Winning with TCO: Register 13-14th October 2026

Total Cost of ownership (TCO) is not a cost tool, but a decision-making principal that enables a Smarter Win-Win Path to Growth:

  • For operators: it helps identify ways of optimising cost-effectiveness, risk and sustainability over the life cycle of their assets
  • For machine manufacturers: it helps understand how to innovate new service models and increase share of after-market revenues

 

In short:

Those who focus solely on the purchase price optimise value in the short term – those who consider TCO, optimise value for both the asset user and asset provider over the entire lifecycle. For the equipment supplier the prize is to win after market revenues that often exceed the initial transactional sales price of the asset.

Productivity and availability take on a new significance. Factors such as system availability, ease of maintenance, as well as energy and resource efficiency, and sustainability are key influencing factors. TCO makes risks visible and enables them to be managed more effectively.

IMPORTANT: It all comes down to a collaborative relationship between customer and supplier.

These are challenges facing many companies, but they also present strategic opportunities to thrive in competitive markets.

Are you ready for this?

This event is designed for ‘doers’ who are open to new ideas, actively engage in discussions and thereby create space for thought-provoking questions. Through engaging discussions and workshops with professional peers, you will gain actionable insights and approaches to integrate the TCO mindset into the value proposition of your company.

Through in-depth discussions and pragmatic approaches, you will take away:

  • Factors influencing TCO
  • Approaches to generate acceptance internally and with customers
  • How to identify and manage risks
  • Identifying the benefits for the asset user – customer and for the company or asset provider.

Real-life experiences from industry leading professionals in their day-to-day work

Falk Möhr, Head of Global Customer Support, ZEISS Semiconductor Mask Solutions
and
Lena Heni, Head of Product Management Services MT – Parts & Tools, Trumpf

will act as catalysts for your questions through understanding:

  • why TCO is so important to them,
  • what challenges they face,
  • what problems they need to solve,
  • how they can build acceptance across all departments and with customers, and
  • how you and your team can approach customers and how success is achieved.

Together, we will develop approaches in workshops that will support you on your path to successful service agreements.

Why take part?

You will interact within an efficient framework of 12–15 service managers and practitioners in small working sessions. This will allow you to assess your current position and exchange ideas. You will discuss in small groups and develop approaches that you can apply to your day-to-day business.

You’ll make valuable new contacts with whom you can exchange ideas or work together on solutions in the future.

Read more about the Agenda and how to register HERE

Service in Industry

Deep Dive into the industrial service 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.