AI in the supply chain – how logistics can be managed in crisis

Logistics
Image courtesy/AI in the supply chain

Logistics plays a major role in all sectors, and there is no exception to the fashion industry. Well-run digitization-based logistics can solve crises—the best examples are the recent container ship trapped in the Suez Canal and the ongoing pandemic that has led to a logistical nightmare for many. FashionUnited discussed the current situation and how artificial intelligence (AI), planning, and accountability can help manage their logistics with Andreas Nierlich, Retail Sales Director EMEA DACH for Blue Yonder, the world’s leading supply chain network.

 

Mr. Nierlich, how can good logistics help handle crises and increase the efficiency of the supply chain given the recent crises and broken supply chains?

 

Good logistics begin with openness and preparation. Transparency with regard to the location of which goods; the digitization of the supply chain makes a huge difference. When planning, you must remember that the future is not deterministic and, therefore, 100% impossible to plan. Machine learning may, however, predict the likelihood of future events. Covid-19 also made very short-term planning changes possible, and digitalization allows us to react to these changes faster and more flexibly. It also helps to evaluate the future better and become agile.

 

Companies that rely on AI-based solutions for their supply chain can mitigate impacts of this magnitude better than those not yet open to modern technology. The company continues to make swift decisions based on data and automate alternate supply sources in events like these.

 

Artificial intelligence can help evaluate the probability of threats to the supply chain. While no AI can predict a pandemic worldwide, technology is a key part of the solution. It can decide in minutes on a data basis and redirect the flow of products so that supply chains are not completely stopped.

 

Companies like Marks & Spencer, Gap, and Macy’s were early adopters of AI, who are Blue Yonder’s customers. Is it just the major corporations that retool and invest in this sector today?

 

Not just that. FashionUnited clients include Best Secret, Bonprix, or Takko, but also outside Europe and not just large companies. For example, a small Polish shoe retailer recently approached them to support its growth strategy through AI and better planning. It is vital for three forces to work together: to be conscious that something needs to be done and concentrate on areas where AI can be used meaningfully and allocate the financial resources required.

 

Where does a company ideally start to rely more on AI and become more digital in its logistics?

 

The first move is to take stock: where does AI have the fastest possible benefits? It always makes sense to start with the markdowns at the end of the chain. There you can easily and without too many adjustments to the process produce added value and fund other items. This is also the strongest justification for a process improvement. But generic recommendations are not available; every enterprise, every condition, and every industry is different.

 

Speaking of digitalization arguments: what is the greatest advantage of investment in the supply chain?

 

Certainly strategic aspects: A business becomes more agile, automation is increased and therefore profitable. There are typically ten euros in benefit for every euro spent. Normally, this happens very rapidly, and in six to twelve months, the investment will pay off.

 

Should it be a very persuasive argument?

 

For example, planning and logistics are interwoven. These two fields in the fashion industry are particularly difficult to cope with, especially because of the long lead times caused by production in the Far East. Several variables influence how the season goes, and, of course, not every pattern can be predicted. When designing and selecting the right strategy, the power of humans is digitalization, and AI helps to make a variety of right choices to execute this strategy. How to sell products to shops is a good example. AI is the most advanced in demand and price analysis and can determine: When should I write down to optimally sell my products by the end of the season? Sustainability also falls into the frame.

 

Should data protection be a problem for future customers to digitize their supply chain more?

 

Today, only a few businesses have a ‘no cloud’ policy. Furthermore, personal data are also not yet processed. One could theoretically descend to the consumer level, but the industry is still far from it. Strong data protection is guaranteed in any situation. Cloud solutions today, such as those from Amazon, Google, or Microsoft, are much more secure than local solutions, especially in the case of hackers. These businesses are investing billions in their public cloud infrastructure. The topic of data protection is very important in Europe.

 

Last but not least, on the corporate side, there are headlines – can you tell us anything about the Blue Yonder acquisition by Panasonic?

 

In July 2020, Panasonic already acquired the remaining 80 percent share (for just under 6 billion US dollars) in Blue Yonder, subject to the normal approvals. The purchase is a long-awaited move in the software industry for Panasonic, which is more lucrative than hardware. In all cases, a conventional Hardware/IoT vendor acquires a software provider that leads to greater interconnection in the future. The combined power of AI, Machine Learning, IoT, and Edge devices allows consumers to optimize their supply chains quickly. This enables us to realize the mission of a self-contained supply chain.

 

Analysis of case:

 

In just two weeks, Bonprix, a fashion retailer, developed an entirely different pricing plan in Germany, accommodating the disrupted supply chain and evolving customer behavior. The Hamburg-based retailer has been using price services from Blue Yonder as a strictly market-driven method since 2014, but the business required more elements such as stock levels and demand in the light of the pandemic.

 

Instead of heavily reducing and supervising the cost of slower-moving goods, Bonprix relied on the complete automated lifecycle pricing strategy of Blue Yonder, which integrates inventory, demand, and large data as well as ever-changing circumstances, so Bonprix workers have been free to devote their resources to other pressing tasks.

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