1. Growth in things connected to the Internet With advances in Internet technology, as well as in

sensors and other technologies, household appliances, vehicles, buildings, factories, and many other things in the world are starting to be connected to the Internet, in

addition to conventional Internet-connected devices such as PCs and smartphones. In the Internet of Things (IoT) era, the number of things connected to the Inter-net is predicted to explode.

2. Growth in data trafficThe data traffic on networks is certain to skyrocket,

given the growth in things connected to the Internet, as mentioned in the previous paragraph, the global pene-

tration of the Internet, and the emergence of various services and applications.

3. Creation of new markets and business model transformationsHow will the explosive growth in Internet-connected

things and data traffic transform existing ICT industries and market structures?

The first projected effect is the creation of new mar-kets and the development and expansion of existing ICT industries and markets. Potential new markets are those for new services and applications focused on adding value to big data collected from devices. Artificial intel-ligence (AI) technologies are expected to analyze and make use of big data created by the IoT. AI advances, then, will likely accelerate the IoT’s creation of markets.

The second projected effect is further competition, as new business domains emerge. The competition around new added value from data and business domains will arise not just between traditional ICT industry enterpris-es but also between entrants from other industries and sectors, including ICT user industries.

In this way, an ecosystem of new ICT industries is ex-pected to form, while existing ICT platforms and new ICT trends, driven by IoT, big data, and AI, influence and interact with each other.

1. Platforms(1) Cloud service market

Cloud services provide Internet resources such as servers, applications, data centers, and cables.

As pointed out in the previous section, the explosive growth in Internet-connected devices will fuel exponen-tial growth in the data generated by these devices. Ex-tracting value from huge numbers of devices and mas-sive volumes of data with conventional cloud services entails very significant costs and labor. Furthermore, applications requiring real-time performance and ser-vices handling big data suffer from latency problems because cloud computing lacks sufficient processing power.

Edge computing is a recent technological trend to overcome these problems. Edge computing is a concept that expands conventional cloud computing to the edges of networks and distributes and allocates resources physically close to end users. The edges of a network re-fer to the borders where a communications network in-terfaces with external networks or the areas where end terminals are connected to the network. In other words, applications are distributed close to where data are cre-ated instead of concentrating data and their processing in the cloud. The goal of edge computing is to make use of more data and derive more value from the data (Fig-ure 2-2-1-1).

Section 1　Current Status of the ICT Industry and Its Structural Reorganization

Section 2　Quantitative Verification of the Market Size, etc.

This chapter organizes the overall structure of the ICT industry, given IoT progress, and provides quantitative verifications of each market’s size, growth potential, and competitive environment.

20

Part 1

Chapter 2Analysis of ICT Industrial Trends in the IoT Era

CW6_AY057D02.indd 20 2016/12/08 10:24:28

Edge or fog computing, when combined with deep learning and other AI technologies, should lead to the implementation of various services and applications. One leading example is the FANUC Intelligent Edge Link and Drive (FIELD) System, a shared IoT develop-ment platform for manufacturers created in Japan that automatically controls machines running in factories. The FIELD System was announced by FANUC, Cisco Systems, Preferred Networks, and Rockwell Automa-tion. FANUC is a Japanese electronics manufacturer in-volved in machine tool robotics and industrial robots. Preferred Networks is a Japanese startup specialized in

business applications of real-time machine learning technologies, with a focus on the IoT. The FIELD Sys-tem is a platform for developing applications to be posi-tioned in the fog layer. The platform is provided together with applications needed for factory workplaces or deep learning. The system takes data from computer numeric control (CNC) machines, robots, machine tools, and various sensors and realizes real-time connectivity be-tween machines through distributed cooperative ma-chine learning that processes data in the fog layer. Through this interconnectivity, the FIELD System aims to boost the productivity of industrial robots.

2. Networks(1) Fixed broadband and mobile communications servicesa. M2M market

Before the IoT had garnered any attention, machine-to-machine (M2M) communications that connect ma-chines via communications carrier networks were in use in many fields. OECD statistics by country on the num-ber and penetration rate of M2M connections using communications networks show that the United States leads the way, with 44 million connections, followed by Japan, with 12 million.

As the penetration of smartphones and other personal communications devices reaches saturation, communi-cations carriers in many countries are moving ahead strategically with the provision of M2M services run-ning on their own mobile communications services in anticipation of the IoT’s emergence. Although no M2M or IoT business models have been established, risings costs, accompanying the increase in connections, is a pressing issue.

Because of this, communications carriers have 2 ma-

jor challenges: (1) creating unified platforms for M2M services and (2) cutting sales costs. The first challenge involves developing a common platform for M2M func-tions, instead of building separate M2M services for each customer, and using the platform as a model to lower service rollout and operation costs. Jasper Tech-nologies is the largest platform provider and supplies platforms to many communications carriers. In Japan, NEC, Fujitsu, NTT Data, and others offer similar plat-forms. For the second challenge, the key to lowering sales costs is a B2B model that can capture large num-bers of devices per contract — in particular, capturing global corporations with large user bases. But to capture global corporations and to resist gigantic communica-tions carriers like Vodafone that possess their own glob-al networks, communications carriers in many countries have to establish environments in which they can pro-vide one-stop services around the world. To this end, communications carriers are forging stronger alliances with each other.

(Source) “Study Report on a Structural Analysis of the ICT Industry in the IoT Era and Verification of ICT’s Multifaceted Contributions to Economic Growth,” MIC (2016)

Figure 2-2-1-1 Edge computing concept

App App App App

AppApp AppAppApp

NetworkEdge computing

App

Reduce communications trafficby temporary processing

big data at network edges

Ensure real-time performance byexecuting processes near the user

Internet Internet

Requires real-time performance

Big data congests bandwidth

Distribute heavy processingloads to edge servers

Cloud computing

21

Part 1

CW6_AY057D02.indd 21 2016/12/08 10:24:31

1. IoT expansion efforts domestically and abroad(1) Developments in IoT standardization

Many players in the IoT world are moving ahead ag-gressively with R&D and standardization. In particular, alliances and consortiums are actively working on inter-national standards.

In our international survey of enterprises (in Japan, the United States, the United Kingdom, Germany, South

Korea, and China), we asked enterprises about their per-spectives on IoT standardization initiatives. The answers fell into 2 camps: countries with many corporations tak-ing their own initiatives — the United States, Germany, and China; and countries without many such enterprises — Japan, the United Kingdom, and South Korea (Figure 2-3-1-1).

Section 3　IoT Progress In and Outside Japan

2. IoT adoption by enterprisesEnterprises, when using and applying data, tend to

pass through 3 stages: they begin by collecting and ac-cumulating data, then make future forecasts based on visualizing and ascertaining current conditions, and fi-nally optimize the target of the data. Through these stages, enterprises change their business processes, add supplementary services to existing products, pro-vide consulting services based on their data, or even trigger business model transformations. In the first stage of collecting and accumulating data, either the added value created with the data is small or it is very difficult for the enterprise to predict how much value will be created by continuing to use and apply the data. This is why enterprises often start small when adopting IoT, using cloud services first and then expanding while observing the benefits of adoption.

The survey of Japanese enterprises found that while 51.5 percent were involved in collecting and accumulat-ing data, only 13.4 percent had expanded added value through business model transformations. This finding

suggests many enterprises currently remain at the col-lecting and accumulating stage (Figure 2-3-2-1).

When enterprises adopt IoT, either they adopt IoT to internal processes with the enterprise acting as the user or they adopt IoT to goods and services the enterprise provides as a supplier. The description below defines the former as IoT adoption to processes and the latter as IoT adoption to products.

(1) Purpose of IoT adoption by enterprisesEnterprises that adopt IoT to processes are primarily

interested in cutting costs. ICT enterprises may consid-er developing IoT services themselves, but in the major-ity of cases IoT solutions from external vendors are used. In either case, suitable capital investments are nec-essary. The primary benefit of IoT adoption to processes is lower costs, but there are examples of secondary ben-efits, such as increasing employee ambition. For exam-ple, Omron, together with Fujitsu, introduced data visu-alization for a production line at its Kusatsu factory. By

(Source) “Study Report on a Structural Analysis of the ICT Industry in the IoT Era and Verification of ICT’s Multifaceted Contributions to Economic Growth,” MIC (2016)

Figure 2-3-1-1 IoT standardization stances of enterprises in 6 countries

0

20

40

60

80

100

Japan(N=173)

UK(N=69)

South Korea(N=91)

U.S.(N=89)

Germany(N=79)

China(N=82)

（％）

Don’t knowNot interested in standardizationDo not engage in standardization activities ourselves, but expect standardization to progressEngage, or plan to engage, in standardization activities ourselves

22

Part 1

CW6_AY057D02.indd 22 2016/12/08 10:24:34

being able to verify the outcomes of improvements visu-ally, workplace motivation was boosted significantly and a virtuous circle leading to more improvements result-ed. Overall, production efficiency was increased by about 30 percent.

The main goal of enterprises that adopt IoT to prod-ucts is increasing sales. Initially, enterprises invest in R&D to a degree commensurate with the expected in-crease in sales and proceed with applying IoT to prod-ucts.

(2) Typical example of IoT adoption to products The main target of enterprises adopting IoT up to now

has been cutting process costs, but expectations are mounting that adopting IoT to products will increase sales. IoT adoption to products is typically done in sev-eral stages.

The first stage is to equip the product with sensors and communications modules so it can connect to the Internet. The next stage is to use data obtained from the product to add more value to the product. The final stage is to either develop new services using the data obtained from the product or to use the enterprise’s internal ICT platforms, or else laterally develop applications, to col-lect and analyze data from the product.

3. International comparison of IoT initiatives by enterprisesBased on the state of IoT initiatives and examples

given in the previous paragraph, we conducted a survey of enterprises (in all industries) in 6 countries (Japan, the United States, the United Kingdom, Germany, South Korea, and China) to verify the actual state of IoT adop-tion as well as the benefits and issues with IoT adoption.

(1) IoT adoption rateWe first confirmed the current state of IoT adoption

among enterprises and their intentions to introduce IoT in the future (around 2020). The current adoption rate in the United States is far ahead, with over 40 percent of companies adopting ICT to both processes and prod-ucts. The United States enjoys rates double the other 5 countries, including Japan, which are around the 20-per-cent level.

As for the intention to adopt IoT by 2020, IoT adoption rates are projected to double or triple current rates in both processes and products. Comparing countries, however, finds that Japanese enterprises have lower in-tentions to adopt IoT in the future. Therefore, there is a real possibility that the current gap will grow with not only the United States but also other countries (Figure 2-3-3-1).

(2) Views on IoT marketsJapanese enterprises showed less enthusiasm, on the

whole, than their counterparts in other countries when asked for their forecasts about how much IoT would add to the market size of their respective industry in the coming years (i.e., their expectations for IoT to increase market sizes). There was also a considerable gap be-tween Japanese ICT enterprises and non-ICT enterpris-es on this question, suggesting that non-ICT enterprises have rather low expectations for IoT (Figure 2-3-3-2). It is possible to surmise that this gap in IoT expectations may be a factor why Japan’s IoT adoption rate and invest-ment trails that of other countries.

(3) Issues with IoT progressWe compared issues complicating IoT progress be-

tween the 6 countries. The countries have common is-sues in the area of IoT infrastructure build-out. On the other hand, the countries had diverging perceptions of issues in the areas of creating new markets or raising capital. These differences may influence the state of IoT progress in each country. Japanese enterprises, in par-ticular, tended to view “personnel training” as an issue more than those in other countries (Figure 2-3-3-3 and Figure 2-3-3-4).

(Source) “Study Report on a Structural Analysis of the ICT Industry in the IoT Era and Verification of ICT’s Multifaceted Contributions to Economic Growth,” MIC (2016)

Figure 2-3-2-1 State of data use and application by Japanese enterprises

51.5

43.5

33.5

22.4

13.4

9.4

30.8

0 10 20 30 40 50 60

Collection / accumulation of data

Identification of the current status through data analysis

Prediction through data analysis (business performance,inventory management, etc.)

Speed-up of responses and operational efficiency improvementby using data analysis results

Expansion of added value through new business models basedon data analysis results

None of the above

Don't know (N=620)

(%)

23

Part 1

CW6_AY057D02.indd 23 2016/12/08 10:24:36

(Source) “Study Report on a Structural Analysis of the ICT Industry in the IoT Era and Verification of ICT’s Multifaceted Contributions to Economic Growth,” MIC (2016)

Figure 2-3-3-1 Current IoT adoption (2015) and future adoption intentions (by 2020)

LegendCountry(1) Current loT adoption (2015)Country(2) Future adoption intention (by 2020)

U.S.①

U.K.(1)U.K.(1)

Germany(1)Germany(1)

Japan(1)Japan(1)China(1)China(1)

SouthKorea(1)SouthKorea(1)

0

20

40

60

80

100

0 20 40 60 80 100Introduction rate in process (level of progress inoperational efficiency improvement using the IoT)

U.S.(2)U.S.(2)

Germany(2)Germany(2)

U.K.(2)U.K.(2)

China(2)China(2)

S. Korea(2)S. Korea(2)

Japan(2)2015 2020

Taking the leadin product

Taking the leadin process

(%)

(%)

Intr

oduc

tion

rate

in p

rodu

ct (l

evel

of p

rogr

ess

inde

velo

pmen

t / p

rovis

ion

of n

ew g

oods

/ s

ervic

es u

sing

the

IoT)

Source: “Study Report on a Structural Analysis of the ICT Industry in the IoT Era and Verification of ICT’s Multifaceted Contributions to Economic Growth,” MIC (2016)

Figure 2-3-3-3 Averages and variation coefficients for IoT progress issues

0

0.1

0.2

0.3

0.4

10 20 30 40 50Average

Policy / support forpromoting penetration

Fund procurement

Creation of new markets

Sophistication / virtualizationof networks

Development of networkinfrastructure

Standardization

Development of ruleson data distribution

Establishment of businessmodels in existing markets

Human resourcesdevelopment

Penetration ofterminals / sensors

Issues that differ amongcountries

Issues common to allcountries

*Deviation value divided by the average. When the coefficient of variation is small, the factor is commonly recognized by all countries as an issue, and when the coefficient of variation is large, there are differences among countries as to whether they recognize the factor as an issue.

(%)

Coeffi

cien

t of v

aria

tion

(C.V

.)

(Source) “Study Report on a Structural Analysis of the ICT Industry in the IoT Era and Verification of ICT’s Multifaceted Contributions to Economic Growth,” MIC (2016)

Figure 2-3-3-2 Predicted market expansion due to IoT in own industry by 2020

0

5

10

15

20

25

Japan(ICT industry

N=76,Non-ICT industry

N=304)

US(ICT industry

N=24,Non-ICT industry

N=98)

UK(ICT industry

N=21,Non-ICT industry

N=63)

Germany(ICT industry

N=21,Non-ICT industry

N=88)

South Korea(ICT industry

N=23,Non-ICT industry

N=93)

China(ICT industry

N=23,Non-ICT industry

N=77)

(%)

ICT industry Non-ICT industry

Prepared based on responses to the question “To what extent do you think the market size of the overall domestic industry to which your company belongs will expand through the progress and penetration of the IoT over the next five years (by around 2020)?”

The market expansion rate predicted by non-ICT companies was only about half the rate predicted by ICT companies.

*�Deviation�value�divided�by�the�average.�When�the�coefficient�of�variation�is�small,�the�factor�is�commonly�recognized�by�all�countries�as�an�issue,�and�when�the�coefficient�of�variation�is�large,� there�are�differences�among�countries�as�to�whether�they�recognize�the�factor�as�an�issue.

24

Part 1

CW6_AY057D02.indd 24 2016/12/08 10:24:38

(4) International comparison of IoT progressBased on the survey results, we created an indicator

to measure the state of IoT progress in each country. We also defined an indicator to express the state of wireless communications infrastructure, which is a key factor in creating the conditions for IoT progress. With these 2 indicators, we created a mapping of the 6 countries. In Japan, the percentage of enterprises pointing out infra-

structure as an issue hindering IoT progress was low internationally. But as seen from the statistics, the IoT progress index in Japan is low compared to the state of its infrastructure build-out. Measures are needed, then, to further IoT use and application, such as personnel training and publicizing IoT usage scenarios among user enterprises (Figure 2-3-3-5).

Source: “Study Report on a Structural Analysis of the ICT Industry in the IoT Era and Verification of ICT’s Multifaceted Contributions to Economic Growth,” MIC (2016)

Figure 2-3-3-4 Number of IoT progress issues by country

39.953.4 50.0 49.0

38.5 44.9

26.9

23.3 25.0 26.0

24.627.1

13.69.7 12.0 15.4

18.014.0

7.48.7 9.8 4.8

13.9 6.512.1 4.9 3.3 4.8 4.9 7.5

0

20

40

60

80

100

Japan(N=594)

US(N=103)

UK(N=92)

Germany(N=104)

South Korea(N=122)

China(N=107)

(%)

This figure groups the issues from Figure 2-3-3-3 as follows.●Infrastructure:“sophistication / virtualization of networks” “development

of network infrastructure” “penetration of terminals / sensors”●Rules:“development of rules on data distribution” “tandardization”●Markets:“creation of new markets” “establishment of business models

in existing markets”●Funds:“policy / support for promoting penetration” “fund procurement”●Human resources:“human resources development”

Infrastructure Rules Markets Funds Human resources

Source: “Study Report on a Structural Analysis of the ICT Industry in the IoT Era and Verification of ICT’s Multifaceted Contributions to Economic

Growth,” MIC (2016)

Figure 2-3-3-5 IoT progress index and an international comparison

IoT progress index (based on a questionnaire surveyof companies) WeightProcessRate of introducing IoT solutions 0.25Amount of IoT-related capital investment by companies that have introduced IoT solutions (percentage of total sales) 0.25

ProductRate of providing IoT goods / services 0.25Amount of sales of IoT goods / services by companiesthat provide IoT goods / services (percentage of total sales) 0.25

Index related to wireless communications infrastructure (ITU*) WeightMobile-cellular telephone sub scriptions per 100 inhabitants 0.5Active mobile-broadband sub scriptions per 100 inhabitants 0.5

Capital investment amounts, instead of product cost reduction rates,were used to be able to compare sales ratios

0

5

10

15

20

25

30

35

0 20 40 60 80 100 120 140Index related to wireless communications infrastructure

US

China GermanyUK

JapanSouthKorea

IoT

prog

ress

inde

x

Source: ITU “ICT Development Index”

25

Part 1

CW6_AY057D02.indd 25 2016/12/08 10:24:39