The Technology Behind Transmetrics: AI and Predictive Analytics for Logistics

The Technology Behind Transmetrics: AI and Predictive Analytics for Logistics
2 min read

Today, we are happy to present you the newest format of our blog – “Transmetrics CEO Comments.” In this set of articles, our CEO will share his professional opinion on the concepts which emerge at the interception of logistics and innovation. The goal of the format is to unravel the misconceptions about the new technologies and to highlight the power that they can bring to logistics.

If you have any questions about the innovation in logistics or wanted to learn more about particular topics, please let us know in the comment section and we will answer them in our future posts!

How is Transmetrics helping logistics companies with the power of AI and predictive analytics?

This is obviously the most frequent question I have been asked since I founded Transmetrics and by now I already have a hand full of answers for different categories of people: customers, investors, partners, which can ultimately be summed up as a following:

We help our customers (logistics service providers and assets providers) save a significant portion of their operational costs, in particular, transportation costs (linehauls between terminals and warehouse/terminal handling). We do this by helping them plan for optimal transportation or space and labor (in case of warehouses) capacity.

Predictive Analytics for Logistics

There are 3 main steps in the process:

Step 1 – Data Cleansing and Enrichment (by using Artificial Intelligence and advanced statistical methods)

  • The issue that many transport companies have is that their shipment data is not clean so they don’t have process transparency. They are unable to measure their efficiency gains, and because the data is generated at multiple points and entered by people, the data quality cannot be easily improved at source. What we do instead is we invest in Artificial Intelligence algorithms which can look at the historical shipment data, identify the issues and improve the data quality to the level where the significant transparency on the businesses is gained.

Step 2 – Forecasting

  • Once the data is cleansed, enriched and structured, we build forecasts for what shipping volumes the company should expect for the next few weeks, so not to focus primarily on historical performance but instead focus on future performance. This enables logistics companies to visualize the problem areas while they are still in the future and they can be corrected by proactive action. The forecasts we produce are very granular and highly accurate. In order to achieve high-quality results, we use historical data and we add the effect of external factors like public holidays, school holidays, industry seasonality, certain business events, and many others.

Step 3 – Predictive Optimization

  • The next module, which focuses on network optimization, helps the planners and dispatchers in making decisions based on the forecasted information. The software can help them with suggestions on where to increase or decrease capacity in order to be very efficient, and it is all done with Artificial Intelligence and complex stochastic optimization algorithms.

All of these steps are packaged in the Software as a Service product, which is offered on a monthly subscription basis. It takes just a few months to implement Transmetrics within the transport company and then the company can already start getting significant savings.”

Lear more about how Predictive Analytics for Logistics transforms the indsutry

Do you want to discuss other questions? Please let us know in the comments!

Transmetrics Demo