Smarter After-Sales Service and Support driven by the Internet-of-Things

White Paper

HiTech

Sukriti JalaliSenior Consultant

Sukriti is part of the Tata Consultancy Services (TCS) HiTech Center of Excellence, leading the IoT and Machine-to-Machine (M2M) initiatives and solutions for the high tech industry. She has over 20 years of industry experience in the design, development and validation of embedded systems, applied to a variety of domains including industrial automation, consumer electronics, automotive electronics, transportation and process control. Her areas of interest include Real Time Systems, Embedded Software, M2M communications and the IoT. Sukriti has presented papers on IoT and M2M at various forums including the Embedded World Conference and IEEE conferences.

Prateep Misra Principal Consultant

Prateep is a Research Area Manager working with the TCS Innovation Labs and leads the development of platforms for IoT applications. He has over 21 years of experience in the IT industry in areas such as software development, research, technology consulting and software quality assurance. His current areas of focus include IT infrastructure architecture and design, IT transformation, storage systems, large scale and real-time analytics platforms, and cloud computing. Prateep has also been involved in the design of the IT infrastructure for a major TCS SaaS offering.

About the Authors

The Internet-of-Things (IoT) and solutions using connected devices are profoundly impacting enterprises, their customers and end consumers. Real-time analysis of device data and its integration with enterprise systems is enabling businesses across industries to automate processes, launch novel services, enhance customer experience and improve the overall decision-making process. High tech, industrial electronics, healthcare and semiconductor equipment manufacturers are poised to increasingly leverage intelligent systems in combination with innovative digital forces such as cloud, analytics, Big Data, mobility and pervasive computing to create smarter service and after-sales support opportunities at multiple levels.

This whitepaper outlines an approach for deploying smart technologies and providing new services that enhance the productivity of the installed base and increase after-sales support revenues. It demonstrates how process improvements and optimization can be achieved by capitalizing on historical as well as real-time data from installed equipment. Deploying smarter after-sales solutions requires a secure, highly scalable, multi-tenant and device agnostic 'connected equipment' or IoT platform. The paper provides insights into the core services that such a platform should offer and elaborates on how it can drive after-sales service and support business.

Contents

Introduction 6

Market Trends and IoT Insights 6

IoT as an enabler of Digital Transformation 7

Current challenges in deploying smart solutions 8

A Sustainable approach to Smarter After-sales 9

A Framework for deploying Connected Equipment 10

Core features of a Connected Equipment Platform 12

Key Considerations for Deploying an After-sales Framework 13

Conclusion 14

API Application Programming Interface

BI Business Intelligence

IDC International Data Corporation

IoT Internet-of-Things

KPI Key Process Indicators

M2M Machine-to-Machine Communication

OPC Object Linking and Embedding for Process Control

OPC-UA OPC Unified Architecture

PaaS Platform as a Service

PLC Programmable Logic Controller

RoI Return on Investment

SCADA Supervisory Control and Data Acquisition

SI System Integrator

TCO Total Cost of Ownership

List of Abbreviations

IntroductionAccording to IDC forecasts, the market for connected and intelligent systems will increase from more than 3.2 billion units and USD1.4 trillion in revenue in 2012, to nearly 5.04 billion units and over USD2.3 trillion in revenue by 2017. Enterprises across industries, from transportation to utilities to healthcare to manufacturing, are already witnessing a sea change in the way they interact with customers, thanks to the cutting-edge benefits of IoT and connected device solutions. Business functions that have a direct effect on customer satisfaction and retention experience the greatest impact of connected devices.

End customers are increasingly demanding proactive and agile customer support, instead of a reactive and delayed response. Functions such as field engineering, spare parts management, equipment reliability, device management, warranty management and other value-added services are poised to undergo a digital transformation, driven by data from connected devices. Equipment vendors also seek unique ways to lower the total cost of ownership (TCO) for end customers. These factors are driving enterprises to adopt new digital technologies and advanced analytics solutions for transforming the after-sales services and support functions.

In addition to expertise in digital technologies and understanding of after-sales processes, organizations need access to predictive analytics, optimization techniques and a connected equipment infrastructure platform. Such a platform enables easy development and deployment of IoT applications, and also provides robust and scalable device management.

Market Trends and IoT InsightsRevenue from service and parts represents an average of more than 25% of the total business of manufacturing companies, with figures reaching as high as 50% for many companies. Current trends indicate that over the next couple of years, manufacturers will increasingly use 'service' as a competitive differentiator to grow revenues and profitability. Service-led innovations and value-added services that are directly linked to equipment data will facilitate this process.

Manufacturers increasingly tap digital technologies to achieve process efficiencies, improve customer satisfaction, offer on-demand business models, and reduce the TCO for maintenance and management of equipment. Innovations such as sensor technologies, always-on connectivity, cloud-based platforms, and Big Data frameworks enable enterprises to accelerate the deployment of IoT-enabled solutions.

1According to the Gartner forecast report published recently , The Internet of Things will include 26 billion units installed by 2020. IoT product and service suppliers will generate incremental revenue exceeding $300 billion, of which more than 80% will be derived from services, by 2020.

Manufacturing and healthcare sectors are also likely to realize the greatest value from IoT. A recent report 2by The Economist Intelligence Unit (sponsored by ARM), 'The Internet of Things Business Index

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[1] Forecast; The Internet of Things, Worldwide, 2013 by Gartner, published 18 November 2013, G00259115

[2] The Internet of Things Business Index by The Economist Intelligence Unit, 2013 http://www.economistinsights.com/analysis/internet-things-business-index

Research by IDC Manufacturing Insights also reiterates that more than 70 percent of manufacturers are exploring strategies to implement smart technologies in the near future, to manage and optimize their own

3or customer-owned equipment .

Industry and digital technology trends are fast converging to create valuable opportunities and competitive differentiators for product manufacturers. Pressure to create innovative service contracts, realize a 360 degree view of equipment, and capture service and spare part entitlements is compelling manufacturers to adopt digital technologies. There is a demand for integrating innovative technologies to enhance customer engagement beyond basic remote connectivity solutions and manufacturers are keen to deploy best practices from their own and related industries. The stage is thus set for manufacturers to understand and leverage the opportunities presented by the IoT to improve their business operations and performance

4against KPIs.

Many industries have been quick to embrace the industry and digital convergence. For instance, the automotive industry has enhanced after-sales services and emergency call systems by leveraging telematics based solutions.

IoT as an Enabler of Digital Transformation

Digital transformation empowers companies to redefine their products, services, business models and customer engagements. This transformation is driven by the innovative use of mobile, cloud, social media and Big Data analytics technologies. IoT adds yet another dimension by digitizing physical objects, accurately observing real world phenomena and meaningfully linking this to enterprise operations. It makes this possible by helping organizations gain three fundamental capabilities – visibility, insights, and control.

Visibility: Sensors embedded in real world objects and personal devices, coupled with communication capability, allow the capture of information in real time and make it available for further analysis and processing. Manufacturers can thus monitor the state and activities of machines, appliances and human resources, as well as their usage patterns and contextual information.

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(see Figure1) indicates that IoT will bring about significant changes to the customer service and support functions. IoT technologies are also expected to unlock new revenue from existing products and services.

Figure 1 : Future impact of IoT at the organizational level

[3] IDC Manufacturing Insights: “Business Strategy: Modernizing the Service Chain with Smart Technology,” (Document # MI241900), July 2013

[4] Further reading on M2M/IoT solutions and technology trends: TCS, “Technology Review and Trends in M2M Communication”, March 2012,www.tcs.com/resources/white_papers/Pages/Technology-Review-Trends-M2M-Communication.aspx

Chart 2: Future impact of the IoT - company level

Where in the business will the IoT have the biggest impact? (Top responses)

Customer service/support

Products or services (B2B or B2C)

Data management & analysis

Source: The Economist Intelligence Unit.

How will the IoT change how the businesscurrently operates? (Top responses)

Unlock new revenue from existing products/services

Inspire new working practices or processes

Change existing business model or strategy321

321

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Insights: Aggregation, correlation and fusion of data from different sensors and objects provide real-time insights with unprecedented levels of granularity and breadth. Organizations can thus achieve situational awareness at both the individual and the aggregate level. Further, analytics on stored historical sensor observation data enables a deep understanding of real world phenomena, business processes and behavior of humans and machines. The system and statistical models help arrive at accurate estimates of un-observable states, and predict future states based on past and present observations. It is also possible to carry out ‘what-if’ analyses with reasonable accuracy using simulation studies on estimated models.

Control: Based on the insights into state and behavior, actuators embedded in things and machines can be given commands to effect changes in behavior and the environment for better control. This is, in fact, similar to closing the loop in a feedback control system. By leveraging IoT, manufacturers can optimize business and operational processes, as well as resource consumption. They can also improve the quality of products in conjunction with the delivery of mass customized products, services and information to targeted customers.

Current Challenges in Deploying Smart SolutionsDespite potential benefits, many organizations struggle to conceptualize and deploy digital solutions for transforming after-sales service and support. Industry research and client feedback point towards a few key challenges in this context, which include:

Moving from traditional product-led to service-centric innovation.

Building a robust foundational technology infrastructure to handle the variety and velocity of data from the globally installed equipment base

Managing stringent security considerations of data access, storage and retrieval. For instance, industries such as semiconductor manufacturing are characterized by high data sensitivity

Difficulty in seamless integration with existing enterprise systems to realize business benefits and better RoI

Mastering the process of including not only historical data but also predictive insights, advanced analytics, modeling and simulation techniques in planning and forecasting

Lack of in-house expertise in cloud, Big Data, mobility, social and IoT, which is essential to conceptualize and build solutions

Absence of a ‘connected equipment’ platform-based approach

Manufacturers can determine requisite areas of focus while designing and developing new solutions, as well as offset industry-specific challenges through comprehensive customer satisfaction surveys. For

5example, ‘The 2013 10 Best Suppliers of Chip Making Equipment’ survey by VLSIresearch lists multiple areas of improvement, such as in-field support engineering, spares support, after-sales support and cost of ownership, that end-customers in semiconductor manufacturing consider.

[5] The 2013 10 Best Suppliers of Chip Making Equipment, https://www.vlsiresearch.com/public/cms_pdf_upload/700225v13.05_web.pdf

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A Sustainable Approach to Smarter After-sales An ideal IoT-enabled after-sales scenario has been depicted in Figure 2. Here, diagnostics, performance and usage data from the installed equipment base is available in real-time or near real-time on an ‘anywhere, anytime availability’ basis. This data, integrated with historical data and master data from other enterprise systems strengthens advanced analytics and helps improve decision making for business users. It also furthers statistical modeling, predictive algorithms, and optimization techniques so that manufacturers can better predict and plan for the future performance of equipment and related services. Predictive insights can help ensure that business users do not narrow their focus to events and data from the past or make only reactive decisions.

Figure 2: Smarter after-sales service and support for the ‘TO BE’ state

While this is the ideal 'to-be' state from a manufacturer's point of view, the practical scenario looks different:

Customers may be at different maturity levels of strategizing and deploying digital an innovative solutions and processes

Some equipment in use may not support data communication, while others may be legacy equipment lacking the right interfaces

Not all after-sales processes may require the same level of IoT-led transformation

Not all processes may justify data interpretation in real-time

Some equipment may be owned by the end customer, and there can be significant issues and sensitivity in transferring and sharing equipment data outside the enterprise environment

After Sales Users

Customer Support Service Support Business Heads Engineering Partners

After Sales Systems

Service Contracts Warranty Systems Spare Parts Management

Predictive Maintainance

WorkforceScheduling

Enterprise Integrations &Process Inter-dependencies

Enterprise Integrations &Process Inter-dependencies

Enhanced Optimization by Connected Equipment Data On Premise/Cloud

Optimization Based OnHistorical Data

EquipmentDiagnostic

Data

EquipmentPerformance &Usage Data

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These factors clearly point towards two possible approaches for smarter after-sales processes. They can be executed in a phased manner or taken up independently, depending on the maturity level of an organization, the business process complexity, as well as alignment to short term and long term business goals. The two approaches are:

Tap into historical data: Manufacturers can review and revise existing business processes, integrations, synergies, equipment service interventions, parts replacements, and failures, to enhance efficiencies and gain improvements over previous implementations. This is possible using advanced analytics, simulation models and optimization techniques on historical or off-line equipment data. A 're-look' at business processes and simplification of IT environments can further accelerate the process.

Leverage connected equipment data: This provides substantial long-term efficiencies and improvement, over and above the benefits achieved in the first approach. Manufacturers can analyze backward data or events in combination with forward looking data and insights to improve the planning, scheduling and modeling processes. The benefits will be more pronounced with significantly improved processes because of the ability to forecast and make proactive decisions.

A Framework for Deploying Connected Equipment A high-level view of a framework for deploying a connected equipment based approach is provided in Figure 3. Services and solutions can fall under one of the three horizons or phases – foundational, value-added and advanced, depending on the current maturity level and future strategic focus of the organization.

Foundational services: They include the basic infrastructure, the equipment for connectivity and device or protocol level integration required to enable devices to communicate their status, location, diagnostics or other events and alarms. At this level, the solution must have data sensing and/or acquisition capability and at least one-way data connectivity to a central system. The main output at this stage includes equipment capable of communication, communication infrastructure set-up, standardized way of data collection, and a sound understanding of protocols and data structures.

Value-added services: These services are based on data collected from the foundational services and can include statistical analysis, simulation and modeling of data over the entire equipment lifecycle. This phase provides fact-based insights and dashboards to business users relating to equipment installations, service contracts, profitability, customer geographies, device usage patterns and equipment performance. It also includes solution areas such as Big Data, reusable statistical models and platform-based service architectures. The main outputs at this stage are platform infrastructure for device and data management, and base level integration with enterprise IT tools and systems.

Advanced services: These have an impact on the business processes and hence the KPIs of the business units. While some solutions in this phase will be used for optimizing internal business processes, many can also be offered ‘as-a-service’ to end customers. Advanced services can be built only when value-added services are in place. For instance, statistical models that use both historical as well as forward looking

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information (value-added services) can be better derived from equipment data on spare parts or consumables (from foundational services). These form an important input for improving the spare parts planning process, replenishment levels and just-in-time inventory levels (advanced services). Similarly, the performance of an equipment part (foundational services) is used to create more precise contract pricing models (value-added services), and this data helps create profitable contracts as well as differentiated service models (advanced services).

Figure 3 – Connected Equipment Framework

The business benefits increase and improve as we move from the foundational to the advanced stage. Services also shift from being equipment-centric at the foundational level to data-centric at the value-added stage to domain centric at the advanced level. Integration with enterprise systems and operations bind the entire solution and are a critical element of the framework. Integration levels across the enterprise increase and become more complex as one moves from foundational to advanced services. The stronger the integration within the enterprise environment, the more pronounced will be the benefits and quicker the returns.

In the absence of real-time data from connected equipment, this framework can also be used to improve after-sales processes using historical data points, with limited benefits.

FOUNDATIONAL Technology Infrastructure

Enablement Remote Monitoring &

Diagnostics

VALUE ADDED Remote Management 360 degree Devices and

Services Analytics Smarter Spare Parts Analytics Big Data Frameworks Training & Learning IoT/HPC Platform

ADVANCED Predictive Maintainance Spare Parts Management Field Force Scheduling Smart Service Contracts On Demand Business Models

Integration with Enterprise Systems & Operations

An Integrated approach to Predictive Analytics, Service Contracts, Maintenance Schedules, Spare Parts Management and Field Force Scheduling brings better results than a silo optimization.

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Core Features of a Connected Equipment PlatformTo realize the full benefits, a secure, highly scalable, multi-tenant and device-agnostic IoT platform is a basic requirement. This platform is where the entire data from various equipment and devices installed in the field is collected and stored. On the one hand, the platform needs to provide device side integrations and APIs, and on the other, it should be able to share data with other enterprise systems. The enterprise systems themselves are a complex mix of layers across Business Transactions, Event Processing, Data Transformation, Data Warehouses, In Memory Analytics, Dash boarding and Collaboration.

The core services or features that a connected equipment platform should provide to application developers, administrators and sensor or device manufacturers include:

Managing device diversity and interoperability: A variety of equipment from different device vendors and OEMs can form part of an IoT ecosystem. Therefore, the platform must allow applications to easily interface with a wide variety of devices and sensors.

Integrating data from multiple sources: The platform must enable easy building of intelligent and context-aware IoT applications. These applications can generate relevant events and alerts by integrating data from multiple sources, including various types of sensor devices as well as web resources such as social network feeds.

Facilitating scale, data volume and performance: A highly scalable architecture is required both in storage and computation. Organizations also need a secure yet lightweight means to transfer data from sensor devices to cloud, thereby reducing network overload.

Flexibility and evolution of applications: It is necessary that sensor configuration data and sensor observations data be available as a service and be separated from the applications. As sensor data is structured and described using open standards and ontologies, it is self-describing, allowing third party developers to easily build new applications from time to time.

Domain-agnostic with pluggable extensions: The core underlying services of the platform should be flexible with respect to the application domain. The domain, industry and application-specific requirements and features can be brought in either in the application layer or by using specific plug-ins. Examples of domain or vertical specific plug-ins include specialized interfaces for medical devices, and specialized interfaces for process control and automation systems such as Programmable Logic Controllers (PLCs) and Supervisory Control and Data Acquisition (SCADA) systems.

Interoperability with other platforms: The platform must be compatible with other IoT/M2M platforms. For example, it must be able to interface with third-party device management services or with external automation and process control systems using protocols such as Object Linking and Embedding for Process Control - Unified Architecture (OPC-UA).

One way to comprehend this is by understanding which components or services of the connected equipment platform help enable the three horizons of the Connected Equipment Services framework. The following table provides a quick way of depicting this and can be used as a reference to improve after-sales service and support as more smart applications are conceptualized.

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Connected Equipment Services Framework

Connected Equipment Enabling Service

Examples of Smart Applications for After-Sales Service and Support

Foundational Sensor services Device management Device connectors Sensor data explorer and

visualization Portals

Industrial equipment remote monitoring and diagnostics

Medical equipment remote monitoring

Remote printer monitoring and diagnostics

Value Added Application development and deployment services

Analytics services Time series data mining Big Data analytics Portals

Remote device management Equipment lifecycle data gathering 360 degree devices and services analytics Spare parts related analytics Equipment contracts profitability Equipment warranty costs

Advanced Custom applications Enterprise software connectors and

analytics programs deployed on top of platform

Predictive maintenance Efficient spare parts forecasting Innovative service contracts Maintenance workforce scheduling On demand business models Equipment warranty management

Table 1 – After-Sales Services and Support using a Connected Equipment platform

Key Considerations for Deploying an After-Sales FrameworkA step-wise and phased process helps efficiently develop and deploy the connected equipment after-sales framework and strategy. Significant points to be considered include:

Current technology landscape

End customers' environment

As-is functional process maps

Existing process of data acquisition, collection, analysis, optimization

Existing business challenges

Short-term and long-term priorities and KPIs

Partners and alliances in the enterprise and IoT/M2M space

Data protection and privacy

Phase-wise investment requirements

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Based on these factors, short term and long term roadmaps must be created for planning and deploying these solutions. Organizations must calculate the RoI and business benefits for each business function that needs to be improved and optimized over existing implementations.

A platform-based foundational approach makes it easy to implement and deploy smart business applications. More focus can be expended on the domain and business solution, rather than technology, platform and infrastructure challenges. Data from the installed base should interact with a host of other enterprise and home-grown systems, such as contract management, spare parts planning and maintenance schedules with a view to enable customers to react in a more predictable manner as well as use this information for better forecasting.

ConclusionWhile there may be differences in how research firms evaluate the IoT market opportunity, there is consensus that the major portion of revenues in the IoT space will come from value-added services. Smarter after-sales service and support using Digital and IoT technologies is one of the compelling use cases that have the potential to provide a long term competitive advantage to equipment manufacturers. Large System Integrators (SIs) with deep domain and technology expertise as well as customer reach and knowledge of after-sales business processes play a key role in realizing these end-to-end solutions.

How organizations deploy smart services and solutions depends on their maturity levels. Some companies have been using foundational services for several years and may require supporting expertise in the value-added and advanced services. Other high tech manufacturers who may have just embarked on this journey can create long term blueprints for these solutions, exploring a standardized way for devices to communicate. To plan for a short term and a long term strategy as well as plan for execution, organizations will need to acquire a better understanding of their as-is business processes, access to IoT and digital expertise, and a good network of alliance partners.

Another area where most organizations may seek expertise in realizing digital benefits is integration with enterprise systems. To achieve long term business objectives, organizations will have to build or buy inter-disciplinary skills and cross-functional domain knowledge required to enable IoT led transformation.

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