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Decision Tree

In: Business and Management

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Los cinco patrones básicos de la mayoría de las series de tiempo aplicables a la demanda son:
1. Horizontal. La fluctuación de los datos en torno de una media constante.
2. Tendencia. El incremento o decremento sistemático de la media de la serie a través del tiempo.
3. Estacional. Un patrón repetible de incrementos o decrementos de la demanda, dependiendo de la hora del día, la semana, el mes o la temporada.
4. Cíclico. Una pauta de incrementos o decrementos graduales y menos previsibles de la demanda, los cuales se presentan en el transcurso de periodos más largos (años o decenios).
5. Aleatorio. La variación imprevisible de la demanda.
Antes de usar técnicas de pronóstico para el análisis de problemas de administración de operaciones, el gerente tiene que tomar tres decisiones: (1) qué va a pronosticar; (2) qué tipo de técnica de pronóstico va a usar, y (3) qué tipo de software de computación utilizará.

métodos de juicio
Un tipo de método cualitativo en el que las opiniones de gerentes y expertos, los resultados de las encuestas de consumidores y las estimaciones del personal de ventas se traducen en estimaciones cuantitativas. métodos causales
Un tipo de método cuantitativo que utiliza datos históricos de variables independientes, como campañas de promoción, condiciones económicas y actividades de los competidores, para pronosticar la demanda. análisis de series de tiempo
Es un método estadístico que depende en alto grado de datos históricos de la demanda, con los que proyecta la magnitud futura de la misma y reconoce las tendencias y patrones estacionales.

planificación, pronóstico y reabastecimiento en colaboración (CPFR)
Proceso de nueve pasos para administrar la cadena de valor, que permite a un fabricante y a sus clientes colaborar en la elaboración del pronóstico por medio de Internet.

Métodos de Juicio para pronósticos

estimaciones del personal de ventas
Son pronósticos compilados a partir de estimaciones de la demanda futura que realizan periódicamente los miembros del personal de ventas de las compañías. opinión ejecutiva
Método de pronóstico en el cual se hace un resumen de las opiniones, experiencia y conocimientos técnicos de uno o varios gerentes para llegar a un solo pronóstico. pronósticos tecnológicos
Aplicación de la opinión ejecutiva para mantenerse al tanto de los últimos adelantos tecnológicos. investigación de mercado
Método sistemático para determinar el grado de interés del consumidor externo por un producto o servicio, mediante la creación y puesta a prueba de diversas hipótesis por medio de encuestas encaminadas a la recopilación de datos. método Delphi
Proceso para obtener el consenso dentro de un grupo de expertos, al tiempo que se respeta el anonimato de sus integrantes.

Demanda espacial versus demanda temporal
Demanda irregular versus demanda regular
Demanda derivada versus demanda independiente

MÉTODOS DE PRONÓSTICO
Métodos cualitativos
Los métodos cualitativos utilizan el juicio, la intuición, las encuestas o técnicas comparativas para generar estimados cuantitativos acerca del futuro. Son métodos más bien adecuados para pronósticos de mediano a largo plazo.

Métodos de proyección histórica
La premisa básica es que el patrón del tiempo futuro será una réplica del pasado, al menos en gran parte. La naturaleza cuantitativa de las series de tiempo estimula el uso de modelos matemáticos y estadísticos como las principales herramientas de pronóstico.

Métodos causales
La premisa básica sobre la que se construyen los métodos causales para pronósticos es que el nivel de la variable pronosticada se deriva del nivel de otras variables relacionadas.

TÉCNICAS ÚTILES PARA LOS RESPONSABLES DE LA LOGíSTICA

Nivelación o ajuste exponencial
Requiere que una cantidad mínima de información sea conservada para su aplicación continua, se ha observado que es la más precisa entre los modelos competidores de su clase, y es autoadaptable a los cambios fundamentales en la información pronosticada.

Corrección por tendencia

Corrección por tendencia y estacionalidad

Definición del error de pronóstico
En la medida en que el futuro no es reflejado perfectamente por el pasado, el pronóstico de la demanda futura por lo general tendrá cierto grado de error. Dado que el ajuste exponencial es una predicción de la demanda promedio, se busca proyectar un rango dentro del cual caerá la demanda real. Esto requiere un pronóstico estadístico.

Monitoreo del error de pronóstico
Una de las ventajas más notables del uso del ajuste exponencial para el pronóstico de corto plazo es su capacidad de adaptarse a los patrones cambiantes en la serie de tiempo. Lo bien que el modelo mantenga su precisión se relaciona directamente con el valor de la constante de ajuste en cualquier punto en el tiempo. Por lo tanto, los procedimientos sofisticados de pronóstico implican el monitoreo del error de pronóstico y realizar ajustes en los valores de las constantes de ajuste. Si la serie de tiempo es estable, se seleccionarán valores relativamente bajos. Durante periodos de cambio rápido, se utilizarían valores altos.
Al no estar limitado a valores sencillos, el error de pronóstico puede ser reducido, en especial cuando los patrones de demanda son dinámicos.
Un método popular para monitorear el error de pronóstico es mediante una señal de seguimiento. La señal de seguimiento es una comparación, por lo general una proporción, del error de pronóstico actual para un promedio de los errores de pronóstico pasados. Esta proporción puede ser evaluada en forma continua o periódica. Como resultado de este cálculo, las constantes de nivelación exponencial pueden ser recalculadas o especificadas de nuevo si la proporción excede un límite de control específico.

Descomposición clásica de series de tiempo
Una categoría de modelos de pronóstico que ha resultado útil durante años es la descomposición de series de tiempo. Estos métodos incluyen el análisis espectral, el análisis clásico de series de tiempo, y el análisis de series de Fourier. Aquí se cubre el análisis de la descomposición de series de tiempo, principalmente debido a su simplicidad matemática y a su popularidad, además de que los métodos más elegantes no han mostrado mayor precisión.
El pronóstico clásico por descomposición de series de tiempo está construido sobre la filosofía de que un patrón de ventas históricas puede descomponerse en cuatro categorías: tendencia, variación estacional, variación cíclica y variación residual o aleatoria. La tendencia representa el movimiento a largo plazo de las ventas ocasionado por factores como cambios en la población, cambios en el desempeño de marketing de la empresa y cambios fundamentales en la aceptación del mercado de los productos y servicios de la empresa. La variación estacional se refiere a las cimas y valles regulares en la serie de tiempo que por lo general se repiten cada 12 meses. Las fuerzas que causan esta variación regular incluyen cambios climáticos, patrones de compra controlados por fechas del calendario y por la disponibilidad de los bienes. La variación cíclica son las ondulaciones de largo plazo (más de un año) en el patrón de demanda. La variación residual o aleatoria es

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