How to implement digitization and automation in outdated sectors such as logistics

Strolling the picturesque paths surrounding Felixstowe, a port town on the moor-strewn coast of southern England, it’s hard to imagine that such a serene-looking place hosted events that disrupted the global logistics industry.

The interconnected and interdependent nature of our modern economy means that the eight-day strike of Felixstowe port workers in September 2022 caused major problems around the world. Moreover, ‘one-in-a-generation’ events are becoming the new normal, causing even more upheaval and provoking the question, ‘Can supply chain technology come to the rescue?’

The last three years have redefined what disruption in the global supply chain means. The COVID-19 pandemic, the blocking of the Suez Canal and the overloading of ports have thrown many companies into chaos in their logistics operations. Research shows that these events serve as a catalyst for investment in innovation such as digitization and automation in supply chains across multiple industries.

It is likely that in the coming years we will continue to see protest activities in ports, railways and trucking that will affect logistics, and other global events such as a pandemic are also possible. But new supply chain management technologies are set to help navigate this uncertain landscape.

Accurate visibility, quick response

The first step towards increasing industry agility and reducing execution risk is moving away from outdated and usually highly manual practices and processes. For example, companies have struggled for years with tracking and collecting data on goods moving from point A to point B.

This opacity is addressed by a range of track and trace solutions that give brands and shippers accurate visibility and the ability to respond quickly to disruptions.

Going further, businesses can now access through digital platforms ‘ready-to-go’ orders. This can help them forecast stock levels or suggest alternative transportation methods to avoid delays or reduce costs.

To make it more concrete, let’s consider the place of origin, a metric used in transportation management: the sum of all delays between the preparation of goods for shipment and their actual departure to their final destination (i.e. time spent on the production floor, in transit, at the port). Digitizing complex manual processes could reduce this rate, to the delight of concerned supply chain professionals.

There is probably no sector more complex and macroeconomic than global supply chain logistics. It is an atlas-spanning industry that affects every aspect of the modern consumer economy. As mentioned, it is also plagued by poor visibility and an almost endless list of things that can go wrong.

Digital twinning, a technology rapidly gaining ground, is now helping to solve these problems.

What are digital twins?

A digital twin is a virtual representation of a physical object or system. This gives organizations the ability to understand and predict behavior. Weather forecasting and air traffic control are two of the most common examples of this technology. When applied to supply chains, it can provide accurate insights and in-depth knowledge of all aspects of the movement of goods around the world, reflecting reality in all its messy glory.

This powerful capability makes it easy to collate or generate (through simulations) datasets that can then be used to predict the behavior of logistics systems to support decisions by understanding their impact. The more accurate a digital twin is, the more it can help you manage costs, inventory, and environmental impacts of your supply chains, and how best to respond to emerging issues.

This technology has great potential to provide supply chain professionals with new levels of understanding of the near-infinite complexity of their field and is likely to be the driving force behind further digitalization in the logistics industry.

The role of AI in logistics

Artificial intelligence has been making headlines for some time now and could provide predictive capabilities that make digital twins even more valuable. It is clear that artificial intelligence and its incarnation, machine learning (ML), will be able to revolutionize the world of logistics through decision support and automation.

However, ML is a difficult feature to integrate and adopt, requiring extensive training and expertise in an organization looking to incorporate it into its toolbox. In addition, one of the key elements of the success of ML models is the quality of the datasets used to train them, as well as having the right people on the team to manipulate them.

Digital twinning can combine the intricacies of the real world with the power of artificial intelligence. By improving the quality of the datasets used as input, the usability of ML can be greatly improved, potentially resulting in unprecedented inventory optimisation, carbon footprint and cost reduction. It can also increase employee and customer satisfaction.

Ultimately, these technologies are intended to make supply chain management less reactive and extremely stressful, and become more proactive and competitive.

Empowering, not replacing employees

The adoption of new technologies, especially those that drive automation and reduce human labor, tends to raise concerns about job destruction. However, as history has shown, jobs are unlikely to disappear, but to change. This is likely to be the case with supply chain digital twins.

By offloading some of the more mundane tasks and decisions to machines, and providing visibility and scenarios for humans to consider, logistics professionals will be able to leverage their experience, knowledge, and cognitive capabilities to drive strategies and deliver organizational value.

Instead of constantly putting out fires and manually dealing with huge amounts of (usually) bad data, in addition to worrying about human errors, they will be able to consider the bigger picture and do their best work. Hopefully, as this becomes more common, some of the concerns voiced by executives in recent surveys will also be mitigated.

Adoption, models focused on trust

Adoption is a key success factor in delivering value from new technologies. Its success usually depends on the cognitive load that the product imposes on users and how it is implemented in the organization.

Making your solution easy to use with a well-designed user interface (UX) and providing documentation, tutorials, and other help can help reduce the former. Implementing change management processes, especially for large teams and companies, can be of great importance for the latter.

It is also important to consider the complex landscape of supply chains and the fact that many different partners must work together to move goods around the world. These companies and individuals tend to have different needs, tech levels, languages ​​and cultures. Therefore, a model of cooperation based on trust should be based on awareness, understanding and taking into account the diversity of the ecosystem.

It is becoming clear that further digitization and automation of supply chains through the popularization of digital twins and other technologies is inevitable. There is a growing body of information, including research, surveys and analysis, that suggests that the logistics world is poised to harness these new opportunities to deliver more efficient, environmentally friendly and value-based global supply chains.

However, as with any change, it will require commitment, investment and collaboration to become a reality.

Tamir Strauss is the company’s director of products and technology zencargo.

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