Consumer Goods - Japan

Japan

Value added in the Consumer Goods market is projected to amount to US$309.7bn in 2024.
A compound annual growth rate of 0.05% is expected (CAGR 2024–2029).
The value added per capita in the Consumer Goods market is projected to amount to US$2,525.0 in 2024.
The value added margin in the Consumer Goods market is projected to amount to 35% in 2024.
Output in the Consumer Goods market is projected to amount to US$890.6bn in 2024.
A compound annual growth rate of -0.07% is expected (CAGR 2024–2029).
The output per enterprise in the Consumer Goods market is projected to amount to US$16.5m in 2024.
The manufacturing intensity in the Consumer Goods market is projected to amount to 21.7% in 2024.
The number of enterprises in the Consumer Goods market is projected to amount to 53.95k in 2024.
A compound annual growth rate of 1.27% is expected (CAGR 2024–2029).
The enterprise density in the Consumer Goods market is projected to amount to 440 in 2024.
The number of employees in the Consumer Goods market is projected to amount to 2,875.00k in 2024.
A compound annual growth rate of 0.06% is expected (CAGR 2024–2029).
The employment rate in the Consumer Goods market is projected to amount to 2.34% in 2024.
The labor efficiency in the Consumer Goods market is projected to amount to US$0.3m in 2024.
The labor productivity in the Consumer Goods market is projected to amount to US$107.7k in 2024.

Key regions: Australia, Spain, France, Germany, South Korea

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Analyst Opinion

The manufacturing market has faced several challenges in recent years due to geopolitical uncertainty, supply chain disruptions, changing consumer preferences, and increasing regulatory scrutiny. However, several positive factors, such as rising global demand, ongoing technological advancements, and increasing investment in automation and digitalization, continue to influence the market, and the outlook for manufacturing remains positive.

While the Covid-19 pandemic has caused significant hardships for manufacturers, those that invested in digitalization and automation of their processes will be best positioned for long-term success. Manufacturers who can effectively balance cost pressures and maintain a strong focus on quality are likely to survive the current crisis and come out more resilient in the end.

Among the factors that could affect the manufacturing market in 2023 is the adoption of advanced technology, such as artificial intelligence, robotics, and the Internet of Things (IoT), which have the potential to improve overall efficiency and productivity while reducing costs.

Furthermore, our analysts believe that sustainability and environmental awareness will become increasingly important trends, as more investors and consumers prefer companies that prioritize these values and develop eco-friendly products.

Finally, geopolitical factors such as trade tensions and changes in government policies could also impact the manufacturing market in 2023, with the Russia-Ukraine war having the biggest impact.

In summary, the current environment presents both challenges and opportunities for the manufacturing market in 2023. However, with the right managerial strategies and high flexibility, companies can succeed and strengthen their long-term market position.

Methodology

Data coverage:

The data encompasses B2B. Figures are based on the value added in the manufacturing market.

Modeling approach:

Market sizes are determined through a bottom-up approach, building on specific predefined factors for each market. As a basis for evaluating markets, we use resources from the Statista platform as well as annual financial reports of the market-leading companies and industry associations, third-party studies and reports, national statistical offices, international institutions, and the experience of our analysts. In addition, we use relevant key market indicators and data from country-specific associations, such as GDP, consumer spending, and consumer price index.

Forecasts:

In our forecasts, we apply diverse forecasting techniques. The selection of forecasting techniques is based on the behavior of the relevant market. For example, the S-curve function and exponential trend smoothing are well suited for forecasting the manufacturing market due to the non-linear growth of this market.

Additional notes:

The data is modeled using current exchange rates. The impact of the COVID-19 pandemic and the Russia-Ukraine war are considered at a country-specific level. The market is updated twice a year.