In recent weeks there has been a bit of a debate between Helen Wang for Forbes and Vivek Wadhwa for the Washington post. It was started with Wadhwa's article 'Why China won’t own next-generation manufacturing', which discussed how, with labor costs no longer providing an advantage for China, manufacturing is likely to move back to the countries in which the parent companies operate. Wang then came back and suggested that innovation with the next phase of technological development will push both China and other countries to improve.
Of the two arguments, I was more persuaded by Wadhwa's regarding the economic savings from not needing to ship raw materials to China and then products back. However, I believe that neither have really approached the issue effectively and have a missed a key element in the argument: Historical data is key.
Wadhwa argues in his piece that, 'Even though China is graduating far more than 1 million engineers every year, the quality of their education is so poor that they are not employable in technical professions.' However, this should really only be a moot point given that the country is spending $150 billion on improving manufacturing in the country, which could pay for the very best people from anywhere in the world. Amongst these people should be a sizable number of skilled data scientists who can look at the data created over the past 50 years to identify the best ways to manufacture products, regardless of whether they are made by humans or machines.
If you were to imagine Apple moving its iPhone manufacturing from Shenzen to the US, in theory it would be relatively simple, given that they know how the phones are made, where the materials come from, and the time it takes to make them. However, the intricacies of their manufacture is something that only the factories in China know because Apple has never technically produced the iPhone, it just designed them. Within these intricacies is a huge amount of data that can be collected to give Chinese firms a huge advantage in future manufacturing processes.
It is something that the world is aware of, with Gartner claiming that China is the third largest market for Enterprise IT, with $155.8 billion being spent on it within the country in 2016. When you combine this with the work being done by incumbents like Alibaba, Baidu and Tencent, it is clear that there is a real focus on data and technological innovation. It is this, combined with their manufacturing background that will help to maintain their dominance in the manufacturing sector.
Equally, the argument that companies should bring their products 'back home' is counterintuitive to the global markets in which they operate. Going back to Apple as a prime example, why would they move their manufacturing back to the US when China has bought more iPhones than the US every quarter since Q1 of 2015 and Apple Insider predicting they had increased sales in the country by roughly 33% in January 2016. Why would the company want to move manufacturing away from its largest market?
The same can be said for almost every data engaged company, as China has as much value as a market than it does as a manufacturing hub. This isn't simply because they have a population in excess of 1 billion people, but because they are creating data at a phenomenal rate.
Take their use of mobile internet, which Statista predicts to be at 664 million users by 2018. 70% of Chinese mobile internet users regularly using m-commerce for shopping (compared to 35% in the US) and this would mean that roughly 464.8 million m-commerce users in China by 2018, more than the entire population of the US. The data that you could gleam from here is phenomenal and should be used to direct both marketing efforts, but also future product features.
The next generation of manufacturing may well be something that requires fewer manual workers, meaning that the baseline costs are cut, but the smarter operators will probably keep their manufacturing in China because they have the data on how it has been done before and are creating the data that will show how to do it in the future.