thailand 2022 preview

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Copyright © 2015. Thai AutoBook. All Rights Reserved.

THE THAI AUTOMOTIVE INDUSTRY 2022 Turning Insights about the Future into

Functional Consequences Today

PREVIEW

Bangkok & St.Gallen, May 2015

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Copyright © 2015 by Thai AutoBook.

All rights reserved. No part of this publication may be reproduced, distributed, or transmitted in any form or by any means, including photocopying, recording, or other electronic or mechanical methods, without the prior written permission of the publisher, except in the case of brief quotations embodied in critical reviews and certain other noncommercial uses permitted by copyright law.

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The Future of the Automotive Industry in Thailand

Over the last 10 years Thailand has become the automotive hub of ASEAN – not only the ‘Detroit of the East’, and not only the ‘Toyota City’ of South East Asia but also the production headquarter for the Japanese manufacturers Honda, Nissan, Mitsubishi, Suzuki, Mazda and Isuzu.

Around these OEMs, Thailand has developed an infrastructure of multinational and local suppliers that is unmatched in South East Asia.

2012 and 2013 were dubbed the ‘Golden Years’ with production of 2.5 Million units propelling Thailand into the Top 10 of global automotive production countries.

With 2014 and 2015 we are now experiencing weaker years – by about 20% – however it is expected that the country’s production will rebound and achieve 3 Million cars by 2017 and 4 Million by 2020.

This expert study – Thailand Automotive 2022 - was prepared to give automotive professionals an additional platform to discuss the future of the industry – challenges, opportunities and issue that will shape the industry over the next 7 year cycle.

The study also includes detailed instructions for managers on how to turn the insights about the future into consequences for their functional strategies today. These instructions are very helpful to make practical use of the study results for your own planning as well as your communication activities with other functions or HQs.

And in Thai-terms: It should be used in a similar way as your ‘fortune teller’ –a friend illuminating the path that lies ahead for all of us.

I trust that it will be of significant value for your organization and invite your feedback to me personally at [email protected].

With kind regards,

Uli Kaiser Thai AutoBook 2015

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THE THAI AUTOMOTIVE INDUSTRY IN 2022: STUDY RESULTS

The Thai Automotive Market

The Thai automotive industry, also known as the Detroit of Asia, is the nation’s success story, as it has been a main contributor towards Thai economic development being the country’s biggest export industry (Thai Automotive Institute, 2012 p. 2-25). In 2012, Thailand stressed its position as a big automotive player by becoming the 7th largest car exporter globally with a total production of 2.45 million cars of which about 1 million were exported (The Economist, 2013).

Car sales growth figures of annually 13% in the Asia pacific region while there is negative growth in North America and only 1% growth in Europe (Siam Commercial Bank, 2013) stress the importance of the South East Asian car market in which Thailand is currently the leader. So far mostly Japanese manufacturers have discovered Thailand as an ideal production base (Kaiser, 2013) to mostly serve the growing ASEAN area consisting of about 600 million people (Saralertsophon 2012, p. 27). Nevertheless, it is incontestable that it is vital for every car manufacturer to be prepared for the future development of the Thai automotive industry since it offers a rare, yet appealing twofold opportunity- on one side as a potential sales market and on the other side as an attractive sourcing and production base to serve global demand (Kaiser, 2012. p. 11).

That’s exactly where the following report begins: The overall objective of this study is to provide an industry intelligence report on how the Thai automotive industry may look like in 2022 by conducting an online Delphi study with local industry experts followed by an in depth scenario analysis. Thereby, it is aimed to give new insights, which, if correctly interpreted and further developed can result in strategic advantages. The intention is to support senior executives and corporate strategy managers who are already involved in the industry or considering entering it, in their strategy development and decision making for the Thai automotive market.

This study is divided into three major parts:

1. Research methodology: This part includes a theoretical background on Emerging Markets (including Thailand), Delphi study methodology, PEST framework and the scenario development framework

2. Projections: The projections and their essence are then introduced and explained 3. Results of the Delphi study: The quantitative and qualitative results of the Delphi study

are presented in detail

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Evaluating the Future of the Thai Automotive Industry in 2022: Study Framework

In this section, the study framework is briefly explained. It structures the focus and selection of the projections (Exhibit 1).

Exhibit 1: Study Framework

The framework of this study is structured into three major sections. The core section is represented by an analysis of the political, economic, social and technological/infrastructure situation of the Thai automotive industry. The second section focuses on the analysis of the development of the Thai automotive industry in the context of ASEAN. Finally, the third section integrates a global perspective by considering developments outside of Asia.

The purpose of the core section is to analyze how the industry's development might look like due to changes in Thailand's political, economic, social and technological/infrastructure environments (Exhibit 1). With respect to politics, the question is how political developments and decisions will affect the car industry's future. From an economic perspective, it is important to state that the focus lays on the industries value chain and not on the macro-economic developments in Thailand. The reason for this is that the information of most value is expected to result directly from the investigation of each single value chain step and that information about macro-economic trends is often already publicly available. The social dimension of the framework evaluates trends among car buyers in Thailand as well as general trends in the Thai society relevant for the automotive industry. Finally, the technological dimension does not focus on actual technological developments such as new energy sources or engine concepts but is interpreted as infrastructure – ‘soft’ infrastructure focusing on human resources, intellectual capital and innovation etc.; ‘hard’ infrastructure focusing on energy, telecom or physical logistics infrastructure.

From a strategic perspective, it is important to not only accurately examine the trends within the Thai automotive industry along the proposed modified PEST analysis but also to include its

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surrounding developments (Exhibit 1). In the ASEAN section, the countries Indonesia, Malaysia and Myanmar are therefore listed because political decisions and the development of the automotive industries in these countries are expected to affect the future of the Thai automotive industry players in 2022. The third section, integrates other major automotive players which also influence the Thai automotive industry who are not as closely connected as the ASEAN players (Exhibit 1).

The Study Framework Applied: Development of Projections

For the purpose of this study, projections on how the Thai automotive industry might look like in 2022 have been developed according to the study framework. These projections have then been tested with experts from the Thai automotive industry using an online, real-time Delphi study tool. Except for the third section, i.e. the global perspective, at least one projection was developed and tested with the experts. Therefore, the countries and regions (Japan, China, India, Europe and USA) in the third section are not represented through a single projection each but are incorporated into other projections.

An extensive secondary research was conducted in order to develop the projections. This helped in identification of the most relevant topics and issues which could be converted into projections for the year 2022 related to the Thai automotive industry. These projections were further discussed with local experts of Thailand's automotive industry to assess their actual relevance and identify necessary adjustments. 20 projections about the Thai automotive industry in 2022 are presented below. The structure is in lines of the study framework (Exhibit 1). The results for each projection are then discussed in the next chapter.

The study framework resp. the majority of projections focuses on the core section, i.e. the modified PEST analysis of the Thai automotive industry. The questions in Exhibit 2 were answered through desk research and in collaboration with industry experts to develop the final projections.

In addition to the questions in Exhibit 2 to evaluate the core session, the following additional questions were influencing the evaluation of the broader context, i.e. ASEAN and worldwide.

ASEAN, India & China Environment Projections

How do the investors perceived the following countries with respect to their attractiveness as investment location for the global automotive industry in 2022 compared to Thailand:

• Malaysia • Indonesia • Myanmar • Vietnam • Philippines • India • China

Since most influences of the global environment section are already incorporated into the other projections, only three remain for China and India. The questions of focus in this case are the following:

China: How does the demand from China for Thai auto input look like in 2022? India: How does the demand from India for Thai auto input look like in 2022?

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Exhibit 2: Thai Automotive Industry (PEST) Projection: Guiding Questions

Political Dimension

How does the regulatory environment support / hinder the investment of foreign auto companies in Thailand in 2022 and what are the most important regulations for the industry itself in 2022?

Economic Dimension

Supplier What is the level of Thai auto suppliers in 2022?

R&D What is the R&D level in the Thai automotive industry in 2022? Where lays the focus and what is the level of innovation?

Sourcing What is the sourcing level in the Thai automotive industry in 2022? What level is the quality and what are the costs?

Production What is the production level in the Thai automotive industry in 2022? Which standard of technology is available and what will be the output?

Marketing How does marketing work in the Thai automotive industry in 2022?

Distribution How does distribution work in the Thai automotive industry work in 2022?

Consumers What does the Thai auto buyer want in 2022?

Social Dimension What is the value of cars for Thai society in 2022 and what are the most important social trends affecting the industry in 2022?

Technology (Infrastructure) Dimension

What is the level of the hard infrastructure (streets, etc.) and the level of the soft infrastructure (blue / white collar workers) for the Thai auto industry in 2022?

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Expert Panel (Delphi): Study Results (Selected View)

In this section, the Delphi study’s results for each projection are presented and discussed. These results include the probability and consensus level assessments of the participating experts. The level of consensus is especially analyzed whenever a dissent among the experts was identified. Additionally, the most important statements of the experts are briefly summarized for each projection.

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Thai Automotive Hub in SEA (TEPP1) (EXAMPLE)

TEPP1: In 2022, Thailand is the largest automotive production base for passenger cars in Southeast Asia.

The industry experts rate the average probability of the "Thai Automotive Hub in SEA" projection at 65% (Exhibit 27). It is expected that Thailand will remain the largest passenger cars production base in South-East Asia.

Strong dissent (Exhibit 27) has been reached among the industry experts concerning this projection.

Exhibit 27: Projection: Thai Automotive Hub in SEA (TEPP1)

No Value Chain Environment Projection Probability Consensus

7 In 2022, Thailand is the largest automotive production base for passenger cars in Southeast Asia.

65% 30

Likely Strong Dissent

The consensus analysis reveals that the experts converge with their probability ratings between 80% and 100%. However, since the expert ratings have ranged from 1% to 100% a strong dissent has been observed (Exhibit 28).

Exhibit 28: Consensus Analysis: Thai Automotive Hub in SEA (TEPP1)

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If this projection were to come true in 2022, 50% (Exhibit 29) of the experts felt that automotive companies in Thailand need to make minor to moderate changes in their operations today in order to be prepared for the future and 46% of them felt that a significant change is necessary.

Exhibit 29: If projection is true in 2022, how much do Automotive companies in Thailand need to change today`s operations to be prepared for the future?: Thai Automotive Hub in SEA (TEPP1)

Experts' comments: Thai Automotive Hub in SEA (TEPP1)

The experts cite three main reasons why Thailand will keep the position of automotive leader in SEA till 2022 and onwards. First of all, they stress the importance of auto infrastructure, which takes a lot of time to establish. In the case of Thailand the infrastructure is already mostly built up. Secondly, Thailand has a very strong domestic automotive cluster that offers several advantages; especially for the component parts industry and will therefore attract many more OEM's to localize in Thailand and thereby increase the number of part suppliers. And thirdly, diversification is believed to happen which will shift the low cost cars segment to Indonesia while the more profitable higher priced cars industry will be fostered in Thailand. Indonesia is perceived as Thailand's only potential real threat within ASEAN for the next 10 years because of growth potential resulting from their growing domestic market and because they still have room to improve. Nevertheless most experts consider it impossible to overtake Thailand within only 10 years.

Exhibit 30: Expert Comments: Thai Automotive Hub in SEA (TEPP1)

TEPP1: Exemplary Comments from Experts

Low Probability High Probability

• Indonesia will overtake Thailand. • Indonesia is a threat. So is India. • Indonesia will be about the same size in 7 to 10

years. • Indonesia will be the largest by then. • Malaysian and Indonesian automotive makers are

• It is already largest right now. • Infrastructure being put in place and all major OEMs

are investing on expansions. • Only serious competition is Indonesia which has

serious infrastructure and logistics weaknesses and can only serve large domestic market. As logistics

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much more in engineering capability than Thais.

costs continue to rise the Thai market manufacturing for export should remain the strongest.

• Available Skilled pool and best location and also other type of car as well Thailand will export 65-70%.

• I think it is likely that Thailand is largest automotive manufacturer - however pickup trucks may be a big % of that

Labour Costs (TEPP3) (EXAMPLE)

TEPP3: In 2022, labour costs for low-skilled and semi-skilled workers in the automotive industry are much lower in Thailand than in China.

The industry experts rate the average probability of the "Labour Costs" projection at 46% (Exhibit 35). It is not expected that the low-skilled and semi-skilled labour costs in the automotive industry will be much lower in Thailand than in China.

Strong dissent (Exhibit 35) has been reached among the industry experts concerning this projection.

Exhibit 35: Projection: Labour Costs (TEPP3)

No Value Chain Environment Projection Probability Consensus

9 In 2022, labour costs for low-skilled and semi-skilled workers in the automotive industry are much lower in Thailand than in China.

46% 30

Unlikely Strong Dissent

Though the consensus ratings converge between 41% and 60%, we see even spread of data across other ranges for example, between 0% and 20% and 80% to 100%, hence a strong dissent is observed (Exhibit 36).

Exhibit 36: Consensus Analysis: Labour Costs (TEPP3)

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If this projection were to come true in 2022, 60% (Exhibit 37) of the experts felt that automotive companies in Thailand need to make minor to moderate changes in their operations today in order to be prepared for the future and the rest of them felt that a significant change is necessary.

Exhibit 37: If projection is true in 2022, how much do Automotive companies in Thailand need to change today`s operations to be prepared for the future?: Labour Costs (TEPP3)

Experts' comments: Labour Costs (TEPP3)

Regarding the comparison between Thailand and China in terms of labour costs, there is not much consensus between the experts. Some experts state that the labour costs are currently lower in Thailand and that they will further rise in China due to high inflation and fast growth, especially in the automotive industry. Additionally, it is believed that the introduction of the AEC will keep the costs low in Thailand since labour migration will be simplified.

Experts on the other hand reason that China is a much bigger country with huge labour resources whereas Thailand is reaching the maximum level of labour use/availability already, which will automatically lead to higher labour costs. At the same time, the Thai government makes the labour cost situation even worse by preventing migration of labour from neighbouring countries. Additionally inflation is not only a problem in China but also in Thailand.

Exhibit 38: Expert Comments: Labour Costs (TEPP3)

TEPP3: Exemplary Comments from Experts

Low Probability High Probability

• Strong unions. • The labour costs will rise as well significantly in

Thailand. The costs will still be lower but not much compared to China.

• Short of worker will drive the wage (up). • China is a big country which doesn't use all of its

labour yet, but Thailand is going to reach the

• It is already so now. • If there's labour shortage foreign workers will be

imported & their labour rate is lower. • China rate of pay increase is higher than Thailand • They are lower now and costs in China will rise

stronger than Thai cost. • Labour cost in China is increasing rapidly due to high

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maximum level of labour use already. • Thailand does everything to impede migration of

labour from neighbouring countries while at the same time forcing increases in labour cost.

• Costs are continuing to increase in Thailand, inflation will hinder the industry.

inflation and fast growth in the automotive industry. It will pass Thailand very soon.

• Could come down from AEC.

…

INSTITUTIONS-RESOURCES MATRIX (I-RM) This PRIMER in APPLYING the INSTITUTIONS-RESOURCES MATRIX (I-RM) provides managers and consultants as well as students with an introduction into “how to apply the I-RM” when developing or assessing a strategy. In short, we believe that the I-RM as a framework fills a gap that supports practitioners to systematically turn insights about the future institutional environment1 of a company (i.e. the competitive environment) into consequences on the corporate/business unit but especially the functional level2 (i.e. the resources/capabilities of functions such as marketing, production or procurement). The I-RM is part of the of strategy formula3 concept based on resp. inspired by McKinsey’s 10 Strategy Tests (Appendix). The strategy formula allows students to better understand what matters for superior strategies (i.e. the creation of competitive advantages) and how the three major elements of strategic management (i.e. strategic analysis, strategy development and strategy implementation) complement each other. Within the strategy formula resp. McKinsey’s 10 Strategy Tests the I-RM basically represents a tool to process insights about future developments within a company as required in the tests #3 to #5.

For a more detailed overview on the strategy formula and its different components, please refer to the PRIMER in STRATEGIC MANAGEMENT available upon request from Prof. Dr. Roger Moser.

STRATEGIC ANALYSIS: TURNING FUTURE INSIGHTS INTO FUNCTIONAL CONSEQUENCES TODAY

Creating an accurate picture of the future is essential for executives to improve their decision making in general and their strategies in particular. About 50% of the challenges that executives face include a structured analysis of more than one alternative that needs to be considered (Exhibit 83). However, many companies do not have well-structured processes in their companies that enable an appropriate information management during rising complexity resp. information requirements.

1 The institutional environment is broadly understood as all major “forces” that can influence the competitive environment of a company.

This includes all aspects that belong to the PESTEL environment – the political, macro-economic, social and technological, ecological or legal environment – or the value chain activities of competitors – the sourcing, R&D, HR, finance, manufacturing, marketing, sales or after-sales activities etc. of competitors – or the behaviour of other important stakeholders such as customers, suppliers or NGOs.

2 The I-RM focuses in its application primarily on the identification of potential consequences of future developments in the institutional environment on the functional strategies of a company. However, in order to identify consequences on a functional level.

3 The strategy formula has been developed by Prof. Dr. Roger Moser, Assistant-Professor of International Management at the University of St.Gallen, for the Competitive & Corporate Strategies course in the MBA program of the University of St.Gallen. The strategy formula structures McKinsey’s 10 Strategy Tests in a different way to better highlight the interdependence between the different strategy tests.

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The information management capabilities of companies can be separated into information gathering and information processing activities (Exhibit 84). Information gathering can either happen through advanced BIG Data analyses (e.g. advanced analytics) or through smart SMALL Data collection approaches (e.g. expert-panels). While there are many external service providers to help with big or small data collection efforts, companies also need structured approaches that support their information processing efforts. The “Institutions-Resources-Matrix” supports executives to transfer their insights about future developments in the institutional environment into functional consequences for their companies.

Exhibit 83: Four Levels of Uncertainty

Source: Courtney et al.: Strategy Under Uncertainty, Harvard Business Review (5), 1997.

Exhibit 84: Information Gathering & Processing (Organizational Information Processing Theory)

Source: Moser, MBA-HSG, 2013.

In short, the organizational information processing theory (OIPT) claims that companies need to adapt their information management capacities (e.g. processes, structures, systems) to the information requirements a company faces. For example, a company operating in the Swiss fresh

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food retail sector faces a different information requirement challenge (i.e. magnitude of uncertainty and ambiguity in the institutional environment of the company) than if it would operate in the Indian retail market. Accordingly, the company needs to have different information management capacities (i.e. industry intelligence gathering and processing). Theoretical considerations and an empirical study4 confirm that a fit between the level of information requirements and the level of information management capacities actually leads to superior strategies which finally positively influence a company’s performance. Although the strategy test (i.e. Test #4 – Does your strategy rest on privileged insights?) among McKinsey’s 10 Strategy Tests that was neglected most among more than 2000 executives around the globe focuses directly on the value of insights into the institutional environment that (almost) nobody else has. It is not the only decisive element when trying to create competitive advantages.5 Therefore, companies do not per se have to invest into their own intelligence gathering efforts although privileged insights (i.e. Test #4) along with having an in-depth understanding of trends (i.e. Test #3) and proactively embracing uncertainty (i.e. Test #5) are often useful to identify future opportunities and create competitive advantages.

Instead, it matters as much for the creation of competitive advantages that companies have intelligence processing processes and structures that actually allow the relevant decision makers (not only at the top) to access, discuss, interpret and finally base their decisions upon. Especially any kind of report about long-term future developments in the less-industry specific institutional environment (e.g. trends in the society, general technological advancements, major changes of policies in governments etc.) are often not easy to transform into consequences for a company that go beyond basic analyses at the corporate or BU level. However, most strategies are finally implemented (i.e. turned into action) on the functional level. This means that there is only a little value for a company as such if (non-) privileged insights about the future institutional environment are not only analyzed and discussed but have a real impact on the resource (re-) allocation (e.g. budgets, time/attention of executives, capabilities of employees) in all affected functions.

The Institutions-Resources Matrix (I-RM) focuses specifically on the structuring of insights about the future and their transformation into consequences for companies – not only on the corporate or business unit level but even the functional level where most strategies are finally implemented (Exhibit 85).

4 Kuklinski, Moser and Callarman have empirically confirmed in a study the existence of ideal profiles of information management

capacities (i.e. different intelligence gathering and processing activities) for different information requirement levels (i.e. different levels of uncertainty and ambiguity ) in the context of foreign Strategic Business Units in China. The transfer of these insights into other contexts seems at least reasonable. The conference paper of Kuklisnki et al. about the study won one of five best paper awards of the European Decision Sciences Conference in 2013.

5 Bradley et al., McKinsey Quarterly, 2011 talk about an Insight Deficit in many companies as more than 50% of the more than 2000 executives in study confirmed that they do not specifically invest in intelligence gathering activities that create insights that other companies do not have access to.

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Exhibit 85: The Institutions-Resources Matrix (I-RM)

Source: Moser, MBA-HSG, 2013.

In fact, the I-RM is basically a tool for any interested party to turn rather long-term future insights into functional consequences today resp. tomorrow. In short, the I-RM involves three major steps.

First, step Ia requires to choose a specific scenario or single projection about the future developments in the institutional environment and identify in step Ib the implications of this specific scenario or single projection on the focal company’s corporate resp. BU strategy.6

Next, step 2a requires choosing a specific functional focus7 for the company resp. the BU as well as identifying those elements of the corporate resp. BU strategy that matter for the chosen functional focus. Step 2b then transforms the implications of the corporate resp. BU strategy identified as relevant for the functional strategy (i.e. insights from step 1b) into consequences for the specific resources of the chosen function. The I-RM includes the following resources in its basic model although executives can add or replace or even delete the suggested resource categories8 according to their specific needs:

Ø Physical Resources Ø Human Resources

6 In general we speak in this context about the corporate strategy of a company if the company has only a limited market/activity focus

that is integrated into a single organizational unit (i.e. business unit strategies). If a company comprises of several BUs (business units) it is recommended to analyse the implications for each BU separately.

7 The most appropriate functional focus depends on the organizational structure of the company as well as the background resp. objectives of the executives applying the I-RM. In most cases it makes sense to focus on the critical sets of activities that are most important for the strategy implementation of a company. Besides the primary value chain activities such as logistics/distribution, R&D, production/operations or marketing/sales it also makes to run separate analyses for the HR or IT function.

8 The five resource categories have been selected as the basic model because they represent a set of resources that virtually and function in a company has to rely on in one way or another. For example, even the human resources department of a company needs some office space (i.e. physical resources), the production/operations function requires the adaption of the skills of its blue-collar workers (i.e. human resources) over time, and even the marketing function has to integrate new technologies such as analytics and social media into its strategy implementation activities. Moreover, all functions need to adapt their organizational resources to the developments in the institutional environment. For example, the integration of TV, internet access the provision of games as a technological trend requires many R&D departments to reorganize their organizational resources to make sure they are close to the consumer market as well as new display technologies at the same time. Finally, relational resources are especially important when the company looks into institutional environments where it has traditionally not been active or when a company has several BUs that do not share many functional activities.

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Ø Technological Resources Ø Organizational Resources Ø Relational Resources

Finally, the optional step 3 allows executives to assess the potential financial consequences of any identified implication for a function and thus provide a first outlook on future budgets of the focal function.

In practice, executives have to repeat especially step 1a/b and step 2a/b for any chosen function for all selected specific scenarios resp. single projections that potentially have a strong impact on the company resp. the function and their set of activities. If such an analysis is done for a single function across major future developments that matter for the company, executives often realize that some consequences for the resources of a function have been repeatedly identified across various scenarios or projections. These consequences are often the most interesting ones as they matter across different scenarios and/or single projections. It is especially these consequences where executives want to spend some more time to assess what this means for the future budget of the function and other aspects of strategy implementation including communication, motivation, qualification and organization.

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