Artificial intelligence in logistics

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2022: How to transform the logistics industry with AI

At the beginning of 2022, artificial intelligence is still not perfect. The technology has led to some major business blunders (for example, in 2016, Microsoft's AI chatbot "learned" to be "racist," "sexist" and "anti-Semitic"). But AI won't disappear from the supply chain. In fact, its prevalence is expected to increase. ^[1] for 2021 indicates that, 17% of respondents said they are already using AI, and another 45% predict that they will use it in five years. A survey of more than 1,000 logistics professionals around the world also found that 25% of them plan to invest in AI products in the next three years.

AI is very complicated, but what we can use is very, very simple. People don't need to have a deep understanding of algorithms. I never thought AI could evolve as fast as it does now, and it's only going to improve, "said Ben Lynch, director of business data analytics at DHL Supply Chain

Growing Use Cases

Over the past five years, artificial intelligence has transformed DHL's relationship with its customers.

The company has gone from providing customers with information about what has already happened to something more predictable. Thanks to artificial intelligence, machine learning and data availability, we can now give them an idea not only what happened, but also what will happen - told Lynch

This transition was caused by complex algorithms that can process a huge amount of data collected.

Every two years we generate as much data as we've ever generated. By 2023, the world will have twice as much data. Because of this, there was a great need for technology to support this data - said Lynch

AI also allows other kinds of technology to be promoted in logistics, such as robotics, said Thomas Evans, Honeywell's chief technology officer for robotics.

% of respondents who plan to invest in products and services over the next three years

Complexity and faster access to AI through third-party vendors, and the ability to build and deploy AI platforms, is a radical change and advantage to supply chain logistics. It will become more advanced as we use more and more data, "Evans said.

However, AI is not a panacea for business problems. He experienced growing pains.

For example, Zillow, an online real estate company, closed Zillow Offers, an artificial intelligence-based home purchase and resale service, because the company bought homes more expensive than they could resell. In the third quarter of 2021, the company wrote off losses of $304 million^[2] But when used correctly, AI is complex, efficient and already pays off. McKinsey's^[3] report found that for early users, supply chain management with AI improved logistics costs by 15%, inventory levels by 35% and service levels by 65% compared to "slower competitors."

The biggest gap Lynch sees going forward, he said, is simplifying data and "getting data and business to talk in the same language."

As the amount of technology and digitalization increased and opened up more and more data, we were faced with a problem: how to take this data and transform it into something more understandable to the operator, "said Ben Lynch

This will help the operator make decisions.

AI makes data more valuable

Lynch also does not expect the data flow to stop. He said he believed it would grow alongside booming e-commerce, fueled by all the consumer data generated by this online activity.

Now that we can figure out what the consumer is going to buy next week, how will we set up our warehouses? Technology is getting better and better, and we're going to get a really good view at the consumer level, not at the aggregate supply chain level, "Thomas Evans reported.

Broader adoption of AI will also depend on robust cybersecurity, Evans said. If data cannot be securely collected, stored and shared with company partners, this becomes a problem rather than an advantage.

As the value of data to run AI systems becomes higher for business, so does the value of data to attackers. "As time goes on, they become more of a target," Evans said.

2020

Using AI to optimize supply chains

Over the years, the use of artificial intelligence in management supply chains SCM has increased significantly worldwide due to higher demand for data transparency and traceability, as well as the need to improve customer service. The leading industries in terms of the adoption of AI in SCM (as of the beginning of 2020) are (26%), telecommunications high technology (23%), (health care 21%), professional services (19%), as well as travel, transport and (18 logistics %).

Despite the benefits of AI integration, some organizations cannot implement it due to the following problems:

• Limited availability of high-quality, consistent and updatable (real-time) data
• Availability of supply chain data across departments (e.g. Marketing, Inventory, Purchasing Manager and others have their own databases)
• Limited integration between systems and databases for data access, cleaning and analysis.
• Limited data management policies associated with extended supply chain

Procurement experts believe that the recent supply chain disruptions caused by the COVID-19 pandemic are more than ever highlighting the need to integrate AI into the supply chain to optimize operations. To avoid a critical failure in the supply chain, an organization needs to have a complete picture of the entire ecosystem; accurately predict supply and demand; and optimally plan logistics and delivery, among other things. AI, along with machine learning, allows organizations to accurately anticipate load/supply problems and, accordingly, take the necessary (preventive/corrective) steps in advance.

Key AI applications to optimize the supply chain:

Improved end-to-end visibility and response time

With AI solutions, real-time and historical data can be collected and analyzed from multiple connected devices and systems (including SCM, ERP, and CRM systems) to obtain broader and deeper work information that is very useful to decision makers. By using these solutions, the procurement team can gain insight into the supply chain, anticipate problems (whether within an organization, for example, due to disruptions, or beyond, such as delayed supply), and take alternative measures to minimize the impact on the supply chain. Delay in actual response adversely affects supply chains and, accordingly, net income.

Accurate forecasting

AI solutions allow organizations to collect information from several different contractors, customers, and their own functions (including suppliers, customers, inventory, and products) in real time and use it for accurate forecasts. Traditionally, forecasting does not include real-time details and is based solely on historical data. However, with the use of AI, the accuracy of forecasting has improved significantly, which allows managers not only to plan better, but also to improve efficiency. In addition, using artificial intelligence to automate decision-making at a lower level could free up bandwidth for managers to focus on developing strategies and making decisions at a higher level.

Efficient supply chain and production planning

AI tools and solutions help analyze huge data sets in real time, balance supply and demand gaps, plan production efficiently, plan production activities efficiently, and develop unmistakable SCM plans and strategies. AI can help properly assess market needs and manage production accordingly to avoid overproduction or product shortages, which can lead to losses.

Vendor Selection and Supplier Relationship Management

AI solutions can be applied to analyze different datasets (such as delivery efficiency, audits, scores, and credit scores) and obtain customized recommendations for supplier relationship management. Current and regular information about potential or existing suppliers can be used to build mutually beneficial relationships.

Logistics Route Optimization

AI solutions allow decision makers to analyze existing routes, identify bottlenecks, and focus on the best route; this reduces both the time and total cost of warehousing and delivery. AI and ML-based data tools help capture details related to moving goods in real time and correctly estimate delivery times.

Warehouse Management (WMS)

When using AI solutions, the amount of both excess and insufficient reserves can be reduced. AI analyzes large datasets much faster and fixes errors that may appear when the analysis is performed manually. Automating day-to-day tasks such as forklift management, sorting and inventory management, using unmanned aerial vehicles or autonomous ground vehicles, transforms warehouse management.

Despite the benefits it offers, AI has yet to penetrate deeper into production. Conceptually strong algorithms, as well as innovations in big data, will not only increase processing power, but also help overcome the problems associated with data integration, contributing to the expansion of the application of AI in SCM.

2018: DHL and IBM study

In May 2018, the company, DHL a participant in the market logistics and express delivery, and the company IBM presented a joint report "Artificial intelligence in logistics." The report assesses the potential of using artificial intelligence in logistics and puts forward a number of ideas about transforming the industry, developing a new class of logistics assets and intelligent support operating systems. DHL and IBM explain what benefits logistics industry leaders can take when using artificial intelligence. It is also emphasized that the moment is the most favorable in terms of performance, availability and cost of artificial intelligence technologies.

Given that AI technologies are already ubiquitous in customer service, as also evidenced by the rapid growth in popularity of applications with virtual assistant (with speech recognition), DHL and IBM conclude that constantly improving artificial intelligence technologies have a number of additional capabilities relevant for logistics. So, they can help the logistics provider improve interaction with the client through interactive communication and even implement the ability to deliver goods before the client orders them.

Many industries are already successfully using artificial intelligence in their daily business processes, such as manufacturing and mechanical engineering. AI technologies allow you to simplify the operation of production lines and the production process using image recognition and dialog interface functions. In the automotive industry, artificial intelligence is actively involved in developing self-learning abilities in an autonomous robot car. There are many other examples that suggest the benefits of using artificial intelligence and its ability to fundamentally change the world of business, as happens in the field of customer relations.

Artificial intelligence will allow you to change the logistics operating model from reactive to predictable, proactive, which will provide better results at optimal costs for the back office, operational interactions and front office. For example, artificial intelligence technologies will allow the use of an advanced recognition system to track shipments and asset status, can lead to complete autonomy of the delivery process at all its stages, and predict fluctuations in global shipment volumes before they occur. Obviously, artificial intelligence complements human abilities, as well as eliminates routine work, which will shift the focus of logistics employees to more important, productive tasks.

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