On the Road: Summer thoughts from Si2 clients

From Machines to Meaningful Partnerships: Lessons from the Summer Road

This summer, Si2’s Peter Schoenle spent an extraordinary amount of time meeting clients and attending trade fairs. We asked him to summarise what he observed so you can get a sense of what your peers are doing and experiencing.

…….This spring and summer, I’ve been on the road—visiting clients, walking trade fair aisles, and listening to leaders in mechanical engineering share their hopes, worries, and frustrations. It’s been a revealing journey, one that tells a clear story about the shifting ground beneath our industry.

If you’re a small or mid-sized mechanical engineering company, you probably feel it too: the old formula of delivering a great machine and handing over the keys is no longer enough. Customers expect more. Service is no longer an afterthought; it’s increasingly the heart of the relationship. And those who fail to adapt risk falling behind.

The End of “Just Delivering the Machine”

The conversations I’ve had with clients paint a consistent picture. Delivering a machine into the customer’s yard and walking away is not an option anymore. Customers want—and often need—support in getting the most from their investment.

Why? Because the machine is just one part of their success. It’s the uptime, the reliability, the training of operators, and the seamless integration into production that determine whether the machine creates value. If these aspects don’t go smoothly, the stress falls squarely on the customer’s shoulders. And when customers are under pressure, they pass that stress back to the manufacturer.

For smaller companies with lean service organizations, this creates a dangerous cycle of firefighting unplanned problems. In a world already strained by demographic shifts and limited resources, that’s a recipe for burnout.

The message is clear: expanding customer collaboration across the entire life cycle is not optional—it’s the only way forward.

Service as a Buying Criterion

What struck me most in recent months is how service is becoming a decisive factor in purchasing decisions. Customers don’t just ask, “What can your machine do?” They ask, “How will you support us in using it successfully?”

That means manufacturers need to think differently. Winning a project is no longer about product performance alone; it’s about positioning yourself as a partner from day one. The real measure of success is not delivery but successful use.

The handover moment is especially critical. Too often, the transition from engineering and sales to the customer’s production team is treated as a formality. In reality, it’s the foundation of the customer’s trust. Get it right, and you build loyalty. Get it wrong, and every hiccup that follows will erode confidence.

Here, structured service packages—what we call Smart Service Packages—can make all the difference. They shift the focus from unpredictable emergencies to planned, proactive support. This not only reduces ad hoc crises but also stabilizes relationships and creates loyalty.

And loyal customers? They always pay off.

Trade Fairs Without Service

This spring, I also spent time at some of the biggest trade fairs in our field—HANNOVER MESSE, LogiMAT, and others. These fairs are known for showcasing product innovations, and they certainly didn’t disappoint in that respect. Gleaming new machines, technical upgrades, digital dashboards—every stand competed for attention.

But here’s what puzzled me: service was almost invisible.

In stand after stand, I saw little or nothing about after-sales, customer support, or lifecycle services. And when I asked exhibitors about it, many stumbled to give a clear answer. For me, that silence speaks volumes.

It may sound provocative, but I’ve come to a blunt conclusion: if you don’t present your service strategy at a trade fair, you don’t have a plan.

Because service is no longer a side topic. It’s a core part of how customers choose partners. If your competitors are talking about services and you aren’t, what message are you sending to the market?

The Digital Services Hype—And the Risk of Shipwreck

Of course, no discussion of today’s industry would be complete without digital services. From predictive maintenance tools to IoT dashboards, new solutions are being launched almost daily. The energy in this space is exciting—but also a little chaotic.

Here’s the risk: many digital services are being pushed to market without a clear business model. Too often, companies pour money and resources into implementing a tool, only to discover later that they can’t monetize it—or even prove its value to the customer.

Why does this happen? I see three common patterns:

  1. Implementation over impact. Companies focus on getting the solution running but don’t ask who benefits, how, and in what concrete financial terms.
  2. Lack of insight. Few organizations truly understand how different customer groups use their machines and how digital services might change that usage—whether through fewer malfunctions, shorter downtimes, or better output.
  3. Weak value proof. Even when benefits exist, they are rarely quantified in a way that convinces the customer. Mechanical engineering sales traditionally emphasize core functionality, not added-value economics.

The result? Many digital initiatives drift like ships without a compass—lots of movement, little progress.

Building Digital Services That Work

So, what’s the alternative? It starts with something deceptively simple: a clear business model.

When my colleague Harald Wassermann and I work with clients on this topic, we encourage them to build their thinking around four key points:

  • The market perspective—understanding the needs of both customers and providers, today and tomorrow.
  • The value proposition—what tangible benefits the service creates, and for whom.
  • The monetary impact—how those benefits translate into real financial outcomes for the customer and for the provider.
  • The resources required—what contributions are needed from both sides to make the proposition sustainable.

This kind of disciplined thinking is hard work. But without it, companies risk endless pilots, frustrated sales teams, and customers who remain unconvinced. With it, digital services become not just tools but growth engines.

Sailing Toward Loyalty

As I reflect on the miles traveled and the countless conversations I’ve had this year, one message stands out: we are moving from an industry of machines to an industry of meaningful partnerships.

Success will not come from the next big technical feature alone. It will come from how well we collaborate with customers across the lifecycle, how clearly we articulate the value of services, and how boldly we integrate service into our strategy.

Those who embrace this shift will build loyal customers, stable revenues, and resilient businesses. Those who don’t may find themselves endlessly sailing, without ever reaching land.

The choice, as always, is ours!

best regards

Peter Schoenle
[email protected]

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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.