The ask o he digi al coach is o suppo he membe s o he o ganisa ion in de eloping and implemen ing
AI solu ions in o de o imp o e quali y managemen .
In doing so, i is c ucial o hem o know wha esis ances and po en ials exis in he de elopmen and
implemen a ion in each indi idual case o a small and medium-sized en e p ise (SME).
• Wha challenges o esis ance could a ise in he de elopmen and implemen a ion o AI solu ions in
he con ex o p omo ing quali y managemen ?
• How should hese esis ances be weigh ed?
• To wha ex en a e hese esis ances classi ied as changeable by he espec i e membe s o he
o ganisa ion?
• Which ac i i ies o ac ion s a egies p o e o be pa icula ly sui able o dealing wi h esis ance
app op ia ely?
You opinion is impo an o us!
How do you a e he ollowing po en ials and esis ances in e ms o hei impo ance?
In you opinion, o wha ex en can he ac o s men ioned be u ilised o expanded (in ela ion o
po en ial) and changed (in ela ion o esis ance)?
0= no
a all
IMPORTANCE
no impo an Ve y impo an
=5
FACTORS REF. Business Unde s anding
UTILISATION/EXPANDABILITY (FOR
POTENTIAL)
CHANGEABILITY (FOR RESISTANCE)
None
Opinion
0%= ga
No high
Ve y high =100%
0
1
2
3
4
5
Po en ials
Χ
0
20
40
60
80
100
The e is al eady expe ience wi h ega d o digi alisa ion
p ojec s
The e is al eady su icien da a collec ion and analysis
Employees a e ained o u u e asks wi h suppo
sys ems
Cos s a e sa ed h ough he use o AI
AI can se e as a solu ion o a speci ic challenge
(conc e e ision)
The membe s o he o ganisa ion ha e su icien AI
knowledge
We ha e su icien skills in dealing wi h AI solu ions in
ou o ganisa ion
0
1
2
3
4
5
Resis o s
Χ
0
20
40
60
80
100
I is di icul o de ine he business p oblem ha o ms he
basis o he AI use case.
The e is no budge a ailable o u u e quali ica ion
equi emen s and aining cou ses
The e is no s a egy on how o deal wi h AI in he u u e.
The business objec i es equi ed o he implemen a ion
o AI solu ions a e no clea ly o mula ed
Subsc ibe o DeepL P o o edi his documen .
Visi www.DeepL.com/p o o mo e in o ma ion.
The bene i s o AI solu ions in e ms o cos s a e di icul
o measu e
The e a e ese a ions abou AI because membe s o
he o ganisa ion ea o hei jobs
Wha solu ions do you know o u ilising he po en ial and dealing wi h esis ance?
(Speci y as selec i ely as possible)
Gene al commen s / ques ions ega ding business unde s anding
Which ques ions emain unanswe ed in he Business Unde s anding (Which) ( ools) (help) (you) ( u he ) (and)
(why?)?
1.
2.
3.
How do you a e he ollowing po en ials and esis ances in e ms o hei impo ance?
In you opinion, o wha ex en can he ac o s men ioned be u ilised o expanded (in e ms o po en ial) and
changed (in e ms o esis ance)?
Whe e do you see he s eng hs and weaknesses o he business unde s anding ools? And i so, which opics a e he mos
impo an o you? mos impo an ?
How do you a e he ollowing po en ials and esis ances in e ms o hei impo ance?
In you opinion, o wha ex en can he ac o s men ioned be u ilised o expanded (in e ms o po en ial) and
changed (in e ms o esis ance)?
IMPORTANCE
0= no impo an a all Ve y impo an
=5
FACTORS REF. Da a Unde s anding
UTILISATION/EXPANDABILITY (FOR
POTENTIAL)
CHANGEABILITY (FOR RESISTANCE)
None
Opinion
0%= no high a all Ve y high =100%
0 1 2 3 4
5
Po en ials
Χ 0 20 40 60 80 100
The da a quali y is e y good, which he o ganisa ion
can d aw on du ing implemen a ion
The membe s o he o ganisa ion know which da a is
equi ed.
The da a equi ed o he AI solu ion is a ailable in su icien
quan i ies.
AI solu ions a e al eady scaled and used ac oss he
o ganisa ion
The e is al eady su icien da a quali y and da a analysis.
0
1
2
3
4
5
Resis o s
Χ
0
20
40
60
80
100
The e a e ese a ions because he o ganisa ion membe s
do no us he new echnology.
The e a e conce ns among membe s o he o ganisa ion
abou he secu i y o he da a
The e is no s a egy o da a use and quali y assu ance in
he o ganisa ion.
The impo ance o collec ing da a is no ye gene ally
p esen in he o ganisa ion.
The e a e no expe s in he o ganisa ion who can
analyse and assess he da a.
The e a e insu icien ime and inancial esou ces a ailable
o conduc in e iews wi h s akeholde s.
The e a e s ic ules in he coun y ega ding he
es ablishmen o new se ices.
The need o adap ma ke esea ch ques ionnai es and
segmen a ions o coun y-speci ic ci cums ances is high.
Wha solu ions do you know o u ilising po en ial and dealing wi h esis ance?
(Speci y as selec i ely as possible)
Gene al commen s / ques ions ega ding da a unde s anding
Wha ques ions emain unanswe ed when unde s anding da a? Which ools help you and why?
1.
2.
3.
How do you a e he ollowing po en ials and esis ances in e ms o hei impo ance?
In you opinion, o wha ex en can he ac o s men ioned be u ilised o expanded (in e ms o po en ial) and
changed (in e ms o esis ance)?
Whe e do you see he s eng hs and weaknesses? (Is he e a (need) ( o ) ( u he ) ( ools?)
I yes, which key opics a e mos impo an o you?
How do you a e he ollowing po en ials and esis ances in e ms o hei impo ance?
In you opinion, o wha ex en can he ac o s men ioned be u ilised o expanded (in e ms o po en ial) and
changed (in e ms o esis ance)?
IMPORTANCE
0= no impo an a all Ve y impo an
=5
FACTORS CONCERNING Da a
p epa a ion
UTILISATION/EXPANDABILITY (FOR
POTENTIALS)
CHANGEABILITY (FOR RESISTANCE)
None
Opinion
g 0%= no high a all Ve y high =100%
0 1 2 3 4
5
Po en ials
Χ 0 20 40 60 80 100
The o ganisa ion egula ly analyses da a in o de o
make decisions
I is clea whe e he da a used o AI solu ions comes
om.
The da a sou ces o po en ial AI solu ions a e us wo hy
The o ganisa ion has usable da a se s e en a e
cleansing he da a
Key igu es a e al eady a ailable o analysis
The e a e expe s in he o ganisa ion who can pe o m
da a cleansing i equi ed.
A ne wo k o expe s has been es ablished ha
can be called upon when equi ed o he de elopmen o AI
solu ions.
can be called upon when de eloping AI solu ions.
Adap ing he da a o ma is e y simple in he speci ic
indi idual case o he AI solu ion
0
1
2
3
4
5
Resis o s
Χ
0
20
40
60
80
100
The p oblem is ha expe s a e no a ailable o no
a ailable in su icien numbe s.
The p e equisi es o c oss-depa men al collabo a ion
wi hin he o ganisa ion a e no me .
The da a used o he AI solu ion is only a ailable in he
o ganisa ion in poo quali y
The esou ces equi ed o ec ui expe s o he use o
AI solu ions a e oo high.
The e is no ne wo k a ailable o access po en ial
expe s.
The amewo k condi ions, e.g. in e ms o ime, p o e o
be di icul o ind expe s.
Wha solu ions do you know o u ilising po en ial and dealing wi h esis ance? (Speci y as selec i ely as possible)
Gene al commen s / ques ions ega ding da a p epa a ion
Which ques ions emain unanswe ed in da a
p epa a ion?
Which ools help you and why?
1.
2.
3.
How do you a e he ollowing po en ials and esis ances in e ms o hei impo ance?
In you opinion, o wha ex en can he ac o s men ioned be u ilised o expanded (in e ms o po en ial) and
changed (in e ms o esis ance)?
Is he e a need o u he da a p epa a ion
ools? Whe e do you see he s eng hs and weaknesses? (P epa a ion) (?)
I yes, which key opics a e mos impo an o you?
mos impo an o you?
QUESTIONS ABOUT YOURSELF
Wha asks do you ha e in he de elopmen and implemen a ion o AI solu ions? (mul iple choice possible)
O he : ...
CEO o he company
CDO/ CFO o he company
O ganisa ion o he implemen a ion o AI solu ions
P oduc ion manage o he company
IT and AI specialis
You opinion is impo an o us!
How do you a e he ollowing po en ials and obs acles in e ms o hei impo ance?
In you opinion, o wha ex en can he ac o s men ioned be u ilised o expanded (in e ms o
po en ial) and changed (in e ms o esis ance)?
0= no
a all
IMPORTANCE
no impo an Ve y impo an
=5
FACTORS BEZ. Modelling
UTILISATION/EXPANDABILITY (FOR
POTENTIALS)
CHANGEABILITY (FOR
RESISTANCES)
None
Opinion
0%= ga
no high
Ve y high =100%
0
1
2
3
4
5
Po en ials
Χ
0
20
40
60
80
100
We ha e al eady gained expe ience wi h simple AI
models o s a is ical analyses.
The p og ammes and compu ing esou ces equi ed o
model de elopmen a e a ailable o easily accessible.
Ou employees ha e basic knowledge o c ea e o
unde s and AI models.
We al eady use ini ial key igu es ha could be ele an o
model de elopmen .
We can unde s and how ini ial AI models a i e a hei
esul s.
0
1
2
3
4
5
Resis o s
Χ
0
20
40
60
80
100
We ind i di icul o selec he igh AI model o ou
speci ic p oblem.
We lack he ime and inancial esou ces as well as he
budge o aining and ex e nal suppo .
We don' ye ha e a clea idea o how o ensu e he quali y
o he AI models du ing de elopmen .
The po en ial bene i s o he models a e di icul o us o
exp ess in igu es be o e implemen a ion.
We don' ha e a con ac pe son o ne wo k ha can
suppo us wi h ques ions abou AI modelling.
Ou eams a e conce ned ha AI models a e oo
complex and ha he way hey wo k is no anspa en .
Wha solu ions do you know o o u ilising he po en ial and dealing wi h esis ance?
(Speci y as selec i ely as possible)
1.
2.
3.
How do you a e he ollowing po en ials and esis ances in e ms o hei impo ance?
In you opinion, o wha ex en can he ac o s men ioned be u ilised o expanded (in e ms o po en ial) and
changed (in e ms o esis ance)?
Whe e do you see he s eng hs and weaknesses o he modelling ools? And i so, which key opics a e mos impo an o
you? mos impo an o you?
