The Si2 Team

Si2 Partners helps clients win in industrial markets -mainly, but not only, through leveraging services. We work globally across various industries and offer consulting solutions, training, and business execution support.

We also operate the Service Leaders Network, a subscription-based community providing experience and knowledge sharing as well as collaborative problem-solving to senior managers and practitioners in our field. 


Our partners and associates combine many years of managerial, consulting and technical expertience and are recognized leaders in their fields. We speak the language of our clients and have shared the challenges and opportunities they face. 

Our unique blend of experience and deep smart expertise in our areas of practice and industries we serve sets us apart.

Harald Wassermann

Areas of Expertise: Service Sales Management, Organizational Transformation, Service and Field Service Operations and Performance Management

Active as a consultant over 15 years, Harald specializes in helping clients unleash their true service potential combining strategy, operations, process and change management in a holistic business (re-)engineering approach. He has worked with numerous medium sized and large companies in Germany, Europe and around the world in diverse industries, including materials handling, plastics processing, food processing, and heavy electrical and mechanical engineering and manufacturing.

Peter Maier

Areas of Expertise: After Sales Services, Service Operations Strategy, Service Performance Management, Technology, Lean Six Sigma Service Management, Spare Parts Management

Peter Maier is an expert in service operations, logistics and parts management. He also specializes in implementation of advanced technology to support services operations and enhance productivity -such as Augmented Reality, Knowledge Management and Service Management Systems. Peter has worked with major companies in industries such as earthmoving and agricultural machinery, warehousing systems and services, F&B processing machinery and many others. 

Titos Anastassacos

Areas of Expertise: Strategy, After Sales Services, Outcome based Services, Service Performance Management, Sharing Economy

Titos Anastassacos has many years international experience in operations, strategy, and business transformation consulting. He specializes in business modeling and strategy, business development, outcome-based services, and service performance management. His clients include a wide range of companies, from capital goods manufacturers to utilities, energy and infrastructure service providers, and digitally native startups building service platforms. 

Nick Frank

Areas of Expertise:
Go-To-Market, Innovation, Design, Organizational Transformation, Service Operations Strategy

Nick Frank has been working as an international consultant for over ten years, specializing in service strategy development, servitization business models, innovation management, service operations, and business development for companies in engineering, manufacturing, equipment manufacturing, and technology. He is also an expert coach, trainer and workshop facilitator.

Philipp Schenkel

Areas of Expertise: Service Design and Development, Service Innovation, Marketing and Communication, Market and Customer Research, Program Management, Process Management

Philipp Schenkel is a consultant specializing in service design, development and innovation for the past five years for companies in manufacturing, engineering and technology sectors. 

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.

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