Design and Smart-Service

Integrate technology and knowledge into Service Propositions to exceed ambitious goals

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

  • Unclear link between technology investment and value creation

  • Difficulty integrating digital capabilities into service offerings

  • Low user adoption due to weak service design

  • Fragmented processes across product and service delivery

  • Lagging organisational readiness to adapt to smart service models

In service-led businesses, competitive advantage depends not just on having the right technologies, but on designing Smart Services that customers value—and are willing to pay for. At Si2, we help teams bridge the gap between digital potential and commercial success through smart, user-centric service design.

Technology must be embedded into compelling service propositions and seamlessly integrated into delivery processes. We support clients in aligning their technology roadmaps with strategic goals, and in identifying how emerging tools—IoT, AI, platforms—can support value creation and differentiation.

Combine business insight with design thinking to shape smart services helps solve real customer problems and enhance loyalty. This includes supporting system selection, vendor management, and implementation. But more critically, it is important to support the team as they  redesign processes, roles, and challenge mindsets to ensure new services can be delivered efficiently and scaled effectively.

Smart Service is not just about digital capability—it’s about delivering measurable outcomes. We see our goal as acting as a catalyst for your people to turn data and technology into action, enabling continuous improvement, stronger customer connections, and sustained growth through service innovation

Key focus areas:

  • Service Management Systems
  • Remote Services
  • Augmented Reality
  • Knowledge Management
  • Internet of Things (IoT)
  • AI and Machine Learning for Service and Asset Management Applications

Si2 Enabler Programmes

Service Portfolio Design

A holistic programme that drives a customer value approach to service proposition development

Service Portfolio Design

Develop a portfolio that supports strategy with compelling sales materials through a servuce savvy sales organisations
Find out more

Service Value Sales Programme

Drive service and sales collaborations to deliver more value for customers and your company

Service Value Sales Programme

Transforms professionals from Feature to Value Selling! – From a customer ‘push to a pull’ mindset!
Find out more here

Digital Savy Service Professional

Enabling professionals to understand, visualise and action data

Digital Savvy Service Professional

For teams looking to boost their teams understanding of how to use data increase productivity and tell more compelling customer stories

Design Thinking for Service

Practical tips to incorporate Design Thinking concepts into Service Design

Design Thinking for Service

For managers looking to gain a more customer centric in the design of their service offers and support processes

Insights

Service in Industry

Deep Dive into the industrial service business.

Join our community to receive analysis, insight, news and more.
We will never share your data

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.