Infrastructure and transport systems

Our engagement with infrastructure and transport systems and service providers is multifaceted.

We work with project owners, managers and investors to conduct techno-economic feasibility and life-cycle analyses, provide cost estimates and risk assessments and develop budgets and business plans. We also help design RFPs, select vendors and support the contracting process, negotiations and client side project management, with a focus on the O&M process over longer time periods.

We work with asset managers and operators to improve asset performance through advanced  O&M and engineering superior customer experience. We help develop and implement asset management strategies, re-engineer processes, deploy advanced practices and technology, select and train personnel and facilitate the required organizational transformation and culture change.

On the vendor side we help our clients better understand  drivers of change in their industry and develop service and solution based strategies. We work with to design and implement outcome based, “infrastructure as a service” business models and offerings, assess risks and develop  pricing strategies and win, negotiate and close bids. In implementation our focus is on putting in place the right organizational capabilities, structures and processes to successfully implement contracts, manage sites and meet objectives. And we help our clients  implement advanced asset management and O&M strategies.

Our clients include engineering, construction and technical services companies, equipment and technology suppliers, specialist transport service providers, power and water utilities and specialist infrastructure service providers and investors.

Ageing infrastructure and rising demand necessitate better services and new business models

Physical infrastructure, from utility networks to transportation hubs and mobility systems, is the backbone of economic growth. Yet budget and other constraints make both public and private investment increasingly more difficult, leaving significant gaps between what is needed and what actually gets implemented. While governments can sometimes reduce or effectively manage demand for infrastructure services, for example by promoting energy efficiency or dynamic pricing rather than building new power transmission capacity, in many cases this cannot be done without adversely impacting growth and development. And demand for infrastructure services is both rising and changing, while the asset base is ageing and declining in capacity and performance.

Against this backdrop ways must be found for investing in infrastructure that minimize the burden on budgets, while bringing adequate returns for investors. Increasingly therefore, both public and private players have been turning to business models which aim to deliver infrastructure “as as service”, bundling assets with services into integrated solutions, as well as improving the back-end of infrastructure investments, in particular operations and maintenance (O&M). The objective is to extract full value from existing and new asset base by increasing assets’ revenue streams, extending their life-cycle, while reducing costs, risks and delivery lead times. Superior operations and maintenance coupled with ability to improve customer experience, is therefore often mandatory not only to win projects, but also to make them economically viable and bankable for investors.

Yet the reality is that the infrastructure asset base has been severely neglected. Current O&M practices are often seriously deficient, failing to maximize asset utilization or meet adequate user quality standards, while incurring needlessly high costs. As a result existing assets deteriorate much faster than necessary, shortening their useful life. According to a survey by the European Federation of National Maintenance Societies, asset management practices in the European infrastructure industry are rated below those of the manufacturing and process industries, not just in overall ranking but in every one of the key subcategories. A number of factors contribute to this situation, including insufficient funding for O&M, a lack of organizational focus and management capacity, as well as significant knowhow deficits.

Pressure for change is however increasing: Owners and operators, both public and private, need to develop comprehensive long term strategies for operating and maintaining infrastructure assets to narrow the investment gap, bend cost curves and expand effective capacity. And they need to take advantage of outcome and  performance based business models, including through public-private partnerships (PPPs), to reduce risks and necessary upfront investment commitments.

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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