Digital Logistics – What does the future hold?
Is digital logistics going to be the disruptor that everyone believes it to be?
Traditional logistics has long been supplanted by the digital logistics ecosystem, but certain stakeholders are still in the process of this shift. They might implement certain digital systems but refuse to make a complete change.
This has large ramifications on the bottom line, as it is estimated that businesses lose $1.6 billion annually due to legacy logistics. In the face of rising global challenges, digital logistics systems play a vital role in how competitive your fleet can become.
What is digital logistics?
This is a broad term that can often confuse people, based on who’s explaining it. Simply put, it’s the digitization of the entire logistics environment, primarily driven by data and analytics. It involves the collection and aggregation of data from different sources, so as to provide a comprehensive overview of your entire system.
Digital logistics is vital in integrating your supply chain, allowing seamless communication between different nodes. The data that is gathered can optimise and automate the larger logistics ecosystem, which can reduce lead time and expenses. It can also allow you to focus on the larger strategy, through data analysis that is incomprehensible to human computing.
Most digital logistics platforms are based around tracking and monitoring of every single part of your supply chain. It feeds into I.T. systems and databases that can process this data, like fleet management logistics platforms. This can increase visibility through a centralised user interface and command centre. It can also expand data transparency and create accountability at every level.
It is important to modernise, as traditional or legacy infrastructure comes with various challenges. Some of these are:
- Cost overruns.
- Non-actionable analytics.
- Inefficiencies and a lack of optimisation, especially with routes.
- Compartmentalisation of processes and a lack of communication.
- Incorrect data collection.
- Inadequate control.
- Vehicle life cycle and procurement concerns.
- Faulty technological infrastructure.
Fleet operators and organisations might delay the adoption of a digital logistics ecosystem for various reasons, but the automation of smaller processes is required for higher efficiency. And this digital habitat is growing at a breakneck speed, demanding an evolution from you.
What is the future of digital logistics?
Understanding the future trends of the digital ecosystem, can help you adjust your strategy accordingly. While some might be ready for implementation before others, there is consensus in the industry that we are moving towards these outcomes.
- Big Data – It’s no longer about terabytes of data, but of exabytes. Digital systems want more and more data to analyse, and this thirst only increases with technological developments. Currently data processing systems can handle a certain load, but big data would refer to data-sets that are beyond the capacity of these systems. They would require specialised computing power, which might come in the shape of quantum or exascale computing.
Newer sensor tech and heightened sensitivity would also increase the complexity of existing data points. This adds layers to the data that is helpful for analysis, especially with multi-modal transport. Big data will lead to refinement and optimisation of the entire supply chain, bringing in predictive technology. It will give you accurate forecasts and analysis, potentially identifying any failure points in your systems.
Larger databases and cloud computing infrastructure will be required, along with a lower latency. This can remove the lag in real-time decision making, which can improve safety. It might even help you analyse macro-economic factors which can push you into newer markets.
- Tracking and Monitoring improvements – You can already track if your driver’s hands have left the steering wheel or whether they’re drowsy, so imagine where the next set of sensors can take us. Technology is evolving fast and is answering real world concerns of supply chain visibility and safety. Advanced Driver Assistance Systems (ADAS) are a great example of this progress, with sensors predicting any potential hazards and sending warning alerts.
However, the true scale of this endeavour lies with the Internet of Things (IoT) devices. In the future, every part of your supply chain will be connected and able to communicate with each other. It can possibly create predictive driving, with your sensors communicating to devices that are not even on your network, such as port terminal or highway authority devices. An important aspect is data generation through perceptive technology. We can see the application of this in smart warehouses and robotics.
- Artificial Intelligence (AI) and Machine Learning (ML) – We already utilise some amount of AI and ML in every aspect of our lives. It is present in a smaller capacity on our phones and our computers. However, the future holds a larger potential for these systems, especially in the supply chain industry. When we talk about optimisation of routes, fuel management, or load capacity, this will be powered by AI and ML.
These systems would be able to handle large volumes of unstructured and structured data, with IoT and embedded systems being the key. Digital infrastructure and seamless connectivity through 5G can help create predictive mechanisms, which can help with procurement and inventory forecasting, smart shipping, and automating your entire workflow. It will increase flexibility and drastically reduce costs, even increasing your last mile reach.
- Edge ecosystems – Edges are boundary points where different members of your supply chain interact – machines, people, data, devices and even sensors. An edge ecosystem allows for decision-making closer to the source of the information, rather than at a centralised point. This can severely reduce lag time and decentralises control.
These edge ecosystems require high processing and computing components to conduct real-time data analysis. Currently these systems are expensive and haven’t reached a high level of efficiency. However, with AI, ML and improved connectivity, the potential for edge computing in supply chains can create a drastic paradigm shift. Post-decision analysis can also be conducted at a central command, which becomes another data point for Machine Learning systems.
- Autonomous vehicles and Robotics – The age of connected vehicles might be near, but so is that of autonomous. Various companies have invested heavily in autonomous systems, trying to overcome any short-term hiccups. This will evolve and there might come a time with driverless movement, which has been estimated to save time and money.
Warehouses are already implementing autonomous and line-following robots, which has reduced lag time and automated various smaller processes. Smart warehouses will connect to global systems to re-route inventory based on predictive demand. This data on load management will also feed into automated deliveries through drones and robots.
- Sustainability – People are concerned about the environment and the supply chain industry is often villainised for its role in emissions. However, with ESG reporting and regulatory compliances, companies will eventually choose to engage with fleet operators and supply chain stakeholders that can match their sustainability commitments.
Data analysis and technology will play an integral role in overcoming these challenges. For example, predicting weather patterns, road conditions, and optimising routes can impact your emission levels. You’ll even be able to control vehicle speed for ideal consumption of energy. Automated sustainability audits can raise any potential red flags, allowing for immediate rectifications. We’ll also see a large shift towards alternate forms of transport – LNG, Electric or Hydrogen – with many stakeholders already incorporating this into their supply chain.
Creating a logistics ecosystem that leverages digital resources is important for every contributor to the global supply chain. You can learn more about this, here.
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