Feathered Correlations: Color Predicting Culture in Diverse Flocks After Disaster

There were once colorful flocks of birds that lived together in a big forest. These flocks of birds had different ratios of beige birds, purple birds, red birds, blue birds, orange birds, green birds, yellow birds, and turquoise birds. These different proportions of colors influenced each flock's values, culture, and atmosphere. Their leaders made decisions based on the most common bird colors.


One day, after a bad storm, the flock leaders made tough choices to help their birds survive.


In Swift's flock, purple and green birds predominated. True to their adventurous nature, Swift sent the purple and green birds to find new food sources (unpaid vacation). She asked the orange birds to scout for materials to rebuild damaged nests because they loved to compete.


Feather's flock mainly had blue, who valued stability, and orange birds, who loved competition. The no-nonsense orange birds got right to work on repairs (no reduced staff). And the peaceful blue birds kept singing to lift spirits, so Feather changed nothing about their routines (nothing changed).  


Hootie's flock had many sociable yellow birds who could always find a profitable solution for everyone and possessed a Win-Win-Win behavior. When the yellow birds' food storage was damaged, instead of reducing their rations (reduced salaries), Hootie asked the red birds to share the extra food they had gathered. So, yellow birds' food storage wasn't changed (no reduced salaries).


Over in Willa's flock, fun-loving turquoise birds were the majority. After the storm, Willa kept all her turquoise birds in their usual nests, singing songs since their cheerfulness helped the whole flock recover (nothing changed). But she had to ask the few red and orange birds to rebuild damaged nests belonging to elder beige birds temporarily.


Each diverse flock recovered based on its colorful culture and connections. But all birds worked cooperatively despite difficulties to continue thriving in the forest.


The SDTEST® gives clues to someone's motivational values. However, additional polls can provide more pieces of the puzzle.


Imagine also giving an "Actions of companies in relation to personnel in the last month (yes / no)" poll. It asks people about actions of companies in relation to personnel in the last month. 


Now imagine 1'000 people who took both tests. You could match up each person's SDTEST® colors with their answers about actions of companies in relation to personnel in the last month.


Comparing tests gives an expanded picture of values in action. More puzzle pieces make the whole image more apparent!


Multiple tests can work together, like colors blending on a palette. Other polls reveal what engages your values, like what is the perception of the actions of companies in relation to personnel in the last month. Combined, they paint a richer picture of what motivates our thoughts and deeds.


Below you can read an abridged version of the results of our VUCA poll "Actions of companies in relation to personnel in the last month (yes / no)". The full results of the poll are available for free in the FAQ section after login or registration.


Actions of companies in relation to personnel in the last month (yes / no)

Country
Language
-
Mail
Recalculate
Critical value of the correlation coefficient
Normal distribution, by William Sealy Gosset (Student) r = 0.0578
Normal distribution, by William Sealy Gosset (Student) r = 0.0578
Non Normal distribution, by Spearman r = 0.0024
DistributionNon
Normal
NormalNormalNormalNormalNormalNormalNormal
All questions
All questions
What actions have been taken in relation to staff in the last month
What actions have been taken in relation to staff in the last month
Answer 1-
Weak positive
0.1333
Weak positive
0.0225
Weak negative
-0.0559
Weak negative
-0.1033
Weak positive
0.0710
Weak positive
0.0335
Weak negative
-0.0588
Answer 2-
Weak negative
-0.0227
Weak negative
-0.0637
Weak positive
0.0085
Weak positive
0.0017
Weak negative
-0.0197
Weak negative
-0.0047
Weak positive
0.0767
Answer 3-
Weak positive
0.0297
Weak positive
0.0126
Weak positive
0.0261
Weak negative
-0.0256
Weak positive
0.0354
Weak negative
-0.0509
Weak negative
-0.0185
Answer 4-
Weak positive
0.0351
Weak positive
0.0566
Weak positive
0.0028
Weak negative
-0.0140
Weak positive
0.0281
Weak negative
-0.0584
Weak negative
-0.0301
Answer 5-
Weak negative
-0.0053
Weak positive
0.0321
Weak negative
-0.0516
Weak positive
0.0332
Weak positive
0.0246
Weak negative
-0.0059
Weak negative
-0.0243
Answer 6-
Weak negative
-0.0208
Weak positive
0.0200
Weak positive
0.0495
Weak positive
0.0006
Weak negative
-0.0027
Weak negative
-0.0086
Weak negative
-0.0322
Answer 7-
Weak positive
0.0503
Weak positive
0.0307
Weak negative
-0.0084
Weak negative
-0.0618
Weak positive
0.0126
Weak negative
-0.0067
Weak positive
0.0025
Answer 8-
Weak negative
-0.0076
Weak negative
-0.0066
Weak positive
0.0003
Weak negative
-0.0527
Weak negative
-0.0270
Weak positive
0.0633
Weak positive
0.0285
Answer 9-
Weak negative
-0.0435
Weak positive
0.0541
Weak positive
0.0294
Weak positive
0.0613
Weak negative
-0.0588
Weak negative
-0.0191
Weak negative
-0.0218


Export to MS Excel
This functionality will be available in your own VUCA polls
Ok


2023.12.09
Valerii Kosenko
Product owner SaaS pet project SDTEST®

Valerii was qualified as a social pedagogue-psychologist in 1993 and has since applied his knowledge in project management.
Valerii obtained a Master's degree and the project and program manager qualification in 2013. During his Master's program, he became familiar with Project Roadmap (GPM Deutsche Gesellschaft für Projektmanagement e. V.) and Spiral Dynamics.
Valerii took various Spiral Dynamics tests and used his knowledge and experience to adapt the current version of SDTEST.
Valerii is the author of exploring the uncertainty of the V.U.C.A. concept using Spiral Dynamics and mathematical statistics in psychology, more than 20 international polls.
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Hi there! Let me ask you, do you already familiar with Spiral Dynamics?