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 = 0.033
Dáileadh Gnáth, le William Sealy Gosset (Mac Léinn) r = 0.033
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
0.0532
Dearfach lag
0.0292
Diúltach lag
-0.0175
Dearfach lag
0.0919
Dearfach lag
0.0301
Diúltach lag
-0.0114
Diúltach lag
-0.1523
Answer 2-
Dearfach lag
0.0208
Diúltach lag
-0.0014
Diúltach lag
-0.0431
Dearfach lag
0.0641
Dearfach lag
0.0449
Dearfach lag
0.0130
Diúltach lag
-0.0931
Answer 3-
Diúltach lag
-0.0053
Diúltach lag
-0.0130
Diúltach lag
-0.0406
Diúltach lag
-0.0456
Dearfach lag
0.0474
Dearfach lag
0.0793
Diúltach lag
-0.0204
Answer 4-
Dearfach lag
0.0427
Dearfach lag
0.0328
Diúltach lag
-0.0200
Dearfach lag
0.0158
Dearfach lag
0.0306
Dearfach lag
0.0217
Diúltach lag
-0.0980
Answer 5-
Dearfach lag
0.0255
Dearfach lag
0.1255
Dearfach lag
0.0143
Dearfach lag
0.0732
Diúltach lag
-0.0019
Diúltach lag
-0.0196
Diúltach lag
-0.1747
Answer 6-
Diúltach lag
-0.0027
Dearfach lag
0.0074
Diúltach lag
-0.0629
Diúltach lag
-0.0074
Dearfach lag
0.0199
Dearfach lag
0.0835
Diúltach lag
-0.0324
Answer 7-
Dearfach lag
0.0110
Dearfach lag
0.0371
Diúltach lag
-0.0688
Diúltach lag
-0.0227
Dearfach lag
0.0471
Dearfach lag
0.0650
Diúltach lag
-0.0523
Answer 8-
Dearfach lag
0.0693
Dearfach lag
0.0825
Diúltach lag
-0.0321
Dearfach lag
0.0139
Dearfach lag
0.0351
Dearfach lag
0.0147
Diúltach lag
-0.1369
Answer 9-
Dearfach lag
0.0643
Dearfach lag
0.1659
Dearfach lag
0.0082
Dearfach lag
0.0699
Diúltach lag
-0.0136
Diúltach lag
-0.0513
Diúltach lag
-0.1826
Answer 10-
Dearfach lag
0.0760
Dearfach lag
0.0730
Diúltach lag
-0.0219
Dearfach lag
0.0254
Dearfach lag
0.0318
Diúltach lag
-0.0138
Diúltach lag
-0.1318
Answer 11-
Dearfach lag
0.0571
Dearfach lag
0.0514
Diúltach lag
-0.0099
Dearfach lag
0.0077
Dearfach lag
0.0206
Dearfach lag
0.0308
Diúltach lag
-0.1211
Answer 12-
Dearfach lag
0.0373
Dearfach lag
0.1013
Diúltach lag
-0.0357
Dearfach lag
0.0357
Dearfach lag
0.0243
Dearfach lag
0.0296
Diúltach lag
-0.1524
Answer 13-
Dearfach lag
0.0621
Dearfach lag
0.1036
Diúltach lag
-0.0438
Dearfach lag
0.0273
Dearfach lag
0.0414
Dearfach lag
0.0176
Diúltach lag
-0.1608
Answer 14-
Dearfach lag
0.0703
Dearfach lag
0.1007
Dearfach lag
9.54E-5
Diúltach lag
-0.0088
Diúltach lag
-0.0011
Dearfach lag
0.0084
Diúltach lag
-0.1174
Answer 15-
Dearfach lag
0.0554
Dearfach lag
0.1349
Diúltach lag
-0.0418
Dearfach lag
0.0179
Diúltach lag
-0.0165
Dearfach lag
0.0219
Diúltach lag
-0.1181
Answer 16-
Dearfach lag
0.0581
Dearfach lag
0.0255
Diúltach lag
-0.0388
Diúltach lag
-0.0407
Dearfach lag
0.0654
Dearfach lag
0.0283
Diúltach lag
-0.0714


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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