{"id":3408,"date":"2017-07-03T17:24:22","date_gmt":"2017-07-03T17:24:22","guid":{"rendered":"https:\/\/www.ing.uc.cl\/industrial-y-sistemas\/?p=3408"},"modified":"2017-07-03T17:24:22","modified_gmt":"2017-07-03T17:24:22","slug":"prof-juan-carlos-ferrer-y-big-data-analytics-en-la-industria","status":"publish","type":"post","link":"https:\/\/www.ing.uc.cl\/industrial-y-sistemas\/2017\/07\/03\/prof-juan-carlos-ferrer-y-big-data-analytics-en-la-industria\/","title":{"rendered":"Columna de Opini\u00f3n Big Data Analytics en la Industria, del Prof. Juan Carlos Ferrer"},"content":{"rendered":"<p><a href=\"https:\/\/www.ing.uc.cl\/industrial-y-sistemas\/wp-content\/uploads\/2017\/06\/juan-carlos-ferrer.jpg\"><img fetchpriority=\"high\" decoding=\"async\" class=\"alignleft size-medium wp-image-3410\" alt=\"Juan Carlos Ferrer\" src=\"https:\/\/www.ing.uc.cl\/industrial-y-sistemas\/wp-content\/uploads\/2017\/06\/juan-carlos-ferrer-300x199.jpg\" width=\"300\" height=\"199\" \/><\/a>&#8220;Tendencias y aplicaciones de Big Data Analytics en la industria&#8221; del Profesor Juan Carlos Ferrer.<\/p>\n<p>&#8220;En su reciente libro The Analytics Edge, Dimitris Bertsimas, del MIT, menciona\u00a0un estudio realizado con mas de 300 compa\u00f1\u00edas norteamericanas que muestra que el tercio superior de aquellas que m\u00e1s basan sus decisiones en datos son, en promedio, el 5% mas productivas y el 6% mas rentables que las dem\u00e1s. La clave est\u00e1 en saber que informaci\u00f3n recolectar y construir \u00a0modelos que agreguen valor a aquellas decisiones.<\/p>\n<p>Big Data no s\u00f3lo es gran vol\u00famen sino tambi\u00e9n gran velocidad de procesamiento y variedad de datos.<\/p>\n<p>En muchas industrias hoy es realista pensar en un buen entendimiento de las conductas y preferencias que mueven a sus clientes; esto es posible a trav\u00e9s de buenos an\u00e1lisis de la inmensa cantidad y variedad de informaci\u00f3n que recolectan de ellos.<\/p>\n<p>De ah\u00ed la importancia del Big Data Analytics como uno de los campos de mayor crecimiento en estos a\u00f1os, que busca identificar patrones en los grandes vol\u00famenes de datos aplicando t\u00e9cnicas estad\u00edsticas para responder las m\u00e1s variadas interrogantes para tomar decisiones.<\/p>\n<p>Antes pod\u00edamos inferir lo que har\u00e1n los clientes. Actualmente vemos c\u00f3mo la industria del retail almacena todas las transacciones de estos con un nivel de detalle que permite modelar e inferir con bastante precisi\u00f3n el comportamiento futuro que podr\u00edan tener.<\/p>\n<p>El uso de Big Data Analytics permite una gesti\u00f3n \u00f3ptima de los inventarios al poder estimar cada vez con mayor precisi\u00f3n qu\u00e9, cu\u00e1nto y cu\u00e1ndo reabastecer el centro de distribuci\u00f3n y sus locales para cada uno de los miles de productos. Aqu\u00ed hemos observado simult\u00e1neamente bajas del 10% en el inventario total, con ca\u00eddas de 30% en la venta perdida por quiebres de stock. Esto es posible gracias a la alta sofisticaci\u00f3n e integraci\u00f3n de modelos matem\u00e1ticos y tecnolog\u00eda.<\/p>\n<p>Industrias que enfrentan problemas de <em>revenue management<\/em> (oferta fija horizonte de venta finito y demanda incierta) tambi\u00e9n se est\u00e1n viendo beneficiadas con esta revoluci\u00f3n de la informaci\u00f3n, al ajustar sus precios con mayor precisi\u00f3n de acuerdo al comportamiento y necesidad de las personas. Aqu\u00ed se han logrado aumentos del 3% al 6% en los ingresos con un tremendo impacto en la \u00faltima l\u00ednea.<\/p>\n<p>Otro \u00e1mbito industrial de crecimiento exponencial en Big Data es la log\u00edstica de la distribuci\u00f3n. Todos los sensores y GPS disponibles permiten almacenar grandes vol\u00famenes de datos georeferenciados que ayudan a planificar de forma certera y eficiente. Aqu\u00ed ha sido clave que nos hemos hecho cargo de la enorme variabilidad que hay en la velocidades de desplazamiento en las distintas horas del d\u00eda y lugares de la ciudad, lo que ha permitido alcanzar ahorros de hasta el 40% en los costos de distribuci\u00f3n.<\/p>\n<p>En salud, vamos a comenzar a observar una mejora cu\u00e1ntica tanto en la calidad y tiempo de los diagn\u00f3sticos como en la efectividad de los tratamiento. Adem\u00e1s, se podr\u00e1 gestionar mucho mejor la disponibilidad de los remedios necesarios en cada lugar y momento del tiempo en base a las necesidades de los pacientes.<\/p>\n<p>En definitiva, Big Data le da tanto al sector p\u00fablico como al privado, la oportunidad de ser m\u00e1s competitivos y eficientes, mejorando el bienestar de las personas y accediendo a importantes reducciones de costos y\/o aumentos de ingresos.<\/p>\n<p>El Big Data Analytics est\u00e1 convergiendo a una gran velocidad con la inteligencia Artificial y la rob\u00f3tica. Algunos ya aventuran que pronto los drones nos entregar\u00e1n paquetes con objetos que a\u00fan no hemos ordenado, en la misma l\u00ednea que Amazon desde hace varios a\u00f1os nos presenta su p\u00e1gina web personalizada con productos que compraremos con mayor probabilidad que otros.<\/p>\n<p>Se vienen grandes transformaciones en la negocios y la industria con el salto que representan tecnolog\u00edas en desarrollo como el incre\u00edble IBM Watson. La misma tecnolog\u00eda que usaron para ganar el concurso Jeopardy ser\u00e1 de extrema utilidad en \u00e1mbitos claves como salud, educaci\u00f3n, finanzas y retail, entre otros&#8221;.<\/p>\n<p>Fuente: Ediciones Especiales del Diario El Mercurio del jueves 22 de Junio de 2017<\/p>\n","protected":false},"excerpt":{"rendered":"<p>&#8220;Tendencias y aplicaciones de Big Data Analytics en la industria&#8221; 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