Margin Not Growth: Why Service Leaders Must Shift Their Focus in an Uncertain Global Environment

With many customers shifting their focus from growth to margins, the opportunities for Service Leaders to increase their influence both within customers, and their own organisations is opening up.

As global trade relations grow increasingly unpredictable, a noticeable shift is underway in the industrial and equipment sectors. Businesses are moving from an aggressive focus on revenue growth to a more measured approach centered on margin optimization and operational efficiency. Whether it’s due to rising tariffs, supply chain fragmentation, or geopolitical tensions, many executive teams are taking a hard look at their portfolios—making deliberate decisions about where to compete, how to allocate resources, and how to maintain profitability under pressure.

This shift has significant implications for industrial service leaders. And those who recognize the moment for what it is—a chance to increase relevance and value—will emerge stronger and more strategically aligned with the business.

Two-Sided Impact for Service Leaders

The current environment creates both external and internal drivers for industrial service to step forward:

‘Externally’, as customers become more cost-sensitive, services that deliver better uptime, predictable performance, and optimized operations will become even more attractive. When capital investments slow, customers look to do more with what they already have—creating a natural opening for strong service propositions.

‘Internally’, product sales may be under pressure from tariffs and global market shifts. This increases the need to extract greater value from the existing installed base.

Service organizations, with their local footprint of people, facilities, and potentially locally sourced parts, are less likely to be affected by trade barriers. This makes them a more resilient and competitive part of the business portfolio.

Together, these dynamics elevate the role of service from a support function to a strategic lever.

The Industrial Fallout of a Trade War

A global trade war introduces a host of uncertainties: higher material costs due to tariffs, disrupted supply chains, volatile currency movements, and increasingly complex compliance environments. For many companies, this leads to squeezed margins, delayed deliveries, and strategic reconsideration of international operations.

In this environment, relying purely on capital equipment sales becomes increasingly risky. Smart companies are shifting attention to their service business, which typically offers:

  • Higher margins
  • Recurring, more predictable revenue
  • Stronger, ongoing customer relationships
  • More local delivery (less subject to tariffs)

Unlike products, service often requires limited physical movement across borders. The “knowledge” component of service—expertise, diagnostics, software—is difficult to tax. While imported spare parts may still face duties, many standard parts can be sourced locally in large markets, reducing tariff impact.

Service as a Strategic Imperative

In response to these challenges, service must be recognized as a central component of industrial resilience. Here are key ways service can support companies through uncertainty:

  • Leverage the Installed Base: Focus on creating more value from existing assets through maintenance contracts, upgrades, and performance-based services.
  • Deliver Revenue Predictability: Recurring service revenues help smooth cash flow and hedge against drops in product sales.
  • Increase Customer Stickiness: High-touch service builds stronger relationships, making customers less likely to switch.
  • Differentiate Through Asset Optimization: Helping customers maximize uptime and efficiency adds measurable value—enabling premium pricing and long-term contracts.
Six Key Levers for Service Optimisation

To make the most of this strategic opportunity, service leaders must take concrete action. Here are six high-impact levers to focus on:

1. Align the Service Portfolio to Customer and Market Realities

A static service portfolio is no longer sufficient. Service leaders must reassess their offerings based on:

    • Customer needs across lifecycle stages
    • Segment-specific pressures and expectations
    • Economic conditions and regional constraints

Companies increasingly use predictive maintenance, IoT-enabled monitoring, and advanced analytics to deliver smarter service. But there’s an additional benefit: these digital tools enable knowledge to cross borders without being taxed. In volatile trade environments, this becomes a unique strategic asset.

2. Drive Operational Efficiency in Service Delivery

Margin pressure demands that service organizations work smarter. Key efficiency improvements include:

      • Field Force Optimization: Use AI to schedule technicians more effectively, reduce travel time, and increase job density.
      • Parts Management: Improve forecasting and local sourcing to reduce inventory costs while maintaining availability.
      • Process Automation: Automate service workflows, from diagnostics to billing, to cut overhead and speed up response times.
3. Move Toward Outcome-Based Service Models

Customers are increasingly focused on results, not transactions. Moving beyond traditional break-fix models, progressive service providers offer contracts tied to:

    • Uptime guarantees
    • Productivity metric
    • Output or efficiency benchmarks

These models reward both parties when performance improves. Critically, they also shift the basis of value from hardware to know-how—making service even more central to the customer relationship. And as knowledge flows digitally and delivery happens locally, these models are less affected by cross-border complexities.

4. Invest in Digitalization and Advanced Technologies

Digitalization isn’t just about efficiency—it’s about resilience. Technologies that deserve investment include:

    • AI and Knowledge Management: Automate decision-making, diagnostics, and knowledge transfer across global operations.
    • Digital Twins: Simulate equipment performance to optimize service schedules and predict failures.
    • AR/VR Tools: Enable remote troubleshooting, technician training, and customer self-service—even across borders.

These investments enhance productivity, reduce travel and shipping, and enable local support in decentralized markets—all of which reduce tariff risk.

5. Rethink Geographic Strategy and Market Focus

In a fragmented global environment, your service footprint matters more than ever. Leaders should evaluate:

    • Regional Hubs: Establish service centers close to major customer concentrations to reduce response times and logistics costs.
    • Localized Supply Chains: Partner with local vendors for spare parts to reduce tariff exposure and delivery lead times.
    • Strategic Alliances: Collaborate with local service providers where in-house presence isn’t feasible.
    • Remote and Nearshoring Solutions: Use digital tools to minimize the need for cross-border technician movement and support.
6. Build Resilient and Value-Based Pricing Strategies

Cost inflation from materials, labour, and logistics is inevitable in trade disputes. Pricing models must evolve accordingly:

    • Value-Based Pricing: Charge based on the customer’s perceived benefit—uptime, reliability, risk reduction—rather than input costs.
    • Tiered Service Packages: Offer options with different levels of service, speed, and scope to match customer willingness to pay.
    • Indexed Contracts: Link pricing to cost indices or inflation measures to maintain margin without renegotiating contracts.

Transparent, performance-based pricing builds trust—even as economic conditions change.

The Road Ahead: Service as a Margin Engine

As industrial markets grapple with unpredictable global conditions, service will continue to move from the margins to the core of strategic thinking. The service business not only offers resilience but provides a platform for sustainable differentiation.

The smartest service leaders will not just react to this shift—they’ll use it to assert greater influence in shaping company direction. By optimizing service operations, embracing digital transformation, and focusing on customer outcomes, they can help their companies navigate uncertainty and come out ahead.

Most importantly, they will find new ways to balance local presence, digital innovation, and customer intimacy in a world where tariffs and disruption are part of the new normal.

Final Word

Service is no longer an afterthought—it’s a driver of both profitability and strategic flexibility. For industrial businesses, now is the time to invest in smarter service models that maximize value, minimize risk, and turn volatility into opportunity. The need to assess operations and the service portfolio (which is where Si2 can help you!)  has never been greater

For service executives, the choice is clear: prioritize margin, build resilience, and lead your organizations through the uncertainty. Because in the next decade, service won’t just support the business—it will be ‘the business!’

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Service Innovation for value-driven opportunities:

Facilitated by Professor Mairi McIntyre from the University of Warwick, the workshop explored service innovation processes that help us understand what makes our customers successful.

In particular, the Customer Value Iceberg principle goes beyond the typical Total Cost of Ownership view of the equipment world and explores how that equipment impacts the success of the business. It forces us to consider not only direct costs associated with usage of the equipment such but also indirect costs such as working capital and risks.

As an example, we looked at how MAN Truck UK used this method to develop services that went beyond the prevailing repairs, parts and maintenance to methods (through telematics and clever analytics) to monitor and improve the performance and  fuel consumption of their trucks. This approach helped grow their business by an order of magnitude over a number of years.

Mining Service Management Data to improve performance

We then took a deep dive into how Endress + Hauser have developed applications that can mine Service Management data to improve service performance:  

Thomas Fricke (Service Manager) and Enrico De Stasio (Head of Corporate Quality & Lean) facilitated a 3 hour discussion on their journey from idea to a real working application integrated into their Service processes. These were the key learning points that emerged:

Leadership

In 2018 the Senior leadership concluded that to stay competitive they needed to do far more to consolidate their global service data into a “data lake’ that could be used to improve their own service processes and bring more value to customers. As a company they had already seen the value of organising data as over the past 20 years for every new system they already had a “digital twin” which held electronically all the data for that system in an organised fashion. Initially, it was basic Bill of Material data, but has since grown in sophistication. So a good start but they needed to go further, and the leadership team committed resources to do this.

  • The first try: The project initially focused on collecting and organising data from its global service operations into a data lake.  This first phase required the development of infrastructure, processes and applications that could analyse service report data and turn it into actionable intelligence. The initial goal was to make internal processes more efficient, and so improve the customer experience. E+H looked for patterns in the reports of service engineers that could:
    • Be used to improve the performance of Service through processes and individuals
    • Be used by other groups such as engineering to improve and enhance product quality.
  • Outcome: Eventhough progress was made in many areas, nevertheless, even using advanced statistical methods, they could not extract or deliver the value they had hoped   for from the data. They needed to look at something different.
  • Leveraging AI technologies: The Endress+Hauser team knew they needed to look for patterns in large data sets. They had the knowledge that self-learning technologies that are frequently termed as AI, could potentially help solve this problem. They teamed up with a local university and created a project to develop a ‘Proof of Concept’. This helped the project gain traction as the potential of the application they had created started to emerge. It was not an easy journey and required “courage to trust the outcomes, see them fail and then learn from the process”. However after about 18 months they were able to integrate the application into their normal working processes where every day they scan the service reports from around the world in different languages to identify common patterns in product problems, or anomalies in the local service team activities. This information is fed back to the appropriate service teams for action. The application also acts as a central hub where anyone in the organisation can access and interrogate service report data to improve performance and develop new value propositions.
  • Improvement:  The project does not stop there. It is now embedded in the service operations and used as a basic tool for continuous improvement. In effect, this has shifted the whole organization to be more aware of the value of their data.

Utilizing AI in B2B services

Regarding AI, our task was to uncover some of the myths and benefits for service businesses and the first task was to agree on what we really mean by AI among the participants. It took time, but we discovered that there are really two interpretations which makes the term rather confusing. The first is a generic term used by visionaries and AI professionals to describe a world of intelligent machines and applications. Important at a social & macroeconomic level, but perhaps not so useful for business operations -at least at a practical level. The second is an umbrella term for a group of technologies that are good at finding patterns in large data sets (machine learning, neural networks, big data, computer vision), that can interface with human beings (Natural Language Processing) and that mimic human intelligence through being based on self-learning algorithms. Understanding this second definition and how these technologies can be used to overcome real business challenges is where the immediate value of AI sits for today’s businesses. It was also clear that the implication of integrating these technologies into business processes will require leaders to look at the change management challenges for their teams and customers.

To understand options for moving ahead at a practical level we first looked briefly at Husky through an interview with CIO Jean-Christophe Wiltz to CIOnet where we learned that i) real business needs should tailored drive technology implementation, and ii) that before getting to AI technologies, there is a need to build the appropriate infrastructure in terms of database and data collection, and, most importantly, the need to be prepared to continually adapt this infrastructure as the business needs change.