A Service Transformation Enabled by the Internet of Things

remote service parts management

If you’ve been tracking The Service Council’s (TSC) recent research, you’ve seen a lot on the topic of transformation, around how businesses are indeed much more focused on service but also around how service organizations in themselves are transforming to be much more customer-centric and revenue-driven.

If you’ve followed other technology news lately, you have probably heard the words ‘Internet of Things’ or ‘Connected Machines’ heard more than once and how there will be x number of connected devices in the coming x years (insert your choice of numbers to replace both the xs). The concept of connected machines is not new, however given the drastically reduced cost and increased simplicity of connectivity we are seeing a greater interest in business models that can be driven by connected machines.

For manufacturing organizations looking to transform their service operations and increase profitability, the promise of connected machines is significant. Our research shows that 89% of manufacturers believe that data directly captured from machines will transform their business operations in the next three years. Depending on the stage of the service transformation journey that the organization is on, directly captured machine data holds significant promise.

Reactive Service (Benefit: Cost Containment)

  • Diagnostic information captured directly from the machine can aid in the appropriate scheduling of technicians and parts for the service task
  • Information captured at the point of customer contact can also promote self-service resolution, if applicable.

Preventive/Predictive Service (Benefit: Customer Satisfaction)

  • Remote monitoring can trigger alerts if asset performance fluctuates outside of accepted norms. As a result, steps can be taken to support an inspection of the asset, by the operating or servicing organization, in order to fix the issue before it becomes critical.
  • Trending data on asset performance tracked against established benchmarks can also alert the servicing organization to future failure therefore triggering service actions to prevent future performance deterioration
  • Intelligence gathered on asset performance as a whole can support planning initiatives in the servicing organization allowing for adequate resource coverage during periods of high service demand

Intelligence-Based Services (Benefit: Revenue Growth)

Asset usage information can yield the generation and administration of new services aimed at increasing customer value. 32% of manufacturing organizations in TSC’s research have developed new services in the previous 12 months and these include:

  • Intelligence services and benchmarking
  • Consulting services
  • Asset optimization services
  • Training
  • Consumable replacement services

Usage information can also support pay-per-use or other consumption-based payment models where the asset or machine-operator pays a certain fee tied to the use or uptime of the asset.

These are just some of the areas where manufacturers can take advantage of remotely captured machine data to improve customer value and increase profitability. With the aid of machine data, those organizations focused solely on reactive service can also begin to venture down the advanced stages of service maturity in order to make themselves indispensible in the eyes of the customer.

All of this said, enabling access to machine data is important but it isn’t a guarantor of success in service delivery. Having the infrastructure to securely access, make sense of, and build business models around the available data is absolutely vital to ensuring the benefits of remotely captured machine data. As manufacturers look to take advantage of the benefits surrounding the Internet of Things, they must evaluate the ability of their current or planned resources to be able to support the change necessitated by the influx of machine data.

Originally published on 7/21/2014