Supply chains in a time of a looming trade war: Is AI-driven reshoring the solution?

In the past week, headlines all over the world were filled with fears and speculations in regards to a potentially imminent US-China trade war:

  • “Trade war ‘is the greatest threat to the world economy’” (CNBC, USA)
  • “Fallout from US-China trade war would hit major global firms” (Asia Times, Hong Kong)
  • “The trade war is a spiral of horror” (Wirtschaftswoche, Germany)

And while the extent of new tariffs, economic restrictions and other potential punitive measures remains mostly uncertain at this point, it is already becoming clear that such a trade war will drastically impact the vast majority of countries and companies. The pressure to adopt and adjust will be especially high on those parties with highly internationalized supply chains and markets.

Aside the upcoming political fallout, one of the key tasks for company executives and government representatives is therefore to determine the potential impact on their respective company or nation and to identify possible solutions.

At the same time, the development of Artificial Intelligence (AI) is advancing quickly, boosting the capabilities of machines. Supply chains are therefore likely to be much less dependent on the location of human capital as in the past.

Could this unfolding political and economic situation in combination with recent advances in AI and Machine Learning turn out to be a blessing in disguise? Will we see a wave of reshoring initiatives around the globe that transform supply chains?

Offshoring pushed the internationalization of supply chains

Over the last few decades supply chains dramatically changed, driven by the opening of new and developing markets, the access to enormous low-wage labor pools as well as the ever-steady reduction of shipping costs. Tremendous production capacities were shifted towards countries that provided a cost advantage over more developed markets – which of course was mostly driven by much lower labor costs. Many industries that rely heavily on (petro-)chemical raw materials used this development to drastically reduce their cost base. While the textile, electronics and toy producers with a big share of repetitive manual tasks in their production processes are the most prominent examples, numerous other industries and producers followed. Production capacities were no longer located close to the key markets, but instead the supply chains grew in geographical extent.

It seemed that only those process industry producers with large volumes, low-value products and a high degree of production automation would keep their plants close to the actual markets (e.g. washing powder, diapers). Overall offshoring has connected the world in ways barely imaginable just a few decades ago and with it the complexity of supply chains rose to unseen levels.

Is AI the joker for the developed markets?  

Recent advances in Artificial Intelligence and Machine Learning, which enable the automation of a growing number of labor intensive tasks which previously could only be performed by humans, are probably initiating a new shift in the decision-making processes of production locations. For example, highly adaptive and self-learning machines are in the next few years expected to essentially take over all labor intensive tasks within the mass production of certain textile products (e.g. shoes). This would reduce the required workforce and hence the implicit advantage of low-wage countries dramatically. Such a development would therefore deprive developing countries of one of their key assets in international trade negotiations or conflicts.

And yet fears in regards to new tariffs or a full-scale trade war are only one of the factors to consider. In parallel, megatrends such as increasingly individualized customer demands and the shortening of product lifecycles also require the attention of producers. This mixture puts the production site and supply chain setup as well as its overall agility at the core of challenges for companies.

Key pull factors to consider for off- and reshoring initiatives

The reshoring of highly automated production facilities closer to key markets can be one measure to meet the political and business requirements in the foreseeable future. However, leveraging AI is simultaneously likely to further lower the costs of logistics operations while the domestic demand in developing markets is growing (e.g. China). The combination of these contrary developments will further complicate defining a suitable supply chain setup.

Overall, AI-driven reshoring will certainly grow in importance especially for producers directly impacted by the looming trade war and its consequences. Companies that aim to stay ahead of their competition will more than ever need to customize their mix of production sites and an agile supply chain setup to best utilize the technological advances and evolving demands while also managing the political framework. Unlike previous shifts (e.g. offshoring in the nineties) this time around there is no automatism which company executives can simply follow and duplicate. The role of supply chain managers will be key to increase the flexibility, speed and adaptiveness of their supply chains.

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written by
Franz Winter
Franz Winter is a senior consultant in the Logistics Practice at CAMELOT Management Consultants. Within this practice his activities are primarily in the context of the Digitalization of Business Models for chemical and pharmaceutical clients. Franz’s areas of expertise are especially in supply chain processes, warehousing and distribution networks.

This post is also available in: German