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XIMENA MARTÍNEZ HERNÁNDEZ XIMENA MARTÍNEZ HERNÁNDEZ INNOVACIÓN 8VO SEMESTRE PRACTICA DE BASES DE DATOS Universidad del Caribe

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Page 1: Revista practica base de datos ximena martinez

XIMENA MA RTÍNEZ HERNÁ NDEZ

INNOVA CIÓN 8VO SEMESTRE

PRA CTICA DE BA SES DE DA TOS

XIMENA MA RTÍNEZ HERNÁ NDEZ

INNOVA CIÓN 8VO SEMESTRE

PRA CTICA DE BA SES DE DA TOS

Universidad del Caribe

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Revista EIA, ISSN 1794-1237 Número 17, p. 21-37. Julio 2012Escuela de Ingeniería de Antioquia, Medellín (Colombia)

ESTRATEGIA DE REDUCCIÓN PARA LA APLICACIÓNGENERALIZADA DE LOCALIZADORES DE FALLAS

EN SISTEMAS DE DISTRIBUCIÓN DE ENERGÍA ELÉCTRICA

ANDRÉS BEDOYA-CADENA*

JUAN MORA-FLÓREZ**

SANDRA PÉREZ-LONDOÑO***

RESUMEN

En este artículo se presenta una estrategia generalizada para llevar a cabo la reducción de sistemas

de distribución ramificados a alimentadores radiales equivalentes, como procedimiento básico para la

aplicación generalizada de muchos de los métodos de localización de fallas basados en la estimación de la

impedancia. La estrategia propuesta se prueba al implementar un método de localización de fallas, donde

se muestra la facilidad para el análisis de las localizadones y adicionalmente con errores en la estimación

de la distancia a la falla inferiores al 3,5 % para fallas monofásicas, bifásicas y trifásicas. Estos resultados

confirman la validez de la propuesta.

PALABRAS CLAVE: calidad de energía; métodos de localización de fallas; alimentador radial equi-valente; sistemas de distribución.

Ingeniero Electricista, Universidad Tecnológica de Pereira. Asistente de Investigación, Programa de Ingenien'aEléctrica, Grupo de Investigación en Calidad de Energía Eléctrica y Estabilidad (ICE3), Universidad Tecnológica dePereira. Pereira, Colombia. [email protected]

Ingeniero Electricista y Magister en Potencia Eléctrica, Universidad Industrial de Santander. Doctor en Ingenien'aEléctrica, Universität de Girona. Profesor Asociado, Programa de Ingeniería Eléctrica, Grupo de Investigación enCalidad de Energía Eléctrica y Estabilidad (ICE3), Universidad Tecnológica de Pereira. Pereira, Colombia. [email protected]

"Ingeniera Electricista, Magister y Doctora (c) en Ingeniería Eléctríca, Universidad Tecnológica de Pereira. ProfesoraAsociada, Programa de Ingeniería Eléctrica, Grupo de Investigación en Calidad de Energía Eléctríca y Estabilidad(ICE3), Universidad Tecnológica de Pereira. Pereira, Colombia. [email protected]

Artículo recibido 16-VI-2011. Aprobado 5-III-2012Discusión abierta hasta diciembre de 2012

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ESTRATEGIA DE REDUCQÓN FARA LA APLICACIÓN GENERALIZADA DE LOCALIZADORES...

REDUCTION STRATEGY FOR GENERALIZED APPLICATION OF FAULTLOCATORS IN ELECTRIC POWER DISTRIBUTION SYSTEMS

ABSTRACT

This paper presents a generalized strategy applied to perform the reduction of power distríbutionsystems composed by several tapped feeders into equivalent radial feeders, as basic procedure required tothe generalized implementation of impedance based fault location methods. The proposed strategy is testedusing a fault location method, where it is shown a straightforward procedure to analyze the locations, andadditionally the results shows errors lower than 3.5 % in the distance estimation for. single line to ground,phase to phase, three phase faults. These results confirm the validity of the proposal.

BCEY WORDS: power quality; fault location methods; equivalent feeder; power distríbution systems.

ESTRATEGIA DE REDUÇÀO PARA A APLICAÇAO GENERALIZADA DELOCALIZADORES DE FALHAS EM SISTEMAS DE DISTRIBUIÇÂO DE

ENERGÍA ELÊTRICA

RESUMO

Neste artigo apresenta-se uma estrategia generalizada para realizar a reducáo de sistemas de distrí-buiçâo ramificados a radiais equivalentes, como procedimento básico para a aplicaçâo generalizada demuitos dos métodos de localizaçâo de falhas baseados na estimativa da impedância. A estrategia propostaprova-se ao levar a prática um método de localizaçâo de falhas, onde se mostra a fadlidade para a análisedas localizacóes e adicionalmente com erros na estimativa da distancia à falha inferíores ao 3,5 % para ocaso monofásico, bifásico e trífásico.

PALAVRAS-CÓDIGO: qualidade de energia; métodos de localizaçâo de falhas; radial equivalente;sistemas de distríbuicáo.

1. INTRODUCCIÓN

La calidad de la enet^'a eléctríca es ton tema deamplia investigación, debido al gran interés que des-pierta en los operadores del sistema eléctríco. Entrelos aspectos más importantes de la calidad se tienenla forma de onda y la continuidad del suministro.

Con reladón a la continuidad, en Colombia sedefinió el índice de Referenda Agrupado de la Discon-tinuidad (IRAD), que relaciona la cantidad promediode energía no suministrada, durante el período usadocomo referencia, y el índice Trímestral Agrupado dela Discontinuidad (ITAD,) que relaciona la cantidadpromedio de energía no suministrada durante el

trímestre de evaluadón (CREG, 2008). La mayoríade entidades reguladoras del mundo han establecidolímites de obligatorío cumplimiento para operadoresde red, so pena de pagar compensaciones.

Las fallas en la red eléctríca son causas funda-mentales que afectan la continuidad del suministrode energía. Si se pueden localizar eficiente y opor-tunamente, se contríbuirá a que las empresas distrí-buidoras de energía eléctríca mejoren sus índices decontinuidad (Mora, 2006).

El problema de localización de fallas en siste-mas de distríbudón de energía eléctríca es complejoy aún no ha sido resuelto en su totalidad. Debido aque muchas de las metodologías propuestas para

22 Revista EIA Rev.ElA.Esc.Ing.Antioq

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localizar fallas emplean datos del modelo de red,que por lo general se encuentran en una base dedatos o en algún programa de simulación, surge lanecesidad de una herramienta que permita efectuarel intercambio de información con el localizadorde fallas, para que éste pueda utilizarse de formageneralizada en cualquier circuito real.

En este artículo se propone una estrategiapara lectura y procesamiento de la información delcircuito real, almacenada en una base de datos eintegrada a una tarjeta de ATP (Alternative TransientsProgram). Además, se propone una metodologíapara la reducción de cualquier circuito a un equiva-lente simplificado con un único lateral de n cargasintermedias, para la implementación generalizadade métodos de localización de fallas en sistemas dedistribución reales.

Como contenido, en la sección 2 se presen-tan los aspectos teóricos de algunos métodos delocalización y del lenguaje de intercambio de datospropuesto para la representación de las cargas y laadmitancia equivalente de un circuito. En la sección3 se describe la estrategia propuesta por los autorespara la reducción de sistemas radiales para obtenerun radial equivalente. En la sección 4 se muestra unejemplo de aplicación de la metodología de reduc-ción propuesta y los resultados obtenidos al aplicar

un método de localización de fallas. Finalmente,en la sección 5 se presentan las conclusiones másimportantes de la investigación.

2. CONCEPTUALIZACIÓN BÁSICAASOCIADA

2.1 Algunos métodos de localizaciónde fallas paralelas en sistemasde distribución

En esta sección se presenta, mediante trescasos, la estructura conceptual de los métodos delocalización de fallas.

2.1.1 Método de la componente reactivade falla

El método descrito en Warrington (1968)determina la distancia a una falla entre los nodos My N de la figura 1, a partir de la reactancia de falla yla reactancia total de la línea.

Para determinar la reactancia de falla se utili-zan medidas de tensión (V^f) y corriente (I,„f) en elnodo M y en estado de falla, como se presenta en (1).

^falla —_Vmf_

= d.Zr+Rf (1)'mf

M

Figura 1. Circuito en condición de falla

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ESTRATEGIA DE REDUCCIÓN PARA LA APLICACIÓN GENERALIZADA DE LOCALIZADORES...

Si se conoce la impedancia total de la líneaentre los nodos M y N, ignorando la carga y

aprovechando que la impedancia de falla (R^ escompletamente resistiva, se propone una compa-ración entre la impedancia de falla y la impedanciade la línea, para así obtener la distancia a la falla (d)mediante la ecuación 2.

_ imagjZf (2)

2.Í.2 Método propuesto por Novosel et al.

El método de Novosel et al. (1998) proponeuna técnica de localización que emplea un circuitode componentes superímpuestas (figura 2). Estecircuito refleja el cambio que sufre una sección delínea de un circuito de distríbución entre los nodosM y N, en estado de prefalla a falla.

La impedancia de la fuente se halla em-pleando (3), en donde las mediciones de tensión enprefalla (V^p y en condición de falla (y^¡), al igualque las corríentes en prefalla (/„,,) y en condición defalla (I^¡), en el nodo M, se obtienen con la red desecuencia positiva.

AV V Ç-V2 ^ m ^ mf mp

s Al 1 .-Im mf mp

(3)

Del circuito de la figura 2 se define un factorde distribución de corriente S¡, con la componentesuperímpuesta de corríente (A/„, ) y la corríente porla falla (Z ), como se presenta en (4).

(4)If +

Utilizando el circuito en falla de la figura 1,pero en componentes de secuencia y considerandola impedancia de secuencia positiva de la línea (ZJy la carga (Z, ^ ) en el nodo N, y empleando (4) sepuede obtener:

(5)

La distancia a la falla (d) y la resistencia defalla (R^ se obtiene resolviendo (5).

2.13 Método propuesto por Choi et al.

El método de localización de fallas propuestopor Choi et al. (2004) ejecuta un análisis directo delcircuito en componentes de fase. De la figura 1, latensión en el nodo M está dada por (6).

= d. [ZJ. + [Vf] (6)

Zload

Figura 2. Circuito de las componentes superimpuestas

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En el nodo de falla (F), existen dos circuitosen paralelo, uno asociado a la admitancia de falla[Yf] y otro a la admitancia de carga [YJ.

La admitancia de la carga fYJ se obtiene cal-culando el inverso de la impedancia de línea entreel nodo F y N y la impedancia de carga conectadaal nodo N. Aplicando la ley de distríbución de co-rríentes en un circuito paralelo, se obtiene el valorde la corríente de falla:

[If] = + ((1 - +(7)

Empleando las ecuaciones (6) y (7), se obtieneuna ecuación compleja que tiene únicamente comoincógnitas la distancia a la falla (d) y la resistenciade falla (R ).

2.2 Retos para la utilizaciónde los localizadores en sistemasde distribución reales

Como se presentó en la sección 2.1, losmétodos de localización de fallas están propuestospara encontrar una falla en una sección de línea(entre nodos M y N); sin embargo, los sistemas dedistríbución reales son de topología radial y bastan-te ramificados, con diferentes tipos de conductor,longitud y configuración. Esto muestra claramenteque la aplicación de un método definido entre los

nodos M y N requiere un conjunto de estrategias quepermitan hacerlo aplicable a un circuito real comoel de la figura 3, tal como proponen los autores eneste artículo.

A partir de la figura 3, Q es la configuracióni-ésima del tramo de línea, que depende del calibre,de la disposición y de la longitud de los conductoresde cada sección.

Como los sistemas de distríbución son comple-jos, se deben tener disponibles la información de laimpedancia de cada tramo de línea (Z) y los valoresde admitancia de las cargas (Y). Adicionalmente,como los métodos de localización están definidospara una sección, se requiere una estrategia generali-zada para su implementación a partir de la definiciónde un radial equivalente, formado solo por líneasy cargas, que represente una paríe del sistema dedistríbución oríginal. En un sistema de distríbuciónexisten tantos radiales equivalentes como nodosfinales haya. Para el sistema presentado en la figura3, se tienen 5 radiales equivalentes y uno de estoscorresponde al presentado en la figura 4.

2.3 Aspectos básicos del XML(Extensible Markup Language)

El lenguaje extensible de marcado XML es unlenguaje que se está con virtiendo rápidamente enun estándar para el almacenamiento estructuradode datos. Este es un metalenguaje extensible de

'HIÖD—f NF5

NFl

Figura 3. Topología general de los sistemas de distribución

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ESTRATEGIA DE REDUCCIÓN PARA LA APLICACIÓN GENERALIZADA DE LOCALIZADORES...

Equivalente hastaNF4yNF2

Equivalentehasta NF5

Equivalentehasta NF3

NFl

Figura 4. Radial equivalente

etiquetas desarrollado por el World Wide Web Con-sortium (W3C), que recurre a etiquetas para marcar,describir, clasificar y organizar información de unamanera específica (W3C, 2008).

El XML se usa para el almacenamientoóptimo de datos y por lo general, los lenguajesde programación empleados para el desarrollode aplicaciones pueden leer la información quecontienen los documentos XML de una forma ágil,sencilla y confiable.

Un documento en formato XML posee comocaracten'stica principal la utilización de etiquetasdefinidas por el usuario con la siguiente estructura:< Etiqueta > INFORMACIÓN </Etiqueta >.

2.4 Manejo de cargas a partirdel análisis matricial

La mayon'a de los transformadores de distribu-ción tienen conexión delta-estrella, y para propósitosde localización de fallas, las cat gas pueden modelarsea partir de una admitancia constante. En caso de unaconexión en delta, si se conoce la admitancia entrefases (Y), la ecuación 8 relaciona las tensiones (V) y lascorrientes (/), de donde se infiere cuál es la matriz deadmitancia de carga (Morales, Mora y Vatigas, 2010).

IAII —

1le\

(YAB + YCA)

-YAB

-YCA

-YAB

(YBe + Yj,B:

-Yac

-YCA

-YBC

(YCA + YBC)

VA

VB

Vc

Cuando la carga es bifásica, se hacen cero lasadmitancias donde hay circuito abierto. Una cargamonofásica es un caso especial de una carga conconexión en estrella aterrizada, que se describe pormedio de la ecuación 9, y las admitancias donde haycircuito abierto son iguales a cero.

'CARGA

YA0

.0

0YB0

00Yr

(9)

2.5 Admitancia equivalentede un circuito

Para obtener radiales equivalentes a partir deun sistema de distribución ramificado, es necesarioacumular subcircuitos que se desprenden de susnodos de bifurcación. Estos sistemas equivalentesson necesarios, dado que son los que utilizan losmétodos de localización de fallas comúnmenteencontrados en la literatura científica (Warrington,1968; Das, 1998; Novosel et al, 1998; Choi et a!.,2004; Mora, 2006).

En la figura 5 se presenta un circuito simplifi-cado de un alimentador con n cargas laterales.

A partir de la figura 5, la admitancia equiva-lente en el nodo (n-l) es la mostrada en (10).

(10)C l = Yn-1 + [Zn-1 +

(8)

Las cargas están representadas por su ad-mitancia y¡ mientras que las líneas se representanpor la impedancia Z¡. Debido a que las matrices de

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1 XI 11 1Figura 5. Reducción de un circuito mediante la admitancia equivalente

admitancias resultan ser singulares y no es posibleobtener su inversa, el cálculo de la admitanciaequivalente se realiza empleando (11) que se de-ríva y se justifica a partir de lo demostrado en lasecuaciones (12).

nsi i = n

-t- /] -1 si 1 < i < n - 1

(11)

La expresión matrícial [4 -I- ß ] , que co-rresponde al segundo término de la parte derechade (10), puede reescribirse realizando algunasoperaciones previas presentadas en (12) (Morales,Mora y Vargas, 2010).

(12)

Este planteamiento es la estrategia básica parala obtención del radial equivalente.

3. METODOLOGÍA PROPUESTAPARA LA REDUCCIÓN DELSISTEMA DE DISTRIBUCIÓN

El desarrollo de una estrategia de reducciónde sistemas de distríbución ramificados a sistemasradiales equivalentes es básico para la aplicaciónautomática y generalizada de localizadores basadosen la estimación de la impedancia (Bedoya, 2010).La metodología automátíca para la reducción de loscircuitos que se propone en este artículo se divide endos etapas príndpales que se presentan en la figura 6.

3.1 Etapa 1. Generación de basede datos del circuito en XMLy almacenamiento en MATLAB

El programa de simulación ATP almacenatodos los parámetros del circuito en un texto planocon una estructura definida denominada tarjeta(ATP, 2002; Príkler y H0idalen, 2002). A partir deestas tarjetas se puede obtener de forma automátícala información necesaría para propósitos de locali-zación de fallas en la red de distríbudón. Para esto,lo prímero que se propone es realizar la lectura delas tarjetas del ATP y guardar su información en unformato estándar para el almacenamiento de datosen XML

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ESTRATEGIA DE REDUCCIÓN PARA LA APLICACIÓN GENERALIZADA DE LOCALIZADORES...

Etapa 1 Schema XMLATPXSchema.\sd

CircuitoSimulado en

ATPCircuito.atp

Archivo XMLCircuito.xml

Almacenar en MATLABArreglo matriciat de líneas y

de cargas

Nodo inicialNodos fínates

Arreglo de admitanciasequivalentes a partir de cada

nodo de bifurcaeión

Figura 6. Etapas de la estrategia general de reducción

Para producir la escritura de la base de datosen XML (archivo con extensión *.xmO, se requieredefinir un esquema estructural utilizando un archivocon extensión *.xsd, que se encuentra asociado a labase de datos escrita en XML.

Finalmente, con la base de datos en formatoXML y mediante la herramienta "The XML Toolbox"(Molinari y Cox, 2007), de distribución gratuita, yen combinación con MATLAB, se efectúa la lecturay almacenamiento de los datos del circuito en dosarreglos matriciales. El primero de estos arregloscontiene la siguiente información de las líneas delcircuito: nombre del tramo de línea, identificadordel nodo inicial y del final, matriz de impedancia deltramo y longitud del tramo.

El segundo arreglo matricial contiene infor-mación de las cargas del circuito, el identificadordel nodo al cual se encuentra conectada la carga ylas matrices de admitancia.

3.2 Etapa 2. Algoritmo de reducciónde sistemas ramificadosa radiales equivalentes

A partir de los arreglos matriciales de líneasy cargas, y con la información del nodo inicial y los

nodos finales del sistema por reducir, se generanotros arreglos matriciales que, junto con los arreglosiniciales, suministran toda la información de los sis-temas radiales equivalentes, tal como se representaesquemáticamente en la figura 7.

3.2.1 Obtención del vector de sistemasradiales

Para obtener el vector de sistemas radiales,se precisa conocer los nodos finales del sistema quese va a reducir. Con cada uno de los nodos finales,que se almacena en el arreglo de topología de unsistema radial, se realiza la búsqueda del nodo al-macenado en el arreglo matricial de líneas comonodo inicial de línea. Este nodo se almacena en elarreglo de topología. A continuación, el nodo inicialalmacenado pasa a ser el final y esta operación serealiza repetidamente hasta recorrer todo el circuito,lo que equivale a encontrar el nodo inicial, que a suvez corresponde a la subestación principal.

A manera de ejemplo sencillo, para el sistemamostrado en la figura 8, que tiene tres nodos finales(N004, N006 y N007) y un nodo inicial {NOOl), si-guiendo el método descrito, se encuentra un arreglode topología de un sistema radial, como el mostradoen la tabla 1.

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Arreglo matriciade Uneas

( Inicio j

Nodosfmales

Nodoinicial

Vector de sistemas radiales

Arreglo de topologia

Nodos de bifurcación

Vector de subcircuitos

Arreglo matricialde cargas

Arreglo de admitancias equivalentes apartir de cada nodo de bifurcación

Figura 1. Reducción de sistemas ramificados a radiales equivalentes

El método descríto permite obtener todos lossistemas radiales del sistema. Finalmente, el arreglode sistemas radiales es un vector que contiene lassecuencias de nodos que forman cada uno de lossistemas radiales equivalentes del sistema ramificadopor reducir. Para el sistema del ejemplo mostrado enla figura 8, el vector de sistemas radiales se presentaen la tabla 2.

NOOl N002S/E • • -

NO 03 N004

• •

N007• -

N005

I NO 06

Figura 8. Sistema de distribución simplificado

Tabla 1. Arreglo de topologia de un sistema radial

Nodo Inicial

'N005'

'N003'

'N002'

'Noor

Nodo Final

'N006'

'N005'

'N003'

•N002'

Fila arreglo de lineas

5

4

2

1

Tabia 2. Vector de sistemas radiales del sistemaramificado de ejemplo

Sistema radial 1

'N003'

'N002'

'NOOr

'N004'

'N003'

'N002'

3

2

1

Sistema radial 2

'N005'

'N003'

'N002'

'NOOr

N006'

N005'

'N003'

'N002'

Sistema radiai 3

'N005'

'N003'

'N002'

'NOOr

'N007'

'N005'

'N003'

'N002'

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ESTRATEGIA DE REDUCQÓN PARA LA APLICAQÓN GENERALIZADA DE LOCALIZADORES...

3-2.2 Determinaáón de los nodosde bifurcación

Para obtener un sistema radial equivalentees imporíante conocer cuáles son los nodos que enel sistema de distríbución presentan bifurcaciones,ya que a paríir de estos se desprenden dos o mássubdrcuitos, que vistos desde un radial equivalenteson admitancias concentradas en estos nodos.

Los nodos con bifurcaciones se identificanmediante un arreglo topológico del sistema de dis-tríbución. Del arreglo matrícial de líneas se extraenlas columnas de nodos iniciales y finales y ademásse adiciona una columna que hace referencia a lafila del arreglo matrícial de líneas.

Para el sistema mostrado en la figura 8, elarreglo de topología corresponde al presentado en latabla 3. Por fin, en el arreglo de topología se buscanen la columna 'Nodo inicial' los nodos que se repiteny estos corresponden a los nodos de bifurcación delsistema ramificado.

Según el arreglo presentado en la tabla 3, losnodos identificados como 'N003 ' y 'N005' son nodosde bifurcación, lo cual se verífica con facilidad alobservar la figura 8.

Tabia 3. Arreglo de topologia del sistema de prueba

Nodo Inicial

•N003'

'NOOZ

'NOOr

'NOOS

•N003'

Nodo Final

•N004'

•N003'

•NOOZ

'N006'

•N005'

Fila arreglo de líneas

3

2

1

S

4

3.23 Obtención del arreglo de admitanciasequivalentes a parür de un nodo debifurcación

Para hallar cuál es el subcircuito que se des-prende del nodo de bifurcación, se busca este nodoen todos los sistemas radiales, a excepción del sistemaradial con el que se inició el procedimiento. Luego,

se guarda la secuencia de nodos del sistema radial,hasta la posición de la columna nodo inicial, dondese encuentre el nodo de bifurcación analizado.

El procedimiento descríto se efectúa paratodos los nodos de bifurcación del sistema. En unarreglo de subcircuitos se almacenan el número delsistema radial del cual empezó la búsqueda, el nodode bifurcación y el subcircuito hallado. Debido aque los subcircuitos encontrados pueden presentarbifurcaciones, se debe hacer una nueva búsquedade subcircuitos en este arreglo. Este procedimientose debe realizar hasta que no se encuentren mássubcircuitos.

Al terminar se obtiene un vector de arreglosde subcircuitos, tal como el presentado en la tabla4, para el sistema mostrado en la figura 8.

Más adelante, se calcula la admitancia equi-valente de cada subcircuito, empezando por el últi-mo arreglo encontrado. Se procede en este orden,puesto que para obtener la admitancia equivalentede los demás subcircuitos se requiere la admitanciaequivalente obtenida para los últimos.

Al final se obtiene un arreglo matrícial deadmitancias equivalentes donde se almacena el nú-mero que identifica al sistema radial, el identificadordel nodo de bifurcación y la admitancia equivalentedel subcircuito.

4. PRUEBAS Y ANÁLISISDE RESULTADOS

4.1 Sistema de distribución utilizadoen las pruebas

Como sistema de prueba se utiliza un sistemade 13,2 ky de 18 nodosy de 17 líneas, que se presen-ta en la figura 9. El sistema tiene un ramal príncipaltrífásico que se bifurca en tres ocasiones. La prímerabifurcación corresponde a un ramal monofásico, lasegunda a un ramal trífásico, que a la vez se bifurca,y la tercera bifurcación a un ramal bifásico.

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Tabla 4. Vector de subcircuitos del sistema de ejemplo

Subcircuitos (1)

tBit

1

2

3

4

5

Sis

tem

a ra

dial

1

2

3

3

3

Nod

o de

bifu

rcac

ión

'N003'

•N003'

"N005"

•N003'

'N005'

Sube

ireu

ito

'N005'

'N003'

'N003'

'N003'

'N005^

'N006A'

•N005'

^ 1004'

'N007'

1^004'

'N006'

4

3

6

3

5

Subcircuitos (2)

Fil

a d

esu

bcir

cuit

os (

1)

1

Nod

o de

bifu

rcac

ión

'N005'

Sub

circ

uito

'N005' 'N007' 6

Tipoi Tipo2 Ttpo3 Tipo3

N002 ilccvi N003m:';^N004 iLcciH

Carga Tipo4

Tipo2 Tipoi Tipo3 7ípo3

Carga Tipo1

Tipo2 Tipo1 Tipo3Kix;;^ N010 líix^ v i

Carga Tipos

- ^Carga Tipo2

7ípo3 T¡po3

Carga Tipoi

Figura 9. Sistema de distribución usado en las pruebas

Escuela de ingeniería de Antioquia31

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ESTRATEGIA DE REDUCCIÓN PARA LA APLICACIÓN GENERALIZADA DE LOCALIZADORES...

El sistema de prueba presenta 5 típos de líneasy 4 típos de cargas que se muestran en la tabla 5 yen la tabla 6 respectivamente.

4.2 Obtención de sistemas radialesequivalentes y arreglosdel sistema de prueba

Los arreglos matriciales iniciales que consti-tuyen los sistemas radiales equivalentes del sistema

de prueba son los arreglos de líneas y cargas. Estosse obtienen por el procedimiento propuesto en lasección 3.1 y presentan la estructura descríta en lamisma sección.

En el sistema de prueba usado en este artículose presentan 5 sistemas radiales. El prímero de ellosempieza en el nodo 'NOOl ' y termina en el nodo'N009'. El segundo sistema radial equivalente vadesde el nodo 'NOOI ' hasta el nodo 'NO 12', tal comose muestra en la figura 10.

Tabia 5. Tipos de líneas del sistema de prueba

Tipo

1 "Trifásica"

2 "Trifásica"

3 "Trifásica"

4 "Monofásica"

5 "Bifásica"

Longitud [km]

6

4

5

5

5

Matriz de impedancia de iinea [oiims]

1,597+4,7 99i

0,343+3,043i

0,343+2,784i

1,065+3,199i

0,229+1,805i

0,229+1,596i

1,334+3,9951

0,289+2,319i

0,289+2,048i

00 .f « i

0 + Oi

0 + Oi

8,212+7,247i

0 + Oi

0,290+ 2,472i

0,343+3 ,040i

1,597+ 4,799i

0,343+ 3,040i

0,229+1,805i

1,065+3,199i

0,229+1,805i

0,289+2,319i

1,334+3,999i

0,289+2,299i

0 + Oi

2,417+4,609i

0 + Oi

0 + Oi

00 + COJ

0 + Oi

0,34 3+2,78 4i

0,343+3,040i

1,597+4,799i

0,229+1,596i

0,229+1,805i

1,065+3,199i

0,289+2,048i

0,289+2,299i

1,334+3,996i

0 + Oi

0 + Oi

" + " i

0,290+2,472i

0 + Oi

8,213+7,246i

Tabia 6. Tipos de cargas del sistema de prueba

Tipo

1 "Trifásica"

2 "Trifásica"

3 "Bifásica"

4 "Monofásica"

iViatriz de admitancia de carga [Siemmens]

1,219e-4-9,756e-5i

-6,098e-5+4,878e-5i

-6,098e-5+4,878e-5i

0,0001-5,000e-5i

-5,000e-5+2,500e-5i

-5,000e-5+2,500e-5i

0 + Oi

0+Oi

0 + Oi

5,882e-5-1,471e-5i

0 + 01

-5,882e-5+1,471e-5i

-6,098e-5+4,878e-5i

1,219e-4-9,756e-5i

-6,098e-5+4,878e-5i

-5,000e-5+2,500e-5i

0,0001-5,000e-5i

-5,000e-5+2,500e-5i

0 + Oi

8e-5-4e-5i

0 + Oi

0 + Oi

0 + Oi

0 + Oi

-6,098e-5+4,878e-5i

-6,098e-5+4,878e-5i

1,219e-4-9,756e-5i

-5,O00e-5+2,50Oe-5i

-5,000e-5+2,500e-5i

0,0001-5,000 e-5i

0 + Oi

0 + Oi

0 + Oi

-5,882e-5+1,471e-5i

0 + Oi

5,882e-5-1,471e-5i

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Tpol Tipo2 Tipo3A/00ÍÍLCC3Í N002 i ï c ^ N003\ÍJicZ:fJ004

nYeqN004

Tipo2 Tipol Tipo3

¡Yeq N003 i

í

Figura 10. Sistema radial equivalente 2

Carga Tipo2

Tabla 7. Vector de sistemas radiales del sistema de prueba

Sistema radial 1 Sistema radial 2 Sistema radial 3 Sistema radial 4 Sistema radial S

'N008''N007'

'N006'

'N005'•N004'

'N003''N002'

•Noor

'N009' 8'N008''N007''N006''N005''N004''N003''N002' 1

'NOir'N010''N004'•N003'

'N002'

'NOOr

'N012''N011'•N010''N004''N003'•N002'

11

10

•N013''N011'

'N010''N004''N003'•N002''NOOr

•N014''N013'

•Noir•N010''N004''N003''N002'

1312

10g

321

'N015''N003''N002'

'NOOr

'N016' 17

'N015' 16'N003''N002'

'N017''N005'

'N004'

'N003'•N002'

'NOOr

'N018''N017''N005''N004''N003''N002'

15

14

Las secuencias de nodos que forman los siste-mas radiales se almacenan en el vector de sistemasradiales, tal como se muestra en la tabla 7.

Para determinar los nodos de bifurcación, sellevó a cabo el procedimiento descrito en la sección3.3.2. Se obtiene el arreglo de topología mostrado enla tabla 8 y a partir de él se determina que los nodosde bifurcación son 'N005', 'N004', 'N003' y 'NOI1 '.

Luego que se han determinado todos los nodosde bifurcación del sistema de prueba, se aplica el pro-cedimiento descrito en la sección 3.2.3 para obtener

el arreglo de admitancias equivalentes mostrado enla tabla 9, a partir de los nodos de bifurcación.

4.3 Descripción de las pruebasy resultados

Para probar la estrategia de reducción sepropone tomar los arreglos matriciales que formanlos sistemas radiales equivalentes obtenidos en lasección 4.2, y usando esta información, programary ajustar un método de localización de fallas basadoen el modelo eléctrico de la red (Das, 1998).

Tabla 8. Arreglo de topología transpuesto del sistema de prueba

N008'

'N009'

8

•N007'

'N008'

7

'N006'

'N007'

6

'N005'

'N006'

5

'N004'

'N005'

4

'N003'

'N004'

3

'N002'

'N003'

2

'Noor

•N002'

1

'NOir

•N012'

11

'N010'

•NOir

10

•NOI 3'

'N014'

13

'N011'

'N013'

12

'N004'

'N010'

g

•N015'

'N016'

17

'N003'

'N015'

16

'N017'

•N018'

15

'N005'

•NOI 7'

14

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ESTRATEGIA DE REDUCCIÓN PARA LA APLICACIÓN GENERALIZADA DE LOCALIZADORES...

Tabla 9. Arreglo de admitancias equivalente del sistema de prueba

Sistema Radiai

1

1

1

2

2

2

3

3

3

4

5

5

5

Nodo

'N005'

'N004'

•N003'

•N004'

'N003'

'N011'

'N004'

'N003'

•N011'

•N003'

'N005'

'N004'

'N003'

Admitancia equivaiente en ei Nodo

5,869e-5-1,471e-5i0 + Oi

-5,869e-5+1,471e-5i

0 + Oi0 + Oi0 + Oi

-5,869e-5+1,471e-5i0 + Oi

5,869e-5-1,471e-5i

2,593e^-1,301e-4i-1,297e-4+6,501 e-5i-1,296e-4+6,507e-5i

-1,296e-4+6,501 e-5i2,593e-4-1,301e-4i-1,296e-4+6,501 e-5i

-1,296e-4+6,507e-5i-1,297e-4+6,501 e-5i2,593e-4-1,301e-4i

0 + Oi0 + Oi0 + Oi

2,797e-4-1,622e-4i-1,106e-4+7,369e-5i-1,691e-4+8,848e-5i

0 + Oi0 + Oi0 + Oi

1,598e-4-8,003e-5i-7,991e-5+4,001e-5i-7,989e-5 +4,002e-5i

2,797e-4-1,e22e-4i-1,106e-4+7,369e-5i-1,691e-4+8,848e-5i

0 + Oi0 + Oi0 + Oi

9,996e-5-5,001 e-5i-4,998e-5 +2,500e-5i

-4,998e-5 +2,500e-005i

5,378e-4 - 2,923e-4i-2,399e-4 + 1,387e-4i-2,979e-4 + 1,537e^i

2,214e-4-1,475e-4i-1,107e-+7,372e-5i-1,107e-4+7,374e-5i

2,593e-4-1,301e-4i-1,297e-4+6,501 e-5i-1,296e^+6,507e-5i

0 + Oi0 + Oi0 + Oi

0 + Oi7,992e-5-4,001 e-5i

0 + Oi

-1,106e-4+7,369e-5i2,212e-4-1,474e-4i-1,106e-4+7,369e-5i

0 + Oi7,992e-5-4,001 e-5i

0 + Oi

-7,991e-5+4,001e-5i1,598e-4-8,001e-5i

-7,991 e-5+4,001 e-5i

-1,106e-4+7,369e-5i2,212e-4-1,474e-4i-1,106e-4+7,369e-5i

0 + Oi7,992e-5-4,001 e-5i

0 + Oi

-4,998e-5 +2,500e-5i9,996e-5 -5,000e-5i-4,998e-5 +2,500e-5i

-2,399e-4 + 1,387e-4i4,797e-4 - 2,774e-4i-2,399e-4 + 1,387e-4i

-1,107e-4+7,372e-5i2,214e-4-1,474e-4i-1,107e-4+7,372e-5i

-1,296e-4+6,501 e-5i2,593e-4-1,301e-4i-1,296e-4+6,501 e-5i

0 + Oi7,992e-5-4,001 e-5i

0 + Oi

0 + Oi0 + Oi

0 + Oi

-1,691e-4+8,848e-5i-1,106e-4+7,369e-5i2,797e-4-1,622e-4i

0 + Oi0 + Oi

0 + Oi

-7,989e-5 +4,002e-5i-7,991 e-5+4,001 e-5i1,598e-4-8,003e-5i

-1,691e-4+8,848e-5i-1,106e-4+7,369e-5i2,797e-4-1,622e-4i

0 + Oi0 + Oi

0 + Oi

-4,998e-5 +2,500e-5i-4,998e-5 +2,500e-5i9,996e-5-5,001 e-5i

-2,979e-4 + 1,537e-4i-2,399e-4 + 1,387e-4i5,378e-4 - 2,924e.4i

-1,107e-4+7,374e-5i-1,107e-4+7,372e-5i2,2148-4-1,475e-4i

-1,296e-4+6,507e-5i-1,297e-4+6,501 e-5i2,593e-4-1,301e-4i

0 + Oi0 + Oi

0 + Oi

Por medio del ATP se simularon fallas monofá-sicas en la fase A del sistema radial equivalente demayor longitud, el cual corresponde al sistema radial1. Las fallas se simularon con diferentes resistenciasde fallas (0,5, 10, 20, 30 y 40 O). Adicionalmente,empleando la ecuación 13 se calcula el error relativoen la estimación de la distancia a la falla. Los resul-tados del error relativo contra la distancia a la fallase muestran en la figura 11.

ErrorRelativoíVo] =DistanciaReal — DistanciaCalculada

DtstanciaReal-*100

(13)

Según la figura 11, se aprecia que los errorespara los diferentes casos de fallas son inferiores al3,5 %, lo que indica una respuesta confiable para fallasmonofásicas, demostrando así que la informaciónobtenida por el algoritmo automático de determina-ción de los sistemas radiales equivalentes es fiable.

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Además, se puede ver que el método delocalización, cuando las resistencias de falla sonsuperíores a 10 fl, subestima el sitio de la falla. Parala resistencia de 0,5 H siempre se sobreestima el sitiode falla y para la resistencia de 5 íi inicialmente sesubestima el sitio de la falla y a partir de los 15 kmdel circuito se sobreestima el sitio de falla.

Ante fallas bifásicas y trífásicas, el método delocalización obtiene gráficos de error relativo quemuestran un comportamiento similar al de la figura11, difiríendo primordialmente en el valor máximode error relativo obtenido. Para fallas bifásicas loserrores son inferiores a 2,5 %, y para trífásicas, infe-ríores a 2,4 %.

Los errores en la estimación de la falla varíande acuerdo con el tipo de falla, pues para cada tipoel análisis circuital que se realiza es diferente y tam-bién porque, a medida que se aumenta la resistenciade falla, el efecto de la carga se hace más evidente.Como la carga es una varíable desconocida paratodos los métodos que usan solo las medidas en

un terminal, el error se hace más pronunciado, talcomo se muestra en la figura 11. El efecto de la sub-estimación está asociado a la menor varíación dela impedancia aparente, respecto a la varíación delequivalente de la resistencia de falla y la impedanciade carga del circuito.

5. CONCLUSIONES

Los métodos de localización de fallas que sebasan en el modelo eléctríco de la red, normalmentese fundamentan en ecuaciones desarrolladas parauna sección del circuito, pero para ser aplicadasen sistemas eléctrícos reales se encuentra una grandificultad en el manejo de información y la obtenciónautomática de los parámetros de la red.

El lenguaje de marcas extensible XML permitesituar toda la información de un circuito de la maneramás conveniente, para aplicar la estrategia gene-ralizada de reducción de sistemas de distríbuciónramificados a radiales equivalentes que se presentaen este artículo.

Falla monofásica fase A Sistema radial 135

3

2S

„ 2

1.5

1

OS

O

•os

N

X.

t

f '^

* •

< -x_-—-î» _ ^ . i «._,.4

r---f--

• •

r--• • WÊÊÊÎ^

• ^ j

••RF=05

»- • RF=5

H-RF=20

^ •RF=30

k-. RF=40

^ ^-"ik

10 15 20 25Distancia a ia falia [i<m]

30 35 40

Figura 11. Error relativo ante fallas monofásicas en el sistema radial 1

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ESTRATEGIA DE REDUCCIÓN PARA LA APLICACIÓN GENERALIZADA DE LOCALIZADORES...

Al revisar las referencias Warrington (1968),Das (1998), Novosel et ai. (1998), Choi et ai. (2004),Mora (2006) y Morales, Mora y Vargas (2010),asociadas a metodologías de localización de fallasque se basan en la estimación de la impedancia,se verifica que en ninguna de ellas se presenta unalgoritmo que permita reducir sistemas ramificadosa radiales equivalentes, para la aplicación gene-ralizada de localizadores de fallas en sistemas dedistribución de energía eléctrica, lo que ratifica elaporte que cumple este artículo.

De acuerdo con las pruebas realizadas paravalidar la propuesta del artículo, se observa que elalgoritmo de reducción desarrollado y aplicado alpropuesto por Das (1998) presenta un buen desem-peño ante fallas monofásicas, bifásicas y trifásicas,pues los errores son inferiores a 3,5 %, a 2,5 % y a2,4 % respectivamente, para un rango de resisten-cias de falla entre 0,5 y 40 D.. En general, compa-rando esta metodología de localización con otraspropuestas, se tiene un comportamiento similar,aunque cabe resaltar que el circuito de prueba no esun circuito comúnmente utilizado en la bibliografíay, por lo tanto, la comparación no es del todo estric-ta. El circuito de prueba empleado en este artículose propone para presentar de manera didáctica unaestrategia de reducción de sistemas de distribución,con el fin de realizar la aplicación generalizada demétodos de localización de fallas que se fundamen-tan en la estimación de la impedancia.

La base de datos que contiene los circuitosradiales equivalentes, generaliza y facilita la laborde implementar de una forma adecuada muchosde los métodos de localización de fallas basados enla estimación de la impedancia. Además esta basede datos no es de uso exclusivo en el problema delocalización de fallas, pues presenta la posibilidadde ser el medio para comunicar información decualquier otro tipo de análisis que tengan relacióncon sistemas eléctricos de distribución.

AGRADECIMIENTOS

Este trabajo fije desarrollado en el grupo deinvestigación ICE3 y apoyado por la UniversidadTecnológica de Pereira por medio de la Vicerrectoríade Investigaciones, Innovación y Extensión y por elprograma de Jóvenes Investigadores e Innovadores"Virginia Gutiérrez de Pineda" de Colciencias.

REFERENCIAS

ATP. (2002). Altemative transient program rulebook. ComitéArgentino de Usuarios del EMTP/ATP_CAUE. 2002.

Bedoya, A. Desarrollo de un modelo para intercambio dedatos entre ATP y MATLAB aplicado al problema de lo-calización de fallas en sistemas eléctricos de distribución.Trabajo de grado (Ingeniería Eléctrica). UniversidadTecnológica de Pereira, Pereira, Colombia, 2010.

Choi, M.-S.; Lee, S-J.; Lee, D.-S. and Jin, B.-G. (2004). "Anew fault location algorithm using direct circuit analysisfor distribution systems". IEEE Trar\sactions on PowerDelivery, vol. 19, No. 1 (January), pp. 35-41.

CREG. (2008). Resolución CREG 097 de 2008. ComisiónReguladora de Energía y Gas, CREG [en línea] (Capítulo11) [consultado el 15 de marzo de 2011]. Disponibleen: < http://www.creg.gov.co/html/i_portals/index.php?p_odgin=intemal&p_name=content&pjd=MI-182&P options = >.

Das, R. (1998). Determining the locattons of faults in distri-bution systems. Doctoral thesis. University of Saskatch-ewan, Saskatoon, Canada, 1998.

Molinari, M. and Cox S. (2007). The XML toolbox: A user'sguide. The Geodise Project, University of Southampton[consultado el 10 de junio de 2010]. Disponible en:<http://www.geodise.org/toolboxes'generic/xml_tool-box.htm>.

Mora, J. Localizaciôn de faltas en sistemas de distribución deenergía eléctrica usando métodos basados en el modeloy métodos basados en el conocimiento. Tesis doctoral.Universität de Girona, España, 2006.

Morales, G.; Mora, J. and Vargas, H. (2010). Fault locationmethod based on the determination of the minimum faultreactance for uncertainty loaded and unbalanced powerdistribution systems. Transmission and Distribution Con-ference and Exposition: Latin America, 2010IEEE/PES.Sao Paulo, Brazil (8-10 November).

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Novosel, D.; Hart, D.; Hu, Y. and Myllymaki, J. System for Warrington, A. R. van C. Protective relays: Their theorylocating faults and estimating fault resistence in distribu- and practice. Vol. 1. London: Chapman and Hall, 1968.tion networks with tapped loads. US Patent number ^^^^.^^^ ^ ^ ^

5,839,093 (17 November 1998). ^^.^^^^ ^^ ^^^^^ ^008 [consultado el 20 de octubre de

Príkler, L. and H0idalen, H. (2002). ATP draw manual, 2010]. Disponible en: < httpvywww.w3.or&TR/xml/>.version 3.5 for Windows 9xlNTl2000lXP. 2002.

Escuela de Ingeniería de Antioquia 37

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Ingenieriay Competitividad, Volumen 14, No. 2, p. 37 - 52 (2012)

INGENIERÍA INDUSTRIAL

Metodología de mejoramientoen el desempeño de sistemas de producción.

Aplicaciones en Pymes de la confección

INDUSTRIAL ENGINEERING

Methodology improvement in the performance ofproduction systems. Applications in SMEs confection

Maria A. Solano*, Juan J. Bravo*, Jaime A. Giraldo** §

* Facultad de ingenieriaEscuela de Ingenieria Industrial y Estadística,Universidad del Valle, Santiago de Cali, Colombia.

** Departamento de Ingeniería Industrial, Universidad Nacional de Colombia,

Manizales, Colombia.

§ alexasolanoce@,hotmail. com, juan. bravo(^correounivalle. edu. co, jaiagiraldog(^unal. edu. co

(Recibido: Abril 25 de 2011-Aceptado: Noviembre 19 de 2012)

ResumenSe presenta una metodología de mejoramiento en el desempeño del sistema de producción en Pymes de la confección,consistente en la utilización de técnicas multicriterio para la selección y jerarquización de las prioridades competitivasa las que el sistema debe responder; el empleo de un procedimiento general para evaluar la coherencia estructural dela estrategia de operaciones en términos de las prioridades competitivas, los sistemas de producción y las palancasde fabricación; y finalmente la modelación del sistema de producción mediante simulación de eventos discretos conel fin de experimentar diversas alternativas de mejoramiento que estén alineadas con las prioridades competitivasmás relevantes. Como resultado se aplicó la metodología propuesta a una muestra de cinco Pymes del sector de laconfección de la ciudad de Manizales (Colombia) en su primera etapa, encontrándose que las prioridades competitivascalidad y tiempo de entrega son las más relevantes. Seguidamente a la Pyme con el peor desempeño se le aplicaronlas demás etapas, demostrándose finalmente la utilidad de la metodología al lograr variar el desempeño de su sistemade producción en términos de aumentar un indicador de efectividad de un valor de 2.12 a 2.32 en una escala de O a 5,mejorando su desempeño en cerca de un 10%.

Palabras clave: Prioridades competitivas, Pymes de confección. Simulación de eventos discretos. Sistemas deproducción

Abstract.This paper presents a methodology for improving the performance of production system in confection SMEs consistingin the use of multicriteria techniques for the selection and prioritization of competing priorities to which the systemshould respond, the use of a general procedure evaluate the structural coherence of the strategy of operations interms of competitive priorities, production systems and manufacturing levers, and finally the production systemmodeling using discrete event simulation in order to experiment improvement alternatives that are aligned with themost important competitive priorities. As a result the proposed methodology was applied to a sample of five SMEsin the manufacturing sector of the city of Manizales in the first stage, finding that the competitive priorities of qualityand delivery time are the most relevant. Next to the worst-performing SMEs were applied to the other stages, showingfinally the usefulness of the methodology to achieve performance vary their production system in terms of raisingan indicator of effectiveness of a value of 2.12 to 2.32 on a scale 0 to 5, to improve its performance by about 10%.

Keywords: Competing priorities. Discrete event simulation. Production systems, SMEs clothing

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1. Introducción

Para Pérez-Castaño (2007) en la medición dela competitividad de- las empresas se empleael Business Competitiveness Index (BCI)propuesto por Michael Porter el cual hace uso deindicadores microeconómicos para la medicióny evaluación del potencial productivo de unaeconomía, que se manifiesta en la sofisticaciónde sus empresas y la calidad de su entornomicroeconómico de negocios.

Las Pymes colombianas del cluster textil-confección, que para Castellanos et al. (2006,p. 38) es un sector de gran dinámica económicaa nivel mundial, presentan debilidadesestructurales e infraestructurales, que no lespermiten alcanzar en el eorto plazo altos nivelesde competitividad acorde a las necesidadesdel mercado. De acuerdo con Giraldo-Garcia(2008), Sarache-Castro (2003), Torres Acosta(2001) y CINTEX (2009), algunos aspectos queinfluyen negativamente en la eompetitividad delas Pymes colombianas son los siguientes:

Debilidades en el direceionamiento estratégicode la fabricación.

Baja capacidad administrativa para vincularsecon el mercado internacional.

Sistemas de producción no alineados con lasprioridades competitivas.

Ausencia de sistemas integrados de planeación,programación y control de la producción.

Deficiencias en los sistemas de costos deproducción.

Desconocimiento de la capacidad de producción

Deficiencias en los sistemas de calidad.

Atraso y obsolescencia tecnológica.

Dificultad para incursionar en mercadossofisticados con productos más diferenciados.

Falta de una mejor comprensión de sus fortalezascompetitivas y debilidades.

Falta una actitud más agresiva hacia elaprendizaje y la modernidad institucional.

Las Pymes de confección en lo particular poseenuna estructura plana en la cual el gerente (enmuchos casos propietario) centra su actividaden desarrollar funciones del nivel operativo,descuidando decisiones concernientes al nivelestratégico y táctico, según lo reporta el estudiohecho por Sarache-Castro (2003). La industriatextil y de confección, se ha destaeado comofactor fundamental en el desarrollo del país,ya que durante más de 80 años ha hecho unacontribución muy importante al crecimiento delas exportaciones y del PIB de la nación. Es dedestacar que la industria de confecciones creció11.8% en términos reales (precios del 2000)entre el 2006 y 2007, según Proexport (2009).

Según información de Inexmoda, Colombia esreconocida intemacionalmente como un paisque presenta grandes fortalezas en el negocio delos textiles y confecciones y en particular, en elde la moda. Sin embargo, algunos subsectoresde textiles y confección durante el período enero- junio del 2009 decrecieron (INEXMODA,2009). La Tabla 1 muestra los valores de lasexportaciones de confecciones colombianas portipo de tejido para los años 2008 y 2009, conun valor total exportado aproximado de 1800millones de dólares. Colombia presenta uno delos costos laborales más bajos de Latinoaméricasiendo la flexibilidad laboral y la disponibilidaddel recurso humano calificado los que puedenpermitir que los proyectos productivos seanrentables en Colombia, (Proexport, 2009).

Tabla /. Exportaciones de confecciones colombianas portipo de tejido. Fuente: Inexmoda (2009).

Subscctor FOB USS

2008 2009

Punto 588,809,095 127,405,857

Plano 603,248,376 254,046,320

Ropa de hogar 139,908,062 46,172,498

Total Confecciones 1,331,965,534 427,624,677

Enmarcado en los anteriores aspectos del sector,se puede concluir que existe un gran potencialen vía de desarrollo, siendo el crecimiento yla evolución factores que han superado todaslas expectativas, donde no propiamente hanestado acompañadas de una adecuada estrategia

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operacional como marco de mejoramiento, sinopor el contrario han estado guiadas de maneraempírica según Trujillo-Cabrera (2005), sintener en cuenta que "el éxito comercial para unaorganización depende de una ventaja en el costoo de una ventaja en el valor'" [Ohmae (1982) yPorter (1991) citados por Sarache-Castro (2003)y Sarache- Castro et al. (2004)].

A nivel microeconómico, el procedimientovalidado por Sarache-Castro et al. (2007)en Pymes del sector metalmecánico y conposibilidad de aplicación en otros sectores,propone un esquema de mejoramiento coherenteen tres aspectos fundamentales, denominadoconjuntamente P-S-P: 1) las prioridadescompetitivas (P), 2), la configuración productivao sistema de producción (S), y 3), las palancasde fabricación (P). Esto significa que unaacción de mejora en un sistema de produccióndebe partir por identificar las prioridadescompetitivas o exigencias del mercado objetivo;a partir de éstas, se debe valorar la coherenciade la configuración adoptada por el sistemaproductivo y el desempeño de sus subsistemas opalancas de fabricación con dichas prioridadescompetitivas, según se expresa en Giraldoet al. (2010). Para Krajewski et al. (2008), lasprioridades competitivas son "... las dimensionesoperativas cruciales que un proceso debe poseerpara satisfacer a los clientes internos y externos,tanto en el presente como en el futuro". A nivelde estrategia de producción, autores comoMiltenburg (2004) e Ibarra (2003) recalcan lanecesidad de medir la mejora en tin sistema deproducción en términos de múltiples prioridadescompetitivas (múltiples criterios), en razón aque éstas últimas están relacionadas de maneramás natural con un mercado objetivo. El estadodel arte permite constatar la existencia de seisprioridades competitivas básicas en producción:calidad, costo, entrega, innovación, flexibilidady servicio [Gaither & Frazier (2000) e Ibarra-Mirón & Sarache-Castro (2008), Miltenburg(2004)].

De otra parte, para Schroeder (2004), laadministración de operaciones tiene relación conla toma de decisiones sobre cuatro cuestionesrelevantes: localización, proceso, capacidady distribución física, siendo estas dos últimas

las que dan a lugar a lo que se denomina laconfigtiración productiva del sistema. Diferentesautores, tales como Domínguez Machuca et al.(1995), Schroeder (2004), Alfalla et al. (2008),entre otros; han reconocido la existenciade 4 tipos de configuraciones productivasgenéricas que son: configuración por proyecto,configuración orientada al proceso o fiancional{job-shop), la configuración orientada alproducto (flow-shop) y configuraciones híbridas.La estructura del sistema de produccióncomprende, por un lado, al subsistema virtualy de decisión (o de gestión), responsable dela fijación de una estrategia funcional y delas funciones de planificación, programacióny control; por otro lado, está el subsistemafísico (o de transformación), conformado porun conjunto de personas, máquinas, materialese instalaciones que en general se encargan deejecutar el programa de producción, bajo algúnesquema de organización productiva.

Definir cuál es la configuración productivamás adecuada para una empresa representa uncompromiso fundamental en el establecimientode la estrategia corporativa. Es decir, como loseñala Domínguez Machuca et al. (1995), estasson decisiones de diseño que pertenecen alnivel estratégico del esquema de administraciónde la producción y que están en relación conel nivel estratégico de la gestión corporativa.La selección de la configuración productivadepende de las prioridades competitivas que sepersigan. Es decir, la configuración productivaa seleccionar o la mejora de una configuraciónexistente, debe ser coherente con el output defabricación que se desea proveer Miltenburg(2004), Ibarra-Mirón & Sarache- Castro (2008).De modo que, la matriz producto - proceso seconvierte en una herramienta para definir laestrategia de operaciones y por ende la ventajacompetitiva que se desea alcanzar.

Algunos autores, establecen que debe existiruna adecuada relación entre la configuraciónproductiva y el cumplimiento de las prioridadesy que éstas deben estar soportadas en lossubsistemas del sistema de producción ó palancasde fabricación. Para Miltenburg (2004) laspalancas de fabricación son: recursos humanos,estructura y controles de la organización.

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fuentes de aprovisionamiento, planifieacióny eontrol de la produeeión, teenología deprocesos e instalaeiones. En Giraldo-García(2008) se plantea que para medir cl grado deefeetividad de un sistema productivo por mediode las prioridades competitivas seleccionadasy jerarquizadas, se requiere intervenir factorescomo la eonfiguración productiva que se adoptey las palancas de fabricación anteriormentemencionadas; sin embargo, realizar estainterveneión en el sistema real puede resultarinapropiado, generar impactos costosos ytraumáticos para la organización.

En Sarache-Castro et al. (2007) se proponeque "... una vez se hayan estudiado condetalle los elementos del sistema P-S-P, esnecesario analizar su coherencia estructural;es decir, qué tan alineados están el sistema deproducción y sus palancas con las prioridadescompetitivas. Por ejemplo, si las prioridadescompetitivas más importantes son el costo y elplazo, el sistema de producción y las palancasdeberán estar orientados hacia el logro de talesobjetivos''. Desde esta perspectiva, la adopeiónde prácticas encaminadas a la mejora continuade los procesos produetivos se convierte enuna de las más importantes tendencias para laadministración moderna. Es por ello que seplantea la pregunta de investigación: ¿Cuálseria la estrategia operacional que se debeimplementar en Pymes del sector confeccionespara mejorar el desempeño de sus sistemas deproducción frente a las prioridades eompetitivasde su mercado objetivo?

Por lo anteriormente expuesto, se pretende eneste artículo mostrar los resultados obtenidosal hacer una investigación en Pymes dela confeeeión textil sobre sus sistemas deproducción y mercado objetivo. Estos resultadoshacen referencia a presentar una metodologíade mejoramiento del desempeño del sistemade produeeión consistente en la utilizaciónde técnicas multicriterio para la selección yjerarquización de las prioridades competitivas alas que el sistema debe responder; el empleo de unprocedimiento general para evaluar la eoherenciaestruetural de la estrategia de operacionesen términos de las prioridades competitivas,los sistemas de producción y las palancas de

fabricación; y finalmente la modelación delsistema de producción mediante simulaciónde eventos discretos con el fin de experimentardiversas alternativas de mejoramiento que esténalineadas con las prioridades competitivasmás relevantes. Como resultado se aplicó lametodología propuesta a una muestra de cincoPymes del sector de la confección de la ciudadde Manizales (Colombia) en su primera etapa,eneontrándose que las prioridades competitivascosto, calidad y tiempo de entrega son las másrelevantes. Seguidamente a la Pyme con el peordesempeño se le aplicaron las demás etapas,demostrándose finalmente la utilidad de lametodología al lograr variar el desempeño de susistema de producción en términos de aumentarun Indicador de Efeetividad del sistema deproducción.

2. Metodología

2.1 Identifícación de las prioridadescompetitivas (P) para las empresas objeto deestudio.

En esta etapa se sugiere apliear el procedimientovalidado por Sarache et al. (2005, p. 86-88), ajustado del sector metalmeeánicoal sector eonfección textil, el cual permitedefinir y jerarquizar el conjunto de prioridadescompetitivas que exige un mercado objetivo.Los pasos utilizados para realizar lajerarquización de las prioridades competitivas ysus dimensiones son:

a. Definir las prioridades fundamentales:eonsiste en detectar las exigencias de los clientesque conforman el mercado objetivo a través deencuestas, investigación de mercados, estudiosde benchmarking, consulta con expertos, etc.

b. Definir las dimensiones para cada prioridad:se desagregan las necesidades de los clientesen términos de dimensiones cualitativas ycuantitativas.

c. Calcular el número de expertos: se hacemediante el empleo de fórmula expresadaen términos del nivel de preeisión deseado,porcentaje de error a tolerar y un nivel deconfianza dado.

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d. Seleccionar expertos: se tiene en cuenta a lospropios clientes del mercado objetivo, expertosconocedores del mercado objetivo (gremios,académicos, agencias gubernamentales), etc.

e. Jerarquizar prioridades y dimensiones: losexpertos proceden a calificar la importanciarelativa entre el conjunto de prioridades y entrelas dimensiones de cada prioridad.

f. Realizar pruebas de concordancia: consiste enmedir el nivel de acuerdo entre los expertos através de un indicador de concordancia.

g. Construir el Indicador de Efectividad: seobtiene de expresión dada en términos de lospesos de las prioridades competitivas, pesos delas dimensiones y calificaciones dados por losexpertos y/o gerentes de empresas y está dadopor la Ec. (1):

(1)/ c = l

Dónde:

IE.: Indicador de Efectividad que alcanza unaempresa i. Se da en una escala de O a 5

i: índice de empresa en estudio

j : índice de prioridad competitiva

k: índice de dimensión de prioridad

1: número de dimensiones de la prioridad j

W..: Peso de la prioridad j en la empresa i(calidad, precio, entrega, fiexibilidad, servicio,etc.)

W.,.: Peso de la dimensión k en el factor j parala empresa i

C..| : Calificación obtenida por la dimensión k,en la prioridad j , para la empresa i

Finalmente una vez definidas las prioridadescompetitivas, es necesario evaluar el desempeñode las empresas en cada una de estas y en cadauna de sus dimensiones, con el fin de procedera clasificarlas en función de sus tendencias,Sarache-Castro et al. (2007).

2.2 Análisis del sistema P-S-P

Consiste en diagnosticar y analizar de maneraintegral las prioridades competitivas (P), laconfiguración productiva (S) y las palancas defabricación (P) de la empresa en estudio, segúnSarache et al. (2007). La información requeridapara el diagnóstico se recolecta a través deun instrumento tipo encuesta. En este paso sedesarrollan tres actividades: 1) desempeño enlas prioridades competitivas, 2) caracterizaciónde la configuración productiva y, 3) análisis delas palancas de fabricación.

2.2.1 Desempeño en las prioridadescompetitivas: En esta parte del diagnóstico,se mide el desempeño de las empresas en lasprioridades competitivas y en cada una desus dimensiones; así mismo, cuantificar eldesempeño (indicador de efectividad: IE.) de laempresa o conjunto de empresas. Es deseableque la medición de este desempeño la haga elrespectivo grupo gerencial de cada empresa através del mencionado instrumento de encuesta(autoevaluación).

2.2.2 Caracterización de la configuraciónproductiva: Para realizar el diagnóstico decada uno de los elementos que forman partedel sistema de producción, la recolección deinformación debe abordar diferentes aspectos,como son: el sistema de aprovisionamiento,el sistema de fabricación y el sistema dedistribución, caracterizando estos sistemas entérminos de si corresponden a configuraciónpor proyecto, proceso o producto e identificarel tipo de sistema de producción que la empresao empresas en estudio aplican, procurandodetectar las características relevantes entérminos de flexibilidad y productividad queofi'ece el sistema empleado.

2.2.3 Caracterización de las palancasde fabricación: Incluye la valoración delconjunto de palancas de fabricación, es decir,recursos humanos, planificación y control dela producción, estructura y controles de laorganización, los procesos y las instalaciones.El detalle de esta caracterización y el análisis delas palancas de fabricación permitirán establecerlas variables de decisión que se tendrán encuenta en la etapa de mejoramiento.

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2.3 Valoración de la coherencia del sistemaP-S-P

Se hace una exploración de los elementos de latriada P-S-P, analizando qué tan relacionadasse encuentran las prioridades competitivas (P)(según lajerarquía obtenida en 2.2.1), el sistemade producción (S) y sus palancas de fabricación

Como se mencionó anteriormente, cada tipode configuración productiva o sistema deproducción logra obtener en mayor o menorgrado impactar a las prioridades competitivas.Por lo tanto, es necesario identificar elmáximo nivel que logra obtener una prioridadcompetitiva con un sistema de produccióndeterminado. Por ejemplo, según Miltenburg(2004), para lograr ser el mejor en flexibilidad,resulta más adecuado tener un sistema Job Shop,de igual manera, si se quiere tener costos másbajos, estos se pueden conseguir con un sistemacontinuo.

De igual modo la relación entre palancas defabricación y prioridades competitivas se puedeobservar en que a medida que se intervienecada palanca, se puede conseguir impactospositivos o negativos en las prioridades, comopor ejemplo, si centramos acciones inicialmenteen la palanca recursos humanos, promoviendola polivalencia de operaciones y el incrementode la eficiencia, se pueden lograr mejoras encosto y plazo de entrega.

En síntesis el resultado de esta etapa es formularun modelo de prescripción coherente del tipoVariables de Decisión: Medidas de Desempeño(VD:MD), para cada empresa en estudioen el cual las variables de decisión (VD) secorresponden con la configuración productivay las palancas de fabricación, mientras que lasmedidas de desempeño (MD) se correspondencon las prioridades competitivas. La formulaciónde este modelo se hace en conjunto con el grupogerencial de la empresa en estudio.

2.4 Defínición y evaluación de las acciones demejoramiento

Con base en la valoración de la coherenciadel sistema P-S-P, el grupo gerencial define

uno o varios escenarios basados en el modeloprescriptivo del tipo VD:MD y evalúa elimpacto de las respectivas VDs en la(s) MDa través de un modelo de simulación de eventosdiscretos y un Indicador de Efectividad (IE).Se espera que el modelo VD:MD de mayorimpacto en las prioridades competitivas másrelevantes sea el que adopte la empresa en elmundo real por lo que en la definición delmodelo se sugiere emplear VDs cuyos valoressean factibles de implantar por la empresadesde el punto de vista económico y téenico.En la construcción del modelo de simulación seutiliza la metodología universalmente aceptadaen estudios de simulación de eventos discretos,Giraldo-García (2008).

3. Resultados y discusión

Se seleccionó de un universo aproximado de20 empresas una muestra de cinco (5) Pymesde la confección ubicadas en la ciudad deManizales (Caldas), aplicándose la metodologíaa todas ellas en la primera etapa (numeral 2.1).Posteriormente se eligió la Pyme con un lE(Indicador de Efectividad) bajo para aplicar lasdemás etapas. A pesar de que la metodologíapuede aplicarse a cualquier grupo de empresasde un sector, se mostrara aquí una pequeñaaplicación al sector confecciones con el fin demotivar la extensión de su uso a un númeromayor de Pymes del sector.

3.1 Identificación de las prioridadescompetitivas para las empresas objeto deestudio.

a. Definir tas prioridades fundamentales: Apartir de la propuesta teórica de Miltenburg(2004) sobre las prioridades competitivas a lasque debe responder un sistema de produccióny con base en las investigaciones de Sarache-Castro (2003) y Sarache-Castro et al. (2011)realizada en el sector de las confecciones,se encontró que las principales prioridadesque un proveedor confeecionista en el mediocolombiano debe potenciar son: costo, calidad,entrega, flexibilidad y asistencia técnica.

b. Definición de las dimensiones para cadaprioridad: Como parte adicional a las preguntas

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de la ronda anterior, Sarache-Castro (2003)cuestionó a cada uno de los representantessobre cuál o cuáles serían los componentes odimensiones de cada una de las prioridades quese definieron anteriormente. En la Tabla 2 sepresentan los resultados obtenidos.

c. Calculo del número de expertos: En esta fasedel proceso se aplicó la expresión propuesta porSaraehe (2003) según se muestra en la Tabla 3,la cual arrojó el empleo de cinco (5) expertos.

d. Selección de expertos: En la Tabla 4 se exponeel listado de los cinco expertos que aceptaronpartíeípar en el presente estudio.

e. Jerarquízación de prioridades y dimensiones.La Tabla 5 muestra la jerarquía de prioridadeseompetitivas y sus dimensiones, establecidaspor los expertos. De acuerdo con los resultadosde la Tabla 5, es importante resaltar que lasprioridades eompetitívas y dimensiones oeomponentes más destaeados son: calidad (lafiabílídad en la entrega), entrega (el tiempo derespuesta a un cliente que pide una cotización^,costo (por ser de tipo unidimensional y derelación directa con el precio unitario) yflexibilidad (tamaño del lote).

f. Realizar prueba de concordancia: Los expertosprocedieron a calificar la importancia relativaentre el conjunto de prioridades y entre lasdimensiones de cada prioridad obteniéndose unindicador de concordancia de Kendall de 0.696,

el cual garantiza la coherencia de los expertos,dado que es superior a 0.5.

g. Construcción del Indicador de Efectividad(IE): La Ec. (2) corresponde a la formulaobtenida de la Tabla 5 que se empleara paravalorar el Indicador de Efectividad IE¡ para cadaPyme estudiada.

Tabla 2. Prioridades competitivas y sus dimensiones.Fuente: Sarache-Castro (2003)

PrioridadCompetitiva

Costo

Entrega

Flexibilidad

Dimensión

Asistenciatéenica

Sin componentes

1. Fiabilidad en las entrega2. Calidad de concordancia3. Posibilidad de rechazo yreclamaciones

1. Plazo de entrega2. Tiempo de respuesta a uncliente que pide una cotización3. Tiempo de respuesta a uncliente que pide información

1. Flexibilidad ante cambios deimprevistos2. Flexibilidad del portafolio defamilias de productos3. Flexibilidad en el tamaño delos pedidos4. Flexibilidad del portafolio detejidos

Sin componentes

IE. = (0.38 [0.35^2,+ 0.14 C. , + 0.51C.J + 0.26 [O.32C.31+ 0.16 C.j + 0.52 C.33] + 0.19 [C.,] +

0.09 [0.46C,,,+ 0.15 C,,, + 0.18 C,,3+ 0.21 C J + 0.08 [C,,,]) * 0.60 (2)

Tabla 3. Calculo número del número de Expertos.

Formula Dónde: Valoresasignados

Cantidad deExpertos

n =P{\-P)K

n: número de expertos

i: nivel de precisión deseado 17

P: porcentaje de error que como promedio se tolera 0.04

K: constante asociada al nivel de confianza 3.8416

5 personas

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Tabla 4. Listado de Expertos.

Experto

El

E2

E3

E4

E5

Empresa/Entidad

Sena

Tropieal Bcaeh

C.l Nicole

C.I Color Siete

C.l Indudise

Área He trabajo

Instructora de Confección

Administrador de Producción

Jefe de Ingeniería

Gerente Comercial

Gerente Genera!

Formación Profesional

Técnieo

Ingeniero Industrial

Ingeniero Industrial

Economista

Tabla 5. Jerarquización de prioridades competitivas para Pymes de la confección.

Prioridades y dimensiones enorden de importaneia

CALIDAD

ENTREGA

PRECIO

FLEXIBILIDAD

ASISTENCIA TÉCNICA

Peso

0.38

0.26

0.19

0.09

0.08

C.

C21

C22

C23

C31

C32

C33

C l l

C4I

C42

C43

C44

C5I

Dimensiones

Calidad de Coneordaneia

Posibilidad de rechazo y reclamaciones

Fiabilidad en ia entrega

Plazo de entrega

Tiempo de respuesta a un cliente que pideinfbnnaeión

Tiempo de respuesta a un cliente que pide cotización

Sin componentes

En el tamaño del lote

Ante eambios de imprevistos

Del portafolio de familias de productos

Del portafolio de tejidos

Sin eomponentcs

Peso entredimensiones

0.35

0.14

0.51

0.32

0.16

0.52

1.00

0.46

0.15

0.18

0.21

1.00

3.2 Análisis del sistema P-S-P

3.2.1 Desempeño en las prioridadescompetitivas

La medición de este desempeño la hizo elrespeetivo grupo gereneial de cada empresaa través del instrumento ^ de encuesta(autoevaluación) empleado y aplicado porSolano (2010). Tomando esta medición yaplicando la Ec. (2) se obtiene para cadaempresa en estudio su respeetivo Indicador deEfectividad (IE) según se muestra en la Tabla 6.Debe connotarse que las Pymes 1 y 3 presentanun 1E¡ entre 2 y 3 que corresponde a undesempeño medio bajo y la Pyme 4 con IE. pordebajo de 2 muestra un desempeño bajo segúnescala mostrada en Sarache-Castro (2003).

Para la aplieación de la metodologia demejoramiento en los siguientes pasos y etapasse empleará la información de la Pyme 1 la

cual empezó a operar en marzo del año 2001,con ventas a nivel nacional e internacional,siendo sus productos reconocidos por serconfeccionados cumpliendo altos estándares decalidad en cuanto a materias primas e insumos.Cuenta con alrededor de 40 empleados entemporada baja y 100 en temporada alta. Porel particular interés de la empresa de entrar aparticipar en el mercado nacional e internacionaladquiere nueva maquinaria que responde a laacelerada evolución que en su momento se daen la comercialización de ropa interior, exterior,casual y deportiva. La empresa aspira a ocuparuno de los puestos destacados en la industriade la región, del país y del mereado arnericano.Desde el año 2001 ha realizado exportaeionesa paises como: Puerto Rico, Panamá, México,Estados Unidos, Ecuador y Venezuela;actualmente su mayor mercado se ha canalizadohacia Venezuela exportando alrededor de800.000 unidades al año.

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Tabla 6. Indicador de efectividad para 5 Pymes de confección de Manizales.

Prioridadescompetitivas

CALIDAD

ENTREGA

PRECIO

FLEXIBILIDAD

ASISTENCIATÉCNICA

Peso

0.38

0.26

0.19

0.09

0.08

C21

C22

C23

C31

C32

C33

CU

C4I

C42

C43

C44

C51

INDICADOR

Dimensiones

Calidad de Coneordancia

Posibilidad de reehazo yreelamaciones

Fiabilidad en la entrega

Plazo de entrega

Tiempo de respuesta a un eliente quepide informaeión

Tiempo de respuesta a un eliente quepide eotizaeión

Sin componentes

En el tamaño del lote

Ante eambios de imprevistos

Del portafolio de familias deproductos

Del portafolio de tejidos

Sin eomponentes

DE EFECTIVIDAD (E)

Peso

0.35

0.14

0.51

0.32

0.16

0.52

1.00

0.46

0.15

0.18

0.21

1.00

Pyme1

3.33

5

4

3

3

4

3

4

4

3

4

3

2.12

Pyme2

4

5

3

3

4

4

1

4

4

3

3

4

3.01

Pyme3

4

4

3

3

3

3

5

3

3

4

4

3

2.15

Pyme4

233

4

3

3

3

3

1

4

3

3

3

3

1.83

Pyme5

3.33

5

3

5

5

5

5

5

5

5

5

3

3.77

3.2.2 Caracterización de la confíguraciónproductiva

El sistema productivo de esta empresacorresponde a un Job Shop dedicado a laproducción de sus propias colecciones y enalgunos casos presta servicios de maquila.El módulo de producción que se simularácuenta eon 12 máquinas discriminadas así: 7fileteadoras, 2 collarines, 2 planas, 1 cerradorade eodo y 1 estación de inspección. Tienemediana flexibilidad, sus diseños en gran parteson propios, y en el caso de la maquila seacogen a los diseños del cliente. El 35 % de suprodueeión se destina al mercado nacional y el65% es para exportación. Posee instalaeionespropias, en un lugar de fácil acceso para larecepción de materias primas y despacho deproductos terminados. La producción se planeay realiza en tiempos cortos, a veces inferiores auna semana empleando un solo tumo de trabajo.Las ventas de la empresa se hacen a través deun grupo de vendedores y un punto de ventapropio, el segmento de mercado que atiende esestrato medio-bajo siendo los mejores mesespara las ventas: junio, octubre, noviembre ydiciembre. Más de la mitad de sus clientes sonintemaeionales.

Posee la Pyme un sistema computarizado deregistro y control de inventarios para todo el

proceso productivo, desde la materia prima,hasta el producto terminado; las compras serealizan al comienzo de la producción; la mitadde los proveedores son de la ciudad y/o regióny la otra mitad son del resto del país. En laslíneas de producción se presenta un alto nivelde inventario en proceso.

Los controles de calidad en la empresa seaplican en todo el proceso, se buscan defectosen la medida, imperfectos en la tela, defectosen el corte, aeabados o costuras utilizando unmétodo de muestreo aleatorio. Pero cabe aclarar,que poseen deficiencias en la recolección dedatos. No se cuenta con el personal idóneo paraliderar procesos de aseguramiento de calidad;se limitan solamente a realizar la inspecciónde productos terminados, sin tener un métodoy criterios estandarizados. El mantenimientolo realiza personal de la empresa, elasifieadoen preventivo y correctivo. Es importantemencionar, que se presenta con mayor fi^ecuenciael mantenimiento correctivo.

3.2.3 Caracterización de las palancas defabricación

Las características esenciales de estas palancasse obtuvieron a través del instrumento deencuesta aplicado por Solano (2010). En

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relación con recursos humanos, en estas Pymesse encuentra trabajando algún miembro de lafamilia, sobre todo en cargos directivos. El niveleducativo que tiene el personal se encuentradividido en 4% técnico y tecnológico, 90%secundario y 6% estudios superiores concluidos.El 70% del personal que labora en la empresase encuentra en producción y el 30 % en elárea administrativa. Se presenta dificultad paraconseguir personal calificado y especializadoque soporte la labor administrativa. Respectoa estructura y controles de la organización, setienen formuladas la misión, visión y políticas,pero estás, no son entendidas y apropiadas enlos niveles táctico y operativo, igualmente, noposeen sistemas de calidad certificados. Noexisten controles en los procesos. Su estructurajerárquica es de 2 niveles: Gerencia General yAdministración.

Para planear la producción se cuenta con unprocedimiento sistemático entre 1 y 3 meses,el cual es elaborado en coordinación con lagerencia, producción y ventas con base enestimaciones aproximadas, los pedidos en firme(50%) y proyección estadística a partir de datoshistóricos (50%). No se aplican herramientasinformáticas para la gestión de la producciónpresentando dificultad para calcular y planear lacapacidad de la planta.

Respecto al aprovisionamiento, la empresaen mención utiliza un sistema de control deinventarios para todos los procesos involucradoscomo son: bodegas de materia prima e insumos,producto en proceso y producto terminado. Nose cuenta con una metodología para establecerla cantidad adecuada de compra de materialessiendo está infiuenciada por el juicio del gerentey necesidades de un programa de producción.En relación con la teenología de procesos laempresa posee equipos semi-automatizados yautomatizados.

3.3 Valoración de la coherencia del sistemaP-S-P

Para la empresa objeto de estudio y basados en laTabla 6, las siguientes prioridades competitivasdeben tener un alto desempeño y cumplimiento:costo, calidad y entrega, pues recogen el 83%

de la importancia relativa. Esto, sin duda, sindescuidar la fiexibilidad y la asistencia técnica,ya que estas últimas pueden ir ascendiendo enun futuro cercano. Cabe mencionar, que deacuerdo a Miltenburg (2004), la prioridad quees coherente con ia configuración productiva(Jop Shop) y que alcanza mejor desempeño esla fiexibilidad, y la peor el costo, por lo que parael caso se percibe que no existe coherencia entrelas prioridades y la configuración. El análisis delas palancas de fabricación muestra debilidadesen algunas de ellas, como son: falta de uso demetodologías y herramientas informáticas paratener una planeación más adecuada; la existenciade un alto grado de participación familiar en lafunción directiva no permite una delimitación enlas funciones y responsabilidades en especial elcargo de dirección de producción, ocasionandosobrecarga de actividades y descuido de lasfunciones propias del área o proceso.

En síntesis, para poder incrementar eldesempeño en las prioridades competitivas másimportantes (calidad, entrega y costo) para laPyme y en común acuerdo con la gerencia sedeben realizar acciones de mejora en: reducciónde costos, mejoramiento de calidad, reducciónde ciclos de fabricación y plazo de entrega.Inicialmente, es preciso intervenir el sistemafísico de transformación mediante un cambioen la distribución en planta con el objetivode mejorar su desempeño, es decir, mejorarla capacidad productiva con los recursosdisponibles. En el caso de la calidad, la soluciónimplica bajar la tasa de defectuosos. Y parael caso de las entregas, se hace necesario eldesarrollo de un programa de mejoramiento dela eficiencia del módulo de confección.

Por tanto el modelo de prescripción coherentedel tipo Variables de decisión: Medidas dedesempeño (VD :MD^), que se propone, enconjunto con el grupo gerencial de la empresa,se estructuró así:

Variables de decisión (VDJ:-Número y tipo máquinas en el módulo real deconfección.

-Propuestas de distribución en planta.-Numero de operarios.-Tasa de defectuosos a alcanzar.

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Medidas de desempeño (MDJ:-Costo-Calidad-Entrega

3.4 Defínición y evaluación de las acciones demejoramiento

El grupo gerencial estableció los siguientescuatro (4) escenarios con base en el modeloprescriptivo propuesto en la etapa anterior:

Escenario I: Representación actual del sistemade producción con su actual distribución enplanta, máquinas y operarios y contemplandoun 3% de producto no conforme o defectuoso yuna tasa de rechazo total del 1%. Este eseenariose usa solo con fines de validación del modelode simulación.

Escenario 2: Propuesta de mejora con cambioen la distribución en planta, retirando 1 máquinafileteadora e ingresando 1 máquina coUarin paraapoyar el flujo de producto en la operación cuellode botella e ingreso de 1 persona adicional parala operación de revisado. Se eontempla como %de producto no conforme o defectuoso del 2%y el rechazo total del producto del 0.5%.

Escenario 3: Propuesta de mejora con cambioen la distribución en planta, se utilizan tiemposde operación de la empresa líder de la región{benchmarking), retiro de 2 fileteadoras eingresando 1 maquina collarín para la operacióncuello de botella, adieionalmente se ingresa 1persona para el revisado. Se contempla como %de producto no conforme o defectuoso del 2%y el rechazo total del producto del 0.5%.

Escenario 4: Propuesta de mejora con cambio enla distribución en planta, retiro de 2 fileteadorasen la operación de pegado de mangas y parala operación de revisión se ingresa 1 personaadicional. Se contempla como % de productono conforme o defectuoso del 2% y el rechazototal del producto del 0.5%.

Los modelos de simulación de eventos discretosy sus escenarios se construyeron basados enlos parámetros de operación que se muestranen la Tabla 7. La validaeión de los modelos de

simulación se hizo comparando la cantidad deblusas producidas (tanto en la simulación delescenario 1 como en el sistema real) medianteel uso de la prueba t según anexo 6 contenidoen Solano (2010).

A partir de una longitud de corrida de 11 díascon un tumo de trabajo en el horario 7 am a 5:30pm y simulando a 27 réplicas, según cálculosobtenidos por Solano (2010), para cada uno delos 4 escenarios se obtuvieron los resultadosmostrados en la Tabla 8.

Para fines de interpretación de los datos de laTabla 8, tener presente que:

El costo unitario de cada blusa es de $ 455(recordar que el eliente coloca materiales,diseños, etc.).

Productividad del factor trabajo = Totalproducción / Total horas trabajadas.

El porcentaje de incremento en unidades serealiza con respecto al total producido real, esdecir, 9478 unidades.

El costo unitario de produeción incluye solomano de obra y gastos generales de fabricación.

Al hacer un comparativo en términos dedesempeño de cada escenario en la Tabla 8 sededuce que el mejor escenario es el 3. Respectoa la pregunta: ¿Cuáles serían las prioridadescompetitivas que se estarían impactandopositivamente con el escenario 3, en pro de lamejora del desempeño del sistema productivo?,tendríamos:

Calidad: con 0,41 unidades rechazadas, quecorresponde menos del 1% de la produccióntotal.

Entrega: obteneión de un ciclo promedio defabricación con un valor de 2,87 minutos porprenda (8 días de plazo de entrega), frentea 3,60 (9) y 5,07 (11) de los escenarios 2 y 4respectivamente.

Costo: se obtuvo un costo unitario según lamano de obra utilizada de $277, frente a $323y $324, de los escenarios 2 y 4 respectivamente.

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Tabla 7. Datos generales empleados en constí^ucción de los modelos de simulación.

Referencia a modelar: Blusa Bebita

Cantidad de la referencia

Máquinas en el módulo real de confección

Tiempo real de la prenda

Numero de operarios sistema actual

Periodo de fabricación

Diagrama de flujo del producto.

Locaciones de proeesamiento y almaeenaje

Secuencias de enrutamiento para eada entidad

Tipos de materia prima (entidades) necesarias para la fabricaeión.

Horario de trabajo y deseansos del personal

Tiempos requeridos por eada entidad.

Tiempos relaeionados eon los alistamientos en las máquinas

Infonnación de unidades defectuosas para el sistema en general

Numero de replieas

9478 unidades en 10 colores

12 discriminadas así:

7 Filctcadoras

2 Collarín

2 Planas

I Cerradora de Codo

I Estación de Revisión

4.15 MIN

13

Die 1 a die al I I de 2010

Ver Tesis de Maestría Solano (2010)

Ver Tesis de Maestría Solano (2010)

Ver Tesis de Maestría Solano (2010)

Ver Tesis de Maestría Solano (2010)

7:OOA.M-5:3OPM

15 MIN de descanso.

30 MIN de almuerzo

Ver Tesis de Maestría Solano (2010)

Fileteadora: 1.5 MIN

Collarín: 1.5 MIN

Plana: 1 MÍN

Cerradora de Codo: 2 MlN

3 % de producto no conforme y 1%rechazado

27 (Ver Tesis de Maestría Solano (2010))

Tabta 8. Desempeño del sistema de producción para 4 escenarios simulados.

ParámetrosEscenario r- • -. Escenario Eseenario

I Escenario 2 ~ .

Día en que termina la produeeión

Produeción total (unidades)

Producción promedio por día (unidades)

Ciclo total promedio (minutos)

Productividad del faetor trabajo (blusas) / (hora)

Tiempo promedio en el sistema (horas)

Tasa de rechazo promedio (%)

Costo unitario

Cumplimiento de la meta de producción (%)

Porcentaje de incremento en unidades

Faeturación de la producción adicional ($ 455 x unidad)

II

9,990

768.52

6.91

6.65

89.67

0.25

384.7

76.85

5.40 %

9

13,793

1,045.42

3.60

9.18

80.63

0.67

323.67

104.54

45.52%

8

14,994

1,153

2.87

9.98

74.58

0.41

277.0

115,3

58.20%

II

10.804

831.11

5.07

7.19

89.09

0.32

324.72

83.11

14%

S232,960 Sl,963,325 $2,509,780 $603,330

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En el escenario 3 el total de producción logradacon base en los cambios de distribución enplanta y adopción de tiempos de operación deuna empresa líder de la región es de 14.494unidades, las cuales se terminan de fabricar eldía 8 a las 4:18 p.m. Esta reducción significativadel plazo de fabricación se debió a que eneste escenario se separaron las operaeionesdel producto en dos, es decir, operaciones deiniciación y de ensamble, en la primera etapa, yen la segunda etapa se involucran operaciones demayor rendimiento, que para el caso de la blusa"Bebita" son las operaciones de pegar,' cerrar ydobladillar, las cuales se realizan en locacionesque desarrollan alta velocidad, logrando así unmejor fiujo del material.

Igualmente en este escenario, con base en losresultados de tasas de utilización de centros detrabajo, se da el mayor porcentaje (promedio68%) de utilización en: collarín 3, revisado1, 2 y fileteadora 3 y 4, donde se realizan lasoperaeiones de: dobladillo, inspeeeión 1 y 2,cerrar lados, respectivamente. Adieionalmentese encuentran 4 locaciones que presentan unvalor promedio del 31% de utilización, lascuales son: cerradora de codo, collarín 1 y 2,plana 1, donde se realizan las operaciones de:pegar cinta al cuello, sesgar manga, pegarsesgo al euello y por último zureir mangas.Igualmente este escenario da la mejor tasa deproductividad del factor trabajo: 9,98 blusas/hora y un incremento en unidades producidascercano al 58%.

Finalmente la valoración de los impactos en elIndicador de Efectividad (IE) de la empresa,se realizó nuevamente revisando todas lasprioridades y dimensiones. Este procesofue ejecutado por la Gerencia General dela empresa objeto de estudio con el apoyode la eseala de Saaty (ver anexo 1 en Solano(2010)). En la tabla 9 se presenta la proyecciónde impactos en las prioridades competitivas.De acuerdo a los resultados obtenidos en laTabla 9, se puede visualizar que el Indicadorde Efectividad de la empresa pasó de un valorde 2,12 a un valor de 2,32 lo que representa unincremento del 10%. Aunque el incremento delIE para la empresa es bajo, este resultado no sepuede despreciar. Además de implementar el

escenario 3 en el sistema real , el IE se puedeseguir mejorando si la empresa empieza atrabajar no solo en las prioridades que alcanzóun aumento, sino también en las palancas defabricación en donde necesita enfocar susesfiierzos: implementar un sistema de calidad,reducción de tiempos de operaeión, mejorar laprogramación de materiales y eapacidad conla ayuda de herramientas informáticas como elMRP y CRP, las cuales constituyen un soporte alproceso de toma de decisiones para programarla producción y evitar realizar los montajes depedidos empíricamente.

4. Conclusiones

La identificación de las prioridades competitivasque el mercado objetivo exige a las Pymes de laeonfeeción debe ser el punto de partida para queestas definan una estrategia coherente e integralde mejoramiento de sus sistemas de producción.Coherente en el sentido que cualquier acciónde mejoramiento que emprendan conlleve allogro de metas que satisfagan las necesidadesde su mercado objetivo, sea este naeional ointernacional, e integral desde el punto devista de evitar obtener solo mejoras loeales opareiales.

Luego de tener elaro cuáles son las prioridadescompetitivas, se debe establecer el nivel dedesempeño de la organización frente a losclientes y fi^ente a sus eompetidores, mediantela medición del indicador de efectividad (IE)propuesto, el cual constituye un aporte esencialpara la identificación de las acciones que sedeben adoptar para el mejoramiento del sistemaproductivo, con el fin de mejorar la posicióncompetitiva en el mereado objetivo.

Según el grupo de expertos consultado, paraque la Pyme de la confección estudiada puedamantenerse en altos niveles de desempeñofi-ente a su mercado objetivo, debe mejorarsimultáneamente en las prioridades competitivas:calidad, costo y entrega, las cuales alcanzan acubrir hasta un 80% de la importancia relativa.Se requiere específicamente mejoras en lasdimensiones: calidad de concordancia, costo demaquilar y plazo en la entrega.

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Tabla 9. Nueva valoración del indicador de efectividad (IE) de la Pyme 1.

Factores ycomponentesen orden deimportancia

Pesoentre

factoresCjk Dimensiones

Peso entre Calificación Calificacióndimensiones Inicial proyectada

CALIDAD

I-NTRIÎGA

COSTO

PLIÎXIBIL1DAD

ASISTIÎNCIATKCNICA

0.36

0.27

0.20

0.09

0.08

C21

C22

• C 2 3

C3I

C32

C33

CU

C4I

C42

C43

C44

C5I

Calidad de Concordancia

Posibilidad de Rechazo yreelamaciones

Fiabiiidad en la entrega

Plazo de entrega

Tiempo de respuesta a uncliente que pide información

Tiempo de respuesta a uncliente que pide una cotización

Sin componentes

En el tamaño del lote

Ante eambios de imprevistos

Del portafolio de familias deproductos

Del portafolio de tejidos

Sin eomponentes

INDICADOR DE EFECTIVIDAD

0.35

0.14

0.51

0.32

0.16

0.52

1.00

0.46

0.15

0.18

0.21

1.00

3.33

5

4

3

3

4

3

4

4

3

4

3

2.12

3.67-

5

4

4

3

4

4

4

4

4

4

3

2.32

El análisis de las empresas objeto de estudio,desde la óptica P-S-P, demuestra que no haycoherencia estructural entre las exigenciasdel mercado, el sistema de produeeiónadoptado y la organización de las palancas defabricación. Dicha situación refleja la ausenciade un enfoque estratégico para la manufacturaen las empresas de eonfección estudiadas;seguramente un estudio en las demás funeionesgerenciales podría reflejar resultados similares.El estudio de cada una de ellas pemiite observaren algunos casos la adopción o la aproximacióna buenas prácticas de producción; sin embargo,no es una situación constante a nivel del sector,pues mediciones efectuadas a través de unindicador de Efectividad muestran Pymes condesempeños medio bajos y bajos.

Experimentar soluciones de mejoramientodirectamente en los sistemas físicos detransformación (SFTs), es costoso, demandaalto consumo de tiempo y específicamente parauna Pyme, cuyos reeursos son muy limitados,le resulta imposible servir de laboratorio deexperimentación, dejando de lado su operacióneconómica. Los aportes teóricos consultados

apuntan a que en los últimos años, se ha dadoun buen desarrollo en el diseño/ejeeuciónde experimentos empleando simulacióncomputarizada, con ventajas muy superioresen términos de costo y tiempo, respecto a laexperimentación física.

S. Bibliografía

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Castellanos, O., Jimenez, C , Sinitsyn, A.,Montañez, & V M., Sinitsyn O. A. (2006).Análisis del desarrollo tecnológico en laaplicación de enzimas en la industria textil.Ingeniería y Competitividad, 8 (1), p. 37-46.

CINTEX, Centro de Investigación e InnovaciónTextil. (2009). Caso de Innovación. SectorTextil, Diseño y Confecciones. http://www.forossemana.com/doc/Doc-1894 20091127.pdf

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Domínguez M, J. A., Alvarez G, M. J.,Domínguez M, M. A., Garcia G, S. & Ruiz J,A. (1995). Dirección de Operaciones. Aspectostácticos y operativos en la producción y losservicios. Editorial Mc-Graw Hill, Madrid

Gaither, N. & Fraizer, G. (2000). Administraciónde la Producción. 8" Edición. ThompsonEditores: México. D.F.

Giraldo G, J. A. (2008). Metodologíasoportada en simulación para el mejoramientode sistemas de. producción. Aplicaciones enPymes metalmecánicas. Tesis de Doctorado.Doctorado en Ingeniería. Universidad Nacionalde Colombia.

Giraldo G, J. A., Sarache C, W.A., & CastrillónG, O. D. (2010). Metodología integral soportadaen simulación para el mejoramiento de sistemasde producción Job Shop. Aplicaciones en pymesmetalmecánicas. Ingeniería e Investigación.Vol. 30. No. I .P97 .

Ibarra M, S. (2003). Modelo y procedimientospara el análisis y proyección competitivade Unidades Estratégicas de Fabricaciónen empresas manufactureras cubanas. TesisDoctoral Universidad Central "Marta Abreu" deLas Villas. Santa Clara, Cuba.

Ibarra M, S. & Sarache C, W. A. (2008).Gestión de la Producción: Una AproximaciónConceptual. Colectivo de Autores. 1". Edición.Editorial. Universidad Nacional de Colombia. .

INEXMODA. El Sector Textil y de la ConfecciónColombiano. http ://www. inexmoda. org. co/TextilConfecci%C3%B3n/ElsectorTextilydelaConfecci%C3%B3nColombiano/tabid/280/Default.aspx

Krajewski, L., Ritzman, L. P., & Malhotra, M.K. (2008). Administración de Operaciones:Procesos y Cadenas de valor. 8 Edición.Pearson Educación. México.

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Pérez-Castaño, B. J. (2007). Competitividad,desarrollo e ingeniería: algunas definiciones y

reflexiones. En: Ingeniería y Competitividad,Vol. 9 NM, p. 84-91.

PROEXPORT. (2009). Invierta en Colombia.Trabajo, Compromiso, Ingenio. Industria Textily Confecciones. Septiembre. http://www.inviertaencolombia.com.co/.../textil.html

Sarache C, W. A. (2003). Modelo con EnfoqueEstratégico y Procedimientos para Contribuiral incremento del nivel de desempeño de lasPymes de confección desde la función deproducción. Aplicaciones en la Región delTolima, Colombia. Tesis de Doctorado enCiencias Técnicas. Universidad Central "MartaAbreu"de las Villas. Cuba.

Sarache C, W. A., Marrero D. F., & HernándezP. G. (2004). Objetivos de la función deoperaciones. Aportes a la industria de laconfección colombiana. Revista UniversidadEAFIT Vol. 40. No. 133. P 35 - 46.

Sarache Castro W. A., Cárdenas D., & GiraldoGarcía J. A. (2005). Procedimiento para ladefinición y jerarquización de prioridadescompetitivas de fabricación. Aplicaciones en laspymes de la industria metalmecánica. RevistaIngeniería y Competitividad, Vol. 7 # 2, pp.: 84-91

Sarache C, W. A., Cárdenas A, D. M., GiraldoG, J. A., & Parra S, J. H. (2007). Procedimientopara evaluar la estrategia de manufactura:Aplicaciones en la industria Metalmecánica.Cuadernos de Administración. No.033. (Ene. -Jun.)p.lO3-123.

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en una empresa perteneciente a la industTia dela eonfección mediante simulación de eventosdiscretos. Tesis de Maestría en Ingeniería, Áreade Énfasis: Ingeniería Industrial, Facultad deingeniería - Universidad del Valle, Santiago deCali, Colombia.

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Business Communication Quarterly75(3) 301 –317

© 2012 by the Association for Business Communication

Reprints and permission: http://www. sagepub.com/journalsPermissions.nav

DOI: 10.1177/1080569912450312http://bcq.sagepub.com

450312 BCQ75310.1177/1080569912450312Sigmar et al.Business Communication Quarterly

1Sam Houston State University, USA

Corresponding Author:Lucia Stretcher Sigmar, Department of General Business and Finance, Sam Houston State University, Box 2056, Huntsville, TX 77340, USA Email: [email protected]

Strategies for Teaching Social and Emotional Intelligence in Business Communication

Lucia Stretcher Sigmar1, Geraldine E. Hynes1, and Kathy L. Hill1

Abstract

Incorporating social and emotional skills (EI) training into the business communication curriculum is important for preparing students to function effectively in a global workplace with its complex informal networks, intercultural issues, team emphasis, and participatory leadership. EI skills enhance communication behavior in work groups and improve the quality of student responses to various business scenarios. Scientific research indicates that modeling social and emotional behavior is key to acquiring competency in these skills. This article describes four classroom strategies for developing EI skills in business communication courses.

Keywords

interpersonal communication, nonverbal communication, teamwork, experiential learning, group dynamics, social and emotional skills

Introduction

Business schools recognize the importance of interpersonal skills development in preparing students to enter a job market where teams are the primary work unit (Yost & Tucker, 2000). Student teams also gain valuable experience in working toward a common goal and gain satisfaction in contributing to the performance and product of the group (Webb, 1995). Evidence shows that such cooperation promotes frequent use

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of higher level reasoning strategies, higher achievement, and more accurate perspec-tive than do competitive or individualistic efforts. These cooperative learning experi-ences also result in students’ being more mature in their cognitive and moral decision making and in considering the viewpoints of others when making decisions (Clarke, 2010; Johnson & Johnson, 2004). In addition to providing opportunities for students to gain new knowledge and abilities, team collaboration develops intrapersonal and interpersonal skills (known interchangeably in the literature as emotional intelligence [EI] or emotional quotient), which are necessary competencies for working effectively with others.

But why do so many of our students seem to have difficulty collaborating on tasks and engaging with business scenarios that simulate what they will encounter in the workplace? Such collaboration demands the development of sophisticated social and emotional skills (Lopes & Salovey, 2004), and yet it is precisely in this area of skills development that our students are lacking.

Social and emotional skills may be a more accurate predictor of personal and pro-fessional success than cognitive knowledge (Covey, 1996; Goleman, 1998b, 1998c), and developing these skills is critical to our business students’ career success. Although pedagogical approaches to teaching EI are plentiful in the literature, several neurologi-cal (Edelman, 1987; Zull, 2002) and scientific inquiries into mirror neuron theory may provide educators a new pedagogical basis for teaching these skills (Gallese, Fadiga, Fogassi, & Rizzolatti, 1996; Iacoboni, 2009; Rizzolati, Fadiga, Gallese, & Fogassi, 1996; Rizzolatti, Fogassi, & Gallese, 2006; Tettamanti et al., 2005). This article sug-gests that these skills may be “deep learned” (Zull, 2002) by active participation in social groups and offers four team-based, experiential learning strategies for teaching essential social and emotional skills in business communication courses.

Emotional Intelligence: Theoretical BackgroundResearchers have long recognized a form of intellect beyond the cognitive. Harkening back to Thorndike’s (1920) initial concept of social intelligence and based on Gardner’s (1983) notion of multiple intelligences, the term emotional intelligence was first used by Salovey and Mayer (1990), who defined the concept as a type of intel-ligence in their seminal article on the subject. Unlike Gardner (1983), however, who emphasized the cognitive dimension of these multiple (“personal”) intelligences, Salovey and Mayer were more interested in the role of emotion in these intelligences. The term emotional intelligence has been most recently popularized by Daniel Goleman’s (1995) landmark book, which sparked much critical inquiry with its per-sonal, professional, and scientific implications.

Theoretical approaches to EI are generally divided into four models: specific ability, integrative, trait, and mixed (Mayer, Roberts, & Barsade, 2008). While the specific ability model focuses on a particular EI skill, the integrative approach focuses on integrating specific abilities into a global perception of EI, such as

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Salovey and Mayer’s (1997) Four-Branch approach, which views EI as a “[cogni-tive] ability to perceive accurately, appraise, and express emotions; the ability to access and/or generate feelings when they facilitate thought; the ability to under-stand emotional knowledge; and the ability to regulate emotions to promote emo-tional and intellectual growth” (p. 10). In addition, Petrides and Furnham’s (2001) trait model concerns self-perception of EI and has more to do with personality than ability. Finally, the broader, mixed models like those of Bar-On (2000) or Goleman (1995) relate “an array of non-cognitive skills, capabilities, and competencies that influence a person’s ability to cope with environmental demands and pressures” (Martinez, 1997, p. 72).

Of these approaches, the mixed-model approach provides a comprehensive plat-form for social and emotional skills development. Goleman’s (1995) five competen-cies of EI are generally accepted as the starting point for discussion and include the ability to become self-aware in managing emotions and controlling impulses, set goals and perform well, be motivated and creative, empathize with others, handle relation-ships effectively, and develop appropriate social skills. Mastery of these competencies greatly affects the way an individual perceives and reacts to internal and external events. This article presents four team-based, experiential learning strategies for teach-ing social and emotional skills in business communication courses following the mixed-model approach and addressing Goleman’s five competencies.

Emotional Intelligence in the WorkplaceOver the past quarter of a century, the expansion of the global marketplace, rapidly changing technologies, and workplace diversity with an increased emphasis on teams have created a demand for emotionally intelligent employees. As a result, emotion management in the workplace has become a popular topic of critical inquiry among organizational behaviorists (Glynn, 1996; Hochschild, 1983; Rafaeli & Sutton, 1989; Van Maanen & Kunda, 1989). Such interest increased significantly with the publica-tion of Fineman’s (1993) Emotions in Organizations and Weiss and Cropanzano’s (1996) “Affective Events Theory.” More recently, a number of studies indicate that EI-skilled people positively influence management/strategic processes (Huy, 2002; Samra-Fredericks, 2004; Zorn, 2001).

Although some professional development specialists have created and successfully marketed EI-specific courses for business and industry over the last decade, EI train-ing may be best accomplished “on the job” (Clarke, 2004; Van der Sluiss, Williams, & Hoeksema, 2002), with skill development occurring through leadership or partici-pation in teams, projects, or assignments (Baron et al., 1999; Blumenfield, Soloway, Marx, Krajcik, & Palincsar, 1991; Evered & Selman, 2001; Vince, 2004). Such EI competencies can translate into tangible workplace benefits such as higher perfor-mance evaluations and increases in merit pay and rank (Lopes, Grewal, Kadis, Gall, & Salovey, 2006).

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Scientific Support of Emotional Intelligence Theory

Although the majority of research supports EI theory, criticism rises generally from the social sciences. Theorists maintain that EI has no objective quantity on which it can be based (Eysenck, 2000; Locke, 2005; Roberts, Zeidner, & Matthews, 2001). Some researchers, while applauding test validity of the specific ability and integrative models, have questioned the mixed model, saying it has no valid assessment protocols (Mayer et al., 2008). Others have questioned whether EI can predict personal and professional success at all (Antonakis, 2003; Antonakis, Ashkanasy, & Dasborough, 2009; Landy, 2005) and have called into question “self-reporting” measures (Conte, 2005). Moreover, despite the plethora of EI testing measures over the years, some critics argue that actual ability is not measured at all; rather, these tests “measure” conformity (Roberts et al., 2001) or knowledge (Brody, 2004)—not actual behavior.

On the other hand, evidence from the neurological sciences suggests that social and emotional intelligence is not only supported by research but also has a physiological basis. Social and emotional intelligence can be observed and measured using neuro-imaging—and can perhaps offer educators insight into how these skills are learned and how these skills should be taught. Electrophysiological studies (Cochin, Barthelemy, Roux, & Martineau, 1999; Fadiga, Fogassi, Pavesi, & Rizzolatti, 1995; Gangitano, Mottaghy, & Pascual-Leone, 2001; Hari, Forss, Avikainen, Kirveskari, & Rizzolatti, 1998) and imaging data (Rizzolattiet al., 1996) indicate that a mirror-neuron system exists in humans (Rizzolati et al., 2006). This system allows subjects to perform move-ments without thinking about it; furthermore, when subjects observe the movements of others, they comprehend those actions without “explicit reasoning” (Rizzolatti et al., 2006, p. 56). This research suggests that a social and emotional brain system is necessary for interacting and relating to other people. We learn first by observing and imitating actions and simultaneously internalizing that experience. This enables these neural networks to provide us the ability to understand and to predict actions and com-plex intentions. In the process, we initiate empathetic emotional responses and an awareness of others. These brain responses to subtleties in movement are the founda-tion for social and emotional intelligence and learning.

Furthermore, proficiency in language usage (verbalizing emotions and articulating actions) is equally important in social and emotional skills competency. Tettamanti et al. (2005) and others found that in addition to being activated by action observation or by hearing action sounds, this same observation-execution system also engages dur-ing the cognitive processing of sentences that describe actions. Researchers have known that putting feelings into words in verbal or written form can attenuate negative emotional experiences (Wilson & Schroeder, 1991), and neuro-imaging studies indi-cate a possible cognitive pathway when affect labeling alleviates negative emotional responses. Data from these studies show that emotional word usage has a demonstra-ble, physical effect on the brain (Lieberman et al., 2007). These findings suggest that the development of a comprehensive emotional vocabulary is fundamental in developing social and emotional intelligence. This vocabulary is important for raising emotional

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self-awareness in oneself and for articulating the feelings of others (Carkhuff, 1993) and is an important aspect in developing empathy.

Social and Emotional Skills in Student Team BuildingTeaching students an emotional vocabulary, identifying and modeling appropriate behavior, mirroring these behaviors, and encouraging higher levels of critical thinking and reflection (challenging or testing assumptions) are essential in the development of EI. As the science indicates, these skills are not learned in isolation.

Edelman (1987) and Zull (2002) observe that social structures like teams allow the exchange and development of emotions and that in the process, neural connections and EI are strengthened, with reciprocity in how these skills are learned: Interaction between team members may facilitate and reinforce emotional and social skills learn-ing (Moriarty & Buckley, 2003), while conversely, emotional and social skills devel-opment may facilitate team-building efforts (Welch, 2003). Other research suggests that highly emotionally intelligent teams are more successful, specifically with higher problem-solving abilities, better performance, and better grades (Druskat & Wolff, 2001; Yost & Tucker, 2000), and emotionally skilled team leaders facilitate better responses from their members (Antonakis et al., 2009; Ashkanasy & Tse, 2000; George, 2000).

Emotional Intelligence PedagogyMany business schools, recognizing the value of team-building skills training, have already implemented such programs for their students (Greenan, Humphreys, & McIlveen, 1997; McGraw & Tidwell, 2001; Mills, Myers, & Rachael, 1991; Moriarity & Buckley, 2003; Thomas & Busby, 2003) or have incorporated EI into their curri-cula in various ways: lecture learning groups (Cockburn-Wootten & Cockburn, 2011), MSCEIT (Mayer–Salovey–Caruso Emotional Intelligence Test) or EISDI (Emotional Intelligence Self-Description Inventory) testing to increase EI awareness (Ashkanasy & Dasborough, 2003; Groves, McEnrue, & Shen, 2008), and self-assessment, journal-ing, role-play, interview, and case analysis (Myers & Tucker, 2005). Other research-ers have suggested the use of games to facilitate social and emotional learning (Hromek & Roffey, 2009).

Many educators agree that information should not be conveyed solely in lecture format and that emotional skills should be taught in an emotional and experiential con-text (Dwyer, 2001; Kremer & McGuiness, 1998). To that end, universities have encour-aged service learning and academic civic engagement (Helm-Stevens & Griego, 2009). Some practitioners urge the use of a team approach to teach interpersonal skills in order to produce a final acceptable product or to attain a predetermined goal (McGrew & Lewis, 1998). Cockburn-Wooten and Cockburn (2011) advocate a collaborative, “learning-by-doing” approach to “reflect and analyze management communication in relation to complexities, failures, context, power, and assumptions, . . . issues

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and tensions around managing relationships, and business communication”(p. 52). Still others see student internships as suitable training ground for learning conflict manage-ment and other interpersonal skills (Stitts, 2006). And because more businesses are using teams at hierarchical levels, educational institutions are also recognizing the need to prepare students for real-world group decision making and functioning within the team structure (Kaplan & Welker, 2001). Boyle and Strong (2006), for example, have proposed a list of key skills (including interpersonal and team-building skills) for enter-prise resource planning. Business schools that already have enterprise resource plan-ning programs can use the list to determine how well they meet industry needs.

Neurological research has indicated that humans develop EI in stages: first, by developing self-awareness in recognizing their own thoughts and feelings toward peo-ple and situations; then moving toward understanding individuals and groups and the subtleties at play in social groups; and then using this information to induce preferred responses in others. If, as the research indicates, effective social and emotional skills are primarily learned through modeling appropriate behavior and social interaction, experiential team building may be the best means of teaching these skills to students.

Student participation in experiential teams provides an opportunity for “active” as opposed to “passive” learning (Cockburn-Wootten & Cockburn, 2011) and for the exchange and development of emotional knowledge. Team-based learning creates stronger relational bonds that facilitate thinking (Clarke, 2010; Moriarty & Buckley, 2003). In addition, within simulated “workplace” groups, students can identify more readily with business scenarios, and by participating in joint problem solving through dialogue and reflection, they can directly experience emotional learning unconsciously and intuitively.

Experiential Teaching Strategies for Business CommunicationThe following sections describe four classroom activities that the authors have used to develop students’ social and emotional skills in the business communication course. As a whole, these exercises roughly follow the stages of EI development (self-awareness in recognizing thoughts and feelings of self and others, understanding oth-ers and the subtleties of social groups, and using information to induce preferred responses). These strategies also stimulate the neural pathways that are fundamental for interacting and relating to other people. By developing an emotional vocabulary and observing and modeling behavior, students can begin the process of “deep learn-ing” Goleman’s (1995) five competencies: self-awareness, goal setting and perfor-mance, motivation and creativity, empathy, handling relationships effectively, and developing and improving social and emotional skills.

Matrix ExerciseAn extensive emotional vocabulary is fundamental to the development of EI. The use of affective language has a physical effect on the brain and can alleviate negative

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emotions (Lieberman et al., 2007), an important skill in management communication, specifically supervisory confrontation. These words are important not only for com-municating on an emotional level with others (i.e., articulating the feelings of others) but also for raising emotional self-awareness (Carkhuff, 1993). Students, however, rarely appreciate the value of having an emotional vocabulary as an interpersonal skill.

A modification of the Emotional Matrix (see the appendix), attributed to Julia West (Bradberry & Greaves, 2009, p. 15), can impress on students the importance of devel-oping their vocabularies by showing them what they lack. Students are given 10 min-utes to complete the blank matrix with high-intensity, medium-intensity, and low-intensity descriptors (three per box) for each of the primary emotions. Descriptors for “happy,” for example, may range from ecstatic (high) to delighted (medium) to glad (low). Students generally have some difficulty in completing the matrix in the time period and struggle with articulating the subtle differences in emotional intensity. They quickly realize that they are underequipped for identifying their own emotions—much less the emotions of others—and recognize the need to develop their emotional vocabularies as a fundamental skill set in the development of empathy. Next, students play Emotion Charades, enacting an emotion pulled at random from a box (e.g., “out-raged”) and identifying the appropriate emotion/intensity level (“angry,” high inten-sity), thus raising emotional self-awareness in themselves (as the actor) and in relating to others (in interpreting emotions). Prizes increase participation and listening/observing skills.

EI debriefing:

1. Was completing the emotional matrix difficult for you? If yes, why? Name some ways you can increase your emotional vocabulary.

2. How effectively did you enact an emotion in Emotion Charades? What non-verbal cues did you give the audience? What nonverbal cues might have conveyed the emotion more quickly or more effectively?

3. Why is an extensive emotional vocabulary important in management communication?

Magic CarpetThis exercise stimulates relational bonds that facilitate thinking. A simple activity using a plastic shower curtain enhances students’ group problem-solving skills through dialogue, reflection, and nonverbal communication.

Preceding the exercise, the instructor introduces the concepts of task function and maintenance function in group problem-solving discussions. Briefly, the task function is performed by team members who are concerned with accomplishing the team’s stated task. Communication includes direction giving, information seeking, informa-tion giving, elaborating, coordinating, enforcing, and summarizing. Team members concerned with the maintenance function are sensitive to relationships among the team members. Communication includes supporting, harmonizing, tension relieving, ener-gizing, encouraging, and facilitating (Whetten & Cameron, 1998). Before the activity,

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the instructor points out the value of both functions for effective group problem solving.

Next, the instructor initiates the activity: The instructor spreads a plastic shower curtain on the floor. The instructor asks for volunteers to stand on the shower curtain. Students who decline to volunteer are assigned to be observers. Ideally, between 12 and 18 students come forward. They typically try to stand as far apart as possible, avoiding touching each other.

The instructor tells this story:

You are standing on a magic carpet, flying high above the clouds. Suddenly you realize that you are headed in the wrong direction! In order to reverse course you must flip over the magic carpet. Naturally, anyone who steps off the carpet will fall to his or her death. Your task is to turn the carpet upside down. Everyone must remain standing on it with at least one foot at all times.

The instructor asks observers to listen closely to the students as they work together to flip the shower curtain while standing on it. The observers are reminded to note who the task function people are and whose contributions are primarily directed to main-taining the group relations.

Students usually begin to solve the task by folding over one side of the shower curtain and crowding together on the other end. After realizing that the size of their magic carpet has decreased alarmingly, they abandon that strategy. The team mood proceeds from silliness, with lots of self-conscious laughter, to determination, and then to frustration as they struggle. Occasionally, a student “sacrifices” for the sake of the group and steps off. Ultimately, someone realizes that twisting the shower curtain from a corner allows the team to move from one side to the other without diminishing its total size. It may take 5 to 30 minutes for the solution to occur to the group.

During the debriefing, observers point out the task leaders and the maintenance leaders, giving examples of statements that the participants uttered for each function and their effect. The instructor finishes with a discussion about the contributions of each communication function.

EI debriefing:

1. Who were the task leaders and the maintenance leaders? How do you know? Give examples of statements for each function.

2. How did each of these functions contribute to the team’s solution?3. What were the failures, issues, and tensions you experienced and how did

these affect your result?4. What did you learn about yourself and about team dynamics that you will be

able to apply in the workplace?

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Corporate Blindfold

This team-building exercise also enhances group problem-solving skills and verbal and nonverbal communication and illustrates communication issues in tall manage-ment hierarchies. Preceding the exercise the instructor introduces formal and informal organizational communication strategies and discusses the trend toward flattened management hierarchies that result in more efficient groups or teams.

The instructor then announces the formation of a company in which the instructor is the CEO. The CEO appoints a “president” who will be his or her direct “report” during the exercise; the remainder of the class serves variously as upper-, mid- and lower-level employees. Students are then instructed to line up behind the president (students who may have supervisory jobs are asked to go to the end of the line to get the most out of the experience). After putting on their blindfolds, the students link hands. The instructor asks everyone to avoid speaking to each other during the exer-cise so that the president (also blindfolded) can hear instructions from the CEO. Guided only by the CEO’s voice, the president begins to take the company forward through “difficult times.” Students, initially uncertain of the direction and people around them, shuffle quietly and slowly at first.

As the president becomes accustomed to following the CEO’s voice, the pace quickens, and the group threads out of the classroom and into the hallways, through doorways, and around obstacles. Students sometimes blunder into walls, door jambs, lounge chairs, or trash cans if the direction they receive from their “supervisors” (the person in front of them) is unclear. However, nonverbal communication in the form of hand squeezing and positioning, or proxemics, usually assists students in determining the direction the company is heading. Invariably, students at the middle and lower levels of the company, unable to hear the CEO’s directions to the president, began to initiate grapevine discussion: “Are you still there?” “Are you OK?” “I can’t see a thing.” “Do you have any idea where we are?” The grapevine is irrepressible and soon moves up and down the organization, and most students forget the instructor’s earlier request to avoid speaking. Occasionally, the CEO will fall silent, causing the entire company to either slow down or stop completely. In response, the grapevine usually begins to speculate loudly on the direction the company is heading.

If the company is moving too quickly, some employees become stretched in their efforts to hold their sections together; sometimes sections of the organization will break off from the company entirely—unless the CEO intervenes to reconnect them. Eventually, the CEO leads the company back to the classroom where the blindfolds are removed and the debriefing begins.

Students are encouraged to draw parallels between their experience and what they might encounter in a real corporation or business scenario: the power of nonverbal communication, the reciprocity of formal and informal networks, the difficulties of communicating quickly and efficiently in tall organizational structures (this usually

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results in an “aha” moment as students grasp the benefits of work groups and teams), and the problems that occur with a lack of, or inaccurate, communication or relation-ship issues in the group. Students at the bottom of the corporation (end of the line) usually have the most difficult time during the exercise since they cannot hear the CEO and are dependent on the person immediately in front of them for any direction at all (after this exercise, real-life supervisors tend to empathize more with employees who may be in lower level positions). This exercise also contributes greatly to creating group cohesiveness in the classroom.

EI debriefing:

1. On whom did you depend for information and direction? Who depended on you?

2. In what ways was this information communicated to you? How did you com-municate this information to others?

3. You were told not to talk during this exercise. Did you follow that directive? How is your reaction similar to the grapevine in organizations?

4. What is the ideal state between the grapevine and formal communication in an organization?

5. Depending on where you were in line, what difficulties in communication did you encounter? How did you overcome those difficulties?

Xion (Adapted From Gochenour, 1993)This role-play activity exposes students to the complexities of intercultural communi-cation. It challenges their assumptions and exposes them to issues of power, failure, and context as they learn conflict management and reflect on ways to induce preferred responses in others. These issues are core to EI.

For this activity:

• Two groups of three are needed to run the simulation.• One team is made up of two women and one man (the Xions from

Country X).• The other team is made up of two men and one woman (the Journalists).• Xions and Journalists meet by chance in a restaurant in Greece.• Journalists try to get permission from Xions to go to the annual Queen’s Gar-

den Festival, take photos, and write a magazine article.

Country X is a matriarchal society. Men keep house, cook, and care for the chil-dren. In all respects, women are viewed by the Xion culture as being superior to men. This belief is reinforced by individual attitudes and institutionalized beliefs, norms, and structures. Marriage is between two women, forming “the Bond.” The Bond then may jointly receive a man to their household for the purposes of having children, tend-ing the home, and so on. The man is protected and “cherished” by the Bond.

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The Xions value art and nature and celebrate the Queen’s Garden Festival each year. No outsiders have ever attended the festival although there is no law against it.

During the simulation, Xions must limit their vocabulary to words of only one or two syllables when speaking with the Journalists. Xions must also avoid making pro-longed eye contact. Staring is impolite and is considered aggressive.

The Journalists join the Xions at their table in the restaurant and try to converse with them. After 15 minutes, they excuse themselves to discuss the best way to approach their objective: receiving permission to attend the Queen’s Garden Festival.

The Xions will grant the Journalists permission to attend the Festival only if they meet all of the following criteria:

1. The female Journalist must ask for permission, and she must ask the Bond, not the Cherished Man.

2. The Journalists must be considerate about the English language limitations and try to use words and pacing that Xions can understand.

3. Journalists must show sensitivity to Xion customs regarding eye contact.

The Journalists typically have difficulty with the conversation at the table since the Xions only answer in one or two syllables. The Xions have difficulty answering with only one or two syllables and not making eye contact. The Journalists get frustrated because the Xions will only briefly make eye contact and won’t really “talk” to them. They then try to start a conversation with the Cherished Man, who cannot talk to them without permission from the Bond.

Moreover, when the Xions and Journalists notice cultural differences, they may interpret those behaviors through the lenses of their own culture, and they often get so engaged in the details of the task that they forget about how important relationships are to accomplishing that task.

EI debriefing:

1. What cultural differences were blatantly visible? Which ones only became apparent later?

2. How did the two cultures display emotions and power differently? What effect did this have on the communication?

3. How did you adjust your perspective so that you understood and valued others?

4. How did you induce preferred responses in others?5. What did the Xion role-play teach you that will help you in the global

workplace?

ConclusionAs this article’s review of the academic and scientific research indicates, experiencing and modeling social and emotional behavior are essential in learning EI. To develop

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312 Business Communication Quarterly 75(3)

the neural pathways, experiential learning and simulation exercises, including role-play and group activities, such as the four described in this article, are essential. This article adds value to the literature because it presents concrete examples of how we as business communication instructors can build our students’ self-awareness and sensi-tivity to the impact of an individual’s verbal and nonverbal behavior.

Incorporating EI into the business communication curriculum is an important step in preparing our students to function effectively in a global workplace with its com-plex informal networks, teams, and participatory leadership, where they must con-stantly learn new skills and adapt quickly to changing technology (Lopes & Salovey, 2004) and where mastery of interpersonal and group skills is needed in order to inter-act effectively with others (Johnson, 2003; Johnson & Johnson, 2003; Muir & Davis, 2004). Awareness of EI strategies enhances students’ communication behavior indi-vidually and in work groups. One student testified after EI training that he has “a better understanding of . . . emotions, optimism, and working positively with others [and enjoyed] . . . the hands-on activities to better understand how to apply [these skills].”

If, as Goleman (1998a) believes, professionally successful people have high EI in addition to the traditional cognitive intelligence or specialized knowledge, we can bet-ter prepare our students by teaching them not only the cognitive knowledge they will need but also the social and emotional skills that will ensure their success.

AppendixEmotional Word Matrix

Intensity

Category High Moderate Low

Happy

Sad

Scared

Angry

Confused

Strong

Weak

SOURCE: Adapted from and reproduced in part by permission from Julia West.

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Sigmar et al. 313

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

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Bios

Lucia Stretcher Sigmar is an assistant professor in the College of Business Administration, Sam Houston State University. She teaches undergraduate courses in business communication and business and professional speaking and is an officer of the Association for Business Communication, Southwest Region.

Geraldine E. Hynes is a professor in the College of Business Administration, Sam Houston State University. She is a past President of the Association for Business Communication and teaches undergraduate and graduate courses in business communication, managerial communi-cation, and business and professional speaking.

Kathy L. Hill is an associate professor in the College of Business Administration, Sam Houston State University. She teaches undergraduate and graduate courses in business com-munication, intercultural business communication, business and professional speaking, and managerial communication.

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THE ROLE OF BUSINESS INTELLIGENCE IN BUSINESS PERFORMANCE MANAGEMENT

Pugna Irina Bogdana

Academia de Studii Economice Facultatea de Contabilitate si Informatica de gestiune Piata Romana nr 6

Bucuresti, [email protected] , tel : 0742483841

Albescu Felicia

Academia de Studii Economice Facultatea de Contabilitate si Informatica de gestiune Piata Romana nr 6 Bucuresti [email protected] tel: 0723581942

Babeanu Delia

Academia de Studii Economice Facultatea de Contabilitate si Informatica de gestiune Piata Romana nr 6 Bucuresti [email protected] tel:0726175137

Business performance management (BPM) is a key business initiative that enables companies to align strategic and

operational objectives with business activities in order to fully manage performance through better informed decision making and action. Effective business performance requires an organization to model and monitor not only its tactics but also its strategies and the assumption on which these strategies are built.

The aim of this paper is to examine the processes, methodologies and technologies underlying BPM, the relation between BPM and business intelligence, and to propose a framework for integrating corporate performance

management and business intelligence in a holistic approach of managing business performance.

Keywords: Business Performance Management (BPM), Business Intelligence (BI), business processes, strategy,

integration Code JEL:M21

Introduction

During the last years, companies have understood the importance of enforcing achievement of the goals defined by

their strategy through metrics-driven management.

Finance organizations have vast technology assets to assist them with day-to-day operations, regulatory

compliance, and financial reporting. Such systems record transactions and manage operational processes, automate

compliance and controls, and roll up financial performance data. To varying degrees, these systems populate data

warehouses (DW) that are exploited by advanced business intelligence (BI) systems. The DW process, though

supporting bottom-up extraction of information from data, fails in top-down enforcing the company strategy. The

missing element — one that finance and IT teams are now pursuing — is the integration of these systems into a

unified source of performance information and analysis capability.

Early adopters of business performance management have focused on making the finance function more strategic –

mainly because people have tended to trust data coming out of a financial system more than other corporate

systems, such as ERP or CRM. Almost every major business function has a performance management element that

can be realized. To enable this requires organizations to put in place the right data platform and source data and

ensure that strategic thinking is driven by the wider needs of the business. Nowadays, organizations of all shapes,

sizes and markets are under pressure to conform to increased regulatory compliance pressures and have a need to

link corporate performance to the decision-making process. BPM can be the right answer – leveraging what you

already have and aligning the various aspects to move in the same direction. It helps organizations translate their

strategies and objectives into plans, monitor performance against those plans, analyze variations between actual

results and planned results, and adjust their objectives and actions in response to this analysis.

In the business literature, performance management has a number of names, including BPM, corporate

performance management (CPM), enterprise performance management (EPM), and strategic enterprise

management (SEM). Although different terms are used, they all mean essentially the same thing. The BPM

Standards Group (2005) has defined BPM as “a framework for organizing, automating, and analyzing business

methodologies, metrics, processes, and systems to drive the overall performance of the enterprise. It helps organizations translate a unified set of objectives into plans, monitor execution, and deliver critical insight to

improve financial and operational performance”.

1. Business information technologies

Business Information Technologies are seen as cutting edge Information Technologies made on purpose to support

business information engineering. Management methods, techniques and support tools could be seamless integrated

with Business Intelligence components in special tailored or customized Performances Management systems. The

main functions of these systems are:

-To gather and store different measures of the business on a regular basis (current state indicators of the business

performances).

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-To gather and store benchmarks and targets (threshold values) and business rules (interpretations of comparison

results between current performance’s indicators and etalon values).

-To facilitate roll-ups and drill-downs of analyzed indicators along hierarchical aggregation criteria (structured

Performance Measurements).

-To keep the ongoing analysis alert - allowing decision makers to quickly evaluate which business processes are

successful, and which need their attention.

To summarize, an effective Business Performance Information System is built and maintained by business users to

support the decision-making process especially at strategic level, making use of various indicators – quantitative

and qualitative, lagging and leading – balanced against targeted objectives and/or industry benchmarks. Lately,

with performance measurement periods becoming shorter, management must have the capability to more

proactively influence the outcome. That requires monitoring and tracking capabilities that can generate current,

complete and accurate information upon which they can act in real time. Business information technologies must

respond to that need of proactively managing business performance.

2. Business intelligence and business performance management

Business performance management (BPM) can be considered as being the final component of business intelligence

– the next phase in the evolution of decision support systems, enterprise information systems and business

intelligence. If BPM is an outgrowth of BI and incorporates many of its technologies, applications and techniques,

than why BI itself can’t deliver the insight needed to improve overall business performance? From a theoretical

viewpoint, it can. From a practical standpoint, it hasn’t (table 1).

Like decision support, BPM is more than a technology. It involves the processes, methodologies, metrics and

technology used to monitor, measure sand manage a business. Once selected the business process that has to be

improved, and the business methodology to be implemented, there are the metrics (to monitor, measure and

change) to be established. These metrics (key performance indicators) are defined and selected by the business and

not by the IT. The final step is to choose the business performance measurement technology. We can say that

business intelligence it is just business measurement and not business performance management.

BPM is not a single technology, but rather a combination of elements – BI, scorecarding, profiling. BI looks at and

analyses the past and what has happened up until today – this is useful, as planning requires knowledge and you

can set planning goals based on the past. Scorecarding enables you measure how you are performing against those

planned goals. Every organization has processes in place that feed back to the overall plan. What’s new with BPM

is the integration of these processes, methodologies, metrics and systems – an enterprise wide strategy that seeks to

prevent organizations from optimizing local business at the expense of overall corporate performance.

Factor Traditional BI BI for BPM

Scale Departmental Enterprise-wide

Focus Historical Timely

Decisions Strategic and tactical Strategic, tactical and operational

Users Analysts Everyone

Orientation Reactive Proactive

Process Open-ended Closed-loop

Measures Metrics Key performance indicators

Views Generic Personalized

Visuals Tables / charts Dashboards / scorecards

Collaboration Informal Built-in

Interaction Pull (ad hoc queries) Push (alerts)

Analysis Trends Exceptions

Data Numeric only Numeric, text, etc.

Table1. Differences between traditional BI and BI for BPM

Source:Ballard, C, Business performance management meets Business Intelligence (2006), http:/www.ibm.com/redbooks

Any BI implementation is aimed at turning available data into information and delivering it to the decision makers.

BPM is focused on a subset of the information delivered by a BI system – the information that shows business

performance and indicates business success or failure and enables organizations to focus on optimizing business

performance. BPM involves a closed-loop set of processes that link strategy to execution in order to respond to that

task. Optimum performance is achieved by:

-Setting goals and objectives – strategize

-Establishing initiatives and plans to achieve these goals – plan

-Monitoring actual performance against the goals and objectives – monitor

-Taking corrective action – act and adjust

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STRATEGY

EXECUTION

Integrated

data

1.Strategize

Strategic plans

Strategic maps

2.Plan

Plans, budgets,

scenarios

Projects/initiatives

3.Monitor Scorecards Reports/analysis

Alerts

4.Act and

Adjust

Forecasts and models

Agents offers and

Figure 1. BPM processes

Source: Turban,E & Aronson, J.E. & Liang, T.P. & Sharda, R. (2007), Decision Support and Business Intelligence

Systems, New Jersey, Pearson Prentice Hall

The key to effective BPM is tying performance metrics to business strategy, and that means a melding of two areas

of technological functionality: strategic management systems and performance metrics. The first are systems that

manage the key business processes that affect strategy execution, including objective management, initiative

management, resource management, risk management and incentive management. The second is essentially a

business intelligence platform for automated data exchange, reporting and analysis.

BPM should produce three core deliverables:

-Information delivery to enable managers to understand the business.

-Performance oversight to enable them to manage the business.

-Performance effectiveness to enable them to improve the business.

Business performance management must be an enterprise-wide strategy that seeks to prevent organizations from

optimizing local business at the expense of overall corporate performance

3. Integrating performance management and business intelligence

Most organizations already have a mix of packages and custom built business intelligence applications, including:

strategic performance management (on top of front office), enterprise analytics for tactical analysis, operational

reports and analytics used to support operational decisions. The problem is that these three decision levels are

separated (in terms of applications, users, data sources) when what is really needed is for them to be integrated.

Strategic planning is based on stand-alone scorecard, budgeting and planning applications that use scorecard

databases that hold only summarized data. There is no detail to allow executives to drill down and find out why a

problem occurred in a key performance indicator. Tactical analysis is based on analytic applications, reporting and

OLAP tools delivering analytics based on summary and detailed data stored in data marts and data warehouses.

Operational reports that support operational decisions are based on detailed databases.

What is needed to manage a business is the combination of strategic and near real time operational analytics- the

integration of objectives driven business management using scorecards and dashboards at the strategic level with

the business intelligence tools and analytic applications that support business measurement at tactical and

operational levels (figure 2).

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Detailed data

Domain analytics Domain analytics

KPIs

Scorecards

KPIs

Formal / informal methodology

Business objectives

operational

decisions

tactical

analysis

strategic

planning

Figure 2. BI integration

Business intelligence projects must be related to strategic, tactical and operational business objectives and BPM,

enterprise analytics and operational BI must be integrated into an overall BI framework in order to effective

manage business performance.

4. BPM framework

The integration of business and IT process management and BI is a key enabler for BPM. It provides the ability to

effectively manage the business and achieving business goals. The BPM framework presented below is based on

the integration of business and IT processes at all decision levels (strategic, tactical and operational).

Business

process view

Business

Performance

Management

IT

process

view

Understand the status of business processes across business and IT, in

context against goals and trends, and enable fast action to improve

execution

Visualize IT process

operations in

business

terms, and

manage

service levels

to business

objectives

Understand the state of

key

business

process in

real time

Figure 3. BPM framework

Business flexibility and agility require continuous monitoring of the business processes and support of an

appropriate BI environment. An environment that provides information sufficiently current (near real time) to

support the requirements for both operational and strategic decision making. BI technologies and products are

evolving in order to provide such an environment, and we can list only some of the new trends:

- linking business process data to operational activity data for a complete for a complete view of the enterprise;

- implementation of business rules and Key Performance Indicators to enable consistent management of the

business activities;

- automatic alert generation for proactive problem avoidance rather than reactive problem impact minimization;

- real time data flow to enable monitoring and proactive management of business processes.

A BI environment that include these capabilities enables companies to proactively manage their businesses, rather

than just react and adjust to business situations as they arise.

The main objective of BPM is to help companies improve and optimize their operations across all aspects of their

business. But implementing BPM is much more than just about choosing new technology – it suppose a constant

analyze of business environment to determine if changes are required to existing business processes. To be

successful with BPM, a company must fully understand it’s own business processes and activities that support each

area of business.

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CONCLUSIONS

Managing and optimizing business performance is a critical requirement not only for maximizing business

profitability but even for remaining in viable in today’s fast moving and competitive business environment.

Effective business performance management will blend business intelligence with elements of planning, budgeting

and real time monitoring as well as providing a window on performance. The integration of business and IT

process management and Business Intelligence is the first step in managing business performance. Finally, BPM is

all about taking a holistic approach for managing business performance. The holistic approach enables the

integration and use of business intelligence, process management, business service management, activity

monitoring and corporate performance management to achieve a single and complete view of the enterprise.

REFERENCES

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and information technology, 2nd International Conference Accounting and 2., Management Information Systems,

Bucharest

2. Ballard, C (2006), Business performance management meets Business Intelligence available on line at

http:/www.ibm.com/redbooks

3. BPM Standards Group (2005) Business Performance Management :Industry Framework Document, available

on line at http:/www.bpmstandardsgroup.org

4. CBR Staff (2006) Look beyond the numbers available on line at http:/www.cbronline.com

5. Ekerson W.W.(2007) “Best practices in operational BI – Converging analytical and operational

processes”available on line at www.tdwi.org/

6. Heizenberg J. (2009) “BI predictions 2009: The paradox between demand and supply”available on line at

www.bi-guru-nhm.com

7. http/www.balancescorecards.org/basics/bscl.html

8. Imhoff C. (2007) “Faster must go faster”available on line at www.paraccel.com

9. Kaplan, R. S. & Norton, D. P. (2001) The Strategy-Focused Organization. Boston, Harvard Business School

Press.

10. Kellen, V.(2001).Adaptive CRM and Knowledge Turnover Blue Wolf available on line at

http://www.bluewolf.com

11. Pugna I., Albescu F., Zaharie D., (2008), Business Intelligence for strategic and performance measurement –

Business Performance Management, 4th International Conference of ASECU- Development: Cooperation and

Competitiveness, Bucharest

12. Turban,E & Aronson, J.E. & Liang, T.P. & Sharda, R. (2007), Decision Support and Business Intelligence

Systems, New Jersey, Pearson Prentice Hall

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Business Communication Quarterly75(3) 301 –317

© 2012 by the Association for Business Communication

Reprints and permission: http://www. sagepub.com/journalsPermissions.nav

DOI: 10.1177/1080569912450312http://bcq.sagepub.com

450312 BCQ75310.1177/1080569912450312Sigmar et al.Business Communication Quarterly

1Sam Houston State University, USA

Corresponding Author:Lucia Stretcher Sigmar, Department of General Business and Finance, Sam Houston State University, Box 2056, Huntsville, TX 77340, USA Email: [email protected]

Strategies for Teaching Social and Emotional Intelligence in Business Communication

Lucia Stretcher Sigmar1, Geraldine E. Hynes1, and Kathy L. Hill1

Abstract

Incorporating social and emotional skills (EI) training into the business communication curriculum is important for preparing students to function effectively in a global workplace with its complex informal networks, intercultural issues, team emphasis, and participatory leadership. EI skills enhance communication behavior in work groups and improve the quality of student responses to various business scenarios. Scientific research indicates that modeling social and emotional behavior is key to acquiring competency in these skills. This article describes four classroom strategies for developing EI skills in business communication courses.

Keywords

interpersonal communication, nonverbal communication, teamwork, experiential learning, group dynamics, social and emotional skills

Introduction

Business schools recognize the importance of interpersonal skills development in preparing students to enter a job market where teams are the primary work unit (Yost & Tucker, 2000). Student teams also gain valuable experience in working toward a common goal and gain satisfaction in contributing to the performance and product of the group (Webb, 1995). Evidence shows that such cooperation promotes frequent use

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of higher level reasoning strategies, higher achievement, and more accurate perspec-tive than do competitive or individualistic efforts. These cooperative learning experi-ences also result in students’ being more mature in their cognitive and moral decision making and in considering the viewpoints of others when making decisions (Clarke, 2010; Johnson & Johnson, 2004). In addition to providing opportunities for students to gain new knowledge and abilities, team collaboration develops intrapersonal and interpersonal skills (known interchangeably in the literature as emotional intelligence [EI] or emotional quotient), which are necessary competencies for working effectively with others.

But why do so many of our students seem to have difficulty collaborating on tasks and engaging with business scenarios that simulate what they will encounter in the workplace? Such collaboration demands the development of sophisticated social and emotional skills (Lopes & Salovey, 2004), and yet it is precisely in this area of skills development that our students are lacking.

Social and emotional skills may be a more accurate predictor of personal and pro-fessional success than cognitive knowledge (Covey, 1996; Goleman, 1998b, 1998c), and developing these skills is critical to our business students’ career success. Although pedagogical approaches to teaching EI are plentiful in the literature, several neurologi-cal (Edelman, 1987; Zull, 2002) and scientific inquiries into mirror neuron theory may provide educators a new pedagogical basis for teaching these skills (Gallese, Fadiga, Fogassi, & Rizzolatti, 1996; Iacoboni, 2009; Rizzolati, Fadiga, Gallese, & Fogassi, 1996; Rizzolatti, Fogassi, & Gallese, 2006; Tettamanti et al., 2005). This article sug-gests that these skills may be “deep learned” (Zull, 2002) by active participation in social groups and offers four team-based, experiential learning strategies for teaching essential social and emotional skills in business communication courses.

Emotional Intelligence: Theoretical BackgroundResearchers have long recognized a form of intellect beyond the cognitive. Harkening back to Thorndike’s (1920) initial concept of social intelligence and based on Gardner’s (1983) notion of multiple intelligences, the term emotional intelligence was first used by Salovey and Mayer (1990), who defined the concept as a type of intel-ligence in their seminal article on the subject. Unlike Gardner (1983), however, who emphasized the cognitive dimension of these multiple (“personal”) intelligences, Salovey and Mayer were more interested in the role of emotion in these intelligences. The term emotional intelligence has been most recently popularized by Daniel Goleman’s (1995) landmark book, which sparked much critical inquiry with its per-sonal, professional, and scientific implications.

Theoretical approaches to EI are generally divided into four models: specific ability, integrative, trait, and mixed (Mayer, Roberts, & Barsade, 2008). While the specific ability model focuses on a particular EI skill, the integrative approach focuses on integrating specific abilities into a global perception of EI, such as

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Salovey and Mayer’s (1997) Four-Branch approach, which views EI as a “[cogni-tive] ability to perceive accurately, appraise, and express emotions; the ability to access and/or generate feelings when they facilitate thought; the ability to under-stand emotional knowledge; and the ability to regulate emotions to promote emo-tional and intellectual growth” (p. 10). In addition, Petrides and Furnham’s (2001) trait model concerns self-perception of EI and has more to do with personality than ability. Finally, the broader, mixed models like those of Bar-On (2000) or Goleman (1995) relate “an array of non-cognitive skills, capabilities, and competencies that influence a person’s ability to cope with environmental demands and pressures” (Martinez, 1997, p. 72).

Of these approaches, the mixed-model approach provides a comprehensive plat-form for social and emotional skills development. Goleman’s (1995) five competen-cies of EI are generally accepted as the starting point for discussion and include the ability to become self-aware in managing emotions and controlling impulses, set goals and perform well, be motivated and creative, empathize with others, handle relation-ships effectively, and develop appropriate social skills. Mastery of these competencies greatly affects the way an individual perceives and reacts to internal and external events. This article presents four team-based, experiential learning strategies for teach-ing social and emotional skills in business communication courses following the mixed-model approach and addressing Goleman’s five competencies.

Emotional Intelligence in the WorkplaceOver the past quarter of a century, the expansion of the global marketplace, rapidly changing technologies, and workplace diversity with an increased emphasis on teams have created a demand for emotionally intelligent employees. As a result, emotion management in the workplace has become a popular topic of critical inquiry among organizational behaviorists (Glynn, 1996; Hochschild, 1983; Rafaeli & Sutton, 1989; Van Maanen & Kunda, 1989). Such interest increased significantly with the publica-tion of Fineman’s (1993) Emotions in Organizations and Weiss and Cropanzano’s (1996) “Affective Events Theory.” More recently, a number of studies indicate that EI-skilled people positively influence management/strategic processes (Huy, 2002; Samra-Fredericks, 2004; Zorn, 2001).

Although some professional development specialists have created and successfully marketed EI-specific courses for business and industry over the last decade, EI train-ing may be best accomplished “on the job” (Clarke, 2004; Van der Sluiss, Williams, & Hoeksema, 2002), with skill development occurring through leadership or partici-pation in teams, projects, or assignments (Baron et al., 1999; Blumenfield, Soloway, Marx, Krajcik, & Palincsar, 1991; Evered & Selman, 2001; Vince, 2004). Such EI competencies can translate into tangible workplace benefits such as higher perfor-mance evaluations and increases in merit pay and rank (Lopes, Grewal, Kadis, Gall, & Salovey, 2006).

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Scientific Support of Emotional Intelligence Theory

Although the majority of research supports EI theory, criticism rises generally from the social sciences. Theorists maintain that EI has no objective quantity on which it can be based (Eysenck, 2000; Locke, 2005; Roberts, Zeidner, & Matthews, 2001). Some researchers, while applauding test validity of the specific ability and integrative models, have questioned the mixed model, saying it has no valid assessment protocols (Mayer et al., 2008). Others have questioned whether EI can predict personal and professional success at all (Antonakis, 2003; Antonakis, Ashkanasy, & Dasborough, 2009; Landy, 2005) and have called into question “self-reporting” measures (Conte, 2005). Moreover, despite the plethora of EI testing measures over the years, some critics argue that actual ability is not measured at all; rather, these tests “measure” conformity (Roberts et al., 2001) or knowledge (Brody, 2004)—not actual behavior.

On the other hand, evidence from the neurological sciences suggests that social and emotional intelligence is not only supported by research but also has a physiological basis. Social and emotional intelligence can be observed and measured using neuro-imaging—and can perhaps offer educators insight into how these skills are learned and how these skills should be taught. Electrophysiological studies (Cochin, Barthelemy, Roux, & Martineau, 1999; Fadiga, Fogassi, Pavesi, & Rizzolatti, 1995; Gangitano, Mottaghy, & Pascual-Leone, 2001; Hari, Forss, Avikainen, Kirveskari, & Rizzolatti, 1998) and imaging data (Rizzolattiet al., 1996) indicate that a mirror-neuron system exists in humans (Rizzolati et al., 2006). This system allows subjects to perform move-ments without thinking about it; furthermore, when subjects observe the movements of others, they comprehend those actions without “explicit reasoning” (Rizzolatti et al., 2006, p. 56). This research suggests that a social and emotional brain system is necessary for interacting and relating to other people. We learn first by observing and imitating actions and simultaneously internalizing that experience. This enables these neural networks to provide us the ability to understand and to predict actions and com-plex intentions. In the process, we initiate empathetic emotional responses and an awareness of others. These brain responses to subtleties in movement are the founda-tion for social and emotional intelligence and learning.

Furthermore, proficiency in language usage (verbalizing emotions and articulating actions) is equally important in social and emotional skills competency. Tettamanti et al. (2005) and others found that in addition to being activated by action observation or by hearing action sounds, this same observation-execution system also engages dur-ing the cognitive processing of sentences that describe actions. Researchers have known that putting feelings into words in verbal or written form can attenuate negative emotional experiences (Wilson & Schroeder, 1991), and neuro-imaging studies indi-cate a possible cognitive pathway when affect labeling alleviates negative emotional responses. Data from these studies show that emotional word usage has a demonstra-ble, physical effect on the brain (Lieberman et al., 2007). These findings suggest that the development of a comprehensive emotional vocabulary is fundamental in developing social and emotional intelligence. This vocabulary is important for raising emotional

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self-awareness in oneself and for articulating the feelings of others (Carkhuff, 1993) and is an important aspect in developing empathy.

Social and Emotional Skills in Student Team BuildingTeaching students an emotional vocabulary, identifying and modeling appropriate behavior, mirroring these behaviors, and encouraging higher levels of critical thinking and reflection (challenging or testing assumptions) are essential in the development of EI. As the science indicates, these skills are not learned in isolation.

Edelman (1987) and Zull (2002) observe that social structures like teams allow the exchange and development of emotions and that in the process, neural connections and EI are strengthened, with reciprocity in how these skills are learned: Interaction between team members may facilitate and reinforce emotional and social skills learn-ing (Moriarty & Buckley, 2003), while conversely, emotional and social skills devel-opment may facilitate team-building efforts (Welch, 2003). Other research suggests that highly emotionally intelligent teams are more successful, specifically with higher problem-solving abilities, better performance, and better grades (Druskat & Wolff, 2001; Yost & Tucker, 2000), and emotionally skilled team leaders facilitate better responses from their members (Antonakis et al., 2009; Ashkanasy & Tse, 2000; George, 2000).

Emotional Intelligence PedagogyMany business schools, recognizing the value of team-building skills training, have already implemented such programs for their students (Greenan, Humphreys, & McIlveen, 1997; McGraw & Tidwell, 2001; Mills, Myers, & Rachael, 1991; Moriarity & Buckley, 2003; Thomas & Busby, 2003) or have incorporated EI into their curri-cula in various ways: lecture learning groups (Cockburn-Wootten & Cockburn, 2011), MSCEIT (Mayer–Salovey–Caruso Emotional Intelligence Test) or EISDI (Emotional Intelligence Self-Description Inventory) testing to increase EI awareness (Ashkanasy & Dasborough, 2003; Groves, McEnrue, & Shen, 2008), and self-assessment, journal-ing, role-play, interview, and case analysis (Myers & Tucker, 2005). Other research-ers have suggested the use of games to facilitate social and emotional learning (Hromek & Roffey, 2009).

Many educators agree that information should not be conveyed solely in lecture format and that emotional skills should be taught in an emotional and experiential con-text (Dwyer, 2001; Kremer & McGuiness, 1998). To that end, universities have encour-aged service learning and academic civic engagement (Helm-Stevens & Griego, 2009). Some practitioners urge the use of a team approach to teach interpersonal skills in order to produce a final acceptable product or to attain a predetermined goal (McGrew & Lewis, 1998). Cockburn-Wooten and Cockburn (2011) advocate a collaborative, “learning-by-doing” approach to “reflect and analyze management communication in relation to complexities, failures, context, power, and assumptions, . . . issues

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and tensions around managing relationships, and business communication”(p. 52). Still others see student internships as suitable training ground for learning conflict manage-ment and other interpersonal skills (Stitts, 2006). And because more businesses are using teams at hierarchical levels, educational institutions are also recognizing the need to prepare students for real-world group decision making and functioning within the team structure (Kaplan & Welker, 2001). Boyle and Strong (2006), for example, have proposed a list of key skills (including interpersonal and team-building skills) for enter-prise resource planning. Business schools that already have enterprise resource plan-ning programs can use the list to determine how well they meet industry needs.

Neurological research has indicated that humans develop EI in stages: first, by developing self-awareness in recognizing their own thoughts and feelings toward peo-ple and situations; then moving toward understanding individuals and groups and the subtleties at play in social groups; and then using this information to induce preferred responses in others. If, as the research indicates, effective social and emotional skills are primarily learned through modeling appropriate behavior and social interaction, experiential team building may be the best means of teaching these skills to students.

Student participation in experiential teams provides an opportunity for “active” as opposed to “passive” learning (Cockburn-Wootten & Cockburn, 2011) and for the exchange and development of emotional knowledge. Team-based learning creates stronger relational bonds that facilitate thinking (Clarke, 2010; Moriarty & Buckley, 2003). In addition, within simulated “workplace” groups, students can identify more readily with business scenarios, and by participating in joint problem solving through dialogue and reflection, they can directly experience emotional learning unconsciously and intuitively.

Experiential Teaching Strategies for Business CommunicationThe following sections describe four classroom activities that the authors have used to develop students’ social and emotional skills in the business communication course. As a whole, these exercises roughly follow the stages of EI development (self-awareness in recognizing thoughts and feelings of self and others, understanding oth-ers and the subtleties of social groups, and using information to induce preferred responses). These strategies also stimulate the neural pathways that are fundamental for interacting and relating to other people. By developing an emotional vocabulary and observing and modeling behavior, students can begin the process of “deep learn-ing” Goleman’s (1995) five competencies: self-awareness, goal setting and perfor-mance, motivation and creativity, empathy, handling relationships effectively, and developing and improving social and emotional skills.

Matrix ExerciseAn extensive emotional vocabulary is fundamental to the development of EI. The use of affective language has a physical effect on the brain and can alleviate negative

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emotions (Lieberman et al., 2007), an important skill in management communication, specifically supervisory confrontation. These words are important not only for com-municating on an emotional level with others (i.e., articulating the feelings of others) but also for raising emotional self-awareness (Carkhuff, 1993). Students, however, rarely appreciate the value of having an emotional vocabulary as an interpersonal skill.

A modification of the Emotional Matrix (see the appendix), attributed to Julia West (Bradberry & Greaves, 2009, p. 15), can impress on students the importance of devel-oping their vocabularies by showing them what they lack. Students are given 10 min-utes to complete the blank matrix with high-intensity, medium-intensity, and low-intensity descriptors (three per box) for each of the primary emotions. Descriptors for “happy,” for example, may range from ecstatic (high) to delighted (medium) to glad (low). Students generally have some difficulty in completing the matrix in the time period and struggle with articulating the subtle differences in emotional intensity. They quickly realize that they are underequipped for identifying their own emotions—much less the emotions of others—and recognize the need to develop their emotional vocabularies as a fundamental skill set in the development of empathy. Next, students play Emotion Charades, enacting an emotion pulled at random from a box (e.g., “out-raged”) and identifying the appropriate emotion/intensity level (“angry,” high inten-sity), thus raising emotional self-awareness in themselves (as the actor) and in relating to others (in interpreting emotions). Prizes increase participation and listening/observing skills.

EI debriefing:

1. Was completing the emotional matrix difficult for you? If yes, why? Name some ways you can increase your emotional vocabulary.

2. How effectively did you enact an emotion in Emotion Charades? What non-verbal cues did you give the audience? What nonverbal cues might have conveyed the emotion more quickly or more effectively?

3. Why is an extensive emotional vocabulary important in management communication?

Magic CarpetThis exercise stimulates relational bonds that facilitate thinking. A simple activity using a plastic shower curtain enhances students’ group problem-solving skills through dialogue, reflection, and nonverbal communication.

Preceding the exercise, the instructor introduces the concepts of task function and maintenance function in group problem-solving discussions. Briefly, the task function is performed by team members who are concerned with accomplishing the team’s stated task. Communication includes direction giving, information seeking, informa-tion giving, elaborating, coordinating, enforcing, and summarizing. Team members concerned with the maintenance function are sensitive to relationships among the team members. Communication includes supporting, harmonizing, tension relieving, ener-gizing, encouraging, and facilitating (Whetten & Cameron, 1998). Before the activity,

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the instructor points out the value of both functions for effective group problem solving.

Next, the instructor initiates the activity: The instructor spreads a plastic shower curtain on the floor. The instructor asks for volunteers to stand on the shower curtain. Students who decline to volunteer are assigned to be observers. Ideally, between 12 and 18 students come forward. They typically try to stand as far apart as possible, avoiding touching each other.

The instructor tells this story:

You are standing on a magic carpet, flying high above the clouds. Suddenly you realize that you are headed in the wrong direction! In order to reverse course you must flip over the magic carpet. Naturally, anyone who steps off the carpet will fall to his or her death. Your task is to turn the carpet upside down. Everyone must remain standing on it with at least one foot at all times.

The instructor asks observers to listen closely to the students as they work together to flip the shower curtain while standing on it. The observers are reminded to note who the task function people are and whose contributions are primarily directed to main-taining the group relations.

Students usually begin to solve the task by folding over one side of the shower curtain and crowding together on the other end. After realizing that the size of their magic carpet has decreased alarmingly, they abandon that strategy. The team mood proceeds from silliness, with lots of self-conscious laughter, to determination, and then to frustration as they struggle. Occasionally, a student “sacrifices” for the sake of the group and steps off. Ultimately, someone realizes that twisting the shower curtain from a corner allows the team to move from one side to the other without diminishing its total size. It may take 5 to 30 minutes for the solution to occur to the group.

During the debriefing, observers point out the task leaders and the maintenance leaders, giving examples of statements that the participants uttered for each function and their effect. The instructor finishes with a discussion about the contributions of each communication function.

EI debriefing:

1. Who were the task leaders and the maintenance leaders? How do you know? Give examples of statements for each function.

2. How did each of these functions contribute to the team’s solution?3. What were the failures, issues, and tensions you experienced and how did

these affect your result?4. What did you learn about yourself and about team dynamics that you will be

able to apply in the workplace?

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Corporate Blindfold

This team-building exercise also enhances group problem-solving skills and verbal and nonverbal communication and illustrates communication issues in tall manage-ment hierarchies. Preceding the exercise the instructor introduces formal and informal organizational communication strategies and discusses the trend toward flattened management hierarchies that result in more efficient groups or teams.

The instructor then announces the formation of a company in which the instructor is the CEO. The CEO appoints a “president” who will be his or her direct “report” during the exercise; the remainder of the class serves variously as upper-, mid- and lower-level employees. Students are then instructed to line up behind the president (students who may have supervisory jobs are asked to go to the end of the line to get the most out of the experience). After putting on their blindfolds, the students link hands. The instructor asks everyone to avoid speaking to each other during the exer-cise so that the president (also blindfolded) can hear instructions from the CEO. Guided only by the CEO’s voice, the president begins to take the company forward through “difficult times.” Students, initially uncertain of the direction and people around them, shuffle quietly and slowly at first.

As the president becomes accustomed to following the CEO’s voice, the pace quickens, and the group threads out of the classroom and into the hallways, through doorways, and around obstacles. Students sometimes blunder into walls, door jambs, lounge chairs, or trash cans if the direction they receive from their “supervisors” (the person in front of them) is unclear. However, nonverbal communication in the form of hand squeezing and positioning, or proxemics, usually assists students in determining the direction the company is heading. Invariably, students at the middle and lower levels of the company, unable to hear the CEO’s directions to the president, began to initiate grapevine discussion: “Are you still there?” “Are you OK?” “I can’t see a thing.” “Do you have any idea where we are?” The grapevine is irrepressible and soon moves up and down the organization, and most students forget the instructor’s earlier request to avoid speaking. Occasionally, the CEO will fall silent, causing the entire company to either slow down or stop completely. In response, the grapevine usually begins to speculate loudly on the direction the company is heading.

If the company is moving too quickly, some employees become stretched in their efforts to hold their sections together; sometimes sections of the organization will break off from the company entirely—unless the CEO intervenes to reconnect them. Eventually, the CEO leads the company back to the classroom where the blindfolds are removed and the debriefing begins.

Students are encouraged to draw parallels between their experience and what they might encounter in a real corporation or business scenario: the power of nonverbal communication, the reciprocity of formal and informal networks, the difficulties of communicating quickly and efficiently in tall organizational structures (this usually

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results in an “aha” moment as students grasp the benefits of work groups and teams), and the problems that occur with a lack of, or inaccurate, communication or relation-ship issues in the group. Students at the bottom of the corporation (end of the line) usually have the most difficult time during the exercise since they cannot hear the CEO and are dependent on the person immediately in front of them for any direction at all (after this exercise, real-life supervisors tend to empathize more with employees who may be in lower level positions). This exercise also contributes greatly to creating group cohesiveness in the classroom.

EI debriefing:

1. On whom did you depend for information and direction? Who depended on you?

2. In what ways was this information communicated to you? How did you com-municate this information to others?

3. You were told not to talk during this exercise. Did you follow that directive? How is your reaction similar to the grapevine in organizations?

4. What is the ideal state between the grapevine and formal communication in an organization?

5. Depending on where you were in line, what difficulties in communication did you encounter? How did you overcome those difficulties?

Xion (Adapted From Gochenour, 1993)This role-play activity exposes students to the complexities of intercultural communi-cation. It challenges their assumptions and exposes them to issues of power, failure, and context as they learn conflict management and reflect on ways to induce preferred responses in others. These issues are core to EI.

For this activity:

• Two groups of three are needed to run the simulation.• One team is made up of two women and one man (the Xions from

Country X).• The other team is made up of two men and one woman (the Journalists).• Xions and Journalists meet by chance in a restaurant in Greece.• Journalists try to get permission from Xions to go to the annual Queen’s Gar-

den Festival, take photos, and write a magazine article.

Country X is a matriarchal society. Men keep house, cook, and care for the chil-dren. In all respects, women are viewed by the Xion culture as being superior to men. This belief is reinforced by individual attitudes and institutionalized beliefs, norms, and structures. Marriage is between two women, forming “the Bond.” The Bond then may jointly receive a man to their household for the purposes of having children, tend-ing the home, and so on. The man is protected and “cherished” by the Bond.

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The Xions value art and nature and celebrate the Queen’s Garden Festival each year. No outsiders have ever attended the festival although there is no law against it.

During the simulation, Xions must limit their vocabulary to words of only one or two syllables when speaking with the Journalists. Xions must also avoid making pro-longed eye contact. Staring is impolite and is considered aggressive.

The Journalists join the Xions at their table in the restaurant and try to converse with them. After 15 minutes, they excuse themselves to discuss the best way to approach their objective: receiving permission to attend the Queen’s Garden Festival.

The Xions will grant the Journalists permission to attend the Festival only if they meet all of the following criteria:

1. The female Journalist must ask for permission, and she must ask the Bond, not the Cherished Man.

2. The Journalists must be considerate about the English language limitations and try to use words and pacing that Xions can understand.

3. Journalists must show sensitivity to Xion customs regarding eye contact.

The Journalists typically have difficulty with the conversation at the table since the Xions only answer in one or two syllables. The Xions have difficulty answering with only one or two syllables and not making eye contact. The Journalists get frustrated because the Xions will only briefly make eye contact and won’t really “talk” to them. They then try to start a conversation with the Cherished Man, who cannot talk to them without permission from the Bond.

Moreover, when the Xions and Journalists notice cultural differences, they may interpret those behaviors through the lenses of their own culture, and they often get so engaged in the details of the task that they forget about how important relationships are to accomplishing that task.

EI debriefing:

1. What cultural differences were blatantly visible? Which ones only became apparent later?

2. How did the two cultures display emotions and power differently? What effect did this have on the communication?

3. How did you adjust your perspective so that you understood and valued others?

4. How did you induce preferred responses in others?5. What did the Xion role-play teach you that will help you in the global

workplace?

ConclusionAs this article’s review of the academic and scientific research indicates, experiencing and modeling social and emotional behavior are essential in learning EI. To develop

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the neural pathways, experiential learning and simulation exercises, including role-play and group activities, such as the four described in this article, are essential. This article adds value to the literature because it presents concrete examples of how we as business communication instructors can build our students’ self-awareness and sensi-tivity to the impact of an individual’s verbal and nonverbal behavior.

Incorporating EI into the business communication curriculum is an important step in preparing our students to function effectively in a global workplace with its com-plex informal networks, teams, and participatory leadership, where they must con-stantly learn new skills and adapt quickly to changing technology (Lopes & Salovey, 2004) and where mastery of interpersonal and group skills is needed in order to inter-act effectively with others (Johnson, 2003; Johnson & Johnson, 2003; Muir & Davis, 2004). Awareness of EI strategies enhances students’ communication behavior indi-vidually and in work groups. One student testified after EI training that he has “a better understanding of . . . emotions, optimism, and working positively with others [and enjoyed] . . . the hands-on activities to better understand how to apply [these skills].”

If, as Goleman (1998a) believes, professionally successful people have high EI in addition to the traditional cognitive intelligence or specialized knowledge, we can bet-ter prepare our students by teaching them not only the cognitive knowledge they will need but also the social and emotional skills that will ensure their success.

AppendixEmotional Word Matrix

Intensity

Category High Moderate Low

Happy

Sad

Scared

Angry

Confused

Strong

Weak

SOURCE: Adapted from and reproduced in part by permission from Julia West.

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Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

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Bios

Lucia Stretcher Sigmar is an assistant professor in the College of Business Administration, Sam Houston State University. She teaches undergraduate courses in business communication and business and professional speaking and is an officer of the Association for Business Communication, Southwest Region.

Geraldine E. Hynes is a professor in the College of Business Administration, Sam Houston State University. She is a past President of the Association for Business Communication and teaches undergraduate and graduate courses in business communication, managerial communi-cation, and business and professional speaking.

Kathy L. Hill is an associate professor in the College of Business Administration, Sam Houston State University. She teaches undergraduate and graduate courses in business com-munication, intercultural business communication, business and professional speaking, and managerial communication.

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Research and Markets: In 2012, the Intel Ivy Bridge

Platform Hit the Market and Its Anticipated There Will

Be More Ultrabooks Unleashed In The Market

Research and Markets

(http://www.researchandmarkets.com/research/64tfwd/current_developmen) has announced

the addition of the "Current Development and Future Trends of Ultrabooks" report to their

offering.

With notebook PCs entering the maturity, the room for the introduction of new features and

applications on notebook PCs is therefore limited. Therefore, vendors have been focusing

on enhancing user experience in battery run time as well as fashionable and lightweight

industrial design, which used to be only common for high-end notebook PCs. After, Intel

put forth the concept of Ultrabook and the pace of such industrial design to become

mainstream is further accelerated. This report provides insight into the ultra-thin trends of

the notebook PCs based on the development of ultrabook market, leading chipmakers, key

components, and major ultrabooks presently available or to be made available in the future.

Key Topics Covered:

1. Introduction

2. Market Development

3. Major Chipmakers' Strategy

4. Key Component Development Trends

5. Ultrabook Product Development Trends

6. Conclusion

List of Tables

List of Figures

Companies Mentioned:

- Acer

- AMD

- Apple

- Asus

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- Fujitsu

- Haier

- Hasee

- HP

- Intel

- Intel

- Lenovo

- Tongfang

- Vizio

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XIMENA MA RTÍNEZ HERNÁ NDEZ

INNOVA CIÓN 8VO SEMESTRE

PRA CTICA DE BA SES DE DA TOS

XIMENA MA RTÍNEZ HERNÁ NDEZ

INNOVA CIÓN 8VO SEMESTRE

PRA CTICA DE BA SES DE DA TOS

Universidad del Caribe