Managerial Network Clusters

Managerial Networks Clusters
Ali Anani, PhD

Workers interact- These are actions that generate different outcomes.
The boundaries of an organizational network are usually very well-defined by its organizational structure.
Employees may engage in a myriad of different interactions. Patti Anklam published several interesting ideas on this subject
Interactions among Workers

Information exchange- the more people know and trust each other the more they exchange information
Awareness of what people know- the more people are aware of what co-workers know, the more likely they will exchange information
Types of Information Exchange and Their Determinants

Knowledge Seeking- People seek information from knowledgeable people to solve problems if no barriers exist. Barriers limit the free flow of consultation on issues related to problem-solving and decision-making
Motivational Energy- Knowledgeable staff may affect people positively or negatively. People tend to consult experts who motivate them while avoiding people who are de-motivating (Unless they have no option but to consult with them)
Types of Information Exchange and Their Determinants- 2

A sample of twenty one managers was taken randomly for a middle-sized company
Face to face interviews and written surveys produced the results shown in the next table
The dimensions taken are the same as discussed in the preceding slides
A Case Study

Survey Results

NeuroXL Classifier from was used to analyze the results as explained in an earlier publication by the author
The first analysis was designed to produce two clusters. (See next slide)
Analysis Methodology

The Two Clusters

The previous slide shows two clearly differentiated clusters.
The meeting point between the two clusters is the frequency of receiving information; otherwise the two clusters diverge
The Two Clusters- 2

In Cluster 1, managers are familiar with who has information and the skills to consult with. However; peer managers are hesitant to seek their advise because these managers do not either motivate their peers or save them time. This realization apparently led to the low frequency of information exchange
The Two Clusters- 3

Cluster 2 compromises managers whose common profile is being low in the familiarity of the knowledge and skills of their peers and are not seekers of opinion to make decision. However; they benefit from the time savings they get from their peers and of the enthusiasm they get from these activities
The Two Clusters- 4

The Two Clusters- 5
The Cluster Radar
The previous clusters are redrawn in a radar graph

The segmentation of managers into three clusters produced the following clusters with cluster 1 having the highest weight
Three Managerial Clusters

The line graph is as shown below. Cluster 2 (14.29% by weight) scores lowly in both dimensions pertaining to other managers being either familiar with their knowledge or skills. The culture and communication levels are low indeed.
Three Managerial Clusters- 2

It was decided to take out the dimension of frequency of decision consulting to see the outcome. The resulting clusters had the following weights. A more balanced cluster weights resulted than the original case

This time cluster 3 realized time savings from consultation after removal of the decision consultancy dimension . Apparently, the benefits are lost because of indecisiveness. However; the issue of time value is critical in both clusters 1 and 2 as time savings from consultation show negative values

This time cluster 3 realized time savings from consultation. Apparently, the benefits are lost because of indecisiveness. However; the issue of time value is critical in both clusters 1 and 2 as time savings from consultation show negative values

The impact of time savings resulting from consultation prompted repeating the cluster analysis without this factor. The weights of the three clusters emerged as follows. Interestingly, the same weights for leaving decision data, but are reshuffled

Cluster 1 shows radical performance difference than both cluster 2 and, to a lesser extent, cluster 3

The managers were divided into four clusters to form four quadrants.
Four Clusters

The managers were divided into four clusters to form four quadrants. The clusters show four different type of managers. Clusters 1 and 3 are the least beneficial from time savings
Four Clusters

The value of cluster risk analysis becomes evident if we take one dimension out. In this example the decision consulting frequency was left out. The results are shown in this slide and the next one
Four Clusters

The problem areas of each cluster may be identified. Satisfying or leaving out one factor leads to reshuffling of the weights of new clusters
Four Clusters

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Managerial Network Clusters

by Ali Anani on Jan 02, 2010

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Managerial Network Clusters — Presentation Transcript