APPLICATION OF DATAMINING TOOL FOR CLASSIFICATION OF ORGANIZATIONAL CHANGE EXPECTATION Şule ÖZMEN...

APPLICATION OF DATAMINING TOOL FOR APPLICATION OF DATAMINING TOOL FOR CLASSIFICATION OF ORGANIZATIONAL CLASSIFICATION OF ORGANIZATIONAL

CHANGE EXPECTATIONCHANGE EXPECTATION

Şule ÖZMENŞule ÖZMENSerra YURTKORU Serra YURTKORU

Beril SİPAHİBeril SİPAHİ

DATA MDATA MIINNIINGNG

Data mining is the nontrivial Data mining is the nontrivial extraction of implicit, previously extraction of implicit, previously unknown, and potentially useful unknown, and potentially useful information from data. information from data.

DDIIFFERENT GOALS CALL FFERENT GOALS CALL FOR DFOR DIIFFERENT FFERENT

TECHNTECHNIIQUESQUES

DATAMDATAMIINNIING NG TECHNIQUESTECHNIQUES

Datamining techniques can be Datamining techniques can be either either

directeddirected

or or

uundirectedndirected..

DATAMINING TECHNIQUESDATAMINING TECHNIQUES

DirectedDirectedGoal isGoal is

to predict, to predict, estimate, classify, estimate, classify, or characterize the or characterize the behavior of some behavior of some pre-identified pre-identified target variabletarget variable

UndirectedUndirectedGoal isGoal is

to discover to discover structure in the structure in the data set as a data set as a whole. whole.

DATAMINING TECHNIQUESDATAMINING TECHNIQUES

DirectedDirected• ClassificationClassification• EstimationEstimation• PredictionPrediction

UndirectedUndirected• Description & Description &

VisualizationVisualization• Association Rule Association Rule

or Affinity or Affinity GroupingGrouping

• ClusteringClustering

Classification is used to develop Classification is used to develop a model that maps a data item a model that maps a data item into one of several predefined into one of several predefined classes.classes.

CLASSIFICATIONCLASSIFICATION

DECDECIISSIION TREE ANALYSON TREE ANALYSIISS

Builds classification and regression trees

Starts with pre-identified target variable in other words dependent variable. This is the initial node

Initial node is split into two or more child nodes

Splitting is based on statistical analysis used by decision tree algorithms

Target Variable

Pre

dict

ive

Var

iabl

es

Target Variable

DECDECIISSIION TREE ANALYSON TREE ANALYSIISS

DECDECIISSIION TREE ALGORON TREE ALGORIITHMSTHMS

CHAIDCHAID (Chi square Automatic (Chi square Automatic Interaction Detector) Interaction Detector)

C&RT (Classification and Regression C&RT (Classification and Regression Tree)Tree)

QUEST (Quick Unbiased Efficient QUEST (Quick Unbiased Efficient Statistical Test)Statistical Test)

CHAID MethodCHAID Method

CHAID was designed to handle CHAID was designed to handle categorical variables only. categorical variables only. SPSS has extended algorithm to SPSS has extended algorithm to handle nominal, ordinal and handle nominal, ordinal and continuous dependent variables. continuous dependent variables.

Components of CHAIDComponents of CHAID

One or more predictor variables.One or more predictor variables. Predictor variables can be continuous, ordinal, or nominal.

One target variable.One target variable. The target variable can be nominal, ordinal or continuous.

CHAID AlgorithmsCHAID Algorithms

A CHAID tree is a decision A CHAID tree is a decision tree that is constructed by tree that is constructed by splitting subsets of the splitting subsets of the space into two or more space into two or more child (nodes) repeatedly, child (nodes) repeatedly, beginning with the entire beginning with the entire data set.data set.


To determine the best split at any To determine the best split at any node, CHAID merges any allowable node, CHAID merges any allowable pair of categories of the predictor pair of categories of the predictor variable (the set of allowable pairs variable (the set of allowable pairs is determined by the type of is determined by the type of predictor variable being studied) if predictor variable being studied) if there is no statistically significant there is no statistically significant difference within the pair with difference within the pair with respect to the target variable.respect to the target variable.


The process is repeated until no The process is repeated until no non-significant pair is found. The non-significant pair is found. The resulting set of categories of the resulting set of categories of the predictor variable is the best split predictor variable is the best split with respect to that predictor with respect to that predictor variable. This process is followed variable. This process is followed for all predictor variables. The split for all predictor variables. The split that is the best prediction is that is the best prediction is selected, and the node is split. The selected, and the node is split. The process repeats recursively until process repeats recursively until one of the stopping rules is one of the stopping rules is triggered.triggered.

APPLAPPLIICATCATIIONON

AAIIM OF THE RESEARCHM OF THE RESEARCH

The ability to be both The ability to be both receptive and responsive to change receptive and responsive to change has becomehas becomeimportant in recent years.important in recent years.

Therefore Therefore our aim is to our aim is to analyze analyze change change patterns that will help patterns that will help managers and organizations to managers and organizations to manage the process of change manage the process of change more effectivelymore effectively

SAMPLESAMPLE

Our sample is consisted of 253 Our sample is consisted of 253 subjects from 7 private Turkish subjects from 7 private Turkish organizations. The sample organizations. The sample is is composed of 44 superiors and composed of 44 superiors and 209 subordinates.209 subordinates.

INSTRUMENTINSTRUMENT

Multi Scale Organizational Multi Scale Organizational Change QuestionnaireChange Questionnaire

Organizational change questionnaire is composed of five scales "Forces of Change", “Change Strategy", "Means of Change", “Resistance to Change", and “Change Expectation" scales

TARGET VARTARGET VARIIABLEABLE

Change ExpectationChange Expectation

•Employee DevelopmentEmployee Development *

•EfficiencyEfficiency

•Organization StructureOrganization Structure

•Acquisition & DivestitureAcquisition & Divestiture

•AlliancesAlliances

•RestructuringRestructuring

* means increase in employee self development & individual learning, increase in employee participation& employee suggestions acceptance

Since organizational change is a Since organizational change is a process that takes time, we process that takes time, we rather asked if the employees rather asked if the employees expected change as a result of expected change as a result of the actions taken within the the actions taken within the firm, not whether the firm, not whether the organization organization has has changed or changed or not. This is also important not. This is also important because if the employees don’t because if the employees don’t believe in the actions taken, believe in the actions taken, they resist and try to block the they resist and try to block the change actions.change actions.

PREDPREDIICTOR VARCTOR VARIIABLESABLES

Change Forces Change Forces

Change StrategyChange Strategy

Means of ChangeMeans of Change

Resistance Resistance to Changeto Change

SCALE PREDICTORS

OrganizationalBusiness InputsCompetitionLaws & Regulations

CHANGE FORCES

Pressure Groups

Value AddedRiskiness

CHANGE STRATEGY

BenchmarkingImprovement in Guidance & ControlImprovement in Human Resource QualityImprovement in Product & Services

MEANS OF CHANGE

Creativity

ResistanceRESİSTANCE TO

CHANGE

DATA TYPE

All variables collected are transformed into dichotomous data, like change expected, not expected; competition exists, do not exist etc.

If business inputs* are If business inputs* are forcing an organization to forcing an organization to change, the expectation of change, the expectation of employee development change is employee development change is 90%.90%.

In addition if benchmarking In addition if benchmarking is applied as a change means is applied as a change means then this percentage increases to then this percentage increases to 95%.95%.

**like customer demand, bargaining power of like customer demand, bargaining power of customers & suppliers, information and customers & suppliers, information and production technology)production technology)

CONCLUSIONCONCLUSION

But if the organization is But if the organization is notnot forced by business inputs even then forced by business inputs even then there is a chance of change there is a chance of change expectation if improvement in expectation if improvement in guidance & control * is applied (78% guidance & control * is applied (78% expect change). expect change).

This increases to 92% with the This increases to 92% with the presence of force of laws & presence of force of laws & regulationsregulations

**like improvement in reward system, like improvement in reward system,

communication between departments, quality communication between departments, quality control, & internal controlcontrol, & internal control


When there is no force of When there is no force of laws & regulations if laws & regulations if benchmarking is applied, the benchmarking is applied, the change expectation rate is 80%.change expectation rate is 80%.


Which Which emphasizesemphasizes the the importance of importance of benchmarkingbenchmarking in in change process. change process. Even when Even when there is no force to change if the there is no force to change if the organization is applying organization is applying benchmarking (which is actually benchmarking (which is actually a proactive change strategy) a proactive change strategy) even this is enough to trigger even this is enough to trigger

change expectation. change expectation.


On the other hand if there is On the other hand if there is no force of business inputs, no force of business inputs, there is no improvement in there is no improvement in guidance & control, and no force guidance & control, and no force of competition then 82 % of of competition then 82 % of employees don’t expect to have employees don’t expect to have a chance to improve themselves. a chance to improve themselves.


As can be seen from the As can be seen from the above example every path has above example every path has

an implication. an implication.


What makes this study What makes this study different from other applications different from other applications is the nature of the problem is the nature of the problem explored. Decision tree analysis explored. Decision tree analysis are widely used in classification are widely used in classification of customers for segmentation of customers for segmentation purpose and other CRM purpose and other CRM applications. applications.

IMPLICATIONIMPLICATION

However the main purpose However the main purpose in this study is to identify in this study is to identify important variables in change important variables in change expectation expectation tthrough classifying hrough classifying the respondents on the basis of the respondents on the basis of their perceptions about the their perceptions about the changechange criterioncriterion. .


Therefore by identifying Therefore by identifying these respondents on the basis these respondents on the basis of the factors effecting their of the factors effecting their change expectations, and change expectations, and describing the important describing the important variables is a valuable variables is a valuable information for developing information for developing strategies and policies of strategies and policies of organizational change. organizational change.


APPLICATION OF DATAMINING TOOL FOR CLASSIFICATION OF ORGANIZATIONAL CHANGE EXPECTATION Şule ÖZMEN...

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