Why are car manufactures shifting production out of China?
Supply chain disruption and geopolitical risks push companies to shift to domestic production out of China, driving data and knowledge in effect.
Over the past 20 years, China has become a global leader in the car parts industry. Its growth was fuelled by European and American car makers, that moved the production of an increasing number of their components to China to save costs.
But international groups and governmental push have now resulted in a firm effort to cut their reliance on China. The move has been prompted by two aspects;
🛑 uncertainty caused by China’s zero Covid-19 policy that forces plants to close at short notice and,
🛑 a longer-term concern about a larger political decoupling in the event of a breakdown in China’s relations with the international community, similar to Russia, that could threaten trade.
In fact, as per the European Automobile Manufacturers Association, global vehicle production dropped by more than 16.9% in 2020 with lower-than-expected recovery in 2021. The industry currently faces a fundamentally changed landscape where established giants are adopting previously unheard-of order-based model to sell cars while dealing with inventory shortages.
To make things worse, the auto sector has been dealing with the pressing issue of job losses since before the first lockdowns took effect in 2020. The livelihoods of auto industry workers have been being challenged by a lot over the past few years, with manufacturing shutdowns and outdated skills being the most prominent of them all.
In such case…
🧑🏼🦰 how do you make sure you can smoothly setup and move your production from overseas domestically, without disrupting customer experience even further?
🧑🏼🦰 How do you not lose tribal knowledge while facing labour shortage and aging society (like e.g. in Japan or Italy which is the third oldest population in the world)?
🧑🏼🦰 And how do you shorten onboarding times and transfer knowledge?
Such processes rely heavily on a swift data and knowledge transfer. Yet, more often than not, companies realise having lack of data visibility. For many organisations, legacy systems and data fragmentation across different systems and tools blocks effective operations.
This is where AI-powered tools can help with the knowledge transfer aspect, discovering and structuring it as a result.
Untrite has been helping large manufacturing clients to use their existing data to increase transparency and efficiency of business workflows (e.g where company has grown due to M&As of other component producers), optimise service performance, assess and mitigate risks that undoubtedly arise in knowledge transfer.
