Summary
The COVID-19 outbreak is now travelling around the world, leaving a trail of destruction in its wake. This report discusses the impact of the virus on leading companies in the industrial automation sector.
Key Highlights
- Industrial automation was not in a great place before COVID-19 struck, having been slowed by flat capital expenditure and declining industrial production.
- The virus has since closed factories, with workers across the world sent home. It has exposed the fact that, despite a lot of hype over the years, advanced factory automation has not been substituted for human workers at scale.
- The virus may serve to accelerate investment in factory automation when the global economy eventually rebounds, but that will take a while.
Scope
- This report analyzes the impact of COVID-19 on the global industrial automation sector.
- It identifies those companies that may benefit from the impact of COVID-19 over a 12-month period, as well as those companies that will lose out.
- It includes a thematic screen, that ranks the 58 leading companies in this sector on the basis of overall leadership in the 10 themes that matter most to their industry, including COVID-19. This generates a leading indicator of future performance.
Reasons to Buy
- COVID-19 is by far the most significant theme to affect the technology industry in 2020.
- It is effectively a stress test on companies’ ability to cope with extreme shocks.
- COVID-19 will test the financial robustness of companies. Many companies will not survive this initial phase.
- Almost all others will suffer a significant drop in revenues.
- This report will help you understand the impact of COVID-19 on the industrial automation sector and identify which types of companies could potentially benefit from the impact of COVID-19, as well as those businesses that are set to lose out.
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Table of Contents
COVID-19 is Now a Major Theme for 2020
COVID-19 Impact on Industrial Automation
Industrial Automation Sector Scorecard
Thematic Briefing
Appendix: Our Thematic Research Methodology