Remove Analysis Remove Data Remove Events Remove Examples
article thumbnail

Predictive Analysis in Logistics and Supply Chain: How to Apply

3PL Links

Predictive Analysis in Logistics and Supply Chain: How to Apply | Image source: Pexels In logistics, predictive analysis is simply the process of identifying and forecasting patterns, trends, and behaviors in both human and machine learning approaches, data, and algorithms.

article thumbnail

6 Types of Automation [Benefits, Pros/Cons, Examples]

Conger

Examples of automation range from a household thermostat to a large industrial control system, self-driven vehicles, and warehousing robots. Examples are industrial robots and multipurpose CNC machines. Process Automation Process automation means using technology to automate manual processes through data and systems integration.

Insiders

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

Trending Sources

article thumbnail

Freight Market Intelligence: Data is crucial, but context is king

Freightos

In this article, Eytan Buchman, Freightos’ CMO, discusses the importance of data and context in global freight and logistics. The future of global freight data lies in real-time information, contextual insights, and aggregated data that can help companies make better decisions and adapt to a rapidly changing industry.

Data 62
article thumbnail

Supply Chain Data Visibility Paramount as Industry Lurches into Next Chapter

IoT World Today

Increasing supply chain data visibility is a priority for logistics organizations looking to improve resilience. Supply chain recovery hinges on incorporating robust data analytics and other data-driven tools into business operations to increase efficiency, reduce costs and proactively manage risk.

article thumbnail

Why near-real-time electronic freight tender trucking data is more reliable than waiting on submitted data

FreightWaves SONAR

Data for data’s sake lacks value, especially in the view of the supply chain. And across the market, submitted data becomes rapidly outdated. And in some industries, outdated data can have disastrous consequences. For instance, take the value added by more accurate data in the health industry.

Data 98
article thumbnail

Generative AI in Supply Chain: How It Impacts Your Logistics

Trinity Logistics

Generative AI is first trained on a foundational model and then fine-tuned with human feedback and additional data. Its responses are based on data it has consumed and a resultant powerful prediction mechanism. That is one example of a public version of Generative AI. Now, none of these are really new technologies.

article thumbnail

Nine Key Steps to Enabling Resilient Supply Chains

Logistics Viewpoints

Organizations must take the following steps to bring departments together to create truly resilient and sustainable supply chains: Leverage external data to sense market shifts Look to external causal factors and forecasting models to identify market shifts. By identifying these gaps, you can create sourcing events to close them.