Aftermarket and
Lifecycle Development

Strengthens customer relationships and share of wallet over the product lifecycle

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

  • Underdeveloped strategies for installed base monetisation

  • Overreliance on high-margin spare parts with limited scalability

  • Lack of investment in service innovation, automation, and analytics

  • Fragmented alignment between product and service teams

  • Missed opportunities to leverage customer data for growth

As new product markets mature, service-led growth depends on unlocking the full potential of the installed base over it’s lifecycle. At Si2, we help companies shift from reactive support to proactive lifecycle value creation—turning after-sales into a powerful engine for loyalty, profit, and innovation.

Key is defining a clear service intent to strengthen the role of aftermarket within the organisation, and developing scalable, technology-enabled offerings. By bringing clarity to lifecycle value potential—from parts and maintenance to upgrades, digital services, and productivity enhancements, service leaders can improve commercial strategies, invest wisely in automation and data analytics, and enhance cooperation with product units. We support teams to build  the capabilities and structures needed to grow lifecycle revenues, defend market position, and deliver customer value long after the initial sale.

With smart aftermarket strategies, companies move beyond defensive service thinking—transforming the installed base into a platform for continuous growth.

Key focus areas:

  • Field Service Management
  • Technical Support
  • Spare Parts & Logistics
  • Warranty Management
  • Service Workshops Management
  • Contract and Site Management 
  • Outcome-based Services
  • Asset Management

Si2 Enabler Programmes

Service Value Sales

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

Service Value Sales

Brings sales & service teams together to create a compelling service sales process & tools.
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Service Business Assessments

Practical programmes that enables management to understand there 'AS=IS' state and so improve service processes and meet customer expectations.

Service Business Assessments

Si2 utilises a mix of proven tools such as, the Service Portfolio Check, Service Sanity Check, Installed Base Evaluation, Service Leaders Network events and Management Organisation & Tools
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Exceptional Customer Care

Typically long term activities that will bring more value to customers and soluion provider

Exceptional Customer Care

A mix of Trusted Advisor workshops for compelling communication, team facilitation to shift mindset, problem solving excellence and dealing with conflict.
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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.