Companies are pressured to continue to develop superior service offers to differentiate their brands, increase margins and secure customer loyalty, while at the same time seeking to embrace the circular economy and under pressure to demonstrate progress against increasingly ambitious ESG goals.
Service supports sustainability
Facts support the idea that service and maintenance support sustainability: keeping products and assets running for their maximum viable lifetime has a positive impact on sustainability. Even in times of recession, the service sector remains inherently resilient; consumers and businesses alike want to retain products and equipment for longer.
The key service tenets within the 9R circular economy framework – refurbish, repair, remanufacture and recycle – sit squarely within any ESG corporate remit. The first two eliminate the need for new manufacturing production, and the attendant consumption of resources, and the last two minimise waste and landfill.
Based on the analysis of historic fault patterns, AI can suggest the most likely parts an engineer will require as standard to secure a fix
A leading consumer goods supplier has calculated that for every three refrigerators they repair, the environmental savings made equate to taking a combustion-engine car off the road. When managing 65,000 product repairs a week, that’s a significant saving.
The move towards electric vehicles in field service operations is also challenging. With the need to ensure sufficient battery capacity, routing and scheduling needs to factor in availability of charge points, the schedule, and range. Excess van stock, including obsolete and excess stock and even colder weather can also significantly reduce range.
The use of predictive intelligence will become even more far reaching. Everything from when a device might be likely to fail, to the parts that might be needed, to skill proficiency and therefore time-to-fix when allocating different engineers, is all within the scope of predictive adoption.
Two factors underpin successfully adopting these competences: the first is the availability of data. And the second is the presence of effective Artificial Intelligence, AI and machine learning capabilities to interpret the findings, detect anomalies and create predictive service insights. Increasingly, we can expect AI insights and analyses to augment and support human engineers.
Real time connectivity to assets enables asset performance management and ultimately asset optimisation
For example, based on the analysis of historic fault patterns, symptoms and resolutions, AI can suggest the most likely parts an engineer will require as standard to secure a fix.
Insightful service is effectively data-driven prescriptive diagnosis combined with intelligent service. At the same time, this real time connectivity to assets and devices also enables asset performance management, and ultimately asset optimisation, both directly linked to customer experience and a successful delivered service first business model.
Customer experience, CX, has hogged the spotlight now for several years. Post pandemic, things have changed. Now, facing a global skills shortage and The Great Resignation, the service sector is also rapidly recognising the importance of the employee experience, EX.
A staggering 40% of field workers are due to retire within the next ten years. Unless we can attract new talent, this invaluable knowledge and insight will be lost. Ignoring the need to create an AI-powered intelligent knowledgebase could well prove a costly oversight.
80% of the global workforce –some 2.7 billion people – are employed on the front line, deskless. The pandemic taught us just how important some of these workers are and, in many cases, how poorly equipped they are. In the absence of a consumer UX-style mobile-first strategy by many employers, with simple and efficient onboarding, they remain woefully forgotten and, in many cases, disconnected.
If organisations want to retain and engage with this workforce, they need to emulate the focus and experience given to more traditional desk-based staff, both office-based and remote.
A shift to a mobile-first focus, and embracing concepts such as gamification, turns mobile devices in the field into a powerful and pervasive technician-enablement platform – and a compelling way to attract and retain new talent. Over the coming year we can expect to see EX increasingly becoming an equal citizen to CX.
Short and long cycle
There is a difference between high volume, break-fix service regimes for products, and servicing major high value asset investments, where service or modernisation programmes may span many months or years. Historically, companies have deployed separate distinct workforces to fulfil short-cycle break-fix requirements versus the long-cycle service planning required for strategic assets and projects.
However, these boundaries are beginning to blur, with a shift towards a multidisciplined blended workforce. The skills shortage means companies want to develop multi-skilled technicians who can perform both a 30-minute fix and also a day-long full asset overhaul.
There’s also a transition from the traditional fixed periodic maintenance model to condition and usage-based service. But managing schedules and maintenance plans for multiple geographically dispersed assets in this way is complex.
Since the pandemic, remote service is no longer a bolt on and is now an integral part of any service offering. Now a service model in its own right, remote monitoring and diagnostics are increasingly working hand-in-hand with remote, virtual assistance.
Regardless of the model, and how service is designed and delivered, the success depends on delivering a consistent, positive customer experience – end to end: whether that’s when calling to book an engineer, using online resources, rescheduling an appointment, or being guided on the phone. Nothing should present itself to a customer as a bolt-on or afterthought.