Success story.
Predictive Forecast of Spare Parts Demand
A heavy vehicle manufacturer was managing spare parts inventories using historical methods, causing stockouts and excess inventory.
We take on any challenge
At Zenta there are no obstacles we cannot overcome.
Challenge
Predict spare parts demand by model and region to optimize levels and reduce storage costs.
Solution
We train time series models in Vertex AI Forecast, fed with sales and telemetry data, and integrate the predictions into BigQuery; we deploy replenishment alerts with Cloud Scheduler.
Results from our management
Forecast 92% accurate at 60 days.
-30% inventory costs.
+15% availability of critical spare parts.
““Thanks to the predictive intelligence implemented with Zenta, we are able to anticipate demand peaks and strategically adjust our production. It’s a tangible competitive advantage.””
What they say about our work.
We have the backing of those who have trusted us.