Transmetrics’ demand forecasting and predictive optimisation platform is powered by artificial intelligence (AI) and machine learning algorithms.
Transmar owns and operates a large fleet of both dry and refrigerated containers, serves thousands of customers, and moves hundreds of commodities throughout the Middle East.
“We strongly believe in the power of Data, and Transmetrics’ AI solution helps us leverage to make decisions both faster and smarter,” said Ahmed El Ahwal, Commercial Manager at Transmar.
“As a regionally focused carrier we are more exposed to volatility, and we’re excited for the capabilities Transmetrics will provide by helping see up to 12 weeks into the future, ensuring we have optimum planning and repositioning plans.
Jon Fath – CEO, Transmetrics
“Transmetrics’ solution helped our team to more accurately allocate our assets, and its monitoring tools and automated forecast result in improved turn-time of our assets.”
Transmetrics software provides daily rolling AI-driven forecasts for the next 10 to 12 weeks based on cleansed historical data and relevant external factors influencing the demand.
The planning and system optimisation tools suggest an optimal and actionable plan for repositioning empty containers, as well as storage, for the next 12 weeks. This also takes into account all the related costs.
The system is equipped to consider repair and maintenance as cost variables which is now work in progress and being co-developed with Transmar.
“This requires deep knowledge of logistics processes, because it is still a very hands-on business, involving Big Data methods, which are used to support our clients’ team in finding smarter ways to reposition assets.”
Transmetrics and Transmar also identified a number of next steps to further increase the benefits of the former’s solutions, such as cabotage management functionality and a management dashboard.
According to Daily News Egypt, the dashboard will include cost reporting and is expected to show how the supply chain will look like for the next three months due to its predictive capabilities.