Ionu Ri i, Raul; Ionica, And eea C is ina; Leba, Monica
A icle
T ans o ma i e Pa adigms in IT P ojec Managemen : A Schola ly
Explo a ion o SAFe® and Azu e De Ops In eg a ion o Enhanced
Inno a ion and S a egic Agili y
ENTRENOVA - ENTe p ise REsea ch InNOVA ion
P o ided in Coope a ion wi h:
IRENET - Socie y o Ad ancing Inno a ion and Resea ch in Economy, Zag eb
Sugges ed Ci a ion: Ionu Ri i, Raul; Ionica, And eea C is ina; Leba, Monica (2025) : T ans o ma i e
Pa adigms in IT P ojec Managemen : A Schola ly Explo a ion o SAFe® and Azu e De Ops
In eg a ion o Enhanced Inno a ion and S a egic Agili y, ENTRENOVA - ENTe p ise REsea ch
InNOVA ion, ISSN 2706-4735, IRENET - Socie y o Ad ancing Inno a ion and Resea ch in Economy,
Zag eb, Vol. 10, Iss. 1, pp. 347-359,
h ps://doi.o g/10.54820/en eno a-2024-0029
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347
ENTRENOVA - ENTe p ise REsea ch InNOVA ion
Vol. 10 No. 1
T ans o ma i e Pa adigms in IT P ojec
Managemen : A Schola ly Explo a ion o
SAFe® and Azu e De Ops In eg a ion o
Enhanced Inno a ion and S a egic Agili y
Raul Ionu Ri i
Uni e si y o Pe osani, Romania
And eea C is ina Ionica
Uni e si y o Pe osani, Romania
Monica Leba
Uni e si y o Pe osani, Romania
Abs ac
This scien i ic in es iga ion p esen s a g oundb eaking explo a ion o in eg a ing he
Scaled Agile F amewo k® (SAFe®) wi h Azu e De Ops, se ing a new benchma k o
inno a ion and s a egic agili y in IT p ojec managemen . The s udy me iculously
examines how his usion op imizes ope a ional e iciency and os e s a cul u e o
con inuous imp o emen and collabo a ion ac oss di e se p ojec eams. Adop ing a
mul i-me ic esea ch app oach, i assesses he ans o ma i e po en ial o combining
he Agile p inciples o SAFe® wi h he obus ools and au oma ion capabili ies o Azu e
De Ops. This syn hesis is p oposed as a dynamic model o managing complex IT
p ojec s whe e adi ional me hodologies ail o add ess he apid pace o
echnological ad ances and ma ke equi emen s. Key indings highligh he
imp o ed lexibili y, isibili y, and p oduc i i y achie ed h ough his in eg a ion,
highligh ing i s impo ance in achie ing success ul p ojec ou comes. I adds he a ea
o s a egic ecommenda ions o IT leade s ying o na iga e he challenges o digi al
ans o ma ion, ad oca ing adop ing hese inno a i e p ac ices as a co ne s one o
u u e excellence in p ojec managemen . This wo k no only con ibu es o he
academic discou se on IT p ojec managemen bu also p o ides p ac ical insigh s o
p ac i ione s seeking o le e age he la es ad ances in Agile Me hodologies and
Azu e De Ops p ac ices.
Keywo ds: SAFe®, Azu e De Ops, agili y, P ojec Managemen
JEL classi ica ion: M15: IT Managemen
Pape ype: Resea ch a icle
Recei ed: 25 Feb ua y 2024
Accep ed: 28 May 2024
DOI: 10.54820/en eno a-2024-0029
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ENTRENOVA - ENTe p ise REsea ch InNOVA ion
Vol. 10 No. 1
In oduc ion
SAFe® and Azu e De Ops in eg a ion is expec ed o imp o e ope a ional e iciency,
os e con inuous imp o emen , and s eamline p ojec eam collabo a ion.
T adi ional p ojec managemen me hods s uggle o adap o echnological
ad ances and ma ke changes. SAFe®, a popula agile amewo k, suppo s scalable
agile p ac ices ha mee business goals. Ins ead, Azu e De Ops p o ides
de elopmen ools o con inuous in eg a ion and deli e y. Toge he , hese wo
solu ions ans o m p oblem-sol ing. This mul i-me ic s udy examines how SAFe®'s agile
p inciples and Azu e De Ops' au oma ion and ooling can c ea e a dynamic
amewo k o managing complex IT p ojec s.
Ou esea ch ques ion is ocused on de e mining he op imal combina ion o a
p ojec managemen me hodology and a so wa e ool o enhance lexibili y, isibili y,
and p oduc i i y. In o de o ind he answe , he esea ch will conduc a ho ough
examina ion o he inco po a ion o SAFe® and Azu e De Ops in IT p ojec
managemen . I will be o ganized logically, s a ing wi h a comp ehensi e Li e a u e
Re iew ha e alua es p e ious esea ch on his inno a i e me hod. The Me hodology
sec ion p esen s a esea ch design ha inco po a es mul iple me ics and combines
quali a i e and quan i a i e analysis me hods. The sec ion emphasizes he p ocess o
Da a Collec ion, which in ol es ga he ing empi ical e idence om wo impo an IT
p ojec s and sys ema ically dis ibu ing ques ionnai es o p ojec manage s and eam
membe s. The Da a Analysis sec ion p o ides a de ailed examina ion o he
echniques used o iden i y pa e ns in p ojec success a es, e iciency
enhancemen s, and eam dynamics. The Resul s sec ion will subsequen ly emphasize
he e ec s o inco po a ing SAFe® and Azu e De Ops, while he subsequen
Discussion will analyse he s a egic bene i s and challenges unco e ed by ou
indings. The Conclusion o he s udy p o ides a concise summa y o i s con ibu ions
and p oposes po en ial a enues o u u e esea ch. I o e s a comp ehensi e
o e iew o how he in eg a ion can imp o e IT p ojec managemen p ac ices.
Li e a u e Re iew
The in eg a ion o Azu e De Ops and SAFe® emphasizes he signi ican and posi i e
e ec i has on IT p ojec managemen . This in eg a ion speci ically p omo es s a egic
agili y and inno a ion wi hin complex p ojec en i onmen s. While hese sys ems a e
p aised o hei abili y o suppo scalable agile p ac ices and acili a e con inuous
in eg a ion and deli e y, esul ing in as e p ojec cycles and imp o ed p oduc
quali y, he e a e s ill signi ican gaps in ou unde s anding o he comple e ange o
hei impac on in eg a ion. P io esea ch (Sha ma, 2018; Bass, 2015; Dingsøy e al.,
2012; Laan i e al., 2013) p ima ily concen a es on he ad an ages o using his
app oach, such as enhanced p ojec e iciency, eam collabo a ion, and isibili y.
Ne e heless, he e is limi ed knowledge ega ding he sys emic obs acles and cul u al
adjus men s ha o ganiza ions mus make o ully exploi hese amewo ks wi h
maximum e iciency.
Mo eo e , al hough he e is empi ical e idence ha con i ms he e ec i eness o
SAFe® in la ge-scale IT p ojec s, u he in es iga ion is equi ed o unde s and he
speci ic bene i s o in eg a ing i wi h Azu e De Ops ools, pa icula ly ega ding
ope a ional and s a egic agili y. The exis ing li e a u e highligh s a no able lack o
esea ch in he heo e ical amewo ks, as ou lined by Bohem and Tu ne (2004) and
Doz and Kosonen (2010), conce ning he equilib ium be ween agili y and discipline
and he no ion o s a egic agili y in ola ile and unce ain con ex s. This sugges s ha
addi ional empi ical esea ch is equi ed o suppo he heo e ical asse ions and gain
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Vol. 10 No. 1
a deepe unde s anding o he p ac ical consequences o hese in eg a ions in
a ious con ex s.
Mo eo e , he cu en academic discussion lacks ho ough esea ch ha assesses
he e ec i eness o in eg a ing SAFe® and Azu e De Ops in di e en indus ies and
p ojec ca ego ies, despi e he po en ial o imp o ed s a egic lexibili y and
c ea i i y. The cu en body o li e a u e mainly consis s o anecdo al o isola ed
ins ances o success, which may no necessa ily be applicable o p o ide a
comp ehensi e unde s anding o he unde lying mechanisms in ol ed. The e o e,
he e is a no able po en ial o u u e esea ch o ill hese gaps by conduc ing
me hodical s udies ha in es iga e he angible impac s o his in eg a ion and by
assessing he mos e icien echniques and s a egies o i s implemen a ion in a ious
o ganiza ional se ings.
Me hodology
The s udy u ilizes a mul i-me ic esea ch design, inco po a ing bo h quali a i e and
quan i a i e analysis me hods. This app oach aims o comp ehensi ely unde s and
he ans o ma i e po en ial and di e se impac o in eg a ing he Scaled Agile
F amewo k wi h Azu e De Ops on IT p ojec managemen p ac ices. The inclusion o
a ious esea ch me hodologies aims o o e a ho ough unde s anding o he
impac s o in eg a ion, u ilizing a b oad a ay o da a sou ces and analy ical
iewpoin s.
Da a Collec ion
To ga he a comp ehensi e ange o insigh s on he in eg a ion o SAFe® and Azu e
De Ops, ou da a collec ion s a egy in ol ed h ee dis inc sou ces:
A. Ou empi ical e idence was p ima ily based on conduc ing ho ough analyses o
wo signi ican IT p ojec s. The ini ial p ojec in he pha maceu ical indus y ocused on
c ea ing a web and mobile so wa e applica ion ha was compa ible wi h bo h
And oid and iOS pla o ms. The p ojec had a di e se eam o expe s om a ious
ields, including so wa e de elopmen , UX/UI design, da a science, pha macology,
and egula o y compliance. Se e al heal hca e p ojec managemen s udies exis ,
add essing di e se a eas like cash low con ol wi h s a egic conside a ions (Ruiz e
al., 2020; Hu e al., 2005), isk analysis u ilizing da a causali y o expe -aligned insigh s
(Ko & Cheng, 2007), and AI-powe ed cons uc ion scheduling wi h echno-
o ganiza ional cons ain s conside ed (Kalai ani & Elampa i hi, 2014; Boejko e al.,
2012). The second p ojec , o igina ing om he inancial sec o , p ima ily aimed o
c ea e a s anda dized applica ion o backend ope a ions. This p ojec ocused on
dis inc ca ego ies o obs acles, om a secu i y pe spec i e on da a secu i y,
ansac ion p ocessing speed, and sys em eliabili y. Agile me hodologies a e
a ou ed in he inancial sec o , speci ically o implemen ing new echnologies
(Khoza & Ma newick, 2020). This aligns wi h he p e ailing inclina ion owa d i e a i e
me hodologies in digi alized p ojec managemen (Guinan e al., 2019; Chalons &
Du , 2017). Clus e analysis no only highligh s he signi icance o comp ehending
eme ging echnologies bu also exposes he challenge o es ablishing p io i ies (Man
& S andhagen, 2017).
The selec ion o hese case s udies aims o o e aluable insigh s in o how he
in eg a ion o SAFe® and Azu e De Ops can e ec i ely ackle a ious p ojec
managemen challenges in di e en indus y sec o s.
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B. The su ey componen o ou s udy was o mula ed as a sys ema ic ques ionnai e
(Fig. 1) a ge ing a wide ange o IT p ojec manage s and eam membe s who possess
expe ise in wo king wi h he in eg a ion o SAFe® and Azu e De Ops. These su eys
co e ed a ious issues such as challenges aced, lessons lea ned, and use ul ools
used by p ojec manage s. The ques ions p o ided se ed as a guide du ing he
in e iews (Schwalbe, 2015). The pa icipan s, who we e employees o wo
mul ina ional ou sou cing companies, we e in ol ed in wo signi ican p ojec s, which
a e he main subjec s o ou case s udies.
Designing and dis ibu ing Su eys: hese we e designed o e alua e a ious ac o s,
such as p ojec deli e y imes, adhe ence o budge , quali y o he inal p oduc , eam
sa is ac ion, and pe cei ed enhancemen s in collabo a ion and communica ion. The
ques ions we e s uc u ed using a Like scale, which encompassed a ange om
s ongly disag ee o s ongly ag ee. Addi ionally, open-ended ques ions we e
included o ga he mo e de ailed eedback.
Figu e 1
Su ey P ocess o Assessing In eg a ion o SAFe® and Azu e De Ops
Sou ce: Au ho ’s wo k
Dis ibu ion: hese we e dissemina ed elec onically, employing a blend o email
in i a ions and pos ings on specialized ne wo king pla o ms aimed a IT p ojec
managemen communi ies.
Analysis was conduc ed on he collec ed su ey da a o measu e he e ec s o
in eg a ing SAFe® and Azu e De Ops on impo an p ojec managemen me ics. This
analysis acili a ed he iden i ica ion o pa e ns in he success a es o p ojec s,
enhancemen s in e iciency, and al e a ions in eam dynamics.
C. In addi ion o he su eys, semi-s uc u ed in e iews we e ca ied ou (Table 1) o
ob ain de ailed insigh s in o he s a egic ad an ages, di icul ies, and p ac ical
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Vol. 10 No. 1
encoun e s o implemen ing he in eg a ion o SAFe® and Azu e De Ops. The
in e iews ocused on indus y expe s, such as Agile coaches, In e iews wi h in ol ed
employees who ha e expe ience leading o pa icipa ing in p ojec s using he
in eg a ed app oach o SAFe® and Azu e De Ops we e ca e ully o ganized and
conduc ed. The in e iew guide was s uc u ed a ound key opics, including s a egic
in eg a ion o IT p ojec s, changes in eam collabo a ion and mo ale, challenges in
adap ing, and obse ed bene i s in speed and quali y o p ojec s. Pa icipan s we e
me iculously chosen based on compe ence and no able achie emen s in success ul
in eg a ion p ojec s. A delibe a e a emp was made o include a wide ange o
pe spec i es om di e en sec o s and p ojec scales o ensu e a ho ough
unde s anding. Each in e iew, conduc ed ia ideocon e ence, las ed 30-40
minu es. In e iews ollowed a semi-s uc u ed o ma , which allowed o in-dep h
examina ion o speci ic a eas o in e es and in es iga ion o eme ging hemes. Da a
om hese in e iews was subjec ed o hema ic analysis o ex ac meaning ul insigh s
in o he s a egic and ope a ional implica ions o SAFe® and Azu e De Ops
in eg a ion. The analysis p o ided aluable insigh s in o con ex ual ac o s, such as
o ganiza ional cul u e, eam s uc u e, and p ojec complexi y, ha a e c i ical o he
success ul implemen a ion o he in eg a ed app oach. These insigh s we e
pa icula ly aluable o enhancing he quan i a i e analysis, as hey included speci ic
examples and es imonials ha highligh ed he bene i s and add essed he
challenges iden i ied in he su ey da a.
Table 1
Da a Collec ion Componen s and Con ibu ions
Da a
Collec ion
Componen
Desc ip ion
Con ibu ion o S udy
Empi ical
E idence
(A)
Analysis o wo IT p ojec s om he
pha maceu ical and inancial
sec o s, ocusing on web/mobile
applica ion de elopmen and
backend ope a ions, espec i ely.
P o ides ounda ional insigh s
in o he p ac ical applica ion
o SAFe® and Azu e De Ops
ac oss di e en indus y sec o s
and p ojec ypes.
Su eys
(B)
O e h ee mon hs, 63 IT p ojec
manage s and eam membe s
comple ed sys ema ic su eys. To
cap u e a wide ange o insigh s,
he ques ionnai es included
a Like scale and open-ended
ques ions. Da a in eg i y was
ensu ed by alida ing 56 ini ial
esponses and including hem in
he inal analysis. Wi h C onbach's
alpha coe icien s abo e 0.8, all
ques ionnai e i ems showed s ong
eliabili y and in e nal consis ency.
O e s quan i a i e da a on
p ojec managemen me ics
like deli e y imes, budge
adhe ence, p oduc quali y,
and eam sa is ac ion. Helps
iden i y pa e ns in p ojec
success and e iciency
imp o emen s.
Su ey
Dis ibu ion
Su eys a e dis ibu ed
elec onically ia email and
specialized ne wo king pla o ms.
Ensu es a di e se and
comp ehensi e ep esen a ion
o pa icipan s om a ious
p ojec s, sizes, and sec o s.
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Su ey
Analysis
Employing s a is ical me hods o
analyse su ey da a.
Facili a es he unde s anding
o he impac o SAFe® and
Azu e De Ops in eg a ion on
p ojec managemen me ics
and eam dynamics.
In e iews
(C)
Semi-s uc u ed in e iews wi h
Agile coaches, De Ops
consul an s, and p ojec
manage s.
P o ides in-dep h quali a i e
insigh s in o he s a egic
ad an ages, challenges, and
p ac ical expe iences o
implemen ing SAFe® and Azu e
De Ops.
In e iew
Execu ion
Video-con e encing semi-
s uc u ed in e iews add essed
s a egic alignmen , eam
collabo a ion, and adap a ion
challenges. O e wo mon hs, 31
subjec s we e in e iewed. All
hema ic i ems analysed had
C onbach's alpha coe icien s
g ea e han 0.85, signi ying a high
le el o in e nal uni o mi y and
accu acy in he esponses.
Allows o a deep di e in o
speci ic a eas o in e es ,
enhancing he quan i a i e
indings wi h conc e e
examples and expe
es imonies.
In e iew
Da a
Applica ion
Analysed using hema ic analysis
o ex ac insigh s.
Complemen s he su ey da a
wi h de ailed explo a ions o
con ex ual ac o s in luencing
he success ul implemen a ion
o in eg a ed p ac ices.
Sou ce: Au ho s’ wo k
The combina ion o su eys and in e iews c ea ed a ho ough da a collec ion
app oach ha enhanced he s udy's esul s, p o iding a well- ounded pe spec i e on
he measu able e ec s and subjec i e expe iences o implemen ing SAFe® and Azu e
De Ops in eg a ion in IT P ojec Managemen .
Da a Analysis
Da a analysis was pe o med wi h SPSS (S a is ical Package o he Social Sciences) as
a so wa e ool o mul i a ia e eg ession o assess he in luence o di e en ac o s on
p ojec success indica o s and clus e analysis o iden i y adop ion pa e ns o SAFe®
and Azu e De Ops p ac ices.
Da a analysis o he pha maceu ical p ojec demons a ed ha he inco po a ion
o SAFe® wi h Azu e De Ops led o a signi ican imp o emen in p ojec deli e y
imelines and quali y me ics. Con e sely, he inancial sec o p ojec exhibi ed a
no able enhancemen in he dependabili y o he backend sys em and a educ ion
in c i ical so wa e p oblems, which can be di ec ly a ibu ed o he adop ion o
in eg a ed p ac ices (Fig. 2).
The da a analysis un eiled clea pa e ns, showcasing a signi ican co ela ion
be ween he deg ee o in eg a ion o SAFe® and Azu e De Ops p ac ices and
enhancemen s in key p ojec pe o mance me ics, such as ime o ma ke ,
adhe ence o budge , and de ec a es. This analysis p esen ed quan i a i e
e idence ha suppo ed he e icacy o he in eg a ion, using da a om a ious
con ex s o wo speci ic p ojec s. The comp ehensi e case s udies o hese p ojec s
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Vol. 10 No. 1
imp o ed he e ec i eness o hema ic analysis, a me hod used o analyse quali a i e
da a. The inco po a ion o SAFe® and Azu e De Ops has unco e ed se e al no able
bene i s, such as imp o ed c oss- unc ional collabo a ion and he es ablishmen o a
cul u e ocused on ongoing enhancemen . In e iews p o ided addi ional insigh s in o
hese pa e ns, as p ojec pa icipan s and expe s sha ed hei expe iences wi h
imp o ed eam dynamics and heigh ened adap abili y in success ully add essing
p ojec obs acles.
The hema ic analysis also e ealed p e alen obs acles aced du ing he
in eg a ion p ocess, including opposi ion o al e ing he o ganiza ional cul u e and he
necessi y o adap o no el ools and p ac ices. Ne e heless, he con e sa ion
pinpoin ed p agma ic solu ions and e ec i e s a egies o su moun hese challenges,
such as specialized aining ini ia i es and g adual implemen a ion echniques. Du ing
he pha maceu ical p ojec , he e was a consis en emphasis on he impo ance o
s ic adhe ence o egula ions, which was achie ed mo e e ec i ely by p omo ing
an inclusi e and collabo a i e en i onmen h ough he u iliza ion o SAFe® and Azu e
De Ops. The inancial p ojec emphasized he c ucial signi icance o backend sys em
dependabili y, whe ein he adop ion o con inuous in eg a ion and deploymen
me hodologies esul ed in a signi ican dec ease in down ime and an enhancemen
in cus ome sa is ac ion. Fu he mo e, he hema ic analysis o bo h p ojec s
demons a ed ha he in eg a ion was c ucial in disman ling obs acles be ween
de elopmen and ope a ions eams, esul ing in a mo e cohe en and uni ied
app oach o p ojec managemen . This cul i a ed a cul u e in which ongoing
eedback and inc emen al enhancemen s became he s anda d, closely adhe ing
o Agile p inciples.
The s udy employs a dual-pa h analy ical me hodology o acqui e a ho ough
comp ehension o how he in eg a ion o SAFe® and Azu e De Ops can ans o m IT
p ojec managemen . The s a is ical analysis o e s empi ical e idence o he bene i s,
suppo ed by a hema ic analysis ha unco e s he unde lying mechanisms and
p ac ices ha d i e hese imp o emen s. This me hodology o e s a comp ehensi e
analysis o how in eg a ion con ibu es o esol ing he complex issues and challenges
aced in con empo a y IT p ojec s. I p o ides aluable insigh s o bo h schola ly
in es iga ion and p ac ical applica ion in he ield.
Figu e 2
Impac o Sa e® and Azu e De Ops In eg a ion on P ojec Success
Sou ce: Au ho ’s wo k
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Resul s
The in eg a ion o SAFe® wi h Azu e De Ops ools esul ed in subs an ial imp o emen s
in p ojec managemen p ac ices, e iciency, and ou comes, as e idenced by he
case s udies o a pha maceu ical web and mobile applica ion p ojec and a inancial
sec o 's backend sys em p ojec . The eam skil ully handled las -minu e modi ica ions
o egula o y equi emen s in he pha maceu ical p ojec , ensu ing ha he p ojec
schedule emained unin e up ed. The adap abili y o he sys em was p ima ily
a ibu ed o he Agile planning and p io i iza ion mechanisms o SAFe®, which we e
enhanced by he lexible deploymen pipelines o Azu e De Ops, enabling quick
adjus men s and imely deploymen s. In he inancial p ojec , he combina ion o
SAFe® and Azu e De Ops allowed o quick adap a ion o new secu i y egula ions.
This made i possible o he eam o smoo hly implemen necessa y changes o he
backend sys ems wi hou expe iencing majo delays. The e iciency was p ima ily
acili a ed by he u iliza ion o Azu e De Ops pipelines o con inuous in eg a ion and
deploymen , which played a i al ole in achie ing a apid u na ound and sus aining
p ojec p og ess.
Enhanced p ojec isibili y (Fig. 3): bo h p ojec s expe ienced a subs an ial
enhancemen in hei abili y o ack and iden i y p ojec p og ess and issues. By
u ilizing Azu e De Ops dashboa ds and implemen ing he s uc u ed i e a ion planning
and e iew mee ings o SAFe®, all pa ies in ol ed we e able o gain immedia e and
up- o-da e in o ma ion ega ding he p ojec 's p og ess, po en ial isks, and obs acles.
By p o iding g ea e isibili y, p ojec manage s we e able o make mo e in o med
decisions and ake p oac i e measu es o add ess issues be o e hey became mo e
se ious.
Enhanced e iciency pha maceu ical p ojec : he p ojec achie ed a no ewo hy
20% dec ease in he ime equi ed o b ing he mobile applica ion o ma ke , wi h
compa able imp o emen s in he de elopmen o he web applica ion. The inc ease
in p oduc i i y was c edi ed o he enhanced wo k lows acili a ed by Azu e De Ops,
such as au oma ed builds and es ing, as well as he i e a i e and inc emen al deli e y
me hod p omo ed by SAFe®.
Financial p ojec : he backend sys em p ojec saw a 30% ise in he equency o
deploymen , accompanied by a dec ease in he numbe o deploymen ailu es. The
signi ican enhancemen can be a ibu ed p ima ily o he e icien in eg a ion o
SAFe® and Azu e De Ops, which acili a ed s eamlined de elopmen and ope a ions
p ocesses.
Figu e 3
Imp o emen s in P ojec E iciency wi h Azu e De Ops and SAFe®
Sou ce: Au ho s’ wo k
