Rethinking Spare Parts: From Cost Centre to Strategic Engine of Resilience and Growth

What was once treated as a necessary operational cost is rapidly becoming a strategic lever for resilience, profitability, and customer retention. Volatile geopolitics, fragile supply chains, younger digital-first B2B buyers, performance-based contracts, and mounting sustainability expectations are converging to redefine what good looks like in spare parts.

The panel discussion between Aukusti Koivisto, Joseph Osta, Lisa-Maria Engert, and Lisa Hellqvist at Spare Parts Business Platform 2026 – Power of 50, reveals a sector in transition, moving from reactive to predictive, from siloed to integrated, from transactional sales to lifecycle value, and from linear consumption to circular models. Yet many organisations are still held back by legacy mindsets, poor data, and fragmented processes.

From necessary to strategic asset

Across many organisations, spare parts are still not recognised for what they already are, one of the highest-margin, most stable revenue streams in the industrial business model.

Several recurring issues point to a lingering cost-centre mentality:

• Parts are often treated as side-business by equipment sales teams, and sometimes dismissed as too expensive internally.  
• Financial functions frequently view spare parts inventory primarily as working capital to be minimised, pushing for stock reductions without always understanding service or uptime impact.  
• Production teams may see spare parts orders as a distraction from building new equipment, particularly when aftermarket and new equipment are not aligned in planning and priorities.  
• R&D for new equipment often designs for performance, not serviceability, leaving service and parts organisations to figure it out later at a much higher lifecycle cost.

The consequence is a structural underutilisation of spare parts as a strategic driver. Instead of being leveraged as a margin engine, a customer lock-in tool, and a data-rich source of lifecycle insight, parts remain trapped in organisational silos.

A more mature view recognises that customers do not distinguish between sales and service. They evaluate the OEM as one entity. If any gear in that experience fails, it influences their decision when purchasing the next machine.

Bridging the ambition–execution gap in predictive planning

Most organisations are now pivoting away from purely reactive inventory management towards predictive planning. But ambition often runs ahead of execution.

1. Data quality and availability  

Almost every discussion around predictive spare parts planning returns to the same foundational issue: data.

• Legacy systems, M&A histories, and decentralised operations have created fractured item master data and multiple truths.  
• Service data, such as failure records, intervention history, and field notes, remains particularly underutilised or unmanaged.  
• Global manufacturers are wrestling with multiple ERPs and inconsistent data definitions across regions and business units.

Many organisations are only at the beginning of their data journey, mapping what exists, improving quality, and consolidating into a single source of truth. Without this, even the most advanced forecasting or AI initiative will struggle.

2. Analytics and skills to go beyond history

Even when data exists, planning often remains anchored in historical consumption and simple rules. That leaves two critical blind spots:

• Infrequently demanded or long-tail parts, which are difficult to forecast through traditional methods.
• Demand patterns driven by external factors, not just past consumption.

But there is growing interest in new data sources and methods:

• E-commerce behaviour as a demand signal: What customers search, which parts are viewed but not bought, abandoned carts, and search terms can all indicate latent demand or misalignment in pricing, availability, or identification.  
• Operational indexes and external indicators: For example, tying parts demand to container movement indices in port and logistics equipment, or to operating hours and flight cycles in aviation.  
• Connected assets: Machine telemetry and condition monitoring as the next frontier in predicting failures and parts needs, particularly for low-frequency, high-impact components.

Spare parts planning must evolve from asking what happened in the past to what is likely to happen next, under different scenarios. Achieving that requires better data, a broader set of signals, and new skills in analytics and scenario-based planning.

Resilience, safety stock, and the new risk calculus

Resilience has become a buzzword across supply chain discussions, but for spare parts leaders, it is an everyday operational reality.

Recent years have exposed the fragility of over-optimised inventories. Successful cost-cutting and stock minimisation translated into severe service risks when Covid-19, shipping disruptions, and sudden tariff changes hit. Manufacturers found themselves working double shifts just to locate or expedite critical parts, and in some cases were unable to fulfil contractual uptime promises.

Two competing pressures now define the resilience debate:

• Commercial and contractual risk: Performance-based and uptime-based service contracts mean that downtime is no longer just a customer problem, but a direct financial exposure for the OEM or service provider.  
• Financial pressure on working capital: Finance functions still expect lean inventories and strong balance sheet performance.

To rebalance these forces, several pragmatic approaches emerge:

• Moving beyond blanket stock optimisation: Rather than across-the-board reductions, organisations are reintroducing or recalibrating safety stocks based on criticality and risk. Simple but disciplined ABC and criticality analyses, applied market by market, become powerful tools for aligning service levels and capital deployed.  
• Using scenario planning: Instead of assuming stable conditions, leading organisations are testing multiple disruption scenarios, geopolitical, logistics, supplier concentration, and designing inventory and sourcing policies around those.
• Creating explicit resilience playbooks: Including predefined priorities when supply is constrained, decision rules for which customers, regions, or contracts get limited parts first, and how to temporarily reallocate stocks between business lines.

Resilience is shifting from an implicit aspiration to a deliberate capability. Spare parts leaders are increasingly asked not only to optimise inventory, but to explain what level of risk the organisation is accepting, and to demonstrate readiness when the next disruption hits.

Pricing: the most visible and least mature lever

While spare parts already deliver strong margins in many industrial businesses, the commercial potential remains far from exhausted.

Pricing emerges repeatedly as the most powerful yet underdeveloped lever:

• Static, cost-plus pricing persists, often disconnected from market dynamics, competitive benchmarks, and lifecycle value.  
• Price levels are sometimes set centrally and left unchanged for long periods, leading to parts that are either overpriced and unsold or underpriced and eroding margins.  
• A fixation on high margins per part can obscure the fact that an unsold part with a high theoretical margin contributes nothing, while a slightly lower margin on a sold part generates real profit and customer retention.

The shift now underway is towards more dynamic, segmented, and value-based models:

• Differentiated pricing by customer segment, contract type, and criticality.  
• Market-aligned pricing based on competitive intelligence and willingness-to-pay, rather than only cost-plus approaches.  
• Integration of delivery performance and reliability into the value proposition, allowing organisations to justify premiums for guaranteed availability or faster lead times.

Spare parts are also moving away from purely transactional sales towards longer-term constructs such as preventive maintenance agreements and, in the longer term, parts-as-a-service concepts. Although the latter are still nascent and complex to implement, the more parts are embedded into contracts and outcomes, the more pricing becomes strategic rather than purely tactical.

Circularity and refurbished parts: potential with conditions

Circular models like refurbishing, remanufacturing, and reusing parts are gaining attention as a way to align sustainability goals with commercial advantage.

However, success in circular spare parts is highly conditional:

• Customers will only choose refurbished parts if they see a compelling price differential, shorter lead times, and comparable performance and warranty conditions.  
• If refurbished parts are available only sporadically or with uncertain lead times, the value proposition collapses. Customers prioritise uptime over sustainability symbolism.  
• Many organisations are starting with specific categories, such as electrical or high-value components, testing feasibility and economics before scaling.

Remanufacturing and refurbishment also require significant investment in capabilities, logistics, and reverse flows. Some companies are further ahead and are already integrating circular offerings into their value proposition. Others still see it as a medium-term ambition constrained by cost and complexity.

Yet, as supply volatility persists and sustainability regulation tightens, circular spare parts models are likely to become less optional and more structural to competitive differentiation.

Connected assets and the expectations gap

Connected equipment and digital platforms are often presented as the key to unlocking frictionless service and spare parts experiences. The reality on the ground is more nuanced.

Customers increasingly behave like digital consumers, expecting to find information quickly, self-serve when convenient, track orders, and access performance data in real time. This extends to parts identification, availability checks, ordering, and logistics visibility.

In response, many manufacturers are building:

• Digital platforms where customers can search and identify parts, verify compatibility with specific serial numbers, and place orders online.  
• Installed base dashboards showing operating hours, shocks, fuel consumption, or driving behaviour, connecting asset performance directly to service and parts recommendations.  
• Smart recommendations, using connectivity data to trigger proactive parts suggestions or maintenance interventions.

These developments show strong promise. Yet several gaps between expectation and reality remain:

• Connected asset penetration is still relatively low as a share of total installed base, limiting the impact of advanced solutions.  
• For many machines, the basic challenge of identifying the right part in an ageing or modified environment remains unsolved if documentation and master data are not robust.  
• A sizeable portion of customers still prefer to call the trusted salesperson or service contact rather than transact entirely via digital channels.

The most effective approaches seem to embrace hybridity rather than forcing a digital-only experience. Digital tools are used to enhance, not replace, human expertise:

• Online catalogues and configurators support error-free identification, even when orders are ultimately placed via phone.  
• Sales teams are encouraged to use the e-commerce platform as their own ordering backbone, ensuring that even phone-based orders generate usable data and insights.  
• Service technicians and back-office experts are supported by digital knowledge bases and installed base visibility, but remain the escalation point for complex or catastrophic failures that cannot be standardised.

The long-term vision of assets autonomously ordering their own parts, and systems orchestrating service flows end-to-end, is widely shared. But delivering value today means incrementally building trust, reliability, and integration between digital experiences and human interactions.

Data: the non-negotiable foundation

Perhaps the most striking point of consensus is that data is both the industry’s biggest obstacle and its greatest untapped asset.

The phrase “messy data” recurs with almost comic regularity across organisations, regardless of size or sector. Core issues include:

• Fragmented item masters, inconsistent naming and coding conventions, and duplicated records.  
• Disconnected systems for sales, service, logistics, and finance, each maintaining its own version of reality.  
• Under-captured or unstructured service data, including technician notes, installed base changes, and field modifications.

No advanced initiative will succeed without addressing foundational data. Whether the ambition is predictive planning, AI-driven recommendations, or dynamic pricing, poor data quality will erode benefits and trust.  

Data strategy is as much organisational as technological. Breaking down data silos often starts with people talking to each other, bridging functions such as sales, service, supply chain, finance, and R&D. Simple acts like aligning on definitions and processes can unlock substantial value. 

Return on investment must be explicit. Cleaning data and consolidating systems is hard work. Organisations increasingly ask what tangible business outcomes will justify the effort. Those who move fastest will be those who can clearly link data initiatives to measurable results.

What the next generation of spare parts leaders must prioritise

As spare parts move to the centre of industrial transformation, the profile of effective leadership in this sector is changing. Several capabilities and priorities stand out as essential:

Shift from past-focused to future-oriented thinking

Planning and decision-making must move beyond what was sold in the past towards scenario-based thinking, external signals, and predictive models that anticipate where demand and risk will emerge.

Treat pricing as a strategic instrument  

Pricing cannot remain a static, back-office exercise. It must become dynamic, segmented, and tightly linked to value delivered, including delivery reliability, contractual commitments, and lifecycle outcomes.

Design resilience, not just efficiency  

The goal is not simply to minimise stock, but to consciously balance cost, risk, and service. This requires clear trade-offs, explicit playbooks for disruptions, and proactive dialogue with finance and leadership.

Integrate digital and human experiences  

E-commerce, self-service portals, and connected asset platforms are critical for scale. But they must be designed to work with trusted human relationships that remain central in B2B.

Build an end-to-end data and process view  

Spare parts leaders need to see beyond their functional silo, connecting insights from installed base, service, inventory, procurement, logistics, and pricing into an integrated perspective on lifecycle value.

Embed sustainability and circularity into the model  

Refurbished and remanufactured parts, closed-loop supply chains, and eco-incentivised service contracts are becoming core components of competitiveness and resilience.

In turbulent markets, spare parts are no longer just something customers reluctantly buy when something breaks. Managed strategically, they become the backbone of uptime guarantees, a rich source of customer and asset insight, a differentiator in sustainability, and a major contributor to margin.

The organisations that recognise this and equip their spare parts leaders with the mandate, tools, and cross-functional support to act accordingly will be the ones that turn today’s volatility into tomorrow’s advantage.