How to Keep Logistics Data Protected
Understand and Enforce Data Protection Requirements Keeping logistics data safe begins with a thorough understanding of the applicable laws or regulations surrounding it. For example, the General Data Protection Regulation (GDPR) has stipulations for handling customer data, including when companies must delete it. The need for data protection knowledge extends to everyone in an organization […]
Supply Chain Visibility (SCV) and its importance for logistics companies
Globalization has made delivery networks much more complicated. Due to large transportation networks, international shipping, numerous compliance standards, etc., supply chains are complicated and opaque. By leveraging data, SCV seeks to strengthen and improve the supply chain. Gathering current information Success for supply chain transparency lies in capturing real-time data. Key performance indicators (KPIs) relevant […]
Why Data Security is crucial at Saloodo!
The concept of European Data Security The concept of European data security refers to the set of laws, regulations, and policies that are in place to protect the personal data of individuals within the European Union (EU). These regulations aim to give EU citizens more control over their personal data and to ensure that their […]
The Saloodo! Scrum Series: Scrum – what it is, how it works, and why it’s awesome
At Saloodo! we all together strive every day to simplify logistics by digitalizing the ordering and execution of shipments while also enhancing the lives of everyone who needs transportation in order to succeed in any type of job or area. Digitalizing an entire industry is not a task that is done in a short manner – […]
Logistics Trends 2023 – Ready For The Future in Logistics & Supply Chain Management
Rise of Automation and AI Automation and artificial intelligence (AI) are on our trend radar for some years now. In 2023 it is becoming more common in a variety of processes. Automation, which is simply a machine performing a series of jobs, has been around for decades. Automation employs technology to reduce the need for […]
Digital logistics: The Future of Logistics in the Metaverse
In the tech industry, the Metaverse is considered the next big thing. Critics will say it will never catch on. In the Metaverse, people will use digital avatars to work, shop and even travel the world. Sound like science fiction? In some ways, it is. Too far-fetched for logistics? That’s exactly what we want to […]
COP27: Decarbonization, deforestation & new trends – 4 key outcomes to close the gap
The United Nations Climate Change Conference COP27 is ending these days in Egypt, and we’ve compiled essential information about how countries are responding to climate change. Decarbonization, finance, research, youth and future generations, adaptation and agriculture, gender, water, biodiversity, and solutions have been the focus of each day of COP27. The decarbonization day, which is […]
Digital Logistics: How Does Video Intelligence Improve Driver Safety?
Although speed is crucial in logistics, one aspect of the supply chain that must be a top priority is safety. Workers at various stages of the supply chain face potentially dangerous situations that could put their bodies or lives at risk. Luckily, advancements in technology enable companies to improve driver safety on the road. Take […]
How digitalisation disrupts logistics
E-commerce efficiencies The rise of the “expectation economy” stemmed from studies showing that consumers, in general, expect their e-commerce orders to be delivered within a matter of hours, complete with tracking information at every step of their parcel’s journey. This has spurred e-commerce giants to build their own logistics digital platforms and footprint in an […]
Digital logistics: Machine Learning in Logistics – Examples & Main Use Cases
What is Machine Learning Machine learning is a subset of artificial intelligence that allows a system to understand and leverage data for better model performance without being particularly designed to do so. Machine learning algorithms use historical data as input to foresee new output values. They are trained to make classifications or predictions using statistical […]
