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Industrial and Technical Services

Our engagement with industrial and technical service providers is multifaceted and deep. We help them with sophisticated market segmentation and competitive analysis to identify growth opportunities and recognize threats and in developing winning strategies at corporate, business unit or regional level. We help design the right business models and offerings, optimize organizational structures and drive change.

On the operational side we work with our clients to improve performance, from deciding how to deploy footprint, capacity and resources to implementing responsive customer service. We help them develop, price, negotiate and win bids; Build superior execution capabilities to deliver large, complex projects on time and within budget, achieve objectives in major contracts or turnaround underperforming ones.We provide expertise and support for operational improvement along the EPC and O&M value chains and productivity improvement of distributed workforces based on lean principles. And we help our clients appraise opportunities through technology, conceptualize digitization initiatives and evaluate, select and implement the right technologies to support objectives, strategies and operational performance initiatives.

Changing market landscape, stronger competitors

Broad based or specialized, pure play service providers have emerged as key constituents in the industrial services market, which is showing signs of increasing concentration in all geographies. As a part of an effort to reduce unit costs through increased utilization, better spread overhead and improve ability to serve large customers across regions, major players have been expanding footprint, extending scope and growing in size. At the same time, changes in OEM strategies and upheavals in a number of end-user markets due to commodity demand and price declines, have fueled a wave of major spin-offs and acquisitions of former OEM service divisions that has visibly transformed the industry from primarily local to increasingly regional or even global. The challenge to large players now is to confront the strong competitive focus of OEMs on comprehensive services on the one hand, and consolidate and drive gains from their larger size on the other, while responding to reducing customer investment, performance challenges and strong price pressures in a number of sectors, including many of the process industries.

In outsourced support services, such as maintenance and asset management, the days of low hanging fruit, when contracts could be won simply through payroll reductions are long gone. Companies must now find new ways to continue delivering on cost reductions (scale) or customer performance improvements (knowhow and skills). Providers must also be prepared to shoulder more risk, as customers demand a stronger focus on outcomes. At the same time OEMs are forcefully pushing into the service market with the intent of capturing significant portions of available revenue pools. They rely on superior product knowledge and new, technology based, offerings, bundling services with core products with the aim of locking customers in and competitors out over the long run. Industrial Internet of Things technology coupled with powerful analytics, supports both better asset performance and reduced cost of delivery, including reduced manpower needs. To compete service providers must face a transition to less labor intensive business models.

Insights and Success Stories

Service in Industry

Deep dive into the industrial service business.

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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:


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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