The impact of artificial intelligence on the supply chain
Artificial intelligence has been helping build a more digital world for longer than you think: in the 1950s, a generation of scientists and mathematicians already had a clear idea of what this concept would be. The highlight is Alan Turing, who prepared a study called “Computing Machinery and Intelligence” in which he discussed how machines could be smarter and how it would be possible to test their progress.
Seventy years later, the subject’s popularity is on the rise due to the COVID-19 pandemic, with different companies competing to adapt to new digital models and generate efficiency. Within these efforts, there is the supply chain sector. With spikes in demand generated by the social isolation and the difficulties of transportation around the world, data can be quite a support in everyday life.
This includes, of course, artificial intelligence itself: a broader concept of creating machines capable of thinking like humans. No wonder, a survey conducted by IBM shows that 46% of purchasing executives say that artificial intelligence and cloud applications will be the biggest areas of investment in digital operations in the next three years.
In a recent McKinsey study of investments in artificial intelligence, some companies interviewed, in various sectors, claim that at least 20% of their EBIT (earnings before interest and taxes) already comes from applications related to AI. At least half of the companies say they started using this type of application during the year 2020.
Within the supply chain, the study shows that the functions in which these new applications are most used involve optimization of the logistics network and improvements in inventory and inventory management. We have discussed topics like this before on the Soluparts blog, addressing the use of immersive technologies as other trends in supply chain.
Supply chain applications
This whole process is part of an intelligent supply chain, capable of bringing at least three benefits: greater efficiency, transparency and better dimensioning of demand over time.
In this context, artificial intelligence assumes a prominent role, in which leading companies in the sector have already invested -at least since 2018- in the automation of repetitive tasks ranging from issuing purchase orders, invoices, contract management to the administration of global processes. According to a Harvard study published three years ago, predictive analysis was already seen as a trend within the industry, capable of improving demand forecasting and improving costs.
In addition to these factors, sensors on machines are added to identify when maintenance will be required and even the use of blockchain to adjust flexible supply networks – but this is the subject of another article. For now, a key concept related to the application of artificial intelligence within the supply chain sector is that of digital control tower.
Applied to leading companies since before the pandemic, according to Harvard University, it consists of providing end-to-end information about global supply chains. This “tower” is nothing more than a control center that works every day of the week and, based on information viewed in 3D and graphics, it is possible to control delivery and stock problems in advance.
Creating this is not an easy task. A recent Oxford study provides detailed information on the subject and, to summarize, provides information that a basic artificial intelligence infrastructure depends on different data sources.
In addition to the traditional ones, such as ERP and customer management systems, this type of intelligence also needs data from physical products: sensors on products, labels, locations and machines. In this set, the internet of things (IoT) plays an essential role, since it allows a physical object to be linked to digital platform using a unique identification.
Benefits of artificial intelligence
The fact is that technologies like these are not a passing trend. A 2019 study by McKinsey that examined more than 400 artificial intelligence use cases in 19 sectors shows that use in supply management and marketing / sales accounts for the majority (two-thirds) of all AI opportunities globally.
Within marketing, for example, artificial intelligence can create $1.4 trillion to $2.6 trillion in value annually, and within the supply chain sector, those amounts can reach $1.2 trillion to US $2 trillion in product supply and manufacturing.
Challenges in applying artificial intelligence in supply chain
Investing in these technologies is not an easy process. The study mentioned above shows that the lack of confidence in artificial intelligence algorithms – which reproduce biased behavior according to the human biases implicit in the data – is one of them, as well as the lack of “success cases” in the sector: while automation has clear benefits and shows a segment with a clear return on investment, some points such as risk assessment, are more challenging as they do not yet have well-defined metrics to measure them in the short term.
In addition, the scarcity of qualified labor to support companies is a major challenge. As these are new applications, it is necessary to wait some time so a significant number of people is trained to deal with the technology.
Faced with this scenario, Harvard researchers raise the question: in a future with end-to-end automated processes, the need for human work will be minimized.
So what will become of humans in the supply chain? The need for “reskilling”, or to be trained again, will be a fundamental point to guarantee jobs.
Analysts capable of drawing insights from the data, using digital tools and being familiar with algorithms will be part of the new routine that the sector must face. Still, there is no clear vision as to how these jobs will be rearranged – it is up to the companies in the sector to design what they want for the future and, from there, to design the new roles that the sector should have.
The fact is that the collaboration between both of them must be essential (and the machines will not completely replace the human role within the operation). In short, at least three new lines of work must be created:
- The “trainers”, able to build AI projects from scratch and make sure they work;
- The “explainers”, who will take the insights from the data gathered by the machines;
- The “supporters”, able to assess the availability of the systems and ensure that they are not down.
Focus on the future
The future is already part of the strategy: a survey conducted by the Accenture Strategy already shows that 90% of supply chain executives believe that their workforce will adapt to digital technologies and 92% say that they will be able to work with intelligent machinery more naturally.
But we must warn you: before adopting the new technologies and innovative processes, evaluate and understand to what extent the investment will pay off in the long run if applied in your specific scenario. Learn more about this feasibility analysis in our article.
To learn more about other technologies that will shape the industry’s behavior in the coming years, read Soluparts articles on smart applications within the supply chain.