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
0.0569
Dearfach lag
0.0313
Diúltach lag
-0.0161
Dearfach lag
0.0906
Dearfach lag
0.0297
Diúltach lag
-0.0118
Diúltach lag
-0.1544
Answer 2-
Dearfach lag
0.0225
Dearfach lag
0.0002
Diúltach lag
-0.0450
Dearfach lag
0.0644
Dearfach lag
0.0442
Dearfach lag
0.0128
Diúltach lag
-0.0940
Answer 3-
Diúltach lag
-0.0030
Diúltach lag
-0.0116
Diúltach lag
-0.0411
Diúltach lag
-0.0465
Dearfach lag
0.0466
Dearfach lag
0.0786
Diúltach lag
-0.0200
Answer 4-
Dearfach lag
0.0440
Dearfach lag
0.0354
Diúltach lag
-0.0189
Dearfach lag
0.0150
Dearfach lag
0.0299
Dearfach lag
0.0204
Diúltach lag
-0.0986
Answer 5-
Dearfach lag
0.0309
Dearfach lag
0.1278
Dearfach lag
0.0137
Dearfach lag
0.0728
Diúltach lag
-0.0011
Diúltach lag
-0.0195
Diúltach lag
-0.1757
Answer 6-
Diúltach lag
-0.0001
Dearfach lag
0.0086
Diúltach lag
-0.0623
Diúltach lag
-0.0085
Dearfach lag
0.0193
Dearfach lag
0.0829
Diúltach lag
-0.0319
Answer 7-
Dearfach lag
0.0127
Dearfach lag
0.0385
Diúltach lag
-0.0683
Diúltach lag
-0.0246
Dearfach lag
0.0468
Dearfach lag
0.0640
Diúltach lag
-0.0519
Answer 8-
Dearfach lag
0.0700
Dearfach lag
0.0853
Diúltach lag
-0.0322
Dearfach lag
0.0146
Dearfach lag
0.0344
Dearfach lag
0.0132
Diúltach lag
-0.1370
Answer 9-
Dearfach lag
0.0670
Dearfach lag
0.1680
Dearfach lag
0.0087
Dearfach lag
0.0692
Diúltach lag
-0.0132
Diúltach lag
-0.0518
Diúltach lag
-0.1822
Answer 10-
Dearfach lag
0.0784
Dearfach lag
0.0758
Diúltach lag
-0.0199
Dearfach lag
0.0245
Dearfach lag
0.0342
Diúltach lag
-0.0133
Diúltach lag
-0.1308
Answer 11-
Dearfach lag
0.0586
Dearfach lag
0.0528
Diúltach lag
-0.0091
Dearfach lag
0.0074
Dearfach lag
0.0198
Dearfach lag
0.0318
Diúltach lag
-0.1198
Answer 12-
Dearfach lag
0.0392
Dearfach lag
0.1042
Diúltach lag
-0.0353
Dearfach lag
0.0357
Dearfach lag
0.0249
Dearfach lag
0.0297
Diúltach lag
-0.1526
Answer 13-
Dearfach lag
0.0646
Dearfach lag
0.1052
Diúltach lag
-0.0444
Dearfach lag
0.0266
Dearfach lag
0.0416
Dearfach lag
0.0176
Diúltach lag
-0.1605
Answer 14-
Dearfach lag
0.0714
Dearfach lag
0.1026
Diúltach lag
-0.0002
Diúltach lag
-0.0090
Diúltach lag
-0.0012
Dearfach lag
0.0086
Diúltach lag
-0.1174
Answer 15-
Dearfach lag
0.0558
Dearfach lag
0.1369
Diúltach lag
-0.0419
Dearfach lag
0.0176
Diúltach lag
-0.0163
Dearfach lag
0.0222
Diúltach lag
-0.1183
Answer 16-
Dearfach lag
0.0592
Dearfach lag
0.0275
Diúltach lag
-0.0384
Diúltach lag
-0.0402
Dearfach lag
0.0652
Dearfach lag
0.0283
Diúltach lag
-0.0710


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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