Why do operating model levers decide customer outcomes?
Executives set strategy, but operating model levers decide whether customers feel the value. An operating model is the set of structures, processes, and governance that turns strategy into performance. People, process, technology, and data act as the four primary levers in that system. When leaders tune these levers in concert, CX improves, cost-to-serve falls, and risk reduces. When leaders optimize them in isolation, transformation stalls and value leaks. Research shows that many companies leave a large share of strategic value unrealized because operating models fail to translate ambition into execution.¹ ²
What defines each lever in practical terms?
Leaders define people as roles, skills, incentives, and ways of working. Leaders define process as the repeatable steps that deliver outcomes. Leaders define technology as the platforms, services, and integration patterns that enable work. Leaders define data as the managed assets and rules that inform decisions. Foundational bodies of knowledge describe how each lever operates. Process change has roots in reengineering and process innovation.³ ⁴ Quality systems such as ISO 9001 define disciplined management practices.⁵ IT service delivery uses ITIL 4 practices.⁶ Enterprise architecture uses TOGAF for structure and traceability.⁷ Data management uses DAMA-DMBOK to govern assets, quality, and lineage.⁸
Context: Why do CX and Service leaders need a single system?
CX and Service leaders run high-volume, high-variability environments. Contact centres, field service, and digital channels amplify complexity through channel mix, regulation, and legacy technology. A single system helps by binding people, process, tech, and data to measurable outcomes such as first contact resolution, average handle time, digital containment, and customer effort. Modern operating model work shifts focus from org charts to end-to-end value creation and the governance that sustains it.¹ ² This discipline avoids project churn and creates a durable link between design choices and performance.
Mechanism: How do the levers work together to move metrics?
Leaders treat the levers as a closed loop. People practices define capability and behavior. Processes codify the path to value. Technology implements that path at scale. Data measures performance and informs continuous improvement. Quality management systems require that loop to be intentional, documented, and auditable.⁵ IT service management translates it into service design, transition, and operation with clear roles and queues.⁶ Architecture methods tie business capabilities to applications and integration patterns to keep change coherent.⁷ Data governance ensures decisions rest on trusted, well-defined data domains.⁸ When leaders align these elements to one customer journey, agents gain clarity, systems reduce rework, and data closes the loop through visible feedback.
Comparison: What breaks when levers are tuned in isolation?
Organizations that train people without redesigning processes create skilled frustration. Organizations that automate bad processes create faster defects. Organizations that centralize data without changing decisions create dashboards without action. The 1990s debate between radical reengineering and continuous improvement showed that scale and speed require both redesign and discipline.⁹ The lesson holds. Leaders win when they sequence improvement so processes are simplified before automation, governance is defined before scaling, and data definitions are agreed before measurement.
Applications: Where do CX leaders start in the real world?
CX leaders start with a customer journey that matters, such as “Resolve a billing error” or “Activate service.” Teams map the current process at the level of value streams and queues. Teams quantify demand, failure demand, and variation. Teams translate findings into a minimal, standards-based target. Reengineering principles encourage elimination of non-value steps and recombination of work to reduce handoffs.³ ⁴ Quality practice asks for control points, owners, and documented procedures.⁵ ITIL 4 supplies incident, request, knowledge, and problem practices for service environments.⁶ TOGAF links the new process to capabilities, applications, and data flows.⁷ DAMA-DMBOK defines data domains, quality rules, and stewardship.⁸ The result is a coherent change that touches scripts, workflows, APIs, knowledge articles, and reports at once.
Risks: What failure modes threaten service transformation?
Service transformations fail when incentives reward volume over resolution, when processes are optimized for internal efficiency instead of customer outcomes, when technology choices lock in bespoke integrations, and when data lineage is opaque. Operating models drift when governance is unclear. COBIT addresses this risk by clarifying enterprise information and technology governance objectives, decision rights, and design guardrails.¹⁰ The antidote is to define who decides, how decisions are escalated, and which measures certify readiness at each change gate.
Measurement: How do leaders prove impact and sustain momentum?
Leaders anchor measurement in a single chain from intent to metric. A clear intent such as “Reduce repeat contacts” becomes an operating hypothesis with leading and lagging indicators. Quality standards encourage documented objectives and continual improvement cycles.⁵ ITIL 4 practices attach KPIs to service levels, backlog health, and knowledge reuse.⁶ Architecture methods ensure that changes to capability maps and integration contracts are versioned and traceable.⁷ Data governance assigns ownership for definitions and quality thresholds.⁸ Executives then review outcomes in a monthly rhythm that inspects both performance and learning, and they adjust the levers in concert.
Solution: A 90-day operating model sprint for CX and Service
Leaders compress risk with a timeboxed operating model sprint. Week 0 to 2 creates a baseline. Teams capture process demand, topology, and pain points across one journey. Week 3 to 6 designs the target. Teams remove failure demand, redesign handoffs, and define role clarity. Week 7 to 10 implements a thin slice. Technology teams configure workflow, knowledge, and integration changes that match the process. Data teams stand up the metrics with clear definitions and owners. Week 11 to 12 stabilizes and scales. Governance defines guardrails and change cadences. The sprint borrows reengineering focus, quality discipline, service practices, architecture traceability, and data governance to deliver measurable value in one quarter.³ ⁵ ⁶ ⁷ ⁸
Impact: What outcomes should executives expect and defend?
Executives should expect fewer handoffs, lower average handle time, higher first contact resolution, faster cycle times, and cleaner compliance posture. They should also expect fewer platforms doing more work through clear capability mapping and API first principles. Operating model work is not a one-off project. It becomes a management system that protects strategy from drift. Recent guidance stresses the need to upgrade the operating model as markets shift and technology evolves.¹ ² Leaders who maintain this system see faster adaptation with less friction.
Operating model design criteria that travel well
Strong operating models share traits that travel across industries. They define clear decision rights across business and technology. They tie flows of work to flows of data. They document changes and measure readiness before release. They scale through standard patterns and guardrails, not bespoke exceptions. They keep people at the center by investing in skills, knowledge, and incentives that reinforce the desired process. They capture learning in the process and knowledge base, not only in decks. Quality, service, architecture, and data disciplines provide the scaffolding for these traits.⁵ ⁶ ⁷ ⁸
Which governance mechanisms keep the model resilient?
Resilient models use three mechanisms. First, standards. ISO 9001, ITIL 4, TOGAF, COBIT, and DAMA-DMBOK create shared language, roles, and checkpoints.⁵ ⁶ ⁷ ¹⁰ ⁸ Second, routines. Operating reviews test whether processes still meet customer intent. Third, transparency. Data lineage, service catalogs, and capability maps make dependencies visible and auditable. Leaders who institutionalize these practices find it easier to onboard new talent, integrate acquisitions, and scale automation without fragmentation.
Next steps: How do we move from slideware to system?
Executives move from slides to system by choosing one journey, one domain, and one unit of value. They place a cross-functional team under a single accountable owner. They apply reengineering to strip waste and friction.³ ⁴ They codify quality controls and roles.⁵ They implement service practices for requests, incidents, problems, and knowledge.⁶ They align architecture so technology changes trace to capabilities.⁷ They name data owners and definitions.⁸ They fund a thin slice and hold it to outcomes. They make the new model the default for adjacent journeys. They then expand with discipline rather than scale chaos.
FAQ
What is an operating model in CX and Service transformation?
An operating model is the system of structures, processes, governance, technology, and data that turns strategy into performance for customer experience and service delivery. It coordinates people, process, tech, and data to produce outcomes such as first contact resolution and customer effort reduction.¹
How do the four levers interact to improve customer outcomes?
People supply capability and behavior, processes codify the path to value, technology executes the path at scale, and data measures and informs improvement. Quality systems and service management practices formalize this loop so changes are intentional and auditable.⁵ ⁶
Why should leaders use standards like ISO 9001, ITIL 4, TOGAF, COBIT, and DAMA-DMBOK?
These frameworks provide shared language, decision rights, and controls across quality, service, architecture, governance, and data. They reduce ambiguity, improve traceability, and make performance repeatable across teams and vendors.⁵ ⁶ ⁷ ¹⁰ ⁸
Which pitfalls derail service transformations most often?
Common pitfalls include automating poor processes, training without redesign, over-customizing platforms, and reporting on data that lacks ownership and clear definitions. Governance frameworks help prevent drift by clarifying decision rights and objectives.¹⁰
What 90-day plan can a contact centre use to start?
Start with one journey. Baseline demand and failure demand. Redesign handoffs and roles. Implement a thin slice across workflow, knowledge, and integrations. Stand up metrics with clear definitions and owners. Stabilize and scale through governance routines.³ ⁵ ⁶ ⁷ ⁸
Who should own the operating model in a CX organization?
A single accountable executive should own the operating model, with federated design authorities across process, service, architecture, and data. This structure keeps decisions fast while holding teams to shared standards.¹ ⁵ ⁶ ⁷ ⁸
Which evidence supports focusing on operating models, not just org charts?
Recent analyses show that strategy underperforms without an aligned operating model and that redesigning how work flows delivers more value than structure changes alone.¹ ²
Sources
McKinsey & Company. 2025. “A new operating model for a new world.” McKinsey Insights. https://www.mckinsey.com/capabilities/people-and-organizational-performance/our-insights/a-new-operating-model-for-a-new-world
McKinsey & Company. 2025. “How the right operating model can fix a strategy that falls short.” McKinsey Insights. https://www.mckinsey.com/capabilities/people-and-organizational-performance/our-insights/how-the-right-operating-model-can-fix-a-strategy-that-falls-short
Michael Hammer and James Champy. 1993. Reengineering the Corporation. HarperBusiness. Google Books page: https://books.google.com/books/about/Reengineering_the_Corporation.html?id=VpYgWyc16twC
Thomas H. Davenport. 1993. Process Innovation: Reengineering Work Through Information Technology. Harvard Business Press. Google Books page: https://books.google.com/books/about/Process_Innovation.html?id=kLlIOMGaKnsC
International Organization for Standardization. 2015, amended 2024. “ISO 9001:2015 Quality management systems — Requirements.” ISO. https://www.iso.org/standard/62085.html and amendment info: https://www.iso.org/standard/88431.html
AXELOS. 2023. “ITIL 4 Foundation and Practice Guides Overview.” AXELOS Resource Hub. https://www.axelos.com/resource-hub/practice/readers-manual-itil-4-practice-guide
The Open Group. 2022–2023. “The TOGAF Standard.” The Open Group. Overview and updates. https://www.opengroup.org/togaf and https://www.opengroup.org/togaf/new-version
DAMA International. 2023. “DAMA-DMBOK2 Revised Edition FAQs.” DAMA International. https://dama.org/dama-dmbok2-revised-edition-faqs/
Wired. 1995. “The Battle for the Soul of Corporate America.” Wired Magazine. https://www.wired.com/1995/08/reengineering
ISACA. 2019. “COBIT 2019 Framework: Introduction and Methodology.” ISACA. https://www.isaca.org/resources/cobit and reference PDF: https://community.mis.temple.edu/mis5203sec003spring2020/files/2019/01/COBIT-2019-Framework-Introduction-and-Methodology_res_eng_1118.pdf