Operational Performance

Streamline service operations chain to enhance quality, enable innovation and deliver profit

The challenges leaders of change typically encounter when striving to ensure the key success enablers are in place include:

  • Operational inefficiencies that drain margins and erode customer satisfaction

  • Inability to scale service delivery effectively

  • Poor visibility into performance drivers and cost structures

  • Resistance to change and fragmented ownership of service processes

  • Misalignment between operational execution and strategic priorities

Superior operational performance alone doesn’t guarantee market success—but without it, service strategies falter. At Si2, we help organisations turn service operations into a strategic asset that enables agility, responsiveness, and profitable growth.

Our programmes improve speed, quality, and cost-efficiency across the entire service value chain—frontline to back-end, suppliers to channel partners. Our focus extends beyond process redesign to transforming the entire operating system, mindsets, and behaviours required for sustained excellence.

From the Service Leadership team to field service supervisors, teams must be aligned around shared goals, performance management routines, and accountability at every level. We work with organisations to reduce complexity, increase asset productivity, and drive improvements in resource utilisation and customer experience.

The approach must be rigorous, data-driven, and results-oriented—ensuring the performance foundation necessary to scale, adapt, and lead in service-driven markets.

Key focus areas:

  • Operations Strategy
  • Lean Service Management
  • After Sales Services
    • Installed Base Management
    • Field Service
    • Spare Parts & Logistics
    • Service Workshop Management
    • Contract Site Management
    • Subcontractor Management
    • Warranty Management

Si2 Enabler Programmes

Service Value Sales Programme

Transforms professionals from feature to value selling - From a customer 'push' to a 'pull' mindset

Service Value Sales Programme

Brings sales & service teams together to create a compelling service sales process & tools
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Service Blueprint

For teams to deliver service excellence by identifying critical touchpoints, key customer decisions and the flow of Information

Service Blueprint

Optimising value at each customer interaction

Service Business Assessments

For teams looking to deliver service excellence through a better understanding of their processes

Service Operations Assessment

A mix of proven ools such as Portfolio Check, Sanity Check, Installed Base, Service Leaders Network
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Insights

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.