Managerial Network Clusters

transcript

Managerial Networks ClustersAli Anani, PhD

Knowlede Familiarity

Skills Familiarity

Frequency of Receiving InformationTime Saving from Consultation

Effect on Enthusiasm

-50.00%

50.00%

Clusters profiles Cluster 1 Cluster 2 Cluster 3 Cluster 4

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 ResultsInformation

Decision Making

Value Creation Energy

Employee No

Knowledge Familiarity

Skills Familiarity

Frequency of Receiving Information

Decision Consulting Frequency

Time Saving from Consultation

1 8 9 5 6 5 52 5 6 4 5 6 43 6 7 6 7 4 64 5 5 3 4 3 75 2 3 6 4 7 66 9 9 6 6 7 47 5 4 3 5 8 78 5 7 4 7 5 49 3 3 6 8 5 6

10 4 6 4 3 6 611 8 5 3 6 4 512 6 6 6 4 4 413 5 5 7 3 6 714 8 9 5 7 8 815 8 6 5 8 4 616 7 8 3 4 6 817 8 5 4 4 7 718 8 8 3 6 4 519 5 5 5 4 6 420 4 5 5 7 7 521 6 9 5 8 4 6

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

-25.00%-20.00%-15.00%-10.00%

-5.00%0.00%5.00%

10.00%15.00%20.00%25.00%Clusters profiles Cluster 1 Cluster 2

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

Cluster 1 weight (%) Cluster 2 weight (%)

45.00%

46.00%

47.00%

48.00%

49.00%

50.00%

51.00%

52.00%

53.00%

47.62%

52.38%Clusters weights

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

Knowlede Familiarity

Skills Familiarity

Frequency of Receiving Information

Decision Consulting Frequency

Time Saving from Consultation

-50.00%

50.00%

Clusters profiles Cluster 1 Cluster 2

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

Three Managerial Clusters

Cluster 1 weight (%)

10.00%

20.00%

30.00%

40.00%

50.00%

60.00%52.38%

14.29%

33.33%

Clusters weights

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

Knowle

de Fam

Decisio

ng Fre

-40.00%

-30.00%

-20.00%

-10.00%

10.00%

20.00%

30.00%

40.00%Clusters profiles Cluster 1 Cluster 2 Cluster 3

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

10.00%

20.00%

30.00%

40.00%

28.57%33.33%

38.10%Clusters weights

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

-30.00%

-10.00%

10.00%

30.00%Clusters profiles Cluster 1 Cluster 2

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

-30.00%

-20.00%

-10.00%

10.00%

20.00%

30.00%Clusters profiles Cluster 1 Cluster 2 Cluster 3

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 weight (%) Cluster 2 weight (%) Cluster 3 weight (%)

10.00%

20.00%

30.00%

40.00% 38.10%

28.57%33.33%

Clusters weights without time savings value

Cluster 1 weight (%) Cluster 2 weight (%) Cluster 3 weight (%)

10.00%

20.00%

30.00%

40.00%

28.57%33.33%

38.10%Without decision making dimension

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

Knowle

de Fam

Decisio

ng Fre

-40.00%

-30.00%

-20.00%

-10.00%

10.00%

20.00%

30.00%

40.00%

Clusters profiles without Time Savings ValueCluster 1 Cluster 2 Cluster 3

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

Four Clusters

10.00%

15.00%

20.00%

25.00%

30.00%

35.00%

40.00%

45.00%

33.33%

14.29% 14.29%

38.10%

Clusters weights

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

Knowle

de Fam

Decisio

ng Fre

-40.00%

-30.00%

-20.00%

-10.00%

10.00%

20.00%

30.00%

40.00%

50.00%Clusters profilesCluster 1 Cluster 2 Cluster 3 Cluster 4

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

20.00%

40.00%28.57%

23.81%28.57%

19.05%

Clusters weights

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

Knowle

de Fam

-50.00%

-40.00%

-30.00%

-20.00%

-10.00%

10.00%

20.00%

30.00%

40.00%

Clusters profiles without Decision ConsultationCluster 1 Cluster 2 Cluster 3 Cluster 4

Managerial Network Clusters

Business