Operating Model Design

From Industrial-Era Control to Market-Speed Adaptation

Your organisation operates under industrial-era assumptions while competing in dynamic markets. Predictive planning in unpredictable environments. Hierarchical control where learning speed matters. Isolated departments when complete teams win.

You get an operating model grounded in learning from real evidence, decisions made by those closest to the work, and continuous adaptation. Systems of work that match market speed. Clear visibility across discovery, delivery, and operations. Engineering economics you can see and act on. Decisions based on what actually happens, not what you hoped would happen.

What This Provides

Strategic consultation on transitioning from Industrial Operating Model assumptions to an operating model fit for dynamic markets.

Not frameworks imposed from the outside. Your operating model grounded in learning from reality, designed for fast feedback, structured around complete teams, and built for continuous simplification.

Includes assessment of core business assumptions, model design, practice integration, and ongoing enablement as your context evolves.

Business assumptions assessment – Examining assumptions about markets, customers, and success. Where industrial-era prediction fails in dynamic environments

Evidence-based operating model design – Systems built on transparency, inspection, and adaptation rather than prediction and control

Complete team structure – Teams with all skills needed to deliver value, eliminating dependencies and handoffs

Continuous simplification – Ongoing removal of structures, processes, and behaviors that no longer serve their purpose

The Fundamental Mismatch

Most organisations operate under an Industrial Operating Model built for predictable markets: efficiency, standardisation, control. This worked brilliantly when demand changed slowly and product lifecycles measured in decades. Today, markets are dynamic. Customer needs evolve rapidly. Competitors emerge quickly. The mismatch between industrial-era assumptions and market reality generates massive waste.

Planning waste

Months creating detailed plans that become obsolete within weeks. Requirements gathered at the start no longer reflect market reality by delivery time.

Decision-making waste

Hierarchical approval chains delay action. By the time decisions escalate through management layers, information is stale and opportunities have passed.

Innovation waste

Rigid processes and risk-averse cultures kill experimentation. Ideas must fit predetermined roadmaps. Small experiments are blocked by governance designed for large capital investments.

Speed mismatch

Markets iterate daily. Organisations plan quarterly. Customer needs evolve continuously. Organisations deliver in large batches after months. This structural incompatibility stems from outdated business assumptions.

“Martin’s depth and breadth of knowledge and experience of the world of Agile/DevOps is incredible. He will switch between hands on development to advanced consulting or training on process, practices and tools to help you in your own DevOps journey. When the going gets tough in challenging situations he is super responsive and goes the extra mile… He is passionate about what he does and is always trying to improve the way we work to build high value products and solutions… Down to earth and straight talking. Highly recommend!”
Nancy Maher | Global Software Lifecycle Management Program Manager | SLB

The New Operating Model

Learning Over Prediction

Decisions based on what you observe and test, not assumptions
Transparency, regular inspection, and adaptation as operating principles
Fast feedback loops replace predictive planning

Distributed Authority Over Central Control

Authority sits with those who have the knowledge
Teams closest to customers and technology make decisions
Fast decisions based on current information, no approval delays

Complete Teams

All skills needed to deliver value without dependencies
Teams own outcomes—customer value and business impact
Deep capability and trust built over time

How This Works

Starts with your context, current operating model, and core business assumptions. Examines where industrial-era assumptions create waste. Designs an operating model grounded in learning from reality and built for continuous simplification. No frameworks imposed from the outside. Timeboxed retainer engagement with full transparency and risk reversal.

Business Assumptions Assessment

Examine core assumptions about markets, customers, and success. Identify where prediction-based structures fail in dynamic environments.

Current-State Analysis

Assess how work actually flows, where waste accumulates, and which structures create dependencies or delay feedback.

Operating Model Design

Co-create operating model: complete teams, decisions made by those who know, fast feedback loops, technical excellence.

Practice Integration

Scrum as social technology, Kanban as strategy for flow, DevOps as ethos—integrated as coherent enablers of the operating model.

Continuous Simplification

Establish ongoing removal of structures, processes, and behaviors that no longer serve their purpose. Prevent drift back to industrial-era patterns.

Who This Serves

Small organisations need clarity without overhead. Larger organisations need visibility without bureaucracy. This works for both.

CTOs and VPs of Engineering scaling product delivery

Product organisations needing alignment across discovery and delivery

Enterprises modernising operating models without losing momentum

Leaders needing visibility and control without micromanaging

What Changes

Industrial Operating Model	New Operating Model
Predictive planning and hierarchical control	Learning-based adaptation and distributed decisions
Isolated departments and dependencies	Complete teams owning outcomes
Slow feedback and delayed decisions	Fast feedback loops and evidence-based action
Output-focused metrics and individual utilization	Outcome metrics and organisational capability

Real-World Impact

A global energy technology company had 27 separate DevOps systems, 800+ projects, and 900+ custom processes. Teams working on the same product used different tracking systems. Leadership had no coherent view of delivery, performance, or investment.

Operating model consolidation and standardization reduced collections from 27 to 7, unified work item tracking, enabled cross-team collaboration, and provided strategic visibility. Engineering teams could focus on delivery rather than wrestling with fragmented systems.

Why NKD Agility

Deep Understanding of Operating Model Theory

Grounded in organisational design principles and how businesses adapt to change. Not framework evangelism.

Multi-Method Integration

Scrum as social technology, Kanban as strategy for flow, DevOps as ethos. Integrated as coherent enablers, not competing frameworks.

Engineering-Grounded

Operating model design rooted in engineering practices, technical depth, and delivery reality. Not process theory disconnected from execution.

Continuous Simplification

Designed for ongoing removal of obsolete structures. Prevents drift back to industrial-era patterns as organisations grow.

Engineering Economics and Evidence

Visibility through delivery metrics and outcome measurement. Industry frameworks as context, not dogma.

Timeboxed Retainer Model

You retain capacity. No fixed scope, no change orders, no hourly billing. Co-create operating model design and enablement within the timebox. Full risk reversal.

Ready to Transition to a Modern Operating Model? Let’s Talk

Book a Discovery Call

Our Happy Clients

We partner with businesses across diverse industries, including finance, insurance, healthcare, pharmaceuticals, technology, engineering, transportation, hospitality, entertainment, legal, government, and military sectors.