Baron Omnichannel and Rai Relational.
• Goal: Build relational value with trust as currency.

Source: Appendix A: Presentation Framework

The Roadmap agenda outlines a four-step plan to optimize processes in a civil service context. It includes auditing high-volatility functions for repatriation, mapping and automating routine versus nonroutine steps, routing predictive activities to balance cognitive load, and measuring process variance beyond averages.

The Roadmap

1. Audit High-Volatility Functions

Identify high-volatility functions and repatriate to Civil Service.

2. Map Routine and Nonroutine

Tag routine vs. nonroutine steps, automate routine, enable nonroutine.

3. Route Predictive Activities

Implement predictive activity routing to balance cognitive load.

4. Measure Process Variance

Track variance in processes, not just averages. Source: Appendix A: Presentation Framework

Government service is portrayed as a dynamic, co-produced relationship rather than a rigid factory line, requiring strategies that align with its inherent physics. The slide advocates embracing intelligent governance through adaptive strategies to transform public service.

Conclusion

Government service is not a factory line. It is a dynamic, co-produced relationship. Our strategy must reflect the physics of that relationship.

Embrace Intelligent Governance. Implement adaptive strategies to transform public service.

Source: Appendix A: Presentation Framework