How YS Transporte suddenly turned three years of telematics data into money without replacing their experienced dispatchers. With them.
YS Transporte had everything: experienced dispatchers with strong instincts, three years of telematics data, a modern TMS. And yet fuel consumption kept rising while on-time delivery fell. No one knew why. The data was there, but no one had the time to make sense of it.
The familiar question: "Do we need AI?" Our answer after discovery: "Yes, but not as a replacement for the dispatchers, as their new co-pilot."
We built a forecasting model from three years of historical data: expected driving times, risk spots for delays, optimal route combinations, fuel-consumption estimates per route. The model runs as a suggestion inside the existing TMS, the dispatchers still make the call. It shows how we put artificial intelligence to work — always tied to a concrete business process.
After 8 months in production the numbers are clear, and the dispatchers are sold. Instead of the feared threat to their jobs, the AI has become a relief: less after-the-fact explaining, more time for the genuinely difficult cases.
The AI suggests, the dispatchers decide — after eight months in production, the tool has become part of everyday work.
Pick a slot or simply call. You tell us what is not working, we ask questions, and we tell you which process gets easier next. Free of charge, no contract.
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