La aplicación de Inteligencia Artificial y Machine Learning en el área logística se ha multiplicado por cuatro en los últimos años. Así lo destaca Pedro Herrera Nachón, socio fundador y director general de NovaQuality, que afirma que “la adopción de este tipo de herramientas comenzó de forma tímida pero actualmente casi el 100% de las compañías las demandan, las están implantando o tienen pensado hacerlo en el corto plazo”. En este sentido, advierte que “en un mercado tan competitivo como el actual, las empresas deben dar los pasos necesarios para optimizar su área logística si no quieren perder competitividad.”
Según este experto las principales aplicaciones de la IA en los procesos de logística se basan, por un lado, en la creación de “modelos de predicción de demanda”, que se nutren de información histórica de la propia compañía y también tiene en cuenta datos de variables externas para planificar la posible demanda. Y, por otro, en la implementación de “modelos de distribución óptima”, que ayudan a optimizar el proceso de salida de la mercancía desde el almacén.
¿Qué beneficios se derivan de la implantación de estas tecnologías en el área logística de la compañía? NovaQuality identifica cinco puntos de mejora que son determinantes en el desarrollo de esta actividad:
- Previsión de las necesidades operativas. Podemos conocer con antelación la actividad prevista de un centro logístico: desde el volumen de entrada y salida de mercancías, maquinaría precisa, capacidad de almacenamiento requerida, etc.
- Aprovechamiento de las rutas de reparto. Permite una mejor programación de las rutas de reparto, garantizando que los desplazamientos sean más ágiles tanto en tiempo como en kilómetros.
- Planificación de las entradas y salidas de vehículos para el transporte. Organiza los horarios en función de la capacidad operativa del almacén y la disponibilidad de material.
- Optimización del equipo de trabajo. La mayor parte de los costes de un almacén pertenecen a la gestión de los recursos humanos. La implantación de Inteligencia Artificial ayuda a optimizar entre un 15-20% el personal asignado a cada tarea, lo que se traduce en un ahorro significativo en los costes.
- Prevención de los errores humanos. Esta tecnología ofrece un seguimiento pormenorizado de los pedidos que minimiza los posibles errores de los profesionales implicados.
- Selección de personal especializado. La organización puede determinar mejor qué perfil de profesionales necesita en cada operación, lo que limita la posibilidad de errores en los procesos de trabajo.
- Mejora del nivel de servicio al cliente. La mejora de la operativa en general también repercute en el servicio que se ofrece a los clientes, tanto en términos de calidad como de agilidad de respuesta, que mejoran sustancialmente.
Pedro Herrera Nachón recuerda que “la clave del éxito de un proyecto Inteligencia Artificial reside en el gobierno de datos, es decir, en contar con datos de calidad, bien recogidos y estructurados”.
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