Designing an Efficient Operating Model: A Practical Guide to Strategy Execution
Written by Thomas Flarup (CEO, HEIMDALL)
Your strategy might be brilliant on paper. But without the right operating model to execute it, even the best ideas stay trapped in slide decks and planning documents.
An efficient operating model is what separates companies that consistently deliver from those that struggle to turn strategic intent into results. It’s the difference between a 90-day product release cycle and a 30-day one. Between decisions that take weeks and decisions that take hours.
In this guide, you’ll learn exactly how to design, implement, and measure an efficient operating model that connects your business strategy to day to day operations. We’ll cover the core elements, practical design steps, sector-specific examples, and the modern drivers—from AI to remote work—that are reshaping how high performing operating models function in 2025 and beyond.
Answer First: What Is an Efficient Operating Model?
An efficient operating model is the integrated system of structure, processes, technology, people, and governance that translates strategy into execution with minimal waste and maximum impact. It’s how your company delivers value to customers while optimizing resources, speed, and quality.
Efficiency here is not just cost reduction. It’s about clarity in decision making, speed of execution, quality of outcomes, and sustainable growth over time.
A well designed operating model connects everything—your strategic vision, organizational structure, core processes, technology stack, and talent—into one coherent way of working. When these elements align, value creation accelerates. When they don’t, friction multiplies.
Consider a global SaaS company that in 2024 reduced its product release cycle from 90 days to 30 days. They didn’t achieve this by working harder. They redesigned their operating model: shifting from functional silos to cross functional product squads, embedding automated testing into their delivery pipeline, and clarifying decision rights so product owners could approve changes without escalating through three management layers.
Key characteristics of an efficient operating model include:
- Clear alignment between strategic objectives and operational activities
- Streamlined decision making processes that minimize bottlenecks
- End-to-end ownership of value streams rather than fragmented handoffs
- Technology and data embedded into workflows, not bolted on afterward
- Governance that enables speed rather than creating bureaucracy
Beyond Org Charts: What Makes an Operating Model Truly Efficient?
Many executives mistake organizational structure for the operating model. They redraw reporting lines, add or remove management layers, and expect efficiency to follow. But structure alone rarely delivers results.
Traditional structures from the 1990s and 2000s—functional hierarchies with deep specialization—were optimized for economies of scale. They worked when markets moved slowly and predictability mattered more than speed. Today’s rapidly changing world demands something different.
After 2020, leading companies accelerated their shift toward operating model design patterns that prioritize flow over control:
- Matrix structure evolution: Companies moved from complex matrix structures with dual reporting to clearer accountability models where one leader owns outcomes
- Product operating models: Tech firms like Spotify pioneered squad-based structures where cross functional teams own products end-to-end
- Platform operating models: Companies like Amazon built internal platforms that enable autonomous teams while maintaining standards
- Value stream organization: Instead of organizing by function, teams align around customer journeys or value creation paths
What makes these modern patterns more efficient isn’t the org chart—it’s what accompanies the structure:
- Fast decision making with clear decision rights at the team level
- End-to-end ownership where one team controls the full customer experience
- Frictionless cross functional collaboration built into how work flows
- Standardized processes and tools that reduce coordination overhead
- Data observability that lets teams self-correct without waiting for reports
The right operating model isn’t about finding the perfect structure. It’s about designing a dynamic system where strategy, people, processes, and technology work together seamlessly.
The Core Elements of an Efficient Operating Model
Efficient operating models are built from a small set of interlocking elements. Each element must be deliberately designed to eliminate waste, reduce friction, and enable focus on what matters most. When one element is misaligned, the entire system suffers.
Here are the key components that define an effective operating model:
1. Clear Customer Value Proposition
Your operating model exists to deliver value to customers. Start by defining exactly what value you’re creating and for whom. A retailer that standardized store operations in 2022 began by clarifying their core promise: convenient shopping, competitive prices, and helpful staff. Every operating model decision flowed from that.
2. Streamlined Governance and Decision Rights
Efficient models have lean governance with clear accountability. Define who decides what, at what level, and with what input. Avoid shadow decision structures where real power differs from formal authority. A technology company eliminated six approval committees and replaced them with three decision forums with explicit mandates and 48-hour response commitments.
3. Lean, Standardized Core Processes
Instead of hundreds of local process variants, efficient models standardize key processes globally while allowing local adaptation where customer needs differ. Map your critical value streams—order-to-cash, idea-to-launch, hire-to-retire—and eliminate non-value-added steps.
4. Embedded Technology and Automation
Technology should be designed into the operating model, not layered on top. Integrated toolchains, workflow automation, and self-service analytics eliminate manual handoffs and speed decisions. A manufacturing company embedded predictive maintenance algorithms into their production workflow, reducing unplanned downtime by 35%.
5. Data-Driven Decision Making
Efficient models use real-time data and analytics to guide decisions. Build dashboards that show leading indicators (cycle time, deployment frequency) alongside lagging outcomes (revenue growth, margin). Make data accessible to frontline managers, not just executives.
6. Aligned Talent Model and Capabilities
Match skills to work requirements. Define roles clearly, build key capabilities through talent development, and design career paths that support the new way of working. Efficient models often require new capabilities—product management, data analytics, agile leadership—that traditional structures didn’t emphasize.
7. Culture and Behaviors That Enable Speed
Even perfect processes fail if culture tolerates blame, hoarding information, or excessive risk aversion. Define the essential behaviors your operating model requires: collaboration, customer focus, continuous improvement, bias for action. Make these explicit and reinforce them through performance management.
8. Flexible Resource Allocation
Efficient models shift resources dynamically based on strategic priorities. Instead of annual budgets locked to departments, leading companies allocate funding to value streams or products and adjust quarterly based on results.
9. Performance Management System
Link metrics to accountabilities. Track the right KPIs at the right levels. Review performance regularly and use data to refine the operating model continuously. An efficient model is never static—it evolves through continuous learning.
10. Resilience and Adaptability
Build in the ability to respond to market changes, disruptions, and new opportunities. Modular designs, loosely coupled teams, and scenario planning capabilities help the model flex without breaking.
Designing an Efficient Operating Model in Practice
This section provides a pragmatic, step-by-step guide for CEOs, COOs, and transformation leaders who need to move from strategy to operational design. The goal isn’t theoretical perfection—it’s a working model that delivers business outcomes.
The typical design journey follows a sequence:
- Clarify strategy and value agenda
- Map current operating model and establish efficiency baseline
- Identify bottlenecks, waste, and friction points
- Design the target operating model
- Embed technology and data
- Align governance, roles, and incentives
- Pilot in a contained scope
- Scale in waves with continuous refinement
Many companies between 2020–2024 learned that piloting a new operating model in a single business unit before global rollout dramatically improved successful implementation rates. Let’s break down each step.
Step 1: Start with Strategy and Value Creation
Efficiency must be defined against strategic intent. What is your organization trying to achieve? Growth? Margin improvement? Customer satisfaction? Innovation speed? Market leadership?
Start by translating your strategy into a clear value agenda. This means identifying specifically where the business must be faster, cheaper, or better to win.
For example, a B2B software firm might face a choice: optimize for speed of feature delivery (releasing new capabilities weekly to stay ahead of competitors) or optimize for cost per feature (maximizing engineering productivity to protect margins). These require different operating models. The strategy dictates the efficiency target.
Key questions to answer:
- What are our strategic objectives for the next 3-5 years?
- Where do we need competitive advantage—speed, cost, quality, or customer experience?
- Which business capabilities are differentiating capabilities vs. table stakes?
- What does “efficient” mean for us—shorter cycle times, lower unit costs, higher throughput, or all three?
Don’t design for generic efficiency. Design for the specific efficiency that drives your strategy. A company pursuing market leadership through innovation needs a different optimal operating model than one pursuing cost leadership.
Step 2: Map the Current Way of Working (Your “Efficiency Baseline”)
Before redesigning, you need a clear picture of how work actually flows today. This mapping surfaces the bottlenecks, handoffs, rework loops, and duplicated activities that drain efficiency.
Map these operating model elements:
- Organizational structure: Reporting lines, spans of control, geographic footprint
- Core processes: How key workflows actually operate (not how they’re documented)
- Decision rights: Who approves what, and how long decisions take
- Technology and tools: What systems support the work, and where are the gaps
- Vendor ecosystem: What’s outsourced, and how are vendors managed
- Locations and workforce: Where work happens, and by whom
Use simple visual tools that stakeholders can understand: swimlane diagrams showing process flow, RACI charts clarifying responsibilities, and value stream maps highlighting cycle times. To further enhance commercial effectiveness, consider integrating Customer Lifetime Value (CLV) strategies for long-term customer profitability.
A European financial services firm discovered during mapping that approvals for standard contracts took 15 days because four different departments signed off, often redundantly. Legal, Compliance, Finance, and the Business Unit each reviewed the same documents for overlapping concerns. This single insight led to a redesigned approval process that cut time to 3 days.
Look specifically for:
- Handoffs between teams or functions where work gets stuck
- Rework and error correction loops
- Activities duplicated across regions or business units
- Decisions that escalate unnecessarily
- Manual data entry or reconciliation that could be automated
Step 3: Redesign for Speed, Simplicity, and Focus
With your baseline mapped and bottlenecks identified, redesign the operating model around principles that drive efficiency: fewer handoffs, clear accountability, empowered teams, and standardized core processes.
Key redesign principles:
Reduce handoffs: Every handoff creates delay and potential for error. Design processes where one team or individual owns the end-to-end flow whenever possible.
Clarify accountability: Each outcome should have one owner. Matrix structure complexity often diffuses accountability; efficient models make ownership explicit.
Empower teams: Push decision rights to the lowest appropriate level. When frontline teams can act without escalating, speed increases dramatically.
Standardize the core, customize the edge: Identify which activities should be standardized globally (back-office processes, technology platforms, compliance procedures) and which should remain close to customers (local sales approaches, product adaptations).
A concrete pattern: Between 2023–2024, several global digital businesses shifted from regional silos to global product squads. Previously, each region had its own product teams building similar features independently. The updated operating model created global product teams that build once and deploy everywhere, with regional specialists focused only on local market adaptation.
Before/after visualization:
| Before | After |
|---|---|
| 6 regional teams building similar features | 1 global product squad, 6 regional adaptation specialists |
| 90-day average release cycle | 30-day release cycle |
| 40% duplicated development work | <10% duplication |
| Unclear ownership across regions | Single product owner per capability |
Step 4: Embed Technology and Data into the Operating Model
Technology isn’t a separate layer—it should be woven into the operating model from the start. Automation, workflow tools, and data analytics platforms eliminate manual work, reduce errors, and accelerate decision making processes.
Since 2020, the adoption of modern SaaS tools has made sophisticated capabilities accessible to mid-sized companies, not just enterprises. The question isn’t whether to use technology, but how to integrate it into the way work flows.
Practical applications:
- Workflow automation: Digital approval workflows that route, track, and escalate automatically, eliminating email chains and lost requests
- AI-driven forecasting: Supply chain and demand planning tools that predict needs with greater accuracy than manual methods
- Self-service analytics: Dashboards that let frontline managers answer their own questions without waiting for IT reports
- Integrated CRM and ERP: Systems that share data seamlessly, eliminating duplicate entry and reconciliation
- Collaboration platforms: Tools that enable asynchronous work and documentation, critical for distributed teams
A retail chain implemented real-time inventory visibility across 500 stores in 2023. Store managers could see stock levels and adjust orders instantly, rather than waiting for weekly reports. Result: 22% reduction in stockouts and 15% reduction in excess inventory.
The key principle: Design technology into processes from the start. Bolting on tools after the fact creates fragmented systems and workarounds that undermine efficiency.
Step 5: Align Governance, Roles, and Incentives with Efficiency
Governance is where many operating models break down. Too many committees, unclear decision rights, and misaligned incentives create friction that negates process improvements.
Lean governance design:
- Reduce the number of governance bodies. Consolidate overlapping committees
- Define explicit decision rights for each forum. What can they decide? What must escalate?
- Set time-bound decision windows. No decision should wait more than X days without escalation
- Make escalation paths clear and fast
Role and span of control changes:
New operating model patterns often require new roles. Product owners who control product backlogs and priorities. Platform leads who maintain shared infrastructure. Value stream owners who are accountable for end-to-end customer outcomes.
Spans of control may widen as teams become more empowered. Managers shift from controlling to enabling.
Incentive alignment:
Traditional incentives reward functional activity (calls made, features coded, cases closed). Efficient models reward outcomes: lead time, customer NPS, unit cost, revenue growth.
Example: A technology services company shifted bonus structures from individual utilization targets (billable hours) to shared value stream targets (project delivery time and client satisfaction). Cross functional collaboration increased because everyone succeeded or failed together.
Efficiency in Different Operating Model Types (Concrete Examples)
Efficiency looks different depending on whether you’re building products, delivering services, running a platform, or operating physical assets. The principles are consistent, but the application varies. Let’s examine four business models.
Product-Centric Digital Businesses
In product-centric companies—software firms, mobile app developers, digital product companies—efficiency is driven by how quickly value reaches customers.
Key operating model characteristics:
- Cross functional product squads (product, engineering, design, QA, operations) own outcomes end-to-end
- Continuous delivery pipelines automate testing and deployment
- Tight customer feedback loops inform priorities weekly or daily
- Standardized engineering practices across teams reduce friction
A mobile app company in 2024 reorganized around customer journeys: “Onboarding,” “Discovery,” “Checkout,” and “Support.” Each journey had a dedicated squad with a product owner, engineers, designers, and data analysts. They released updates twice weekly instead of monthly.
Efficiency metrics:
| Metric | What It Measures |
|---|---|
| Deployment frequency | How often code reaches production |
| Lead time for changes | Time from commit to production |
| Change failure rate | Percentage of deployments causing problems |
| Mean time to recovery | How fast issues are resolved |
Service and Consulting Businesses
In professional services—consulting, legal, accounting—efficiency comes from repeatability, knowledge leverage, and utilization.
Key operating model characteristics:
- Standardized delivery methodologies and playbooks
- Knowledge management systems that capture and reuse solutions
- Global staffing pools with dynamic resource allocation
- Balance between custom work and modular, reusable solutions
Global consultancies invest heavily in capability hubs—centers of expertise that develop reusable frameworks, tools, and training. A team in New York can access a methodology developed in Singapore, rather than reinventing it.
Efficiency metrics:
- Utilization rates (billable hours as percentage of available hours)
- Project cycle times (proposal to completion)
- Client satisfaction scores (NPS, repeat engagement rate)
- Revenue per consultant
- Realization rate (actual fees vs. standard rates)
The most efficient service models protect margins by turning custom work into intellectual property that can be reused. Every engagement should make the next one faster and more profitable.
Platform and Marketplace Businesses
Platforms and marketplaces—think Uber, Airbnb, or enterprise software platforms—create efficiency through scalability and self-service.
Key operating model characteristics:
- Stable core platform services that all participants use
- Automated onboarding for suppliers, partners, and customers
- Self-service features that minimize human intervention
- Strong trust and safety operations that maintain quality
- Data observability across the platform for rapid issue detection
A marketplace launched in the 2010s structured its operating model around distinct functions: Platform Product (building core capabilities), Marketplace Operations (managing supply and demand balance), Trust & Safety (quality and compliance), and Growth (customer acquisition). Each function had clear accountability.
Efficiency metrics:
| Metric | What It Measures |
|---|---|
| Marginal cost per transaction | Cost to process each additional unit |
| Time to onboard new supplier | Speed of supply growth |
| Platform availability | Uptime and reliability |
| Resolution time for disputes | Operational quality |
Manufacturing and Asset-Intensive Businesses
In manufacturing, mining, and heavy industry, efficiency is grounded in lean principles, standardized work, and asset utilization.
Key operating model characteristics:
- Lean manufacturing principles: eliminate waste, standardize work, continuous improvement
- Predictive maintenance using IoT sensors and analytics
- Global plant networks with shared planning functions
- Centralized shared services for non-production activities
Automotive and industrial companies after 2020 significantly increased their use of IoT and data analytics to improve Overall Equipment Effectiveness (OEE). Sensors on production equipment feed data to predictive algorithms that schedule maintenance before breakdowns occur.
Efficiency metrics:
- Overall Equipment Effectiveness (OEE): availability × performance × quality
- Scrap rate: percentage of production that fails quality standards
- On-time delivery: percentage of orders delivered as promised
- Inventory turns: how efficiently working capital is used
Modern Drivers of Efficiency: Data, AI, and New Ways of Working
Between 2020 and 2025, three forces are reshaping what’s possible in operating model design: data availability, AI capabilities, and new work models. Leaders who understand these drivers can build adaptive operating models that would have been impossible a decade ago.
AI-enabled efficiency:
- Demand forecasting that reduces inventory costs while improving service levels
- Automated customer support handling routine inquiries without human intervention
- Anomaly detection that spots problems before they become crises
- Process optimization using machine learning to identify improvement opportunities
New work models:
- Remote and hybrid work as permanent features, not temporary exceptions
- Distributed teams that require new collaboration norms and digital tools
- Gig and contingent workforce models that provide flexibility
- Asynchronous work practices that span time zones
Self-correcting operating models:
- OKRs (Objectives and Key Results) that align teams around outcomes
- Real-time dashboards that surface problems immediately
- Observability platforms that trace issues across complex systems
- Continuous feedback loops that enable rapid adjustment
Data-Driven Optimization and Observability
End-to-end visibility is the foundation of continuous improvement. When leaders can see what’s happening across the operating model in near real-time, they can spot bottlenecks, identify root causes, and adjust without waiting for monthly reports.
What observability enables:
- Real-time tracking of lead time, throughput, and cost-to-serve
- Early warning indicators that predict problems before they materialize
- Root cause analysis when issues occur
- Evidence-based decisions about where to invest in improvement
A retail chain implemented real-time store performance dashboards in 2023. Store managers could see hourly sales, staffing levels, and inventory positions. Regional directors could see patterns across stores instantly. The result: daily adjustments to staffing and inventory that previously happened weekly at best.
Build your measurement system around integrated metrics that cover:
- Speed: Cycle times, decision latency, time-to-market
- Quality: Error rates, rework, customer complaints
- Cost: Unit costs, overhead ratios, cost-to-serve
- Outcomes: Customer satisfaction, revenue growth, market share
New Work Models and Distributed Teams
Remote and hybrid work, widespread since 2020, fundamentally change the practical operating model. The rituals, tools, and communication patterns that worked in co-located offices don’t automatically translate to distributed teams.
Practices that maintain efficiency in distributed models:
- Asynchronous decision logs where proposals and decisions are documented for those not in the meeting
- Virtual ceremonies (standups, retrospectives, reviews) with clear purposes and time limits
- Documented processes that don’t rely on tribal knowledge passed through hallway conversations
- Collaboration tools that create visibility into work progress without micromanagement
Demographic trends reinforce this shift. Millennials and Gen Z, now the majority of the workforce, expect autonomy and flexibility. Organizations that design operating models assuming everyone works 9-5 in an office will struggle to attract and retain talent.
Efficient operating models deliberately design for distributed work. They don’t treat remote as a temporary accommodation—they build it into the core model.
Measuring the Efficiency of Your Operating Model
What gets measured gets improved. An efficient operating model requires a clear measurement system that tracks performance, validates changes, and guides continuous improvement.
Categories of metrics to track:
Category Example Metrics Financial Unit cost, gross margin, cost-to-serve, overhead ratio Speed Cycle time, decision latency, time-to-market, lead time Quality Error rates, rework percentage, defect rates, first-time-right Customer NPS, customer satisfaction, churn rate, retention Employee Engagement score, turnover, time-to-productivity Resilience Time to recover from disruption, system availability Building metrics into operations:
- Include operating model metrics in regular business reviews (weekly, monthly, quarterly)
- Link metrics to specific accountabilities—someone owns each number
- Set targets based on baseline performance and strategic requirements
- Review trends, not just snapshots, to understand trajectory
A financial services company reduced decision latency from 2 weeks to 2 days for product pricing changes. They achieved this by clarifying decision rights (one team could decide, rather than consulting three) and tracking decision time as a KPI in weekly operations reviews.
Linking Metrics to Operating Model Changes
Metrics should not just track performance—they should validate whether specific operating model changes actually worked.
How to measure operating model improvements:
- Establish baseline metrics before making changes
- Define target metrics for the new operating model
- Pilot the change in a contained scope (one region, one business unit, one product)
- Measure results over a meaningful period (typically 3-6 months)
- Compare pilot results to baseline and to non-pilot control groups
- Adjust the design based on what you learn
- Scale what works
A technology company ran an 18-month transformation of its product development operating model. They measured deployment frequency, lead time, and customer incident rates quarterly. After the first quarter of pilots, they discovered that teams needed more investment in automated testing than originally planned—incident rates weren’t improving as expected. They adjusted, and by month 12, all metrics were hitting targets.
Combine leading and lagging indicators:
- Leading indicators (deployment frequency, decision speed, employee engagement) signal whether the operating model is working as designed
- Lagging indicators (revenue growth, margin, customer retention) confirm whether the efficiency improvements translate to business outcomes
From Pilot to Scale: Making Efficiency Stick
Many organizations redesign their operating model on paper but fail in implementation. Drawings and diagrams don’t change behavior. This section explains how to turn a new operating model into daily reality.
The scaling sequence:
- Choose pilot scope: Select a business unit, region, or product line that’s representative but contained. Big enough to be meaningful, small enough to manage.
- Run a time-boxed experiment: Typically 3-6 months. Implement the new operating model fully within the pilot scope.
- Measure results rigorously: Compare to baseline and control groups. Gather qualitative feedback alongside quantitative metrics.
- Adjust the design: Pilots always reveal issues. Update the target operating model based on what you learn.
- Scale in waves: Roll out to additional units in planned phases. Don’t try to change everything everywhere at once.
- Stabilize and optimize: Once scaled, continue measuring and refining. The operating model should evolve through continuous improvement.
Typical time horizons for large operating model shifts: 12-24 months from pilot to full scale. Some elements move faster, some slower. Visible executive sponsorship throughout is non-negotiable.
Transformation story structure:
A European manufacturing company redesigned its supply chain operating model after the 2021 disruptions revealed critical vulnerabilities. Their journey:
- Baseline (Q1 2022): Mapped current state, identified 6-week average lead time and 15% supply disruption rate
- Pilot (Q2-Q4 2022): Tested new model in one product line—integrated planning, supplier visibility platform, flexible sourcing
- Scale (2023): Rolled out to three additional product lines, adjusted based on learnings
- Stabilization (2024): Full implementation, lead time reduced to 3 weeks, disruption rate below 5%
Change Management and Capability Building
An efficient operating model requires people to learn new skills and unlearn old habits. This isn’t a soft concern—it’s a core workstream that determines success or failure.
Skills often required for new operating models:
- Product management and product ownership
- Agile leadership and facilitation
- Data literacy and analytics
- Cross functional collaboration
- Continuous improvement methodologies
Building capabilities:
- Training programs that teach new skills in the context of actual work
- Coaching for leaders transitioning to new management styles
- Communities of practice where practitioners share learning
- Clear career paths that reward new capabilities
Role changes, job descriptions, and career paths must be updated to reflect the new way of working. People need to understand not just what’s changing, but why it matters and how they fit in the new operating model.
Treat capability building as a core workstream with dedicated resources, timelines, and accountabilities. It’s not an afterthought or a nice-to-have.
Governance of the Transformation Journey
Operating model transformations need their own governance structure—not another bureaucracy, but a lean mechanism that monitors progress, removes obstacles, and maintains focus on value creation.
Transformation governance elements:
- Transformation Office: A small, dedicated team that coordinates activities, tracks progress, and escalates issues
- Steering Committee: Executive sponsors who meet monthly to review progress, make key decisions, and remove barriers
- Quarterly Strategy Reviews: Deeper assessments that examine whether the transformation is on track and adjust course if needed
- Clear decision rights: The Transformation Office manages day-to-day; Steering Committee owns major scope and investment decisions
Transformation KPIs to track:
KPI What It Measures Milestone completion Are we hitting planned deadlines? Value realization Are we achieving expected benefits? Adoption rates Are people actually using new processes and tools? Capability readiness Are people developing required skills? Risk issues What obstacles are we encountering? Stakeholder engagement Are key stakeholders bought in? Track these over the 12-24 month journey. Review monthly with the Transformation Office and quarterly with the Steering Committee. Adjust the plan as reality reveals what works and what doesn’t.
Conclusion: Building an Efficient Operating Model for the Next Decade
An efficient operating model is a dynamic system that turns strategy into results with speed and minimal waste. It’s not an org chart. It’s not a process manual. It’s the integrated way your organization works—connecting strategic vision, organizational structure, core processes, technology, data, and people practices into one coherent system.
True efficiency comes from alignment across all these elements, not from one-off cost cuts or restructuring exercises. The companies that operate effectively in competitive markets have built operating models where every component reinforces the others.
If you’re leading an operating model transformation, here’s where to start:
- Define your value agenda: What specific efficiency improvements will drive your strategy?
- Map your current state honestly: Where are the real bottlenecks and waste?
- Design for the outcomes you need: Speed? Cost? Quality? All three?
- Run focused pilots before scaling: Learn before you commit
- Measure outcomes rigorously: Track leading and lagging indicators
- Build capabilities deliberately: People make the model work
- Iterate continuously: The model is never finished
Looking ahead to 2025-2030, the environment will only become more demanding. AI will automate more routine work and raise expectations for speed and personalization. Data will become even more central to decision making. Remote and hybrid work will be standard. Sustainability initiatives will be integrated into operating model design.
In this context, your operating model isn’t a one-time transformation project. It’s an ongoing leadership responsibility—a living system that must evolve as strategy, technology, and markets change.
The organizations that thrive will be those that treat their operating model as a source of competitive edge, continuously refined to deliver better outcomes with greater efficiency. Start with clarity about what efficiency means for your strategy, and build from there.
Contact HEIMDALL – Commercial Excellence Partner
Written by Thomas Flarup (CEO, HEIMDALL)
