1. Businesses must understand the changing landscape and how it could affect their decisions on the location of manufacturing plants and could use a new methodology for making better decisions about plant location in the region.
2. ASEAN countries account for about 5 percent (McKinsey Global Institute) of global manufacturing (in value added terms) with dominant shares in sub-sectors such as chemicals, food and beverage, metals, and motor vehicles with new trends shaping these sectors.
2. ASEAN countries account for about 5 percent (McKinsey Global Institute) of global manufacturing (in value added terms) with dominant shares in sub-sectors such as chemicals, food and beverage, metals, and motor vehicles with new trends shaping these sectors.
MANUFACTURING COMPETITIVE INDEX
1. Country's industry attractiveness for FDI can be measured using a framework categorising manufacturing sectors into five broad categories. Industries within each group have similar sources of competitiveness and share important factor inputs and geographic requirements, such as the need for proximity to certain types of transportation infrastructure and talent requirements.
2. The framework's result is a competitiveness index derived from a detailed database of hundreds of indicators weighted by their importance to the cost and revenue base for a particular sub-sector. The indicators are grouped into two primary categories (Cost and Quality).
3. Cost — Factors such as utility rates, wages, property prices and taxes, and fiscal or tax incentives, that have a tangible impact on a manufacturing operation’s profitability. Examples of data inputs in the cost model include employee headcount, utility usage, and size of property.
4. Quality —The overall infrastructure and ecosystem that facilitate and enable manufacturing operations. Components include the labor or talent pool, business environment, quality of life, infrastructure such as roads, utilities, and Internet access for improved connectivity; physical access to other markets; and the current ecosystem or linkages for a given industry. Examples of data inputs into the quality model include sector GDP growth, volume of imports and exports for the associated sector, quality of infrastructure, and employment rate.
5. Below is a table showing the top 4 attractive ASEAN countries by cost and quality considerations for identified industry. The score for each location is calculated using an algorithm based on the raw data point and weights. A high score indicates a better quality location.
3. Cost — Factors such as utility rates, wages, property prices and taxes, and fiscal or tax incentives, that have a tangible impact on a manufacturing operation’s profitability. Examples of data inputs in the cost model include employee headcount, utility usage, and size of property.
4. Quality —The overall infrastructure and ecosystem that facilitate and enable manufacturing operations. Components include the labor or talent pool, business environment, quality of life, infrastructure such as roads, utilities, and Internet access for improved connectivity; physical access to other markets; and the current ecosystem or linkages for a given industry. Examples of data inputs into the quality model include sector GDP growth, volume of imports and exports for the associated sector, quality of infrastructure, and employment rate.
5. Below is a table showing the top 4 attractive ASEAN countries by cost and quality considerations for identified industry. The score for each location is calculated using an algorithm based on the raw data point and weights. A high score indicates a better quality location.
MOTOR VEHICLE AND COMPONENTS MANUFACTURING
1. Cost optimisation is critical in this sector for locating operations balancing low manufacturing costs with overall supply chain costs.
2. Thailand has the best position to capture the opportunity and attract manufacturing FDI although it’s overall cost index is higher than Indonesia, Vietnam and the Philippines. Its quality index has the strongest weighted score due to its high quality and mature automotive manufacturing ecosystem.
3. Indonesia is expected to see an increase in FDI from its strong local demand for automobiles although its quality index lags behind and developing a robust auto ecosystem could make Indonesia more competitive in the ASEAN market. The Philippines and Vietnam also score highly on the cost factors, but their respective automotive industries lack both a sizeable motor vehicle and components manufacturing base and sufficient local demand to attract a greater share of investment.
CHEMICALS
1. Quality considerations notably business environment, regulation, ease of import and export, quality of infrastructure and the availability of skilled workers play a stronger role over cost in guiding investment decisions.
2. Singapore has a strong result on the quality index due to its dedicated industry infrastructure on Jurong Island and strong connectivity through shipping routes, making it an attractive location demonstrating that quality considerations allow a country to offset its higher costs.
3. Indonesia, the Philippines, and Vietnam have similar levels of attractiveness both on cost and quality dimensions. Vietnam is singled out for its successful efforts in attracting investment in chemical production from aggressive government policies in promoting the industry.
3. Indonesia, the Philippines, and Vietnam have similar levels of attractiveness both on cost and quality dimensions. Vietnam is singled out for its successful efforts in attracting investment in chemical production from aggressive government policies in promoting the industry.
FOOD, BEVERAGE, AND TOBACCO
1. Cost and quality factors are equally competitive in a food, beverage, and tobacco sector.
2. Based on the competitiveness index, Thailand’s agricultural resources, sophisticated farming technology, and international quality standards make it a particularly attractive location for investment. Similarly Indonesia has a robust agricultural industry to supply raw materials and strong local demand has generated significant FDI in the sector.
3. 67 million households across ASEAN are part of the “consuming class,” with incomes exceeding the level for them to make significant discretionary purchases and is expected to increase almost double to 125 million households by 2025.
3. 67 million households across ASEAN are part of the “consuming class,” with incomes exceeding the level for them to make significant discretionary purchases and is expected to increase almost double to 125 million households by 2025.
4. Therefore maintaining low costs and producing affordable products is a priority for manufacturers to serve this market.
MANUFACTURING TRENDS IN ASEAN
1. Intra-regional trade in goods could increase with implementation of the AEC integration plan. This development could allow ASEAN to build integrated supply and value chains spanning the region and greater integration could produce productivity benefits in addition to boosting demand and creating consumer surplus. A harmonized market could lower inventory costs by reducing the number of specialized products companies need to keep in stock and minimizing obsolescence at the same time reducing ‘factory-to-shelf’ time and help preserve working capital small-medium enterprises with savings about 5 percent of the total cost base for food manufacturing.(McKinsey Global Institute)
2. China is shifting from an export driven economic model to a consumption-driven one as a result of rising wages. Although China has many advantages including a much better developed supply base, advanced infrastructure, robust manufacturing and engineering capacity, and a huge domestic market, there are still opportunity to create an opening for Southeast Asian economies to set up factory clusters in their own region due to the availability of low-cost labor in countries such as Cambodia, Indonesia, Laos, Myanmar, and Vietnam. In 2012, average labor productivity in Vietnam’s manufacturing sector was only about 7 percent of that in China. (McKinsey Global Institute)
3. Disruptive technologies could help manufacturers increase profit margins and lower costs, potentially creating $25 billion to $45 billion of annual economic impact in ASEAN by 2030 (McKinsey Global Institute). The use of big data and the Internet of Things could improve demand forecasting and production planning, leading to better customer service and higher profit margins.
2. China is shifting from an export driven economic model to a consumption-driven one as a result of rising wages. Although China has many advantages including a much better developed supply base, advanced infrastructure, robust manufacturing and engineering capacity, and a huge domestic market, there are still opportunity to create an opening for Southeast Asian economies to set up factory clusters in their own region due to the availability of low-cost labor in countries such as Cambodia, Indonesia, Laos, Myanmar, and Vietnam. In 2012, average labor productivity in Vietnam’s manufacturing sector was only about 7 percent of that in China. (McKinsey Global Institute)
3. Disruptive technologies could help manufacturers increase profit margins and lower costs, potentially creating $25 billion to $45 billion of annual economic impact in ASEAN by 2030 (McKinsey Global Institute). The use of big data and the Internet of Things could improve demand forecasting and production planning, leading to better customer service and higher profit margins.
4. For costing management, analyzing detailed, real-time data on everything from suppliers’ inventory and shipments in transit, to downstream customer demand, allows manufacturing companies to tighten inventory control and maximize production capacity. However, many manufacturing firms in ASEAN are still lagging behind in applying available technologies to their operations. Companies will need to recruit or groom three types of talent: workers with deep analytical skills to execute big data analyses; managers and analysts who know how to request and consume these analyses; and supporting technology personnel focused on implementation.
(SOURCE: MIDA, Mckinsey)
