Why we focus on artificial intelligence and machine learning

Six reasons why artificial intelligence and machine learning are the key drivers for growth not only in the logistics industry

The digitisation of supply chains and the interconnection of all processes are the leading factors behind growth in the logistics industry, as well as it’s the main goal of our software company Evertracker. This is why we have developed a sophisticated IoT platform capable of continuously gathering data and why we are focusing on machine learning and artificial intelligence. Our clients use our software to achieve full transparency over their logistics services, predict events and to automate processes. We are working towards a fully connected supply chain.

The future of logistics will contain many different means and innovations, such as drones, robots and self-driving trucks. However, there will not just be a single innovation that will revolutionise the delivery processes, rather it will be a combination of everything together. The winner of the ongoing battle in the logistics industry will be the one who has the highest flexibility and full control over all processes. A common goal for successful businesses should be to own the final customer and the majority of the value chain.

In order to achieve this goal, companies need to invest in smart software solutions, such as machine learning or artificial intelligence. Steering processes on a large scale and using all kinds of different instruments requires a highly scalable solution and maximum process automation. Human functionality and its ability to control complex processes in real-time are limited. The more flexibility and growth you want achieve, the more automation is necessary for that success. Smart solutions are not only able to generate data, but can also focus on the most relevant information, which not only give you a good understanding of your processes, but which also let you steer them autonomously.

Six reasons why we made our solution smart

IoT is an important instrument for us to constantly gather real-time information. However, at the same time, IoT is merely a functional instrument. The real value is added through our machine-learning algorithms and artificial intelligence.

We have identified six main reasons why we are focusing so heavily on making our solutions smart.

1. Usability

Smart solutions that understand the usage and automate internal processes, increase usability. As we were aiming to build a plug-and-play solution, we focused on smart algorithms from the very beginning. We automated most of the configuration processes and built APIs for a seamless integration. This allows our clients to implement our solution into their daily processes with almost no additional effort. Our software is therefore very easy to use and enables our clients focus on answers.

We at Evertracker believe that the less input a software requires, the more user-friendly it gets. Furthermore, it allows them to integrate solutions into existing processes without adding more operational work on their side.

2. Scalability

The second reason why we invest most of our time and resources into machine-learning algorithms and artificial intelligence is the scalability of our product that comes together with our approach.

As we are automating most of our internal processes, the operational effort involved in maintaining and controlling our clients’ devices is reduced, while simultaneously allowing our clients to focus on using our software instead of configuring it. This enables our clients to use hundreds or thousands of devices simultaneously, integrating them into their processes, without managing every single one of them. We focus on adding value by giving answers instead of producing data and additional workloads.

3. Deviations

Our software knows the “normal”, either through the integration of existing information or through our machine-learning algorithms. The benefits of using smart algorithms to detect the normal allows us to focus on the abnormal and on deviations. Artificial intelligence understands deviations on a large scale, which allows our clients to monitor and control all of their processes. Our clients can react faster and proactively to unexpected events and errors.

Using smart algorithms does not require everything to be pre-set from the beginning. Through the constant analysis of inflowing data and the comparison to the past and other resources, our software is continuously learning to become faster and more precise.

4. Cost-efficiency

A big advantage that arises from artificial intelligence is cost-efficiency. Firstly, because our clients do not need to increase their workforce to control and manage our software, they are able to monitor all of their processes in real time by focusing on incidents. Secondly, they can focus on increasing the quality and operations of their processes with just an increase of resources.

In addition, smart solutions do not just generate data which results in an increase in data consumption and server capacity, they focus on the most relevant information.

5. Predictions

One of the most important benefits of artificial intelligence and machine-learning algorithms is the ability to predict. Knowing what happens in supply chains leads to increased quality and more flexible interactions. Using IoT sensors to gather information and to visualise the results only leads to a picture of the past. Alternatively, our software gathers real-time data and then compares them with historical information and external resources. This enables our software to understand context and therefore leads to prediction in real-time.

This allows us to point out errors to our clients that could occur and to highlight problems as soon or even before they occur.

6. Automation

Nowadays, automation is the key driver for growth. Automation brings flexibility, increases the quality and especially boosts operations despite increasing organisational structures. However, in order to automate processes, you must first invest in artificial intelligence and machine-learning solutions. Traditional software solutions where you have to set all parameters manually might also lead to process automation, but only intelligent software solutions can provide automation on a large scale. The complexity and variety of processes make it impossible for human functionality to know and input all potential parameters. However, if a software solution learns the patterns of your logistics network and allows you to regulate these findings, you can very quickly automate processes along the entire value chain. Important here is the fact that not only is the smart automation algorithm important, but that it is even more important to understand these patterns and the recurring events that you want to automate.

Conclusion

I believe that real-time data and gapless information is one of the key factors for successful companies. That is why we at Evertracker have built and provide a sophisticated IoT platform. However, our IoT platform is a functional instrument, but it is only one part of the optimal solution. I believe that only through artificial intelligence and machine learning, our clients can create leverage for the generated data. Companies should focus on understanding reality, on predicting the future and on the automation of processes in order to reach a high level of efficiency and generate sustainable growth.

But solutions that only analyse the history will never support this goal, because they don’t tell you what will happen in the future.

Software and hardware solutions should enable users to focus on their operations and foresee incidents rather than analysing the past. That’s what our company Evertracker is offering with its sophisticated IoT platform combined with machine learning and artificial intelligence.

Learn more about Evertracker: www.evertracker.com