Parts as a Profit Engine

maximise profit & Loyalty from your installed base over the product lifecycle

Why

No Parts, No Service

A reliable spare parts supply is essential to delivering great service and maintaining long-term customer satisfaction. But it’s not just about having parts available, it’s about ensuring the customer has a solution that ensures maximum availability at minimal cost: whether that be through a specific part number or an alternative. At one level these solutions can involve the  implemention of  SMART sourcing strategies or much more down to earth and  involve bundling parts into kits,  or developing upgrades that provide real customer value (whether through modernisations or managing obsolescence).The goal is to have the right part is in the right place at the right time. We aspire to take spare parts and associated services to market in a way that enhances the customer experience.

In fact, spare parts and upgrades form a business in their own right. For equipment manufacturers, they are often the primary revenue driver for Service — and when executed well, they become a strategic engine of profit and customer loyalty. Margins on spare parts are typically much higher than those on the original equipment they support.

Managing spare parts effectively requires different processes and structures compared to those used for manufacturing core products. That’s why a successful spare parts strategy must be fully aligned with the leadership’s vision and objectives for the service business.

In fact parts and upgrades is a business in it’s own right and for equipment manufacturers is the major revenue driver for Service and if done right, a strategic driver of proft and loyalty. The margins for spare parts are generally significantly higher than those for primary products they are sold into.

The processes and structures for a good spare parts management are more complex and different from those for the production of primary products. Hence key to success is to ensure the parts strategy is alignment with the Leadership vision and objectives for their service business.

Who should be involved

All members of Service team from Leadership, Parts & Upgrade management, Logistics, shipping and warehouseing, Service engineers, Help desk, Contract management & Sales administration.

How the programme works

Si2 Programmes are tailored to the specific needs of situation, pulling on a numbers of methods which Si2 partners have found to be good practice in their careers. They are very practical, typically collaborative and all have the goal of quickly delivering value for the programme:

 

1. Service Assessments: Are a key element of the programme to identify and quantity the challenge, the opportunity and the business case for change. The assessment will depend on your priorities and situation, but typically they are looking to drive excellence in the following areas:

  • Parts identification and ordering
  • Efficient processes with high transparency and short response times
  • Spare parts organization: ensureing clear responsibility and expertise in particular single point contacts
  • Spare parts procurement, alternative options, retro-standardization
  • Inventory management: High availability and delivery readiness with the lowest possible stock levels
  • Physical logistics: storage concepts, distribution, make or buy decision making
  • Spare parts distribution: increasing market share, fending off independent suppliers, branding
  • Efficient returns management, warranty and goodwill processing
  • Effective use of Data and Systems.

 

2. Change Management: having identified  challenges, Si2 advisors works with client teams 

  • Service Business Mentoring & Coaching: To guide leaders and teams in their process improvement actions, acting as a sounding board, project manager and ensuring team members are held to account.
  • Meeting Facilitation and Workshops: Where required the coaching can broaden out into team workshops to drive mindset change and project management
  • Interim management: where leadership or expertise is missing, Si2 can take on responsibility  for acheiving the intended goals
  • Specification and Scoping of Data projects: Whether it be specifying the IT tools that underpin the processes, or the use of advanced analytics to automate processes and drive better decision making, Si2 will support the team with expert advice, data mining or project management.
  • Parts Value Pricing: One of the quickest ways to drive up profitability is to ensure spare parts and upgrades are correctly priced. This analytical activiy involves an in depth analysis of  part families, the margins they generate and the competitive position in the market.
  • Parts Logistics Processes & Services: Process Improvement using proven Lean techniques of  internal logistics processes, planning the location of localised and regional inventory, as well as the development of value added services such as consignment stock. 
  • Customer Service enhancement: actions and activities to develop value propositions around parts and upgrades, as well the effective promotion of these to the customer base. 
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Presentation

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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.