Industry 4.0 has presented extensive possibilities for product and service companies to innovate upon and disrupt their own business models. Forrester reports that 73% of manufacturers believe they are not putting data to effective use. Another 82% are affected by unplanned asset failures, according to research by ServiceMax, a field and asset services firm.
The conveniences of product interconnectivity, complex data management, and cloud-powered data storage and analytics have enticed organizations to offer innovative services that were not possible earlier. Firms are now turning to “servitization” to offer their customers new services, which draw insights from customer usage patterns and product performance derived from aggregated and enriched data. These services come bundled with new-age technologies such as internet of things (IoT), artificial intelligence, and more.
A servitization solution is comprised of platforms and applications that automate multi-step processes occurring between people and systems, improving efficiency and ensuring high-quality customer experiences.
A connected product in the field is a source and repository of valuable data that can be used to improve product uptime, enhance customer service, and optimize internal operations. Servitization, therefore, can help generate new revenue streams, and income is generated not merely from the product alone, but also from the services it offers. For instance, a customer can pay an original equipment manufacturer (OEM) a fee based only on product usage like number of hours an asset is available for production or asset productivity.
The challenges of servitization
Though many manufacturers are shifting to servitization, many challenges remain – as highlighted in a recent blog post by Tata Consultancy Services.
The technologies underpinning the model are new, and getting businesses to completely reimagine their operations is a big ask, particularly in the automotive aftermarket segment. It’s not just businesses but customers, suppliers, distributors, and channel partners, who are key stakeholders in the aftermarket sector, who need to adapt to new revenue and monetization models – any change in the existing supply chain or business model will impact them directly. In addition, breaking traditional operational silos is another challenge manufacturers face, as servitization requires them to operate across different functional teams.
TCS has delivered servitization solutions to its customers, aided by a comprehensive suite of managed services from AWS, which span IoT, data storage and processing, machine learning, and data analytics. By leveraging its core expertise in IoT, analytics, and digital process transformation, TCS has successfully transformed the business models of numerous customers. Managed services allow enterprises to focus on rapidly experimenting and delivering solutions that provide real business value while letting AWS handle undifferentiated tasks such as infrastructure provisioning, maintenance, scaling, and patching.
Architecting servitization solutions
A robust solution that supports a servitization business model must have the following capabilities:
- Scalability – Ingesting and processing large-scale telemetry data from hundreds to millions of devices.
- Edge processing – Processing data with reaction times of milliseconds or microseconds at the location or source of devices.
- Comprehensive security – Offering end-to-end security spanning devices, network, and cloud infrastructure.
- Cost efficiency – Deploying servitization at low costs and adopting the right pricing model as the business grows, which will be realized over a period of time.
- Customer experience – Retaining customers by delivering high-quality service enabled by servitization.
TCS recommends AWS’s advanced services such as IoT Core, Greengrass, IoT Analytics, Kinesis Data Streams, Kinesis Data Analytics, Sagemaker, Elastic MapReduce, Lambda, and more for powering these solutions.
The benefits of servitization
Besides developing technology solutions, servitization has also helped OEMs improve the operations of equipment maintenance. This is enabled by solutions that directly impact the overall maintenance of equipment and the business process around it; for example, condition monitoring, fault prediction, and business process transformation, to name a few.
Enabled by IoT and cutting-edge cloud technology, OEMs glean useful insights by analyzing real-time data from operational assets and products in the field and leverage this information for predictive maintenance. In the servitization model, predictive maintenance is the preferred technique as it helps customers identify errors before they occur.
To illustrate the benefits in the servitization context, consider how an industrial air conditioning OEM may architect a technology solution. The solution must collect data from tens of thousands of internet-connected air conditioners and analyze the telemetry for anomalies in near real-time. If equipment faults are detected or predicted, the solution must initiate workflows in the customer relationship management and field service management applications to have customer service representatives facilitate repairs. This deeper understanding of the product’s behavior under real-world conditions will also be used to refine its design based on operational parameters and performance.
The success of a predictive maintenance approach lies in the ability to gather real-time data from assets in the field. This requires assets to be equipped with sensors that can be remotely accessed, with the data being transferred to the back-end monitoring and analytics platform. Insights from this analytics engine can alert the field workforce to potential equipment failures, helping organizations to plan and optimize maintenance operations, thus minimizing asset downtime losses. Empowered by the servitization business model, predictive maintenance can offer additional capabilities such as automating customer service, spares and inventory management, logistics and route optimization, and resource scheduling and utilization improvements.
In summary, servitization has offered OEMs a new business model to differentiate themselves from their competition. TCS leverages its domain expertise, reference architecture, and assets to accelerate the design and development of solutions. A superior solution should adopt a cloud-native approach leveraging edge computing capabilities, auditable security, data monetization, and integration with legacy applications. Essentially, organizations need to quickly adopt servitization before they become laggards.
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