基于本书测试 «Spiral Dynamics: Mastering
Values, Leadership, and Change»
(ISBN-13: 978-1405133562)
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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.


上个月与人员有关的公司的行动(是 /否)

圖表相关性
?
这是民意调查的响应与螺旋动力测试颜色之间的关系
VUCA
?
这是表格中相关性的新接口视图,通过螺旋动力学水平,波动性,不确定性,复杂性和歧义(V.U.C.A.)通过投票的响应与螺旋动力学颜色之间的正相关和负相关依赖性显示
國家
語言
-
Mail
重新计算
的相关系数的临界值
正态分布,威廉·西莉·格塞特(William Sealy Gosset)(学生) r = 0.0513
正态分布,威廉·西莉·格塞特(William Sealy Gosset)(学生) r = 0.0513
非正态分布,Spearman r = 0.0021
分配非正常普通的非正常普通的普通的普通的普通的普通的
所有问题
所有问题
上个月与员工有关的行动已采取了什么行动
上个月与员工有关的行动已采取了什么行动
Answer 1-
弱阳性
0.1198
弱阳性
0.0270
弱负
-0.0440
弱负
-0.0911
弱阳性
0.0366
弱阳性
0.0224
弱负
-0.0284
Answer 2-
弱负
-0.0043
弱负
-0.0435
弱负
-0.0056
弱负
-0.0099
弱负
-0.0106
弱负
-0.0082
弱阳性
0.0688
Answer 3-
弱阳性
0.0297
弱负
-0.0167
弱阳性
0.0178
弱负
-0.0157
弱阳性
0.0361
弱负
-0.0357
弱负
-0.0102
Answer 4-
弱阳性
0.0310
弱阳性
0.0576
弱负
-0.0088
弱负
-0.0303
弱阳性
0.0208
弱负
-0.0324
弱负
-0.0177
Answer 5-
弱负
-0.0102
弱阳性
0.0411
弱负
-0.0344
弱阳性
0.0143
弱阳性
0.0225
弱负
-0.0119
弱负
-0.0216
Answer 6-
弱负
-0.0258
弱负
-0.0049
弱阳性
0.0461
弱负
-0.0084
弱阳性
0.0004
弱阳性
0.0086
弱负
-0.0210
Answer 7-
弱阳性
0.0245
弱阳性
0.0332
弱负
-0.0199
弱负
-0.0333
弱阳性
0.0114
弱阳性
0.0044
弱负
-0.0054
Answer 8-
弱负
-0.0151
弱负
-0.0038
弱负
-0.0111
弱负
-0.0293
弱负
-0.0268
弱阳性
0.0616
弱阳性
0.0242
Answer 9-
弱负
-0.0561
弱阳性
0.0437
弱阳性
0.0370
弱阳性
0.0622
弱负
-0.0532
弱负
-0.0101
弱负
-0.0285


出口到MS Excel
您自己的VUCA民意调查中可以使用此功能
好的


2023.12.09
FearpersonqualitiesprojectorganizationalstructureRACIresponsibilitymatrixCritical ChainProject Managementfocus factorJiraempathyleadersbossGermanyChinaPolicyUkraineRussiawarvolatilityuncertaintycomplexityambiguityVUCArelocatejobproblemcountryreasongive upobjectivekeyresultmathematicalpsychologyMBTIHR metricsstandardDEIcorrelationriskscoringmodelGame TheoryPrisoner's Dilemma
Valerii Kosenko
产品负责人 SaaS SDTEST®

Valerii 于 1993 年获得社会教育心理学家资格,此后将他的知识应用于项目管理。
Valerii 于 2013 年获得硕士学位以及项目和项目经理资格。在硕士学习期间,他熟悉了项目路线图 (GPM Deutsche Gesellschaft für Projektmanagement e. V.) 和 Spiral Dynamics。
Valerii 是探讨 V.U.C.A. 不确定性的作者。使用螺旋动力学和心理学数理统计的概念,以及 38 个国际民意调查。
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你好呀!让我问你,您已经熟悉螺旋动态吗?