Growth in aftermarket products and services remains one of the most significant untapped revenue streams for industrial-equipment companies. From software and spare parts to additional services and extended-warranty programs, these industrial aftermarket opportunities potentially represent billions of dollars in unlocked revenues in many industries.
The importance of services is borne out in the data: companies with significant services businesses deliver outsize returns to shareholders compared with those with lower services penetration, and organizations can realize margins that are up to four times higher on services than are typical in their equipment businesses. In medical technologies, for example, an analysis of ten-year growth patterns showed that each additional percentage point by which services businesses grow over product businesses correlates to an increase in enterprise value of about 50 percent (Exhibit 1).
Moreover, sales efforts can be more targeted because services are typically sold to an installed base that OEMs already know and can closely monitor. That typically yields a higher ROI and faster time to impact than most new equipment-growth opportunities. Indeed, the experiences of several industrial manufacturers show that service-related initiatives can often deliver value within three to six months, from conceptualization to execution and bottom-line impact.
Yet even though the opportunity is real, so too are emerging threats. The consumerization of the B2B experience (and growing expectations for seamless customer experience) is putting OEMs’ service businesses at risk in favor of faster, more nimble competitors, ranging from local mom-and-pop businesses to large, specialist service providers. At the same time, the shift to omnichannel and virtual sales can lead to fewer personal interactions, making it more important to deliver consistently across the customer journey.
The better news is that aftermarket organizations can prepare themselves for this transition. Some are already there: growing capabilities, high adoption of extensible customer-relationship-management (CRM) tools, and an increasingly large ecosystem of solutions make digital and analytics easier, less expensive, and less cumbersome to deploy. In fact, about 60 percent of surveyed aftermarket executives say they have deployed one or multiple use cases at scale beyond a pilot phase.
Building a tech-enabled aftermarket commercial engine
The organizations that have been successful in systematically delivering consistently high aftermarket growth rates execute a set of five levers that collectively form a differentiated commercial engine (Exhibit 2). Pioneers have leveraged digital and analytics to power each component of the commercial engine, increasing both the effectiveness and efficiency of their sales force and network of distributors or dealers.
A closer look at these success stories uncovers a significant number of use cases that accelerate revenue and margin growth while involving only limited investment and time to impact—the latter measured in months or even weeks. Many of these use cases can be deployed across a wide range of aftermarket settings, including in environments where indirect channel partners play a major role in selling and delivering services.
Lever 1: A granular view of opportunity at the customer level
To fully capitalize on their aftermarket sales potential, organizations can first establish a clear picture of individual opportunities at the customer level. Analytics can measure the “gap to entitlement,” or the proportion of a customer’s aftermarket spend that the company is not capturing—and subsequently generate and prioritize sales leads. These approaches can help answer critical questions that many OEMs struggle with:
- Where is my installed base and how is it being operated?
- What services could be consumed (the full entitlement)?
- What services are being consumed (share of entitlement)?
- What are the highest potential opportunities across the installed base to drive additional growth?
Analytics can measure the “gap to entitlement,” or the proportion of a customer’s aftermarket spend that the company is not capturing—and subsequently generate and prioritize sales leads.
Scraping data to estimate installed base. One large industrial player wanted to better identify aftermarket growth opportunities for its parts and components but was challenged by the limited data shared by its distributors and limited visibility on the installed base. Working with the sales organization, a dedicated team scraped data from the internet and enriched the transactional database with fields on installed base size. They then built analytics to benchmark distributors’ performance and estimate an entitlement share by product line. This approach identified a potential revenue uplift of about 15 to 25 percent, and armed distribution managers with individualized distributor scorecards to better drive performance reviews.
Measuring propensity to buy. An inside sales team can use propensity-to-buy analytics to discover whether customers are interested in aftermarket products and services. A global medtech company with an established equipment-maintenance offering was struggling with low contract-attach rates for its services. To help the sales force prioritize leads, the company mobilized a team to evaluate customer data including the customer’s subsector, equipment-servicing history, and buying behavior across equipment. From these sorts of data points, the team built an algorithm that predicted each customer’s likelihood of purchasing a maintenance contract. In parallel, managers made sure to assign salespeople based on their depth of knowledge of the specific product and customer end-market knowledge. By increasing effort on a more targeted set of prospects, the company increased overall sales by 15 percent.
Using technology to monitor equipment use. A further example comes from a specialized-equipment supplier that sought to drive sales with authorized dealers and service providers. The company developed a QR code and a digital platform to support logistics tracking and equipment start-up and expanded it to serve field technicians with potential leads. Every unit in manufacturing was assigned a QR code to help track all activities throughout a product’s lifespan. Service technicians scanning the QR code were offered additional leads to qualify during their site visit, all managed in the back end by a marketing team.
Lever 2: Unique offers that meet customer needs
Digital and analytics can support marketing and services product-management organizations in adjusting their offering to meet constantly evolving customer needs.
Finding new service approaches. Analytics have unlocked new as-a-service business models, as at a leading industrial player that sought to develop additional revenue streams from its installed base of connected equipment in the field. The company created an analytics engine to predict failures and false alarms, then offered a customer-facing version as an annual subscription service. The subscriptions not only drove an increase in revenue but, more importantly, also helped the OEM identify opportunities to sell product upgrades, replacement parts, and other services. The pull-through value of these ancillary sales ultimately ended up being worth much more to the business than the subscription revenue itself.
Segmenting customers for tailored offers. Analytical tools can also help organizations better build needs-based offerings. A medtech company wanted to increase attach rates on its installed equipment base but was anchored to a service offering designed around a single plan. Competitors with a high focus on services had recently transitioned to à la carte offerings tailored to customer needs. In response, the company’s product-management team defined a needs-based segmentation and launched analytics research, using a mix of customer surveys and focus groups conducted with the sales organization. The team assessed the fit of offerings, tested features, and quantified customers’ willingness to pay, then refined the service offerings around multiple tiers with updated pricing schemes. The analytics enabled the team to measure accurate impact from the company’s transition to the new offering—and better translate customer needs into specific features. The company is targeting a five to ten percentage-point increase in attach rates as a result.
Lever 3: A sales force that relentlessly pursues the top opportunities
To make the most of these opportunities, top organizations look to a customer-aligned sales force with accountability to focus on core aftermarket selling and tactical account planning.
Revamping coverage models. Analytics can help optimize aftermarket sales coverage across geographies and accounts. A leading industrial-equipment OEM with a dedicated aftermarket sales force had gone through multiple reorganizations of its sales force but wanted to support more aggressive aftermarket targets. It ultimately built a customer data cube that pulled from CRM systems, sales reports, and external data, then used clustering algorithms to size the aftermarket potential at each account and assess the share of wallet (or, conversely, growth potential) across thousands of accounts globally. In initial pilots, the new approach to sales coverage led to an immediate increase of 5 to 10 percent in sales productivity and also improved outreach to the installed base. At a larger scale, the OEM could better identify resource needs for the best aftermarket coverage of accounts.
Understanding sales relationships further down the value chain. Increasing service sales can be especially challenging for manufacturers that rely on third-party sellers to reach end customers. Nevertheless, these OEMs can follow a similar process to understand the impact on sales outcomes of their seller’s interactions with end users’ internal stakeholders. These insights can be particularly critical in subsectors where sellers bring a broad and complex offering portfolio to clients and require extensive support from technical sales. That was the situation for a leading national distributor that sought to understand win rates and sales drivers. After creating a data cube pulling from more than 20 tables, the company’s data scientists developed machine-learning models to identify predictors of sales outcomes. Their work uncovered that sellers’ interactions with the right technical sales reps were a high predictor of win rates. Better matching of sellers with the right tech rep counterparts ultimately led to a more than $40 million increase in sales.
Deploying automation. A multinational machine tool builder with a fragmented installed base, low aftermarket ticket per unit, and a lean inside-sales aftermarket team sought to create a sales campaign at scale. The company built a low-cost digital stack to automate the sales outreach using mostly off-the-shelf third-party solutions. The stack consisted of an installed base repository using machine learning to mine shipment and CRM data. Algorithms were then layered to generate leads while an intelligent-assistant bot automated outreach and qualified responses before forwarding them to an actual salesperson. This combination generated 20 percent more leads and created 20 percent extra bandwidth for the inside-sales team, allowing the OEM to better cover its installed base.
Lever 4: The right price to maximize value
Finding the right prices for aftermarket services can help align organizations’ offerings with customer needs. Analytics can play a critical role by analyzing nontraditional data sources for crucial competitive insights.
Pushing beyond transaction data. To optimize its spare-parts pricing, a leading industrial player built a transactional data cube, which it enriched with further information that influences pricing—such as competitive intensity, criticality to equipment, and replacement life cycle. The organization then developed a set of analytics to identify opportunities and levers in pricing architecture and discount management. By designing a live-pricing dashboard to track leakage, the company was able to take action across sales reps, value levers, and customers, yielding top-line sales increases of between 3 and 5 percent.
Reassessing which variables matter. In another example, a leading OEM wanted to address high variability in pricing realized on maintenance and repair transactions after aligning sales force incentives to margin realization and tightening delegation of authority rules did not yield expected results. The challenge in implementing stronger pricing rules was the unique context for each deal. After building a data lake, each maintenance and repair deal was assigned a long list of descriptive characteristics such as location, customer segment, prior buying behavior, deal scope, and net promoter score (NPS) history. Advanced analytics algorithms highlighted six variables that explained most of the variance, which the OEM commercial team validated. A pricing recommendation tool was integrated into the CRM to provide real-time guidance to sales teams, and a more sophisticated delegation of authority process accommodated more deviations from the algorithm’s recommendations. This dynamic scoring model reduced variance in margin by more than five percentage points while boosting average margin by four percentage points.
Lever 5: An outstanding customer experience
OEMs can finally leverage digital and analytics to improve the customer experience, as at a global industrial OEM that realized the complexity of its touchpoints with end customers was depressing customer experience scores and revenue. The company developed a taxonomy of six essential customer journeys and prioritized the most critical pain points together with a set of digital interventions to address the most important issues. The analytics showed that customers that received poor service tended to churn much faster and bought fewer services, for a total potential revenue increase of more than 25 percent. The effort also revealed that small customers were the largest source of growth, rather than the large ones the executive team tended to focus on. This ability to quantify the business importance of experience let the organization create a compelling business case to address experience issues that had long slipped through the cracks.
A large advanced-industries manufacturer provides a further example: it had created a B2B e-commerce platform for parts sales, but the end-to-end process for customers purchasing parts remained complicated. By using design thinking, the company uncovered pain points in the customer journey and substantial leakage in parts orders. A customer-friendly redesign brought the online part-ordering portal up to the highest standard in B2C online sales—increasing revenue from existing customers by 3 percent in the first year and 10 percent in the second.
Capturing the value
While individual digital and analytics use cases offer significant value, the greatest benefits come from driving a technology road map that helps capture benefits at the system level. A doubling in EBITDA over three years is not uncommon for organizations that get it right. But the experiences of companies that have successfully deployed these use cases underscore several elements that are critical for success:
- Identify and prioritize use cases based on business value and focus on those that will truly move the needle. While letting a thousand flowers bloom can spur innovation, focus is required to fully unlock competitive advantage.
- Go fast and think big. For almost all use cases, technology has matured to the point where development timelines can be measured in weeks and months, not years. Winners create dedicated cross-functional teams that can move fast and aim for major impact.
- Focus on adoption. The adoption and use of new commercial tools and approaches require real change from product teams, sales teams, and others. For business leaders, managing through this change and driving adoption is likely to be the single most important contribution to capturing value.
As digital and analytics technology becomes increasingly accessible to a broad range of organizations, we believe the deployment of these capabilities in the service of aftermarket growth will increasingly differentiate winning services organizations from those that fail to adapt.