The Boao Forum for Asia 2017

Pre-conference Report

Unleashing the value of the Industrial Internet of Things

In order to be successful and generate further growth, companies will use the Industrial Internet of Things to improve efficiency by optimizing the supply chain, boost revenues by enhancing customer experience and upgrade the risk management by improving product safety. However, a transformation from interpretation to prediction in the usage of data is crucial.

Value of IoT in the Industrial sector
In today's business world, all companies are facing a challenge that can be turned into a great opportunity: the transformation from a reactionary towards a visionary approach. Retrospective analysis and delayed responses are no longer suitable for today's rapidly changing business environment. As with the increased use of sensors and improved quality of data, Internet of Things (IoT) allows companies to act with foresight, preventing significant losses and creating value.

According to Gartner, the number of IoT equipment installed worldwide reached 6.4 billion in 2016, representing a 30% year-on-year growth, and it is expected to reach 20.8 billion in 2020. The global endpoint spending on IoT was about USD 1.414 trillion in 2016, composed of USD 546 billion from consumer applications, USD 201 billion from cross-industry business applications, and USD 667 billion from vertical industry applications. By 2020, the total expenditure on IoT is expected to reach USD 3.011 trillion, and the afore-mentioned market segments are expected to grow to USD 1.534 trillion, USD 566 billion and USD 911 billion, respectively. This represents compound annual growth rates (CAGR) of 29%, 30% and 8%, respectively.

IoT projects are currently mostly used in the industrial sector. IoT Analytics believe that the manufacturing industry accounts for around 25% of IoT applications while Harbor Research and CISCO estimated its percentage at 27% and Gartner calculated a 15% share1. Although estimates by research firms vary, the manufacturing industry takes the lead in IoT. The figure below shows Gartner's forecast of the overall IoT market and Industrial IoT applications. (Figure 1)

In China, the ecosystem for IoT has become increasingly mature as demand for industrial IoT applications continues to increase. According to CIC estimates, the scale of Industrial IoT in China reached RMB115.7 billion in 2014, accounting for 18% of the overall industry of IoT, while it today reaches approximately RMB150 billion, a growth rate of 29%. By 2020, Industrial IoT is expected to account for 25% of the overall IoT with an industrial scale exceeding RMB450 billion2.

The source of value and how it works
Given the great potential of Industrial IoT, we need to reflect on the ultimate origin of its value. IoT creates an overall new type of value, which is particularly different from the one derived from products and services: self-managed information and insights. More precisely, IoT can turn almost anything into a source of relevant information.

As early as 2015, Deloitte for the first time published the concept of the new value source derived from IoT, the so called "information value loop" (Figure 2). The core question of every company when defining a strategy is: how do we create value and how can this value be captured? The IoT is changing the way of how companies create value: traditionally, value creation was considered to be driven by the concept of the so-called "value chain" – a linear series of steps, that transforms inputs into outputs. The IoT technology allows to capture the information generated by these products and services – information that creates value in a fundamentally different way, put together and explained in the "information value loop".

IoT can significantly reduce the cost of computing and data storage, overturning previous definitions and frameworks for business value. We can think about the business value and opportunities generated by IoT via the following indicators (Figure 3).

The analysis from the above three dimensions clearly demonstrates that the business value of IoT will increase efficiency, promote business growth and enhance risk management, explained in more detail in Figure 4 below.

Embodiment of the value of Industrial IoT applications in China
While China's manufacturers recognize the importance of industrial IoT, they have not established clear-cut IoT strategies.
The Deloitte Survey on the Industrial IoT Applications in the Chinese Manufacturing Industry shows that 89% of the companies surveyed believe Industrial IoT is critical to business success in the next five years. While 72% have started Industrial IoT applications in one form or another, only 46% have established clear-cut Industrial IoT strategies and plans. (Figure 5)

Manufacturers are still in the beginning phase of data applications – the shift from interpretation to prediction takes time.
Most companies surveyed have begun to use sensors to collect data from products and devices or are intending to do so. More precisely, in terms of product data, 45% of the companies surveyed have already begun to collect data and 31% intend to start the collection. In terms of equipment data, 53% of the companies have started to collect data while 26% have made plans for collection. (Figure 6)

However, these companies remain in the perception stage of data application, and have not reached the action phase yet (Figure 7).

In-depth Industrial IoT applications require companies to change the way they use data—a transformation from interpretation to prediction. After using the data collected from a variety of sensors to interpret patterns of historical performance and the root causes, companies need to adopt a forward-looking perspective: how can the collected data be used to improve intermediate process and product sales? What sort of products and services may bring in new sources of revenue in the future? And what kind of IoT applications may open up new markets?

Key drivers - optimizing supply chain for efficiency improvement, enhancing customer experience for revenue growth and improving product safety for better risk management.
Our findings show that the Industrial IoT applications of Chinese manufacturers are mainly driven by efficiency improvement although revenue growth and risk management promotion have started to attract increased attention.

  • Efficiency Improvement
    In terms of efficiency improvement, optimizing supply chains through Industrial IoT applications has received the most attention, with 116 out of the 156 companies surveyed (74%) desiring to improve the efficiency of their supply chains and reduce costs through Industrial IoT applications. Some 110 companies (70%) desire to use technologies such as predictive maintenance to improve operational efficiency and reduce downtime, while others hope to improve business agility and legal compliance (Figure 8).

    Real-time data of supply chains can help pinpoint problems even before they occur. As a result, a company may reduce inventory and even capital requirements. Industrial IoT can help manufacturers better understand this information. By connecting factories to suppliers, all parties involved in the supply chain can track the interactions among them, the material flow, and the manufacturing cycle. Systems that support Industrial IoT enable location tracking, remote inventory monitoring and access to reports of parts and products moving in the supply chain. They can also collect and provide delivery information to enterprise resource planning (ERP), product lifecycle management (PLM) and other systems.

  • Revenue growth
    When it comes to the value proposition of IoT, industrial companies focus not only on efficiency improvement and cost reduction but also on business growth. Through data analysis, including the previously undeveloped data, translating the data into applicable market insights helps companies to better serve their customers, providing new opportunities to improve customer loyalty and satisfaction.

    Out of the 156 companies surveyed, 113 (72%) desire to improve their customer experience and generate revenue through Industrial IoT applications, while 107 companies (69%) hope to develop new products and services with the data generated by Industrial IoT and 95 companies (61%) want to use the IoT data to help them achieve innovation in their business models (Figure 9).

  • Enhance risk management
    Regarding the optimization of the risk management, key areas the companies surveyed focus on are product safety (77%), asset security (65%), operational security (65%), and effective management of warranty and recall (61%) (Figure 10).

    In terms of product safety, companies have improved quality control by maintaining the traceability of digital thread of products from raw materials to end products. Companies also use artificial intelligence algorithms and optimization programs to reduce rework and waste.

The focus of future Industrial IoT applications will shift from equipment and assets to products and customers.
Industrial companies equipped with IoT may generate business growth mainly in two ways: new products and services and closer customer relationships. To develop more attractive products or to enhance existing customer relationships, a significant amount of data concerning products and customers is needed.

At present, there is much less information on products and customers available compared with the data on assets and equipment. Driven by the demand for efficiency promotion as well as business growth, companies will shift their attention from equipment and assets to products and customers.

When asked in which areas more detailed and constructive data is needed, 69% of the companies chose the product data while 61% selected the customer data, surpassing the operational data (53%), sales data (53%) and asset and equipment data (42%). (Figure 11)

Key challenges - lack of interoperability standards, data ownership and security as well as under-qualified operators (Figure 12).

  • The lack of interoperability standards
    For 52% of the companies surveyed, the lack of interoperability standards is one of the major challenges in applying Industrial IoT technologies. Related studies show that due to the lack of interoperability 40% of the potential value of Industrial IoT cannot be realized4.
  • Ownership and security of data
    A total of 46% of the companies surveyed believe ownership and security of data are major challenges in applying Industrial IoT applications. The market has yet to agree on who owns the data, manufacturers or users of the equipment with which the data is collected. Most equipment suppliers tend to provide customers with an effective access to raw data, encouraging users to participate in manufacturing improvements. Regardless of the role they play — the data owner or the data guardian — equipment suppliers can reap their own profit from data generated by the Industrial IoT only after they share the data with and provide valuable services to their customers.

    Security is another obstacle for Industrial IoT. The sustained surge in the number of connected devices has provided industrial systems with unprecedented opportunities for growth and performance improvements. Nevertheless, this growth also poses new risks for industrial companies, especially considering the exponential risk of data breach. The security issue of Industrial IoT covers all aspects – from industrial processes and applications to safety and reliability requirements – and can therefore not be addressed in isolation.
  • Lack of relevant technical personnel
    Lack of qualified technical personnel is another major challenge for 42% of the companies surveyed. Considering factors such as the big variety of Industrial IoT applications and circumstances, new data sources, changes in system architecture data as well as multi-structured data, today's manufacturing companies do not have adequate analytical capabilities and required talents. Although many manufacturers do have sufficient experience in data analysis, their experience, however, mainly concentrates on the descriptive analysis based on the structural data sets instead of the predictive and pattern analysis using collected real-time big data in conjunction with a variety of unstructured data5.

    Although many universities are trying to develop appropriate talents in the field of data sciences, the number is still limited. Competition for high-end talents will become more intense. Thus, companies should recognize that building partnerships with educational institutions is becoming increasingly important.

Unleashing the business value of Industrial IoT
Industrial IoT will become a new source of revenue and improve efficiency and security, creating new value for businesses. To realize such value, companies need to take the following strategies into consideration:

Aim high, start small, create value and accelerate upgrades
Building an industrial IoT framework largely depends on a clear-cut strategy, which defines scopes and targets of IoT applications. A company without a clear-cut strategy always leans on a single-issue technology to solve diverse business problems while a company with a clear-cut strategy focuses on the comprehensive application of multiple technologies to change the overall way it operates and does business.

Industrial IoT has significant potential but applying it requires changes and adjustments in business culture, infrastructure, technical capability and human resource. Thus, if companies attempt to solve problems in a comprehensive manner, their growth might be stalled.

Consequently, companies should aim high but start small to create value and upgrade fast. Only when a series of small tasks is completed, big changes can happen. Companies should first launch specific pilot projects that will support the long-term goals, and find the necessary technologies for future promotion and fast upgrades only during this process.

Focus on the product and customer lifecycles
The value of industrial IoT does not only derive from management of products and equipment but also from management of products and customer lifecycles.

In order to extend these two lifecycles, identifying ways to convert a one-time transaction into a sustainable income source is crucial. One way to achieve this is for example the Manufacturing-as-a-Service (MaaS), which is based on Pay per Use. But many other ways that ensure closer customer relationships and sustainable value creation and fee charges can be considered.

Develop the ability to apply big data
The implication of big data is not to collect more data as such, but to be able to accomplish in-depth analysis to solve problems or to identify predictive policy decisions.

When companies build big data applications, they should start by designing a top-level framework based on business strategies and IT strategies. This framework should include the following elements: a) targets and strategies for big data applications, providing the roadmap for building applications and platforms; b) circumstances where big data analysis and modeling are used, providing clear configuration of big data applications based on value chain and customer lifecycle; c) big data analysis and modeling, which provides direction for problem solving through identifying challenges and applying multiple algorithms and d) a big data technology platform, which provides the necessity to track development trends of technologies and utilize all kinds of application systems in the company.

Improve security
Many companies decided to establish information security frameworks and mechanisms to minimize the risks. Information security mechanisms include information security targets (incidences, breaches, minimal value of production end time), security measures (physical measure, network, host, data, personnel, emergency preparedness and document management measures) and security management systems (for data centers, networks and sensitive devices and so on).

In addition to traditional information security risks, cyber risk has become an increasingly sensitive issue of IoT. Companies can manage cyber risk by applying the following measures:

  • Define interoperability standards: following a universal standard can help ensure secured and effective communication and collaboration amongst devices.
  • Use special devices and components instead of retrofitting the old systems: since old systems are not designed to cope with IoT security problems, companies should use new security technologies instead, specifically designed for IoT or components targeting cyber security problems.
  • Clarify areas of responsibilities for participants of the ecosystem: everyone in the IoT ecosystem should understand where their responsibilities begin and end, evaluating the potential risk at every juncture. Knowing the origin of a certain risk factor can help develop more secured solutions.
  • Develop data baseline: data baseline can help companies distinguish suspicious situations from normal ones, enabling companies to react when data goes out of the normal range.
  • Enhance data governance: management systems on data collection, usage and storage can help avoid damage and prevent negative influence from spreading.
  • Establish flexible coupling systems: if coupling systems are loose and flexible, the breakdown of a single system will not result in losses on a large scale.

Ensure proper positioning and cooperation in the ecosystem.
The overall system of Industrial IoT cannot be established by one single manufacturer. Rather, such system needs to be developed within a complete ecosystem.

GE Digital is now working with Dell, EMC, Microsoft, SAP, Nokia and dozens of other companies to develop an Industrial IoT platform, which allows these companies to develop new industrial applications and offer value-added applications to customers. And this is only one case among many others. Companies like Honeywell, Schneider, Cisco, IBM and Accenture are also in close cooperation, building an industrial IoT platform.

Of course, not every company can become an ecosystem builder and promoter like GE, especially if there are already too many IoT platforms on the market. The industry as a whole is expected to go through numerous integrations of IoT platforms while many existing ones will be eliminated.6 Whether companies should position themselves as builders of ecosystems, providers of modular products or establishers of channels will depend on how their businesses are designed and how profound their knowledge of their end users is.

Technological advances have unlocked the potential of IoT solutions in industrial applications. Such solutions improve operation efficiency, increase sources of revenue and inspire innovation. IoT has proved to be able to help companies create more and sustainable value and to convert one - time transactions in the past to long- term customer relationships. Although connectivity and security problems remain an issue, we still expect IoT to sweep through many important segments in the industrial sector.



  1. "Study on IT hardware and equipment for IoT: Industrial IoT has a huge potential", 2015-7-30,
  2. CIC, Report on the IoT Industry and Investment Prospects Forecast Based on the Data During the 13th Five-Year Plan
  3. The concept of "information value loop" came from Michael E. Raynor and Mark J. Cotteieer, "The more things change: Value creation, and the internet of Things" Deloitte Review 17, 2015-7-27, internet-of-things
  4. GS1 Global Barcode Organization, "Gaining Interoperability in the Digital Economy", 2015-7-17, industries/ GS1_Technical_Industries.PDF
  5. Zhang Lili, Jiudao Tech "The four major areas of Industrial IoT and big data analysis",
  6. Brian Buntz, " Drones, AR, and IoT Survival of the Fittest: 10 Tech Trends for 2017", 2016-12-8, Internet of Things Institute http://www.

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