Data Mining Visualization and Employee Communication Preferrences
Tuesday, 28 August 2007
The Keirsey™ Temperament Sorter®-II uses four scales to determine both Temperament and Character classifications. The four scales measure an employee's preference for Extraversion versus Introversion, Sensing versus Intuiting, Thinking versus Feeling and Judging versus Perceiving.
The four disticnt temperament patterns are the following:
1. Guardian: regards duties and
accountabilities, following rules and not stepping over the lines. The
four types of guardians are inspectors, protectors, providers, and
supervisors.
2. Idealist: holds a vision of what
might be possible, reaching goals without compromising beliefs. The
four types of idealist are healers, counselors, champions, and teachers.
3. Artisan: deals with the here and now,
being practical with his/her faculties is most important. The four
types of artisans are composers, crafters, performers, and promoters.
4. Rationals: plans what can be done,
rewriting the rules to solve the problems. The four types of rationals
are builder/architects, fieldmarhals, inventors, and masterminds.
Each of these temperament exhibit a pattern of communication using the
following four preference scales:
The four preference scales:
Expressive versus attentive
Observant versus
instropective
Tough-minded versus friendly
Scheduling versus probing
For example, the idealist-teacher type
described below is a predominant eNFj (expressive, introspective,
friendly, and scheduled)
For detail descriptions of these
preferences, see this page:
http://www.advisorteam.org/administering_the_KTS-II/background.html
The video below shows a 3D visualization of a group of employees and
their communication preferences (Using MineSet Visualization). In the 2nd half where the blue and red
dots represent male and female, note that sex is not a differentiating
factor. There is range of value of Being Observant and Probing where
there is no employee. Also note there are four major clusters. This signals a line up of a very strong set of
values preceding a certain corporate event.
Note that the color dimention is the fourth communication preference "Tough minded" versus "Friendly" - with red being the toughest, yellow neutral and green the least.
Data mining can be used to predict a specific behavior, i.e. take an action based upon available variables. Here, it is useful to record decisions employees make. Employees with similar Keirsey temparement and communication preferences may have a higher chance of making the same communication decisions.
Data mining is used when it's not clear what to look for. Data mining can show unexpected relationship and correlations. Here, a visualization of a data set in 3D can quickly show anomalies or unusual events. Data mining answers questions that can not be asked before hand - since the questions didn't exist. This is exactly what communicator theorists called "You don't know ... what you don't know". If you know what you are looking for, then use SQL. In relationship database queries, SELECT statements require precise knowledge of what is being looked for. Systems such as prolog, triple-stores, or Baysian-net systems (i.e. Autonomy or other knowledge management systems) enable deductions of associations of arbitrary relationships.
