tástáil bhunaithe leabhair «Spiral
Dynamics: Mastering Values, Leadership,
and Change» (ISBN-13: 978-1405133562)
Urraitheoirí

The Tale of the Tall Oak

Once upon a time, there was a tiny oak tree sapling named Peety. Peety dreamed of growing up into a mighty oak tree. 


Each year, Peety grew a little bit taller. He stretched his branches toward the sun and felt his trunk thicken as he grew. 


Over many years, Peety grew from a sapling into a young tree and finally into a tall, mature oak! He was so tall that he could see over the whole forest.


Peety noticed that the other tall oak trees had thick trunks, too. His friend Paul reached high into the sky just like Peety. Paul's trunk was thick and sturdy at the base. 


The small saplings that were sprouting had skinny little trunks. But Peety knew that would change over time as they grew taller.


Peety realized that, just like him, the taller an oak tree was, the thicker its trunk became. 


So even though the forest was filled with all different sizes of oak trees, Peety noticed a pattern - a correlation between tree height and trunk width. The tall trees always had thicker trunks, while the small saplings had skinny trunks. This was how pine trees grew strong enough to reach great heights! 


If you record how a tree grows - its height and trunk thickness - and plot it on a picture or graph, then the correlation is when these two things change together. That is, if you see that one is increasing, the other is also increasing, and vice versa.


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


Imagine also giving a "Fears" poll. It asks people to rate different fears from 0 (not scary) to 5 (very scary). 


Now imagine 100 people who took both tests. You could match up each person's SDTEST® colors with their rated fears.


If people high in Blue values feared uncertainty more, that insight ties values to perceptions. Blue people may resist change more.


Or if Orange achievers feared failure most, that reveals their drive. They may overwork to avoid mistakes.


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 how your hobbies show what activities you enjoy most. 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 “Fears“. The full results of our VUCA poll “Fears“ are available for free in the FAQ section after login or registration.


Eagla

Tír
Teanga
-
Mail
Athchúrsáil
Luach criticiúil an chomhéifeacht comhghaoil
Dáileadh Gnáth, le William Sealy Gosset (Mac Léinn) r = 0.0331
Dáileadh Gnáth, le William Sealy Gosset (Mac Léinn) r = 0.0331
Dáileadh Neamh -Ghnáth, le Spearman r = 0.0013
ImdháileadhNeamhghnáchNeamhghnáchNeamhghnáchGnáth-Gnáth-Gnáth-Gnáth-Gnáth-
Gach ceist
Gach ceist
Is é an t-eagla is mó atá agam ná
Is é an t-eagla is mó atá agam ná
Answer 1-
Dearfach lag
0.0563
Dearfach lag
0.0317
Diúltach lag
-0.0161
Dearfach lag
0.0907
Dearfach lag
0.0298
Diúltach lag
-0.0126
Diúltach lag
-0.1537
Answer 2-
Dearfach lag
0.0216
Dearfach lag
0.0002
Diúltach lag
-0.0458
Dearfach lag
0.0654
Dearfach lag
0.0445
Dearfach lag
0.0124
Diúltach lag
-0.0937
Answer 3-
Diúltach lag
-0.0035
Diúltach lag
-0.0111
Diúltach lag
-0.0421
Diúltach lag
-0.0456
Dearfach lag
0.0466
Dearfach lag
0.0786
Diúltach lag
-0.0201
Answer 4-
Dearfach lag
0.0435
Dearfach lag
0.0353
Diúltach lag
-0.0181
Dearfach lag
0.0145
Dearfach lag
0.0301
Dearfach lag
0.0197
Diúltach lag
-0.0979
Answer 5-
Dearfach lag
0.0299
Dearfach lag
0.1279
Dearfach lag
0.0136
Dearfach lag
0.0730
Diúltach lag
-0.0007
Diúltach lag
-0.0207
Diúltach lag
-0.1746
Answer 6-
Diúltach lag
-0.0004
Dearfach lag
0.0082
Diúltach lag
-0.0629
Diúltach lag
-0.0078
Dearfach lag
0.0193
Dearfach lag
0.0830
Diúltach lag
-0.0318
Answer 7-
Dearfach lag
0.0122
Dearfach lag
0.0381
Diúltach lag
-0.0686
Diúltach lag
-0.0242
Dearfach lag
0.0471
Dearfach lag
0.0636
Diúltach lag
-0.0513
Answer 8-
Dearfach lag
0.0698
Dearfach lag
0.0849
Diúltach lag
-0.0321
Dearfach lag
0.0146
Dearfach lag
0.0345
Dearfach lag
0.0130
Diúltach lag
-0.1368
Answer 9-
Dearfach lag
0.0665
Dearfach lag
0.1674
Dearfach lag
0.0092
Dearfach lag
0.0691
Diúltach lag
-0.0128
Diúltach lag
-0.0528
Diúltach lag
-0.1812
Answer 10-
Dearfach lag
0.0778
Dearfach lag
0.0755
Diúltach lag
-0.0180
Dearfach lag
0.0231
Dearfach lag
0.0346
Diúltach lag
-0.0146
Diúltach lag
-0.1298
Answer 11-
Dearfach lag
0.0584
Dearfach lag
0.0524
Diúltach lag
-0.0096
Dearfach lag
0.0081
Dearfach lag
0.0199
Dearfach lag
0.0318
Diúltach lag
-0.1197
Answer 12-
Dearfach lag
0.0380
Dearfach lag
0.1042
Diúltach lag
-0.0352
Dearfach lag
0.0357
Dearfach lag
0.0254
Dearfach lag
0.0286
Diúltach lag
-0.1515
Answer 13-
Dearfach lag
0.0644
Dearfach lag
0.1057
Diúltach lag
-0.0448
Dearfach lag
0.0268
Dearfach lag
0.0416
Dearfach lag
0.0169
Diúltach lag
-0.1600
Answer 14-
Dearfach lag
0.0717
Dearfach lag
0.1026
Diúltach lag
-0.0006
Diúltach lag
-0.0089
Diúltach lag
-0.0012
Dearfach lag
0.0080
Diúltach lag
-0.1168
Answer 15-
Dearfach lag
0.0549
Dearfach lag
0.1375
Diúltach lag
-0.0420
Dearfach lag
0.0178
Diúltach lag
-0.0160
Dearfach lag
0.0216
Diúltach lag
-0.1180
Answer 16-
Dearfach lag
0.0591
Dearfach lag
0.0273
Diúltach lag
-0.0386
Diúltach lag
-0.0399
Dearfach lag
0.0653
Dearfach lag
0.0282
Diúltach lag
-0.0708


Easpórtáil go MS Excel
Beidh an fheidhmiúlacht seo ar fáil i do vótaíochtaí VUCA féin
Go maith

2023.11.22
Valerii Kosenko
Úinéir an Táirge SaaS Pet Project Sdtest®

Bhí Valerii cáilithe mar shíceolaí oideolaíoch sóisialta i 1993 agus ó shin i leith chuir sé a chuid eolais i bhfeidhm i mbainistíocht tionscadail.
Fuair ​​Valerii céim mháistreachta agus cáilíocht an tionscadail agus an bhainisteora cláir in 2013. Le linn a chláir mháistir, bhí sé eolach ar threochlár Project (GPM Deutsche Gesellschaft Für Projektmanagement e. V.) agus dinimic Spiral.
Ghlac Valerii tástálacha éagsúla dinimic bíseach agus d'úsáid sé a chuid eolais agus taithí chun an leagan reatha de SDTest a oiriúnú.
Is é Valerii údar iniúchadh a dhéanamh ar neamhchinnteacht an V.U.C.A. Coincheap ag baint úsáide as dinimic bíseach agus staitisticí matamaiticiúla i síceolaíocht, níos mó ná 20 vótaíocht idirnáisiúnta.
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