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
0.0562
Dearfach lag
0.0311
Diúltach lag
-0.0164
Dearfach lag
0.0903
Dearfach lag
0.0301
Diúltach lag
-0.0120
Diúltach lag
-0.1534
Answer 2-
Dearfach lag
0.0217
Dearfach lag
0.0011
Diúltach lag
-0.0455
Dearfach lag
0.0660
Dearfach lag
0.0440
Dearfach lag
0.0117
Diúltach lag
-0.0942
Answer 3-
Diúltach lag
-0.0034
Diúltach lag
-0.0104
Diúltach lag
-0.0419
Diúltach lag
-0.0451
Dearfach lag
0.0462
Dearfach lag
0.0780
Diúltach lag
-0.0204
Answer 4-
Dearfach lag
0.0436
Dearfach lag
0.0362
Diúltach lag
-0.0177
Dearfach lag
0.0150
Dearfach lag
0.0296
Dearfach lag
0.0189
Diúltach lag
-0.0984
Answer 5-
Dearfach lag
0.0298
Dearfach lag
0.1270
Dearfach lag
0.0133
Dearfach lag
0.0724
Diúltach lag
-0.0002
Diúltach lag
-0.0199
Diúltach lag
-0.1742
Answer 6-
Diúltach lag
-0.0003
Dearfach lag
0.0089
Diúltach lag
-0.0627
Diúltach lag
-0.0074
Dearfach lag
0.0190
Dearfach lag
0.0825
Diúltach lag
-0.0321
Answer 7-
Dearfach lag
0.0123
Dearfach lag
0.0388
Diúltach lag
-0.0684
Diúltach lag
-0.0238
Dearfach lag
0.0468
Dearfach lag
0.0631
Diúltach lag
-0.0517
Answer 8-
Dearfach lag
0.0699
Dearfach lag
0.0857
Diúltach lag
-0.0318
Dearfach lag
0.0150
Dearfach lag
0.0341
Dearfach lag
0.0125
Diúltach lag
-0.1372
Answer 9-
Dearfach lag
0.0666
Dearfach lag
0.1681
Dearfach lag
0.0094
Dearfach lag
0.0694
Diúltach lag
-0.0131
Diúltach lag
-0.0533
Diúltach lag
-0.1815
Answer 10-
Dearfach lag
0.0776
Dearfach lag
0.0744
Diúltach lag
-0.0185
Dearfach lag
0.0224
Dearfach lag
0.0352
Diúltach lag
-0.0135
Diúltach lag
-0.1293
Answer 11-
Dearfach lag
0.0585
Dearfach lag
0.0531
Diúltach lag
-0.0094
Dearfach lag
0.0086
Dearfach lag
0.0195
Dearfach lag
0.0313
Diúltach lag
-0.1200
Answer 12-
Dearfach lag
0.0378
Dearfach lag
0.1030
Diúltach lag
-0.0357
Dearfach lag
0.0350
Dearfach lag
0.0261
Dearfach lag
0.0297
Diúltach lag
-0.1510
Answer 13-
Dearfach lag
0.0642
Dearfach lag
0.1044
Diúltach lag
-0.0454
Dearfach lag
0.0259
Dearfach lag
0.0424
Dearfach lag
0.0183
Diúltach lag
-0.1595
Answer 14-
Dearfach lag
0.0718
Dearfach lag
0.1034
Diúltach lag
-0.0003
Diúltach lag
-0.0085
Diúltach lag
-0.0016
Dearfach lag
0.0074
Diúltach lag
-0.1172
Answer 15-
Dearfach lag
0.0550
Dearfach lag
0.1382
Diúltach lag
-0.0418
Dearfach lag
0.0181
Diúltach lag
-0.0163
Dearfach lag
0.0211
Diúltach lag
-0.1183
Answer 16-
Dearfach lag
0.0591
Dearfach lag
0.0276
Diúltach lag
-0.0384
Diúltach lag
-0.0397
Dearfach lag
0.0651
Dearfach lag
0.0280
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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