Gestión de proyectos en la cuarta revolución industrial. Proyecto de producción de cerveza
Abstract
Hochschule Albstadt-Sigmaringen
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UNIVERSIDAD DE VALLADOLID
ESCUELA DE INGENIERIAS INDUSTRIALES
G ado en Ingenie ía de O ganización Indus ial
Ges ión de P oyec os en la Cua a Re olución
Indus ial. P oyec o de p oducción de
ce eza.
Au o :
Rod íguez Ma ínez, Ma ía Es e anía
Responsable de In e cambio en la U a:
Ángel Manuel Gen o Municio
Uni e sidad de des ino
Hochschule Albs ad -Sigma ingen
Valladolid, Julio 2021.
TFG REALIZADO EN PROGRAMA DE INTERCAMBIO
TÍTULO: P ojec Managemen in he Fou h Indus ial Re olu ion. Bee
p oduc ion p ojec .
ALUMNO: Ma ía Es e anía Rod íguez Ma ínez
FECHA: 28 de Julio de 2021
CENTRO: Hochschule Albs ad -Sigma ingen
UNIVERSIDAD: Hochschule Albs ad -Sigma ingen
TUTOR: Be nd S auß
Facul y o Enginee ing
Cou se o S udy Business Adminis a ion and Enginee ing
TOPIC
P ojec Managemen in he Fou h Indus ial
Re olu ion. Bee p oduc ion p ojec .
Bachelo - Thesis
Submi ed in ul ilmen o he equi emen s o he academical deg ee
Bachelo o Science
Submi ed in he sp ing semes e 2021 on 20.07.2021
Inqui ies abou his publica ion should be add essed o
Ma ía Es e anía Rod íguez Ma ínez
S uden numbe : 91794
Pos aBe 22/2
72458 Albs ad
Business Enginee ing and Adminis a ion
Semes e 7
E-Mail: [email p o ec ed]
Supe iso /Examine : P o . D . Be nd S auß, Uni e si y o Albs ad -Sigma ingen
Examine : P o . D . De k Rembold, Uni e si y o Albs ad -Sigma ingen
ABSTRACT AND KEYWORDS
II
ABSTRACT
El obje i o de es e documen o es encon a soluciones a los p oblemas de ges ión de
p oyec os que su gen como consecuencia de la cua a e olución indus ial, que es á
cambiando la indus ia al y como la conocemos y nos si úa en un pun o c í ico de
adap ación a una nue a ealidad que ae á consigo g andes opo unidades y ambién
g andes iesgos. Además, la ges ión de los nue os p oyec os 4.0 supond á un e o de
comunicación en e expe os en ecnologías y lenguajes in o má icos muy di e en es, po
lo que es e documen o des aca los elemen os a ene en cuen a en la e olución
ecnológica y es udia cómo ges iona un p oyec o en una Sma ac o y.
The aim o his documen is o ind solu ions o he p ojec managemen p oblems ha
a ise as a esul o he ou h indus ial e olu ion, which is changing indus y as we know
i and places us a a c i ical poin o adap a ion o a new eali y ha will b ing g ea
oppo uni ies as well as g ea isks. In addi ion, he managemen o new 4.0 p ojec s will
pose a challenge o communica ion be ween expe s in e y di e en echnologies and
compu e languages, which is why his documen highligh s he elemen s o be aken in o
accoun in he echnological e olu ion and s udies how o manage a p ojec in a Sma
ac o y.
KEYWORDS
Cua a e olución indus ial, ges ión de p oyec os, Sma Fac o y, me odologías de
ges ión de p oyec os.
Fou h indus ial e olu ion, p ojec managemen , Sma Fac o y, P ojec managemen
me hodologies.
Table o Con en s
III
TABLE OF CONTENTS
ABSTRACT ..................................................................................................................... II
KEYWORDS ................................................................................................................... II
LIST OF TABLES ........................................................................................................ VII
LIST OF FIGURES ........................................................................................................ IX
ACADEMIC HONESTY DECLARATION .................................................................. XI
INTRODUCTION ........................................................................................................ XIII
1 THE FOURTH INDUSTRIAL REVOLUTION ...................................................... 1
HISTORICAL CONTEX ................................................................................. 1
FOURT INDUSTRIAL REVOLUTION ......................................................... 3
1.2.1 WHAT IS THE FOURT INDUSTRIAL REVOLUTION ........................... 3
1.2.2 FOURTH INDUSTRIAL REVOLUTION TECHNOLOGIES ................... 6
▪ INTERNET OF THINGS ............................................................................. 7
▪ ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING ............. 12
▪ BIG DATA AND CLOUD COMPUTING ................................................ 13
▪ BLOCK CHAIN ......................................................................................... 15
▪ AUTONOMOUS CARS ............................................................................ 16
▪ 3D PRINTING ............................................................................................ 16
▪ ADVANCED ROBOTICS ......................................................................... 17
▪ NEW MATERIALS ................................................................................... 17
1.2.3 IMPACT AND CHALLENGES ................................................................ 18
2 PROJECT MANAGEMENT ................................................................................. 23
PROJECT CONCEPT .................................................................................... 23
2.1.1 DIFFERENCE BETWEEN PROCESS, PROJECT AND PROGRAMME
23
PROJECT MANAGEMENT ......................................................................... 24
Table o Con en s
IV
2.2.1 PROJECT MANAGEMENT CONTEXT .................................................. 25
2.2.2 PROJECT MANAGEMENT METHODOLOGIES .................................. 26
3 METHODOLOGIES COMPARISON ................................................................... 49
WHEN THE METHODOLOGIES SHOULD, OR SHOULD NOT, BE USED
50
3.1.1 T adi ional Me hodologies ......................................................................... 50
▪ WATERFALL ............................................................................................ 50
▪ PRINCE2: ................................................................................................... 51
▪ PMBOK ...................................................................................................... 52
3.1.2 Agile Me hodologies .................................................................................. 53
▪ SCRUM ...................................................................................................... 54
▪ KANBAN ................................................................................................... 55
▪ LEAN ......................................................................................................... 56
▪ XP ............................................................................................................... 57
▪ OTHER METHODOLOGIES .................................................................... 57
COMPARISON BETWEEN METHODOLOGIES ....................................... 59
3.2.1 AGILE VS TRADITIONAL ...................................................................... 59
3.2.2 TRADITIONAL: WATERFALL VS PMBOK ......................................... 63
3.2.3 AGILE ........................................................................................................ 63
▪ SCRUM VS KANBAN .............................................................................. 63
▪ XP VS SCRUM .......................................................................................... 65
▪ SIMILARITIES BETWEEN ...................................................................... 65
HYBRID METHODOLOGIES ...................................................................... 66
4 BEER PROJECT 4.0 .............................................................................................. 69
PROJECT CONTEXT .................................................................................... 69
4.1.1 PARTICIPANTS ........................................................................................ 69
Table o Con en s
V
4.1.2 PROJECT MANAGEMENT ..................................................................... 70
METHODOLOGIES FOR THE MANAGEMENT OF 4.0 PROJECTS
APPLICABLE TO THIS PROJECT. ......................................................................... 76
4.2.1 CHARACTERISTICS OF THE INDUSTRIAL REVOLUTION
PROJECTS ............................................................................................................. 76
▪ PRESSURE ON PROJECT DEVELOPMENT TIMES ............................ 76
▪ BUSINESS MODEL ORIENTATION ...................................................... 76
▪ INTER-RELATION BETWEEN FIRMS: COOPERATING IN A
NETWORK ........................................................................................................ 77
4.2.2 PROJECT OF THE TECHNOLOGICAL REVOLUTION ARE COMPLEX
IN NATURE ........................................................................................................... 78
PROBLEM SOLUTION ................................................................................ 78
4.3.1 JUSTIFICATION OF THE METHODOLOGY ........................................ 78
4.3.2 CONCLUSION OF THE METHODOLOGY TO BE USED ................... 82
5 CONCLUSION ...................................................................................................... 86
6 REFERENCES ....................................................................................................... 87
VI
Lis o ables
VII
LIST OF TABLES
Table 1. Fou h Indus ial Re olu ion Technologies. Sou ce: (Klaus Schwab, 2016). .... 6
Table 2. Classi ica ion o p ojec managemen me hodologies. Sou ce: (Ma o ic, 2020)
........................................................................................................................................ 26
Table 3. PRINCE O ganisa ion Sou ce: (AXELOS, 2017)............................................ 32
Table 4. PM2 p ojec phases. Sou ce: (Eu opean Union, 2021) ..................................... 34
Table 5. A eas o wa e all me hodology. Sou ce: Own made ollowing (Bha sa , 2021;
In ini y, 2021 Alsham ani & Baha ab, 2015; And ei e al., 2019; Balaji & Mu ugaiyan,
2012; Hawo h, 2021; Mo on, 2011) ............................................................................. 36
Table 6. Wa e all equi emen s. Sou ce: Own made (Azanha e al., 2017; As on, 2021;
Monday, 2019; Team Wo k, 2021) ................................................................................ 51
Table 7. PRINCE2 equi emen s. Sou ce: Own made ( Azanha e al., 2017; As on, 2021;
Monday, 2019; Team Wo k, 2021) ................................................................................ 52
Table 8. PMBOK equi emen s. Sou ce: Own made (Azanha e al., 2017; As on, 2021;
Monday, 2019; Team Wo k, 2021) ................................................................................ 52
Table 9. SCRUM equi emen s. Sou ce: (As on, 2021; Azanha e al., 2017; Monday,
2019; Team Wo k, 2021)................................................................................................ 55
Table 10. KANBAN equi emen s. Sou ce: (As on, 2021; Azanha e al., 2017; Monday,
2019; Team Wo k, 2021)................................................................................................ 56
Table 11. Di e ences be ween agile and adi ional p ojec managemen app oaches.
Sou ce: (Shenha & D i , 2007) ..................................................................................... 59
Table 12. T adi ional s Agile p ojec Managemen . Sou ce: Own made. (Azanha e al.,
2017; Hawo h, 2021; Lay on e al., 2020; Ma o ic, 2020; Shaydulin & Syb and , 2017;
Špundak, 2014) ............................................................................................................... 60
Table 13. Di e ences be ween agile and adi ional so wa e p ojec managemen .
Sou ce: (Hoda e al., 2010) ............................................................................................. 61
Table 14. Compa ison be ween XP ans SCRUM. Sou ce: (Knibe g, 2007) .................. 65
Table 15. Bee p oduc ion p ojec . De ici s and Imp o emen s. Sou ce: Albs ad -
Sigma ingen Uni e si y. ................................................................................................. 69
Table 16. Si u a ion A p ojec bee po duc ion. Sou ce: sel made. ................................ 73
Table 17. Si ua ion B p ojec bee p oduc ion. Sou ce: sel -made. ................................ 74
INTRODUCTION
XIV
A he Uni e si y o Albs ad Sigma ingen, a bee p oduc ion p ojec is being ca ied ou
wi h he aim o imp o ing he quali y o bee p oduc ion and o be a leade in inno a ion.
To his end, he p oduc ion p ocess is based on Indus y 4.0 echnology and hus simula es
a sma ac o y. Due o he echnical na u e o he p ojec and he pa icipa ion o s uden s
om di e en speciali ies, we a e aced wi h he a o emen ioned p oblem ha a ises in
p ojec s o he ou h indus ial e olu ion: communica ion be ween expe s in di e en
echnologies.
The aim o his documen is o s udy he possible solu ions o he p oblems ha a ise in
he managemen o his p ojec and he elemen s o be aken in o conside a ion o p ojec s
in he ou h indus ial e olu ion. To do his, he ou h indus ial e olu ion will be
s udied, he ac o s ha ha e led us o i and he echnologies ha make i up, no only a
an indus ial le el, bu also in he di e en ields i co e s. A e wa ds, p ojec
managemen and he exis ing me hodologies used o manage p ojec s will be p esen ed.
Subsequen ly, hese me hodologies will be compa ed in o de o know when hey should
o should no be used. And inally, all he knowledge ob ained will be applied o he
sea ch o he bes solu ions o he p ojec in a Sma ac o y.
The documen will be s uc u ed as ollows: in he i s chap e we will go in o he ou h
indus ial e olu ion in dep h, in he second chap e we will s udy p ojec managemen
and i s me hodologies, and hen in he hi d chap e we will ocus on compa ing hem, so
ha in he ou h chap e , ocused on he bee p oduc ion p ojec , we can p o ide solu ions
based on wha has been analysed, and inally, we will p esen he conclusion o he wo k.
THE FOURTH INDUSTRIAL REVOLUTION
1
1 THE FOURTH INDUSTRIAL REVOLUTION
HISTORICAL CONTEX
The indus ial e olu ions ha began in he mid-18 h cen u y led o he mechanisa ion o
indus ies and he eplacemen o human labou and ha e e ol ed in o wha is now known
as he ou h indus ial e olu ion. Be o e del ing in o his las e olu ion, we need o
know he backg ound ha has led us o whe e we a e oday.
In he ollowing i is has o be speci ied wha is mean by he indus ial e olu ion. The e
a e many de ini ions o his e m. Da id Landes, p o esso , economis and his o ian a
Ha a d, Columbia and Be keley uni e si ies, de ails ha he e a e a leas h ee meanings
o his e m. The i s de ini ion e e s o echnological inno a ions ha p omo e a shi
away om a isanal p oduc ion o ac o y p oduc ion, eplacing human skill wi h
machine y and animal powe wi h plan -based sou ce ene gy. The second de ini ion is
used o poin ou an impo an echnological change a some his o ical poin in ime o as
a esul o inno a i e echniques. And inally, he hi d de ini ion e e s speci ically o
he pe iod in he 18 h cen u y, beginning in England and sp eading une enly ac oss
con inen al Eu ope, which b ough abou socio-economic change as a esul o
mechanisa ion and indus ialisa ion. (Landes & An olín Fa gas, DL 1979)
The e o e, we could de e mine ha an indus ial e olu ion is a p ocess o change, caused
by a ealloca ion o powe and weal h be ween g oups and indi iduals, based on new
echnological possibili ies and b inging wi h i s ong social changes and a edis ibu ion
o economic weal h. In sho , i is abou changes in h ee ields: echnology, weal h and
socie y, which a e in e wined o e ime and build on each o he , leading o a si ua ion
ha is so di e en om he ini ial one ha i jus i ies he use o he e m " e olu ion".
(Sil a e al., 2019)
A be e unde s anding o he e m Indus ial Re olu ion leads o he assump ion ha he
e olu ions ha e aken place h oughou his o y when new echnologies and no el ways
THE FOURTH INDUSTRIAL REVOLUTION
2
o pe cei ing he wo ld igge a p o ound change in economic sys ems and social
s uc u es. The e olu ion ep esen s a adical u ning poin , changing and in luencing all
aspec s o li e. (Klaus Schwab, 2016, pp. 6–7)
The Ag icul u al Re olu ion led o an inc ease in ood su plus and quali y, s imula ing
economic and popula ion g ow h. The in oduc ion o mechanised a ming sys ems
gene a ed a su plus o ag icul u al labou , which was la e con e ed in o indus ial
labou , leading o he mig a ion o he wo king class, esul ing in u banisa ion and he
eme gence o ci ies. This ac o was one o he undamen al pilla s o he i s indus ial
e olu ion.
The i s indus ial Re olu ion spanned om abou 1760 o a ound 1840, o igina ed in
England. This e olu ion was d i en by he cons uc ion o he ailway and he ad en o
he s eam engine. The la e , led and enabled p oduc ion o be mechanized o he i s
ime, ma king he beginning o he mechanical p oduc ion, and u he d i ing social
change. The second indus ial e olu ion, which ook place be ween he la e 19 h and
ea ly 20 h cen u ies, sp ead o o he coun ies such as F ance, Ge many, Belgium, Japan
and he Uni ed S a es. Technological and scien i ic inno a ions and he ad en o new
ene gy sou ces such as oil and elec ici y made mass p oduc ion and he de elopmen o
he assembly line possible. P oduc ion managemen was imp o ed, p oduc ion imes we e
educed, and he quan i y o p oduc s manu ac u ed a lowe p ices inc eased. In addi ion,
he de elopmen o means o anspo led o he globalisa ion o he ma ke . The hi d
indus ial e olu ion, beginning in he 1950s, led o he inc easing au oma ion o
manu ac u ing and he dis up ion o indus ies. In 2007, Je emy Ri kin, sociologis and
ad iso o he Eu opean Commission and Pa liamen , es ablished in his book “The Thi d
Indus ial Re olu ion: How La e al Powe is T ans o ming Ene gy, he Economy and he
Wo ld” he concep o he hi d Indus ial Re olu ion, which was app o ed by he
Eu opean Commission (Ri kin, 2011). Bu was in 1996 when Je emy Ri kin, s a es in his
book “The end o wo k” ha : “We a e indeed expe iencing a g ea momen o his o ical
ans o ma ion owa ds his hi d indus ial e olu ion, and we a e inexo ably heading
owa ds a wo ld o nea wo klessness. The so wa e and ha dwa e al eady in place a e
enabling a apid ansi ion o a silicon-based ci ilisa ion. The un esol ed ques ion is how
THE FOURTH INDUSTRIAL REVOLUTION
3
many human beings will be le in he pa h o he indus ial ans o ma ion and wha he
inal wo ld on he o he side will look like”. (Ri kin, 1996).
FOURT INDUSTRIAL REVOLUTION
In his sec ion, he concep o he ou h indus ial e olu ion i will be desc ibed in dep h,
ollowed by a s udy o he echnologies ha comp ise i and, inally, an analysis o he
mos impo an p ojec s ha a e being de eloped.
1.2.1 WHAT IS THE FOURT INDUSTRIAL REVOLUTION
The i s hing o no e is ha he e is ye no single globally accep ed de ini ion o e e o
and desc ibe his e olu ion. This is e lec ed in he numbe o comple ely homologous
meanings ha exis . One o he bes known is he Ge man e m "Indus y 4.0" bu i is no
he only one. Some o he mos commonly used e ms a e "Digi al Fac o y", "Digi al
Manu ac u ing", "Sma Fac o y", "Ne wo ked Fac o y", "In eg a ed Indus y", "Digi al
Re olu ion", "P oduc ion 4.0", "Human-Machine Coope a ion", in he Uni ed S a es i is
known as "Indus ial In e ne " o "Ad anced Manu ac u ing", in he Eu opean
Commission as "Fac o ies o he Fu u e" and in he Uni ed Kingdom as "The Fu u e o
Manu ac u ing". (Büchi e al., 2020)
1.2.1.1 HISTORICAL CONTEXT OF THE FOURTH INDUSTRIAL
REVOLUTION
The e m Fou h Indus ial Re olu ion was i s used by Klaus Schwab a he 2016 Wo ld
Economic Fo um, e e ing o he his o ic e en we a e cu en ly expe iencing. Howe e ,
he use o he concep " he ou h indus ial e olu ion" is no new. I was i s in oduced
in 1988 (Ros ow, 1988) o iden i y he p ocesses o ans o ma ion and e olu ion o
in en ions in o inno a ions by scien is s in ol ed in p oduc ion eams. F om hen on, he
e m became associa ed wi h he de elopmen and applica ion in nano echnologies. F om
hen on, he e m became associa ed wi h he de elopmen and applica ion in
nano echnologies. (Pa hasa a hi & Thilaga a hi, 2011, pp. 392–398) un il 2016, when
THE FOURTH INDUSTRIAL REVOLUTION
4
Klaus Schwab used i again, bu his ime o ela e i o Indus y 4.0 and he echnological
e olu ion we a e expe iencing.
On he o he hand, he Indus y 4.0 concep eme ged in 2011 in Ge many due o he
Ge man indus ial plan "Indus ie 4.0". (Kage mann e al., 2013, pp. 1–84) whose aim
was o p omo e he ad ancemen o manu ac u ing. In 2013 he Ge man go e nmen
published he documen 'Recommenda ions o implemen ing he s a egic ini ia i e
Indus ie 4.0' by ACATECH 2013 (Kage mann e al., 2013) causing a wo ldwide impac
ha igge ed he de elopmen o simila s a egies in o he coun ies. (Kage mann e al.,
2013)(Kage mann e al., 2013)
1.2.1.2 THE FOURTH INDUTRIAL REVOLUTION OR INDUSTRY 4.0
The ou h indus ial e olu ion, o Indus y 4.0, is globally associa ed wi h he indus ial
en i onmen . Some au ho s desc ibe i as a new e olu ion cha ac e ised by he use o
cybe -physical sys ems in he manu ac u ing en i onmen (Liu & Xu, 2016) he aim o
which would be cos -e ec i e mass cus omised manu ac u ing wi h sho p oduc li e
cycles (Veza e al., 2015, pp. 555–560). Mo eo e , his e olu ion is cha ac e ised by he
combina ion o echnological and human capabili ies wi h he aim o imp o ing
p oduc i i y and weal h in p oduc ion. Indus y 4.0 could e en go u he and become a
manu ac u ing ne wo k in which machines and p oduc s in e ac wi h each o he wi hou
human con ol (I ano e al., 2016, pp. 386–402). E ik B ynjol sson y And ew McA ee,
om he Massachuse s Ins i u e o Technology (MIT), desc ibe i as " he second machine
age", 2014, s a ing ha digi al echnologies mani es hemsel es especially wi h indus ial
au oma ion (B ynjol sson & McA ee, 2014). Indus y 4.0 he e o e aims o de elop a
communica ion sys em be ween p oduc ion equipmen and p oduc s based on hype -
connec ed echnology and in eg a ing all p oduc ion p ocesses (Shao e al., 2019, pp. 1–
12).
This e olu ion, howe e , is no jus abou connec ing in elligen machines and sys ems
in indus ies. I s scope is much b oade , encompassing echnological ad ances in many
di e en ields such as gene ic sequencing, nano echnology, enewable ene gies o
THE FOURTH INDUSTRIAL REVOLUTION
5
quan um compu ing. Indeed, i is p ecisely his usion and in e ac ion o di e en
echnologies ac oss physical, digi al and biological domains ha makes he ou h
indus ial e olu ion undamen ally di e en om p e ious ones (Klaus Schwab, 2016,
p. 12). Ano he majo di e ence wi h p e ious e olu ions is ha , hanks o globalisa ion,
he spill-o e e ec and di usion o eme ging echnologies and inno a ion is much as e
and mo e apid (Klaus Schwab, 2016, pp. 12–13). The Fou h Indus ial Re olu ion
c ea es a wo ld in which i ual and physical manu ac u ing sys ems coope a e wi h each
o he in a globally lexible way.
Mo eo e , his e olu ion is mani es ing i sel in all aspec s o socie y, including
echnology, p oduc ion, consump ion and business, and is in luencing all a eas o human
li e. (Li e al., 2017, pp. 626–637).
Finally, in o de o unde s and why he e is no uni o m and globally accep ed concep o
desc ibe his e olu ion, i is necessa y o conside ha he e is cu en ly a e y la ge
numbe o echnologies ha make up his e olu ion, mo e han 1200 acco ding o
(Chia ello e al., 2018, pp. 244–257). In addi ion, he e a e many s akeholde s -
poli icians, manage s, en ep eneu s, academics and o he s - each seeking hei own
bene i and wi h di e en needs. And inally, aking in o accoun he speed wi h which
inno a ions become obsole e nowadays and ha he e is a wide a ie y o applica ions
om sma ac o ies, ci ies, medicine, homes o objec s, we can unde s and why he e a e
so many concep s, meanings, e ms, o desc ibe (Büchi e al., 2020, p. 3).
All hese ac o s inc ease he complexi y o es ablishing a common concep , bu wha we
can de e mine a e he common elemen s ha make up Indus y 4.0, which a e de ices,
connec i i y, app op ia e da a, good se ice o ien a ion, au oma ion sys ems and
connec ions be ween he physical and i ual wo ld (Ha ison e al., 2016, pp. 1046–
1051).
THE FOURTH INDUSTRIAL REVOLUTION
6
1.2.2 FOURTH INDUSTRIAL REVOLUTION TECHNOLOGIES
In his sec ion, a s udy is made o he echnologies ha a e shaping his e olu ion in o de
o be e unde s and i . The ou h indus ial e olu ion has p e iously been de ined as he
usion o echnologies, and hei in e ac ion, in physical, digi al and biological domains
(Klaus Schwab, 2016).
Following his desc ip ion, we will p oceed o classi y he echnologies ha cha ac e ise
his e olu ion in o digi al, physical and biological. The ollowing able shows he
di ision o hese echnologies:
The ollowing sec ions analyse each o hese g oups, as well as he echniques and
echnologies o which hey a e composed.
1.2.2.1 DIGITAL
The i s echnological ield p esen ed is Digi al. As can be seen in he Table 1 wi hin his
sec ion we ind he ollowing echnological ends:
• The In e ne o Things (IoT)
• A i icial in elligence and machine lea ning
• Big da a and cloud compu ing
• Digi al pla o m
• Block chain
FIELDS
TECHNOLOGIES AND EXAMPLES
1. DIGITAL
The In e ne o Things (IoT)
A i icial in elligence and machine lea ning
Big da a and cloud compu ing
2. PHYSICAL
Au onomous Ca s
3D p in ing
Ad anced obo ics
New Ma e ials
3. BIOLOGICAL
Neu o echnology
Gene ic Enginee ing
Table 1. Fou h Indus ial Re olu ion Technologies. Sou ce: (Klaus Schwab, 2016).
THE FOURTH INDUSTRIAL REVOLUTION
7
▪ INTERNET OF THINGS
The e m “In e ne o Things” was p oposed by Ke in Ash on back in 1999 (Ash on,
2009) and he used i o desc ibe he ne wo k connec ing physical objec s in he wo ld o
he In e ne . Howe e , he idea o being able o connec objec s in an in elligen way ook
oo a he end o he 19 h cen u y when he i s eleme y expe imen s in his o y we e
ca ied ou on Mon Blanc, and la e , no able scien is s such as Nikola Tesla and Alan
Tu ing con inued hei esea ch. Howe e , i was no un il he end o he 1970s ha he
i s ARPANET ne wo k was de eloped, which became he INTERNET in he mid-
1990s. Since 1999, when Ke in Ash on used he e m IoT, an exponen ial g ow h was
expe ienced, a e olu ion ha has led o he popula isa ion o wi eless connec i i y, WIFI,
and o a momen o e olu iona y e e escence wi hin he IoT.
Acco ding o Edua do Oma Sosa “IoT is conside ed as a second wa e in he ICT indus y
a e he compu e , In e ne and mobile ne wo ks” (Edua do Oma Sosa, 2012, p. 28).
Indeed, as we ha e been analysing h oughou his pape , we a e acing a e olu ion in
which he In e ne o Things is he undamen al pilla . Fu he elabo a ing on he concep ,
i could be desc ibed as a sys em composed o physical de ices (including embedded
de ices and digi al machines wi h in e ne connec i i y, humans, senso s, e c.) ha ha e
he capabili y o in e ac wi h each o he au onomously h ough he use o he in e ne , in
o de o imp o e e e y hing om people's li es, h ough a coun y's economy, o
indus ial and na u al esou ce e iciency. In i s simples o m, i can be desc ibed as a
ela ionship be ween p oduc s, se ices, places, e c. and people, made possible h ough
connec ed echnologies and a ious pla o ms. (Klaus Schwab, 2016, p. 22).
Cu en ly, he la ges olume o in e ac ion wi h he in e ne is ca ied ou by humans
connec ing h ough hei de ices. Howe e , in he u u e his in e ac ion will be ca ied
ou by he de ices hemsel es wi hou he need o human supe ision.
As a esul o his e olu ion and g ow h, he numbe o in e ne -connec ed de ices pe
pe son has inc eased. Acco ding o he Cisco In e ne Business G oup (IBSG, 2011), in
2010 he e we e 12.5 billion connec ed de ices and 6.8 billion o he wo ld's popula ion
had 1.84 connec ed de ices pe pe son. Thus, be o e 2010 he e we e mo e connec ed
THE FOURTH INDUSTRIAL REVOLUTION
8
de ices han people. This s udy p edic ed ha by 2020 he e would be a wo ld popula ion
o 7.6 billion and 50 billion connec ed de ices a 6.58 connec ed de ices pe pe son. This
means ha one pe son would ha e almos 7 de ices connec ed o he in e ne .
Figu e 1. Connec ed de ices pe pe son. Sou ce: (Cisco, 2011) shows he numbe o
connec ed de ices pe pe son.
In Ma ch 2020 Cisco published he Cisco Annual In e ne Repo (2018-2023) (Cisco, U.
annual in e ne epo , 2020), which s a es ha 66% o he wo ld's popula ion, 5.3 billion
people, will ha e in e ne access by 2023 Figu e 2. In addi ion, 29.3 billion
connec ions/de ices will be connec ed, which ansla es in o 3.6 pe pe son and almos
10 pe household Figu e 3. O hose 29.3 billion, 50% will be M2M connec ions
suppo ing a ange o IoT applica ions, i.e., 14.7 billion de ices on a global scale Figu e
4. The ollowing images show he da a jus men ioned.
Figu e 1. Connec ed de ices pe pe son. Sou ce: (Cisco, 2011)
THE FOURTH INDUSTRIAL REVOLUTION
9
Figu e 2. Global In e ne use g ow h Sou ce: (Cisco, U. annual in e ne epo , 2020)
Figu e 3. Global de ice and connec ion g ow h. Sou ce: (Cisco, U. annual in e ne epo , 2020)
Figu e 4. Global M2M connec ion g ow h. Sou ce: (Cisco, U. annual in e ne epo , 2020)
THE FOURTH INDUSTRIAL REVOLUTION
16
1.2.2.2 PHYSICAL
In his sec ion some examples o he Fou h Indus ial physical echnologies a e
p esen ed.
• Au onomous Ca s
• 3D p in ing
• Ad anced obo ics
• New Ma e ials
▪ AUTONOMOUS CARS
This echnology is s ill in an expe imen al phase. Au onomous ehicles in e p e da a and
make decisions, and he e is e en he possibili y o an ex e nal highe con ol aking o e
he ope a ion o he ehicle in ce ain ci cums ances. These ehicles know he mapping,
ead he signs and in e p e he a ic da a. By de ining he o igin and des ina ion o he
ehicle, he ehicle chooses he ajec o y and execu es i . Howe e , he e a e o he
au onomous ehicles such as ucks, d ones, planes and boa s. As echnologies such as
senso s and a i icial in elligence p og ess, he capabili ies o all hese au onomous
machines will inc ease a a apid pace.
The p oblems a e associa ed wi h se e al aspec s: The ehicle is no able o in e p e he
eac ions o o he d i e s, which may handicap some o he decisions made. Legisla ion
does no ye ecognise he use o au onomous ehicles in a gene al way, equi ing he
p esence o a d i e . In he e en o an acciden , he esponsibili ies o each pa y a e no
de ined, and may a ec he owne and/o d i e o he ehicle as well as he insu ance
company o he manu ac u e /p og amme o he ehicle. Gi en he po en ial o a ehicle
o cause damage, i is essen ial o ensu e ha he e is no ex e nal con ol capable o
manipula ing he ehicle.
▪ 3D PRINTING
Addi i e manu ac u ing o 3D p in ing consis s o c ea ing a physical objec by p in ing
a 3D digi al model o design in laye s. Un il now, sub ac i e manu ac u ing was ca ied
ou in e e se, emo ing laye s o ma e ial un il he desi ed model was ob ained.
The e o e, 3D p in ing allows manu ac u ing companies o p in wi h less ma e ial, less
ooling, mo e p oduc cus omisa ion, a a lowe cos and as e han sub ac i e
THE FOURTH INDUSTRIAL REVOLUTION
17
manu ac u ing. In addi ion, his manu ac u ing has he po en ial o c ea e e y complex
models wi hou he need o ools (Klaus Schwab, 2016, p. 147). I is being used in a wide
ange o applica ions, om la ge (wind u bines) o small (medical implan s). Bu he
cu en ocus is on au omo i e, medical and ae ospace applica ions. 3D p in ing has
limi a ions o size, cos and speed, bu as hese a e o e come, i will be included in o he
elec onic componen s such as p in ed ci cui boa ds and e en human cells and o gans.
In addi ion, esea che s a e al eady wo king on 4D p in ing ha would lead o a new
gene a ion o sel -modi ying p oduc s ha would espond o en i onmen al changes and
could be used o make clo hing o oo wea , as well as o heal hca e as implan s designed
o i he human body (Klaus Schwab, 2016).
▪ ADVANCED ROBOTICS
Robo s ha e e ol ed so much ha hey a e inc easingly used in all sec o s o a wide
ange o asks. New echnologies a e c ea ing mo e lexible and adap able obo s, which,
hanks o he e olu ion o senso s, a e able o be e unde s and hei en i onmen and
de elop esponses acco dingly. Human-machine collabo a ion is becoming an e e -
close eali y and is al eady aking place in many indus ies. (Klaus Schwab, 2016)
▪ NEW MATERIALS
This echnology e e s o ma e ials ha a e ligh , s ong, ecyclable and adap able.
Mo eo e , hese new sma ma e ials a e capable o sel - epai ing, cleaning and e en
e u ning o hei o iginal shape, and could be a b eak h ough in he igh agains clima e
change and ha e a majo impac on new o ms o manu ac u ing. (Klaus Schwab, 2016)
1.2.2.3 BIOLOGICAL
Bio echnology ha nesses cellula and biomolecula p ocesses o de elop new
echnologies and p oduc s o a ange o uses, including de eloping new pha maceu icals
and ma e ials. Resea che s in S ockholm, o example, a e wo king on wha is being
ou ed as he s onges bioma e ial e e p oduced. Secondly, medicine. Robo s and high
ech can as ack a cu e o pa alysis. Mo eo e , 3D x- ay analysis allows scien is s o
ab ica e a piece o li ing bones eady po implan a ion in 3 weeks. And being able o use
genome edi ing in o de o unde s and changes ha lead cance b ing us close o ind a
cu e.
THE FOURTH INDUSTRIAL REVOLUTION
18
1.2.3 IMPACT AND CHALLENGES
“F om he pe spec i e o human his o y, he e ha e ne e been a ime o g ea e
p omise o po en ial pe il” –Klaus Schwab.
Like i s p ecu so s, he ou h e olu ion is gene a ing bo h eno mous economic po en ial
and ea s abou he changes i implies. Li ing h ough a e olu ion is no easy, he models
o he pas a e obsole e while he u u e ones a e no ully de eloped and socially
accep ed. (Sil a e al., 2019, pp. 7–8).
Klaus Schwab wa ned o he si ua ion we ind ou sel es in a he Wo ld Economic Fo um,
adding ha we a e cu en ly on he b ink o an economic e olu ion ha will impac and
change ou li es, jobs and e en he way we ela e o each o he . He wa ned ha he scale,
scope and complexi y o his e olu ion will esul in a ans o ma ion unlike any hing
humani y has expe ienced be o e (Klaus Schwab, 2016)
P ecisely how and when people and socie ies adop new pa e ns o beha iou and
hinking will de e mine, o a la ge ex en , how hey will be a ec ed by economic and
echnological change (Sil a e al., 2019)
In his sec ion we will s udy he main epe cussions ha his e olu ion will ha e, bo h
he posi i e aspec s ha i will b ing and he challenges and nega i e impac s ha could
a ec us, ocusing on h ee main poin s: business, he economy and he labou ma ke .
1.2.3.1 COMPANIES
One o he bigges bene i s o he ou h indus ial e olu ion o businesses will be
imp o ed p oduc i i y. The basic p inciple is ha companies will be able o c ea e sma
g ids ha will be able o con ol hemsel es, along he en i e alue chain. (Pe asso, 2016)
The au oma ion o ac ions will educe p oduc ion imes, cos s and ailu es, inc ease
wo ke s' sa e y and allow hem o spend hei ime on ac ions ha eally add alue. The
applica ion o new echnologies acili a es da a-d i en decision making, imp o es
p oduc quali y, enables he c ea ion o new p oduc s and se ices o highe quali y,
making manu ac u ing mo e lexible and he low o in o ma ion be ween di e en
depa men s and s akeholde s mo e e icien .
THE FOURTH INDUSTRIAL REVOLUTION
19
Howe e , no e e y hing is posi i e. Acco ding o expe s, only hose who a e able o
inno a e and adap will bene i , and as hese a e ecen echnologies, hey will equi e a
g ea economic e o ha no all companies will be able o a o d. Mo eo e , he cybe
isks in ol ed in au oma ing a company mean ha cybe secu i y mus be s epped up, he
digi al di ide and echnological dependence and he di icul y o inding people
specialised in he new echnologies a e some o he majo challenges ha companies will
ha e o ace.
1.2.3.2 ECONOMY
The ou h e olu ion has he po en ial o aise global income le els and imp o e he
quali y o li e o en i e popula ions (Klaus Schwab, 2016) . Each e olu ion has led o
inc eased p oduc i i y and indus ial quali y, as well as socio-economic g ow h o
coun ies. The ou h indus ial e olu ion will add $14.2 illion o e he nex ew yea s
and in ensi y globalisa ion ha will posi i ely a ec echnological impac . (Schä e ,
2018, pp. 5–7). P oo o economic imp o emen is he inc ease in GDP a e each
indus ial e olu ion shown in he igu e.
Figu e 7. GDP a e he indus ial e olu ion Sou ce: TEDX
On he o he hand, i also sugges s ha i will inc ease wage inequali y and lead o
geopoli ical clashes. The WEF i sel acknowledges ha " he bene i s o openness a e a
isk" om p o ec ionis measu es, especially non- a i ba ie s and global ade
THE FOURTH INDUSTRIAL REVOLUTION
20
egula ions, which ha e been exace ba ed since he 2007 inancial c isis: a challenge ha
he ou h e olu ion will ha e o o e come i i is o deli e wha i p omises.
1.2.3.3 LABOUR MARKET
Employmen is one o he g ea challenges o he ou h indus ial e olu ion, which will
d i e he c ea ion o jobs ha a e di icul o eplace in e ms o echnology, c ea i i y
and leade ship, bu ne e heless, many jobs will disappea . In 2020, he Wo ld Economic
Fo um (WEF) p esen ed he epo en i led "The u u e o Jobs", which analyses he
des uc ion and c ea ion o jobs in he coming yea s as a esul o au oma ion. Many jobs
in ol ing epe i i e and p ecise asks ha e al eady been eplaced by new echnologies
and he au oma ion o p ocesses (The Fu u e o Jobs Repo , 2020).
1.2.3.4 REFLECTIONS
As discussed abo e, each e olu ion has led o an inc ease in indus ial p oduc i i y and
quali y, as well as socio-economic g ow h o coun ies. Howe e , he weal h o coun ies
has no been equi able o all, he e olu ions ha e also b ough inequali y. The goal in
he ou h indus ial e olu ion is no only o achie e highe p oduc ion bu o do so wi h
sus ainable de elopmen ha ad oca es sus ainabili y and inclusi e social and economic
de elopmen (Uni ed Na ions, Gene a, Swi ze land/2014)
Finally, I would like o end his opic wi h Klaus Schwab's hough s on he subjec :
"Fi s , I eel ha he equi ed le els o leade ship and unde s anding o he changes
unde way, ac oss all sec o s, a e low when con as ed wi h he need o e hink ou
economic, social and poli ical sys ems o espond o he ou h indus ial e olu ion. As
a esul , bo h a he na ional and global le els, he equisi e ins i u ional amewo k o
go e n he di usion o inno a ion and mi iga e he dis up ion is inadequa e a bes and,
a wo s , absen al oge he .
Second, he wo ld lacks a consis en , posi i e and common na a i e ha ou lines he
oppo uni ies and challenges o he ou h indus ial e olu ion,
THE FOURTH INDUSTRIAL REVOLUTION
21
a na a i e ha is essen ial i we a e o empowe a di e se se o indi iduals and
communi ies and a oid a popula backlash agains he undamen al changes unde way."
(Klaus Schwab, 2016, p. 13)
22
PROJECT MANAGEMENT
23
2 PROJECT MANAGEMENT
PROJECT CONCEPT
A p ojec could be de ined as a empo a y endea ou composed o a se o in e ela ed
ac i i ies ca ied ou in a coo dina ed manne by a pe son o en i y o p oduce a unique
p oduc , se ice o esul and o achie e goals and objec i es, usually o achie e bene i s,
change o added alue. (Nokes & Kelly, 2007). Being empo a y, i has a de ined
beginning and end in ime, (usually wi h ime cons ain s and o en wi h unding o
s a ing cons ain s). Acco ding o he (PMBOK, 6 h edi ion) a empo a y e o ha is
unde aken o c ea e a unique p oduc , se ice o esul . (A Guide o he Fundamen als o
P ojec Managemen (PMBOK Guide), Six h Edi ion, 2017, p. 4). A empo a y, single,
mul idisciplina y and o ganised e o ha is ca ied ou wi h deli e ables subjec o
p ede ined equi emen s and cons ain s (Indi idual Compe ence Baseline Fü
P og ammmanagemen , 2017). Mo eo e , i is a complex and dynamic sys em,
(consis ing o mul idisciplina y ac i i ies), which needs o be ac ed upon h oughou i s
li e, in o de o achie e he objec i es o : scope, ime, cos , quali y and s akeholde
sa is ac ion. (Paja es e al., 2017, pp. 125–126).
The main objec i e o a p ojec is o sa is y a clien 's need. (G ay & La son, 2018, p. 6).
Fu he mo e, he main cha ac e is ics o a p ojec a e he ollowing: Ha ing an es ablished
objec i e; a de ined li e span wi h a beginning and an end; he in ol emen o se e al
depa men s and p o essionals; doing some hing ha has ne e been done be o e; speci ic
ime, cos , and pe o mance equi emen s. (G ay & La son, 2018, pp. 7–8).
2.1.1 DIFFERENCE BETWEEN PROCESS, PROJECT AND
PROGRAMME
A common concep ual p oblem is o e e in e changeably o p ocess and p ojec . I is
impo an o s ess ha p ojec s should no be con used wi h day- o-day wo k (p ocesses).
Al hough bo h a e aimed a achie ing a goal, p ocesses usually in ol e doing he same
PROJECT MANAGEMENT
24
wo k o simula ing i epea edly, whe eas a p ojec is ca ied ou only once and when
comple ed esul s in a new p oduc o se ice.
Recognising he di e ence is impo an because oo o en esou ces can be deple ed in
day- o-day ope a ions, which may no con ibu e o he o ganisa ion's long- e m s a egies
ha equi e inno a i e new p oduc s. (G ay & La son, 2018, pp. 8–9). Mo eo e , in
p ac ice, managing hese di e en p oduc ion app oaches equi es he de elopmen o
di e en echnical skills and managemen s a egies. (Ca ani, 2011)
Ano he common concep ual misconcep ion is he use o he e ms p ojec and
p og amme as synonyms. A p og amme is a g oup o in e ela ed p ojec s designed o
achie e a common goal o e a long pe iod o ime. Each p ojec wi hin a p og amme has
a p ojec manage . The main di e ences a e in scale and du a ion. P og amme
managemen is he p ocess o managing a g oup o ongoing, in e dependen and
in e ela ed p ojec s in a coo dina ed manne o achie e s a egic objec i es. While each
p ojec e ains i s own objec i es and scope, he p ojec manage and eam a e also
mo i a ed by he o e a ching p og amme objec i e. (G ay & La son, 2018, pp. 8–10).
PROJECT MANAGEMENT
The o icial de ini ion p o ided by he P ojec Managemen Ins i u e (PMI) s a es ha
p ojec managemen is he use o knowledge, skills and echniques o execu e p ojec s
e ec i ely and e icien ly. I is a s a egic compe ence o o ganisa ions, enabling hem
o link p ojec esul s wi h business goals o be e posi ion hemsel es in he ma ke place.
P ojec managemen is unde s ood as he applica ion o knowledge, skills, ools and
echniques o p ojec ac i i ies o mee p ojec equi emen s. (A Guide o he
Fundamen als o P ojec Managemen (PMBOK Guide), Six h Edi ion, 2017, pp. 10–11).
The o icial de ini ion p o ided by he Associa ion o P ojec Managemen (APM)
s a es: p ojec managemen ocuses on con olling he in oduc ion o he desi ed change.
This in ol es: unde s anding s akeholde needs; planning wha needs o be done, when,
by whom and o wha s anda ds; c ea ing and mo i a ing he eam; coo dina ing he wo k
o di e en people; moni o ing he wo k being done; managing any changes o he plan;
PROJECT MANAGEMENT
25
achie ing sa is ac o y esul s. (Di ec ing Change, 2008, pp. 3–5). P ojec managemen ,
hen, is he applica ion o knowledge, skills, ools, and echniques o p ojec ac i i ies o
mee he p ojec equi emen s.
2.2.1 PROJECT MANAGEMENT CONTEXT
Al hough p ojec s can be ound in ancien ci ilisa ions, such as he Egyp ians, G eeks and
Romans, i was no un il ecen yea s ha p ojec managemen was de eloped as a
discipline wi h he de elopmen o he CPM (C i ical Pa h Me hod) and PERT (P ojec
E alua ion and Re iew Techniques) me hods by he Uni ed S a es Depa men o
De ence, in he con ex o he Pola is P og amme.
As a discipline, p ojec managemen has mos ly been de eloped by p o essionals who
b ing oge he and s uc u e he knowledge, skills, ools and echniques ( ha ) can inc ease
he chances o success in many p ojec s (A Guide o he Fundamen als o P ojec
Managemen (PMBOK Guide), Six h Edi ion, 2017). In ac , he mos commonly used
managemen me hodologies ha e been de eloped by in e na ional p o essional
associa ions, such as he P ojec Managemen Ins i u e (PMI) and he In e na ional P ojec
Managemen Associa ion (IPMA). These p o essionals s udy he ools o p ojec
managemen in di e en a eas wi h he aim o inc easing he scope and quali y o p ojec
managemen ; p o iding a o um o ideas, applica ions and solu ions; s imula ing he use
o p ojec managemen o he bene i o business and he public; collabo a ing wi h
uni e si ies and o he educa ional ins i u ions; os e ing academic and indus ial
de elopmen ; and engaging in in e na ional ne wo king. (Lledó & Ri a ola, 2010, p. 16).
O he popula bodies o knowledge, guidelines and me hodological amewo ks include
PRINCE2 (P ojec s in Con olled En i onmen s), de eloped and widely used by he UK
Go e nmen , he P2M (P og am and P ojec Managemen o En e p ise Business
Inno a ion) o he P ojec Managemen Associa ion o Japan and he APM Body o
Knowledge o he B i ish Associa ion o P ojec Managemen (APM), among o he s.
PROJECT MANAGEMENT
32
Topica (WHAT)
P inciples (WHY)
P ocess (HOW)
Business Case
Business jus i ica ion
S a -up
O ganisa ion
Lea ning om expe ience
De ined oles and
esponsibili ies
S a ing a p ojec
Quali y
Managemen by phases
P ojec managemen
Plans
Managemen by excep ion
Con olling a phase
Risk
P oduc ocus
Managemen o p oduc deli e y
Change
Adap a ion o he
en i onmen
Managemen o phase limi s
Closing o a p ojec
P og ess
Lea ning om expe ience
De ined oles and
esponsibili ies
S a ing a p ojec
Table 3. PRINCE O ganisa ion Sou ce: (AXELOS, 2017)
PM2
A me hodology endo sed by he Eu opean Commission, which o e s solu ions and
bene i s h ough e ec i e p ojec li ecycle managemen . PM² has been c ea ed wi h he
needs o EU ins i u ions and p ojec s in mind bu is ans e able o p ojec s in any
o ganisa ion. The PM² Me hodology is buil on P ojec Managemen bes p ac ices and is
suppo ed by ou pilla s (Eu opean Union, 2021).
The basis is ma ke bes p ac ices ha suppo 4 pilla s (Figu e 10), namely Go e nance,
Li ecycle, P ocesses and Tools. The spi i o he PM2 me hodology is de ined in de ail in
he PM2 Philosophy, which includes PM2 bes p ac ices and p o ides a common se o
belie s and alues o PM2 p ojec eams (Kou ounakis & Ma aslis, 2018).
PROJECT MANAGEMENT
33
Figu e 10. PM2 Pilla s. Sou ce: (Eu opean Union, 2021)
As men ioned abo e, PM2 is based on he bes p ac ices o o he me hodologies such as
PMBOK. P oo o his is he ollowing Figu e 11 which shows he p ojec li ecycle, e y
simila o he one shown in Figu e 9.
Figu e 11. PM2 li ecycle. Sou ce: (Eu opean Union, 2021)
PROJECT MANAGEMENT
34
The ollowing Table 4. PM2 p ojec phases shows a summa y o he concep s o each:
phase o he p ojec .
WATERFALL
This me hodology is a classical model de eloped and p io i ised in he li e cycle p ocess
(Bha sa , 2021, pp. 23–24). This model, p esen s a sequen ial de elopmen (Balaji &
Mu ugaiyan, 2012, p. 27). This me hodology is dis ibu ed in se e al s ages. The ou pu ,
o end o he p e ious s age will o m he inpu o he nex s age, and so on. (Alsham ani
& Baha ab, 2015, p. 106). An example o his can be seen in he ollowing image:
Figu e 12. Wa e all me hodology. Sou ce: (In ini y, 2021)
Table 4. PM2 p ojec phases. Sou ce: (Eu opean Union, 2021)
PROJECT MANAGEMENT
35
▪ WATERFALL AREAS
As i could be seen in he Figu e 12, he wa e all a eas a e:
AREAS
DESCRIPTION
REQUIREMENT
GATHERING
o The collec ion o cus ome and s akeholde equi emen s
is he i s s ep o his me hodology. I is he i s s ep in
o ganising and planning he en i e p ojec wi hou he
in ol emen o he cus ome .
o The equi emen s mus be documen ed de ailing he
necessa y cha ac e is ics and da a.
ANALYSIS
o As discussed abo e, he inpu o his a ea is he ou pu o
he p e ious a ea, so he inpu o he analysis s age is he
equi emen s documen om he p e ious s age.
o The equi emen s documen is analysed and he models
ha will be used o design logical and heo e ical
solu ions a e de eloped.
DESING
o The inpu o his sec ion a e he solu ions elabo a ed in he
p e ious analysis.
o In his sec ion he decisions made ea lie a e modi ied i
necessa y and all echnical equi emen s a e e iewed.
o A e all his has been done, a conc e e plan is ob ained in
which he heo e ical solu ions ha e been ansla ed in o
conc e e speci ica ions.
CODING
o Following he conc e e speci ica ions o he p e ious
sec ion, he ac ual code is de eloped.
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TESTING
o Wi h he ac ual code w i en in he p e ious s age, he
code is examined o de ec s and bugs.
o Some imes his s age may ake us back o coding o
ensu e ze o de ec s.
o I he e a e no de ec s, he inal s age is passed.
OPERATIONS
o Wi h he applica ion inalised in he p e ious s age, he
implemen a ion o he applica ion will be ca ied ou in
his a ea.
o Suppo , upda ing and main enance o he applica ion is
included.
Table 5. A eas o wa e all me hodology. Sou ce: Own made ollowing (Bha sa , 2021; In ini y,
2021 Alsham ani & Baha ab, 2015; And ei e al., 2019; Balaji & Mu ugaiyan, 2012; Hawo h,
2021; Mo on, 2011)
▪ ADVANTAGES AND DISADVANTAGES
To summa ize in he ollowing images he ad an ages and disad an ages a e shown:
Figu e 13. Ad an ages and disad an ages o wa e all me hodology. Sou ce: (In ini y, 2021)
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2.2.2.2 AGILE METHODOLOGIES
Th oughou he 21s cen u y, he use o agile me hodologies o he de elopmen o
compu e so wa e has been sp eading. The basis o all o hem is he es ablishmen o
wo k cycles, a he end o each o which a mo e and mo e comple e unc ional p oduc
will be ob ained (inc emen al p ocesses). Agile me hodologies a e hose ha allow he
way o wo king o be adap ed o he ci cums ances o he p ojec , achie ing apid
esponses and lexibili y o adap he p ojec and i s de elopmen o he ci cums ances o
he en i onmen . The aim is o inc ease he clien 's con idence by in ol ing hem in he
p ocess, coope a ing wi h he eam and ob aining esul s on a egula basis.
The bene i s o his me hodology o he companies ha apply i a e o manage hei
p ojec s in a lexible, au onomous and e icien way, educing cos s and he e o e
inc easing hei pe o mance. These me hodologies a e cha ac e ised by educing he
la ge amoun o documen a ion ha is gene a ed in p ojec s ha ollow adi ional
me hodologies, con inuously adap ing o he ci cums ances and needs o he clien and
p esen ing an inc emen al de elopmen o a p oduc .
In Feb ua y 2001, a mee ing was held in Snowbi d (U ah, USA) wi h se en een c i ics o
es ablish p inciples o imp o ing so wa e de elopmen . As a conclusion o his mee ing,
a documen called he Agile Mani es o was p oduced (Beck e al., 2001). The Agile
Mani es o is a se o ules, s anda ds and guidelines ha a me hodology mus comply wi h
in o de o be conside ed agile. Al hough he Agile Mani es o assesses ha all pa ies
in ol ed in he de elopmen o a p ojec a e impo an , some imes ce ain elemen s mee
and need o be p io i ised.
In ac , he e a e di e en ypes o me hodologies ha ha e been nuanced acco ding o
he needs o he ype o p ojec , bu all o hem a e guided by he Agile Mani es o, which
includes hese ou p emises:
o Indi iduals and in e ac ions o e p ocesses and ools.
o Wo king so wa e o e comp ehensi e documen a ion.
o Cus ome collabo a ion o e con ac nego ia ion.
o Responding o change o e ollowing a plan. (Beck e al., 2001)
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This me hodology is widely used in so wa e de elopmen , bu i is also in e es ing o
de elopmen p ojec s in which di e en i e a ions a e needed o each he esul . In ac ,
one o he main ad an ages ha we ind in he use o agile me hodologies is i s adap a ion
o he needs o he p ojec . (J. Highsmi h & A. Cockbu n, 2001, pp. 120–127).
In addi ion, he e a e a numbe o ad an ages when applying his ype o me hodology,
such as cus ome sa is ac ion, by in ol ing hem in he decision-making p ocess o he
p ojec , being in o med a all imes o he p og ess o he p ojec and i s di icul ies, in
o de o ob ain a mo e accu a e opinion o he app oach o esou ces, he imp o emen o
he in ol emen and mo i a ion o he eam is plausible because hey a e equal
pa icipan s in he same, knowing a all imes he s a us o he p ojec , and by pe o ming
di e en i e a ions, we inc ease he e iciency and speed o he wo k done, elimina ing
any unnecessa y ea u es.
The ad an age we ge om he implemen a ion o agile me hodologies in complex
p ojec s is ha we do no ha e o wai un il he end o he p ojec o ge he esul o he
p ojec , bu we will also wo k by unc ional, i e a i e and inc emen al deli e ies, h ough
which he clien will be able o know how he p oduc is g owing and how i is being
buil .
The ollowing a e he bes -known agile me hodologies cu en ly in use:
EXTREME PROGRAMMING, XP
The XP me hodology is an agile me hodology dedica ed o so wa e de elopmen . I is
one o he mos success ul oday and is dedica ed o he de elopmen o sho - e m
p ojec s wi h a small eam size. The me hodology consis s o apid (o ex eme)
p og amming, whose pa icula i y is o ha e he end use as pa o he eam, which is
conside ed one o he equi emen s o success in he p ojec .
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▪ EXTREME PROGRAMMING HAS THE FOLLOWING CHARACTERISTICS:
o I e a i e and inc emen al de elopmen : Small imp o emen s ha ollow one a e
he o he .
o Con inuous uni es ing: O en epea ed and au oma ed, including eg ession
es ing ( o disco e bugs in unc ionali y). I is ad isable o w i e es code be o e
coding.
o G oup p og amming: i is ecommended ha de elopmen asks a e pe o med by
wo o mo e people in he same posi ion. In his way, he code is e iewed and
discussed while i is being w i en, which ensu es an inc ease in quali y ha is mo e
impo an han possible loss due o unp oduc i i y.
o Bug ixing: Be o e adding new ea u es, i is impo an ha all bugs a e ixed. This
is sol ed by inc easing he numbe o deli e ables.
o In eg a ion o he p og amming eam wi h he clien /use : I is ecommended ha
a ep esen a i e o he clien wo ks oge he wi h he de elopmen eam.
o Code e ac o ing: This consis s o ew i ing ce ain pa s o he code o imp o e i s
eadabili y and main ainabili y, wi hou modi ying i s beha iou . Tes s mus
ensu e ha no bugs ha e been in oduced in he e ac o ing.
o Sha ed code owne ship: Ins ead o di iding he esponsibili ies o he
de elopmen o each module in di e en wo king g oups, his me hodology
p omo es ha any membe o he eam can co ec and ex end any pa o he
p ojec . F equen eg ession es ing ensu es ha po en ial bugs a e caugh .
o Simplici y in he code: This is he bes way o make hings wo k. XP claims ha i
is be e o s a wi h 'simple' de elopmen and ha e o do ex a wo k i
imp o emen s a e needed, han o use complex so wa e and code, whe e making
changes is eally complica ed.
o Simplici y and communica ion a e ex ao dina ily complemen a y. Wi h mo e
communica ion i is easie o iden i y wha should and should no be done. The
simple he wo king sys em, he simple he communica ion in he wo king eam,
which leads o mo e comple e communica ion, especially i he eam o
p og amme s can be educed.
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▪ XP ROLES
Al hough he numbe o oles has e ol ed since i s ini ial concep ion, and a ies
depending on he p oduc o p ojec being de eloped, he o iginal p oposal o he XP
me hodology included he ollowing:
o Cus ome / Use : This is he pe son in cha ge o w i ing he Use S o ies, which
includes all he desi ed unc ionali ies. He/she mus also pa icipa e in he unc ional
es ing o he p oduc o alida e i s implemen a ion. He/she ca ego ises he asks by
di icul y and/o impo ance, deciding which ones should be de eloped in each wo k
cycle. The e is only one clien o use pe p ojec wi hin he eam who, i necessa y,
mus ac on behal o as many people as may be a ec ed by he solu ion.
o Coach: The Coach (" aine ") is esponsible o ensu ing ha he XP me hodology is
being implemen ed co ec ly. He/she needs o know he XP p ocedu es in dep h o
lead he eam du ing he de elopmen o he p ojec .
o Big Boss: The Big Boss (Manage ) has he main unc ion o being he link be ween
he cus ome and he de elopmen eam. He/she mainly pe o ms coo dina ion asks.
o P og amme : P og amme s a e he main de elope s o he p oduc . They w i e and
implemen he sys em code. They mus be in cons an communica ion wi h he o he
membe s o he eam, as he pe o mance o he es o he ac i i ies depends on hei
wo k.
o Tes e : The Tes e ( es manage ), pe o ms he unc ional es s in conjunc ion wi h
he clien on a egula basis. I is usually a single pe son, who mus be in cons an
communica ion wi h he p og amming eam o sol e possible code e o s.
o T acke : The T acke mus con inuously e alua e he s a us o he p ojec , compa ing
i wi h he es ima es made bo h a he beginning and du ing he cou se o he p ojec .
He/she econside s objec i es, deadlines and esou ces in each wo k cycle o imp o e
he es ima es.
All o hese oles a e p esen in i ually any p ojec whe e his me hodology is used,
al hough i is common o he same pe son o assume se e al o hem simul aneously. I
is common o se e al o he unc ions o T acke , Coach and Big Boss o all on he same
membe o he eam.
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SCRUM
SCRUM is a wo king me hodology o he de elopmen and main enance o p oduc s o
any complexi y. I is one o he mos ep esen a i e agile me hodologies cu en ly used.
I s ini ial ocus was o use in so wa e de elopmen p ojec s, al hough i s p inciples a e
easily adap able o any con ex o a ea o knowledge. The Sc um me hodology is a
amewo k based on i e a i e and inc emen al p oduc de elopmen , whe e he di e en
e sions alida ed by he eam a e pe iodically o malised, acili a ing he de elopmen
o op imal solu ions adap ed o he needs o he end cus ome . All o his is based on
eamwo k, wi h di e en speci ic p o iles, and on cons an mee ings, no mally scheduled,
making his one o i s undamen al pilla s.
The gene al s uc u e o he wo k p ocess acco ding o Sc um s a s wi h he egis a ion
o cus ome eques s, which is ca ied ou by he "P oduc Owne ", who is he
in e media y be ween he end cus ome and he de elopmen eam. Wi h all he needs
egis e ed, we p oceed o plan how o p oceed and he esou ces o be alloca ed, as well
as de ining he egula and pa ial deli e ies o be made, called "sp in s". A e planning,
e e y hing ag eed be ween he eam and he P oduc Owne is eco ded and he di e en
i e a ions o p oduc de elopmen begin, which a e managed by a "Sc um Mas e ", who
would be a manage and acili a o o he eam. Du ing he de elopmen phase, sho daily
mee ings (maximum 15 minu es) a e held o edi ec he wo k plan. A he end o each
sp in , he en i e eam mee s wi h he P oduc Owne o e iew he s a us o he
o icialised e sion, o wa n o any di icul ies, o he objec i es achie ed and o sugges
ac ions o inc ease he inal pe o mance o he p oduc . All e sions a e egis e ed in
o de o ha e he necessa y aceabili y. Once he whole p ocess is inished, a
e ospec i e mee ing is held, which mus be a ended by he en i e Sc um Team, wi h he
objec i e o eco ding he lessons lea ned, possible imp o emen ac ions and ha d poin s
o he p ojec .
This philosophy can be applied o any ype o p ojec in which de elopmen is ca ied
ou , whe he IT o mechanical, simply by a ying he phases and in some cases he
execu ion imes. Bu wi h he sole objec i e o ob aining a p oduc ha sa is ies he end
cus ome by op imising esou ces and maximising he pe o mance o he inal p oduc .
PROJECT MANAGEMENT
48
con inuous and agile, so i is necessa y o be ac i e and deli e he p oduc as as as
possible o sa is y he cus ome /use , as well as o keep a dis ance om he compe i ion
(i any).
5. Empowe he eam
A eam should no be seen as a "se o esou ces" ha a e associa ed wi h a se ice. I
should no be alued in numbe o hou s o in economic cos . Ideally, he de elopmen
eam should assume i s own managemen , ha e manageable and ealis ic asks, and a
di ec con ac wi h he clien .
6. Build in eg i y in
The p ojec , bo h clien - acing and use - acing, mus o e a obus image. In eg i y is
achie ed by combining lexibili y wi h a p oduc ha is main ainable in he long e m,
ca ying ou con inuous i e a ions in sho cycles, in o de o imp o e unc ionali ies
based on use eedback.
7. See he whole
Mos o oday's p ojec s a e highly complex. To manage hem co ec ly i is necessa y o
di ide and decompose hem in o smalle asks. I is necessa y o educe he size o he
eam in o de o in ol e all pa ies. P ojec s can e en be in he hands o se e al eams
simul aneously.
PROJECT MANAGEMENT METHODOLOGIES COMPARISON
49
3 METHODOLOGIES COMPARISON
As discussed in he p e ious opic one me hodology desc ibed by he PMI (A Guide o
he Fundamen als o P ojec Managemen (PMBOK Guide), Six h Edi ion, 2017) is: “A
me hodology is a sys em o p ac ices, echniques, p ocedu es and ules used by hose
wo king in a discipline”. (Michael DeP isco, 2021)
Bu acco ding o (As on, 2021) a me hodology mus be oo ed in some hing mo e
undamen al so i de e mines ha his de ini ion should include hemes. (As on, 2021)
I he e o e de e mines ha me hodologies should apply di e en p inciples, hemes,
amewo ks, p ocesses and s anda ds o help s uc u e he way we deli e p ojec s.
Following his desc ip ion is he ollowing classi ica ion:
Figu e 15. P ojec Managemen Me hodologies. Sou ce: (As on, 2021)
In he g aph in blue, we ind he mo e adi ional me hodologies and in pink he AGILE
echniques. Wi hin he adi ional me hodologies, PRINCE2 me hodology de ines a
comple e me hodology wi h hemes, p inciples, and p ocesses and PMBOK desc ibes
s anda ds wi h some p ocess. In he AGILE me hodologies, XP, like PMBOK desc ibes
s anda ds and some p ocess while Sc um, Kanban and Sc umban de ine p ocesses, Agile
de ines p inciples and Lean de ines hemes.
PROJECT MANAGEMENT METHODOLOGIES COMPARISON
50
F om his poin on, he chap e will be o ganised as ollows: i s we will desc ibe he
si ua ions in which he me hodologies desc ibed in chap e 2 a e and a e no used; hen
we will ocus on de e mining wha he di e ences a e be ween hese p ac ices and o he s;
and inally he conclusion will be p esen ed.
WHEN THE METHODOLOGIES SHOULD, OR SHOULD NOT,
BE USED
In he p e ious chap e , me hodologies ha e been p esen ed, bu when is i ecommended
o use hem and o wha kind o p ojec s, and con e sely, when is i no ecommended
o use hem?
This sec ion desc ibes i s he adi ional me hodologies and hen he agile
me hodologies.
3.1.1 T adi ional Me hodologies
Acco ding o (Azanha e al., 2017) adi ional p ojec Managemen Me hodologies do no
do no ully mee he equi emen s o lexibili y o abso b changes in he p ojec .
Fu he mo e, adi ional p ojec managemen s a e no compa ible wi h he complexi y and
dynamic change o so wa e (Augus ine e al., 2005). Following his idea, (Chin, 2004)
decla ed ha adi ional me hods ha e signi ican limi a ions in si ua ions whe e
inno a ion is high and eams a e small (Chin, 2004).
▪ WATERFALL
I can be a use ul and p edic able app oach i he equi emen s a e ixed, well documen ed
and clea , he echnology is unde s ood and ma u e, and he p ojec is sho . (As on, 2021).
Following on om his idea, (Monday, 2019) es ablished ha his me hodology is ideal
as long as he planning, scope and equi emen s a e ex emely clea and he ou come wi h
his me hod will be success ul and p edic able.
Mo eo e , in o de o he objec i e and equi emen s o emain he same, s akeholde s
mus know exac ly wha i is o wha hey wan . So ha he p ojec is consis en and
p edic able. On he o he hand, his me hodology is e y use ul i he indus y in which
PROJECT MANAGEMENT METHODOLOGIES COMPARISON
51
he p ojec is ca ied ou is egula ed and equi es ex ensi e p ojec acking and
documen a ion. (Team Wo k, 2021)
On he o he hand, as i is such a igid me hodology, and no e y adap able o any change,
i is no ad isable o use i i he objec i es and equi emen s a e no well de ined and he
p ojec may change.
Following his line, i is also no ecommended i con inuous es ing mus be ca ied ou ,
adap ing o he clien 's eques s, and making deli e ies du ing he execu ion o he p ojec .
Recommended
No Recommended
Fixed equi emen s and a ge s
Unde ined and a iable equi emen s and
objec i es
P edic able
P ojec no p edic able
In e es ed pa ies wi h clea ideas
S akeholde s wi h di use ideas
Sec o wi h egula ed measu es
Sec o wi h no documen a ion equi emen s
No p ojec deli e ies o he cus ome
equi ed
P oo o execu ion mus be sen o he clien
Highly epe i i e p ojec s: cons uc ion
and manu ac u ing o he same p oduc
Highly a iable p ojec s
Table 6. Wa e all equi emen s. Sou ce: Own made (Azanha e al., 2017; As on, 2021; Monday,
2019; Team Wo k, 2021)
▪ PRINCE2:
I is a cascading p ojec managemen me hodology ha includes p inciples, hemes and
p ocesses. (As on, 2021). I is a e y in e es ing s uc u e o execu ing la ge and
p edic able p ojec s ha de e mines wha will be deli e ed, ensu es a easible app oach
and de ines in de ail he p ojec pa s, oles and esponsibili ies. I is designed o la ge-
scale IT p ojec s (As on, 2021). Following his line o hough , (Monday, 2019) also
ad oca es he use o his me hodology in la ge, well-de ined p ojec s.
On he o he hand, like wa e all, i is no ecommended i he p ojec is small, as i can
be a e y ime-consuming me hodology o implemen . Mo eo e , his me hodology does
PROJECT MANAGEMENT METHODOLOGIES COMPARISON
52
no ocus on eamwo k (Monday, 2019). Finally, as i is a adi ional me hodology, i s use
is no ecommended in e y lexible p ojec s wi h a high olume o changes.
Recommended
No Recommended
Fixed equi emen s and objec i es
Unde ined and a iable equi emen s and
objec i es
La ge, well-de ined p ojec s. La ge scale
IT p ojec s
Small and ill-de ined p ojec s
P edic able, no changes
P ojec no p edic able
No emphasis on eamwo k
Impo ance o eamwo k
Table 7. PRINCE2 equi emen s. Sou ce: Own made ( Azanha e al., 2017; As on, 2021; Monday,
2019; Team Wo k, 2021)
▪ PMBOK
As men ioned abo e, i is no a me hodology, bu a se o s anda ds ha de e mine he 5
s eps o ca y ou a p ojec . I s use is ecommended o managing la ge-scale depa men s,
companies ha wan all he depa men s o companies in he g oup o wo k in a
s anda dised way. I is also applicable o smalle p ojec s wi h high s anda disa ion (Team
Wo k, 2021)
On he o he hand, his me hodology is no ecommended o small companies ha wo k
wi h p ojec s wi h a high olume o changes a a high pace and i is no ecommended i
i is necessa y o map, e i y, he execu ion o he p ojec in a way ha changes he scope
o he p ojec .
Recommended
No Recommended
Fixed equi emen s and objec i es
Unde ined and a iable equi emen s and
objec i es
La ge-scale p ojec s
Small and ill-de ined p ojec s
P edic able, unchanging
High olume o changes
No mapping equi ed
Need o mapping
Table 8. PMBOK equi emen s. Sou ce: Own made (Azanha e al., 2017; As on, 2021; Monday,
2019; Team Wo k, 2021)
PROJECT MANAGEMENT METHODOLOGIES COMPARISON
53
3.1.2 Agile Me hodologies
Howe e , Agile i sel is no a me hodology o p ocess ha can be used. Agile is he global
e m used o i s implemen a ions, such as Sc um, XP, Kanban, Sc umban, e c.
I is cha ac e ised by emphasising adap abili y in he ace o changes in si ua ions,
p omo ing adequa e communica ion and con inuous imp o emen be ween he wo k eam
and be ween he eam and he clien . They a e excellen me hodologies o use in dynamic
en i onmen s, wi h he possibili y o changing he equi emen s du ing he execu ion o
he p ojec ., dynamic en i onmen s ha ha e a business en i onmen in luenced by
cons an changes. (Azanha e al., 2017). Following his idea, his me hodologies a e
usually conduc ed unde unce ain ies in u bulen en i onmen s, cha ac e ized by
complex p ojec s, unp edic able ac i i ies and changes, scena ios whe e he adi ional
app oaches ha e limi a ions. (Chin, 2004). O he au ho s co obo a e ha he agile
app oach is bes sui ed o dynamic en i onmen s ha ha e a business en i onmen
in luenced by cons an changes. (Boehm, 2004).
On he o he hand, i is impo an o men ion ha agile me hodologies abandon planning,
epo ing and scheduling in a ou o lexibili y and communica ion. (Azanha e al.,
2017). So ha , agile me hodologies a e noy sugges ed as he bes uni e sal p ac ices
(Highsmi h, 2004).
The e o e, agile me hodologies a e in e es ing o use in dynamic, changing p ojec s,
whe e he solu ion a he beginning o he p ojec is no known in i s en i e y since i can
be adap ed as he p ojec is execu ed. P ojec s ha need o wo k as and whe e apid
p og ess and de elopmen is mo e impo an han a pe ec esul . Fo ins ance, so wa e
p ojec . Ne e heless, Howe e , i has been p o en ha hese me hodologies a e no only
applicable o so wa e de elopmen p ojec s.(Con o o e al., 2014) and ha hey can be
used in p ojec s such as he ollowing image:
PROJECT MANAGEMENT METHODOLOGIES COMPARISON
54
Figu e 16. Managemen p ac ices ela ed o he agile p ojec managemen app oach. Sou ce:
(Con o o e al., 2014)
Howe e , i is no ad isable o use hese me hodologies i he p ojec equi es a high
deg ee o documen a ion and epo ing. I he deli e ables ha e exac ed and immo able
deadlines and mus be p edic able and clea om he beginning. Finally, i he p ojec o
be de eloped does no need he clien 's opinion, he ideas a e clea and ixed and canno
be a ied du ing he execu ion, hese a e no he bes me hodologies o apply. (Team
Wo k, 2021).
Al hough as me hodologies belonging o his la ge g oup hey sha e many simila i ies,
he Agile me hodologies s udied in he p e ious chap e a e p esen ed below o de e mine
in mo e de ail when i is ad isable and when i is no ad isable o use hem.
▪ SCRUM
This me hodology was o iginally designed o so wa e de elopmen and R&D, al hough
i has also been applied o o he ypes o p ojec s.
I is an ideal me hodology o c ea i e p ojec s, whe e changing some hing does no imply
pu ing he whole p ojec a isk. (As on, 2021). The e o e, i s use is ecommended in
dynamic p ojec s, whe e con inuous imp o emen is desi ed. I is no mally used in
p ojec s wi h small g oups o up o 10 people, al hough i is ue and al hough i is no
ecommended, he e a e companies ha ha e used i o la ge p ojec s and ha e been
success ul (Monday, 2019).
PROJECT MANAGEMENT METHODOLOGIES COMPARISON
55
As an agile me hodology, i dispenses wi h a lo o he documen a ion phase, he e o e,
Sc um is ecommended in p ojec s whe e his is no a egula o y equi emen o he clien
o he company. In addi ion, i ocuses on as deli e ies and a lo o con ol o e he
p ojec , in ol ing he clien a all imes in decision making, he e o e, i is essen ial o be
able o coun on he clien 's eedback.
Finally, i is an ideal me hodology o implemen in changing en i onmen s, whe e he
objec i es do no ha e o be de ined om he beginning and whe e changes can be made
in he middle o he p ojec . (Monday, 2019; Team Wo k, 2021; Azanha e al., 2017;
As on, 2021; Augus ine e al., 2005; Beck e al., 2001; Chin, 2004; Highsmi h, 2004; J.
Highsmi h & A. Cockbu n, 2001; Ma o ic, 2020).
Recommended
No Recommended
Unde ined and a iable equi emen s and
objec i es
Fixed equi emen s and a ge s
Unp edic able, changing en i onmen s
P edic able
Dynamic and c ea i e p ojec s
In e es ed pa s wi h clea ideas
Small g oups o up o 10 people
Big g oups, mo e han 10 people
No egula o y equi ed
Highly epe i i e p ojec s: cons uc ion and
manu ac u ing o he same p oduc
Clien in ol ed
No p ojec deli e ies o he cus ome
equi ed
Table 9. SCRUM equi emen s. Sou ce: (As on, 2021; Azanha e al., 2017; Monday, 2019; Team
Wo k, 2021)
▪ KANBAN
Ideal me hodology o ope a ional o main enance en i onmen s whe e p io i ies end o
a y equen ly and equi e consis en pe o mance.
This me hodology was de eloped speci ically o so wa e de elopmen , al hough i is
applicable o i ually any p edic able p ocess. (Monday, 2019). I is highly
ecommended o apply i you wan o ha e a global ision o he execu ion o he p ojec ,
i s p ocess and he upda es ha a e being ca ied ou . The e o e, i is ideal o wo king
PROJECT MANAGEMENT METHODOLOGIES COMPARISON
56
wi h con inuous imp o emen . Al hough we will la e s udy he di e ences be ween he
me hodologies, i is wo h highligh ing ha one o he di e ences wi h SCRUM is ha
KANBAN does no equi e daily mee ings.
On he o he hand, i he p ocess o be ca ied ou is e y complex o consis s o many
s ages, i is no ad isable o use his me hodology as i will lead o a g ea was e o ime.
Recommended
No Recommended
Ope a ional o main enance
en i onmen s
Fixed equi emen s and a ge s
Need o ha ing a global ision o he
execu ion p ojec
Complex p ojec s
P edic able p ocess
Non de ined p ocess
Con inuous imp o emen
No need o imp o e
Dynamic and c ea i e p ojec s
Sec o wi h egula ed measu es
Table 10. KANBAN equi emen s. Sou ce: (As on, 2021; Azanha e al., 2017; Monday, 2019; Team
Wo k, 2021)
▪ LEAN
I is a me hodology ha is easy o implemen in manu ac u ing o p oduc ion
en i onmen s o a physical p oduc such as a ca . In addi ion, his me hodology is also
widely used in p ojec deli e y p ocesses as i educes unnecessa y da a, inc eases he
alue o he p ojec and op imises i . (As on, 2021). Con inuing wi h his idea, (Team
Wo k, 2021) co obo a es ha his me hodology is cha ac e ised by imp o ing and adding
alue o he p ojec o he clien as well as educing cos s. (Monday, 2019) adds ha his
me hodology inc eases wo k e iciency, elimina es was e o obsole e s ock and imp o es
he quali y o cus ome ela ions and communica ion. Howe e , i is no ecommended
o use in eams wo king digi ally.
PROJECT MANAGEMENT METHODOLOGIES COMPARISON
57
▪ XP
As an Agile me hodology, XP has e y simila cha ac e is ics o use o hose men ioned
abo e. Howe e , we can highligh ha i di e s om o he me hodologies such as Sc um
in ha XP es ablishes ules ela ed o design, coding and es ing speci ic o de elopmen
p ojec s.
In addi ion, i has been ound o be a e y use ul me hodology o os e ing eamwo k
and collabo a ion among p ojec membe s, especially o small eams.
▪ OTHER METHODOLOGIES
The me hodologies desc ibed abo e a e he mos widely used by companies bu i is ue
ha he e a e many o he me hodologies including PRiSM, C i ical Pa h, PERT, C ys al
Me hod in which p ojec p ocesses a e gi en low p io i y emphasising he skills,
communica ion and in e ac ion o he eam o Adap i e F amewo k (APF o APM),
whe e he objec i e o his me hodology is o be adap able o change, in ac , i was
designed aking in o accoun he ine i abili y o change. The e o e, eams mus be
p epa ed o an icipa e isks and cons an ly e-e alua e esul s and decisions. The scope o
he p ojec is a iable, bu he ime and cos a e cons an , making i possible o adjus he
scope o he p ojec du ing execu ion o ge he maximum business alue om he p ojec .
This me hodology equi es high communica ion be ween all s akeholde s. Finally, his
me hodology is ecommended i he inal objec i es a e known bu i you need
p edic abili y and do no ha e he necessa y esou ces o deal wi h scope a ia ions,
ewo k o misuse o ime, i is no ad isable o use his me hodology.
ABSTRACT
The ollowing image shows he classi ica ion acco ding o he di e en me hodologies
ha ha e been explained, depending on whe he hey a e s able p ojec s o p ojec s ha
need o be ca ied ou quickly and whe he hey a e ixed o dynamic p ojec s:
PROJECT MANAGEMENT METHODOLOGIES COMPARISON
64
On he o he hand, he e a e a numbe o simila i ies be ween he me hodologies o
conside :
• Bo h me hodologies need o be es ed be o e a eam can decide which app oach
o adop
• Bo h ocus on apid deli e y o unc ionali y
• Bo h will discuss equen ly wi h he cus ome o ge hei eedback as ea ly as
possible.
(And ei e al., 2019, pp. 129–130)
As bo h me hodologies ha e a numbe o e y use ul and bene icial beha iou s, b inging
hem oge he as a hyb id me hodology has esul ed in SCRUMBAN.
SCRUMBAN
This is a hyb id me hodology, meaning a mix u e o 2 known me hodologies in which he
app op ia e cha ac e is ics needed o he execu ion o he p ojec a e aken ad an age o .
Al hough his me hodology has no been p esen ed in he p e ious chap e , being one o
he many applicable hyb id me hodologies, i is in e es ing and applicable o many
p ojec s.
This hyb id me hodology helps o imp o e he e ec i eness o Sp in engagemen .
Howe e , i also in oduces he WIP bounda y as a mechanism o ca alyse inc emen al
change. The WIP bounda y a oids he need o commi o d i ing change, educes any
dys unc ional eliance on e o and imp o es o e all sys ems hinking when conside ing
po en ial imp o emen s. (Julio Roche, 2019)
PROJECT MANAGEMENT METHODOLOGIES COMPARISON
65
▪ XP VS SCRUM
These wo agile me hodologies a e closely ela ed o each o he and he e o e he
di e ences be ween hem a e minimal:
XP
SCRUM
ITERATION
TIME
1 o 2 weeks.
2 weeks un il one mon h.
CHANGING
ITERATIONS
I accep s changes in i s i e a ions as
long as a pa icula equi emen has
no been s a ed.
Mee ing i ems a e de ined in he
backlog and no changes can be made
un il he end o he backlog.
ITERATION
ORDER
Requi emen s a e p io i ised by he
cus ome (p oduc owne in
SCRUM) and he eam mus ollow
i .
The p oduc owne p io i ises he
p oduc backlog bu he eam
de e mines he o de .
BEST
PRACTICES
P ocess adap a ion depending on he
p ojec s ype
Gene ic and equal applica ion ac oss
all p ojec s
SOFTWARE
The so wa e needs o be alida ed
all ime, o ex end ha es a e
w i en p io o he ac ual so wa e.
The alida ion o he so wa e is
comple ed a he end o each sp in , a
Sp in Re iew.
Table 14. Compa ison be ween XP ans SCRUM. Sou ce: (Knibe g, 2007)
▪ SIMILARITIES BETWEEN
Figu e 20. Simila i ies be ween Lean, XP and Sc um. Sou ce: (Lay on e al., 2020)
PROJECT MANAGEMENT METHODOLOGIES COMPARISON
66
HYBRID METHODOLOGIES
So a we ha e desc ibed when he di e en me hodologies should be used o no and
ha e been compa ed be ween hem, bu in a momen we ha e w i en he hyb id
me hodologies since we ha e ocused on deepening and knowing p ope ly all he
me hodologies and hei uses in o de o choose he bes me hodology o combina ion o
me hodologies o apply in he nex chap e o sol e ou p ojec managemen p oblem.
Many a icles s a e ha he e is no single p ojec managemen me hodology ha co e s
all needs, hence he exis ence o hyb id me hodologies. Following his line o hough A
case s udy o a B azilian pha maceu ical company IT p ojec (Azanha e al., 2017) He
de e mined ha in o de o selec he igh me hodology i is e y impo an o ake in o
accoun he decision s a egy and added ha in many cases a single me hodology will no
be su icien bu ha he combina ion o adi ional and agile me hodologies will no be
enough can be cus omized and adap ed o he equi emen s o each p ojec . (Azanha e
al., 2017).
In addi ion, he ollowing image shows he o he s udy in which he compa ison and
e alua ion o e y di e en agile me hodologies de e mined ha agile me hodologies do
no adap well o la ge scale which could explain he exis ence o adi ional wa e all
app oach (Shaydulin & Syb and , 2017).
PROJECT MANAGEMENT METHODOLOGIES COMPARISON
67
Figu e 21. Resul o he e alua ion o di e en me hodologies. Sou ce: (Shaydulin & Syb and ,
2017)
Fu he mo e, he same s udy, he esul o which has been p esen ed in he pic u e abo e,
demons a ed ha o all he me hodologies compa ed, none adequa ely add essed all he
impo an aspec s o he so wa e design p ocess. This same a icle o e ed a hyb id
implemen a ion idea consis ing o he ollowing: using wa e all o p ojec planning;
Sc um o sho - e m goals and XP o so wa e emedia ion.
Mo eo e , Vijayasa a hy s a ed ha mo e han 45% o so wa e eams use a hyb id
app oach (Vijayasa a hy & Bu le , 2016). As can be seen in he ollowing g aphic:
Figu e 22. Me hodologies used in p ojec s. Sou ce: (Vijayasa a hy & Bu le , 2016)
PROJECT MANAGEMENT METHODOLOGIES COMPARISON
68
In addi ion, he same s udy made a compa ison o he numbe o eams in ol ed in a
p ojec and he me hodologies ha we e mos commonly used e icien ly and e ec i ely.
Figu e 23. Numbe o eams and p ojec managemen . Sou ce: (Vijayasa a hy & Bu le , 2016)
BEER PRODUCTION PROJECT
69
4 BEER PROJECT 4.0
This chap e p esen s he bee p oduc ion p ojec a he Uni e si y o Albs ad
Sigma ingen.
PROJECT CONTEXT
The p ojec consis s o au oma ing he b ewing p ocess by implemen ing a Sma Fac o y
simula ion. The main objec i e is o imp o e he quali y o bee p oduc ion and o be a
leade in inno a ion. The aim is o imp o e p ocess s abili y and p oduc quali y in he
e men a ion a ea.
The e men a ion p ocess is p one o quali y luc ua ions, he aim o he s uden s is o
op imise he p ocess by elimina ing de ici s.
Below is a able wi h he de ici s and he objec i es o be achie ed by au oma ing and
op imising he p ocess.
As shown in he able, he e would be a po en ial inc ease o 66.16% by elimina ing
14.34% o he de ici s and inc easing capaci y and quali y by 51.82%.
4.1.1 PARTICIPANTS
The p ojec is ca ied ou by s uden s o he Uni e si y o Albs ad Sigma ingen om
h ee di e en compu e science deg ees, esul ing in h ee g oups, each consis ing o
only s uden s o he same deg ee and ocusing on a speci ic p og amme.
De ici s
Imp o emen s
Low p ocess s abili y
High p ocess s abili y
High quali y luc ua ions
Consis en ly high p oduc quali y
Uncon ollable quali y
Au oma ed con ol and documen a ion o
he e men a ion p ocess
Lack o au oma ion
Reduc ion o bene i s -14.34% (~115
housand €)
Inc ease in p o i po en ial 66,16% (~ 530
in housands o eu os €)
Table 15. Bee p oduc ion p ojec . De ici s and Imp o emen s. Sou ce: Albs ad -Sigma ingen
Uni e si y.
BEER PRODUCTION PROJECT
70
Those in g ade Business In o ma ic a e ocus on using SAP, hose in g ade In o ma ic
Secu i y a e mo e ocus on SPS and hose in g ade a e ocus on MQTT commmunica ion.
The so wa e hey use is as ollows:
SAP is a kind o ERP sys em en e p ise which sol es planning sys em. The e a e a lo o
p o ide s o ERP bu SAP is he mos well-known and impo an one because a lo o
companies ope a e i . PLC (SPS) is a p og ammable logic con ol o con ol de ice.
MQTT is a p o ocol used o communica ion be ween he ERP sys em and he SPS
sys em. This eam was he in e media e laye whe e hey ansla e he messages which
come om SPS in o a message ha SAP could unde s and.
4.1.2 PROJECT MANAGEMENT
In his sec ion we will s udy wha p ojec managemen echniques ha e been used so a ,
hen we will s udy he p oblems ha ha e a isen in he pas , and inally we will s udy he
solu ions and p opose new o ms o managemen ocused on Indus y 4.0 and i ual
p ojec s.
4.1.2.1 TOOLS USED SO FAR.
✓ CANVAS
This me hodology is commonly used o he de elopmen o business models and has
nine sec ions, which a e as ollows:
Figu e 24. Can as ool es uc u e.
BEER PRODUCTION PROJECT
71
Howe e , a kind o CANVAS model has been used in his p ojec , which p o ides a
summa y and he main ea u es o he model ha he s uden s mus ake in o accoun in
o de o implemen he p ojec :
Figu e 25. Ve sion o Can as used in he Bee p oduc ion p ojec . Sou ce: Albs ad -Sigma ingen
uni e si y
✓ SEQUENCE DIAGRAM
Sequence diag ams a e in ended o de e mine he in e ac ions be ween he di e en
objec s and o desc ibe he sequence and o de o he objec s.
✓ GANTT DIAGRAM
As al eady discussed in sec ion X o chap e 3, he Gan cha is a g aphical p ojec
managemen ool whose pu pose is o de e mine he ime spen on a ask o ac i i y wi hin
a o al ime.
Howe e , as some s uden s ha e commen ed, he Gan was no always adhe ed o as he
p ojec was no so much ixed, bu e ol ing.
BEER PRODUCTION PROJECT
72
4.1.2.2 PROJECT MANAGEMENT CHALLENGES
Despi e he ools used, he e a e se e al managemen p oblems in he p ojec . In he
p e ious yea , he cou se consis ed o a ound 12 s uden s and h ee la ge g oups. This
yea he e a e h ee s uden s in o al, di ided in o wo g oups. Please no e ha he con en
has been simpli ied due o he smalle numbe o s uden s.
Be o e we s a desc ibing he p oblems, le us di e en ia e be ween he wo g oups. Las
yea 's la ge g oup will hence o h be called Sample A and his yea 's small g oup will be
called Sample B.
The a ie y in he g oup allows us o ca y ou a s udy o he si ua ion in o de o d aw
conclusions. In his sec ion we p esen he si ua ion s udied in he p e ious yea compa ed
o his yea .
SITUATION A
As men ioned abo e, a o al o 12 s uden s om h ee di e en b anches o compu e
science pa icipa ed in his p ojec . Sample A is made up o h ee g oups, each consis ing
only o s uden s om he same b anch.
One o he p oblems ha could be obse ed was a p oblem o in e p e a ion, as hey
belong o di e en b anches o compu e science, he compu e languages o each g oup
o s uden s a e di e en bu he da a o he g oups a e in e ela ed and he e o e need each
o he . This leads o di icul ies in he in e p e a ion o da a, loss o ime and compu e
e o s.
On he o he hand, a communica ion p oblem was obse ed. Weekly mee ings we e held
o sha e wha each eam was doing, wha p oblems a ose and wha hey we e going o do
un il he nex weekly mee ing. These mee ings we e a ended by he whole g oup o
s uden s, bu only a ew o hem spoke, wha was p esen ed was no w i en down, each
g oup p esen ed hei asks and did no ake in o accoun o he people's ci cums ances.
The lack o communica ion esul ed in los ime in implemen a ion, asks being duplica ed
o no ca ied ou a all, and e o s a he end o he p ojec ha we e igge ed by poo
managemen a he beginning. All his esul ed in a g ea loss o ime, delays in he wo k
and s ess o he s uden s on da es close o he deli e y o he p ojec .
BEER PRODUCTION PROJECT
73
SITUATION A
Numbe o pa icipan s
A ound 15
Numbe o g oups
3 g oups: SAP, SPS, MQTT
P ojec managemen
ools used
-Gan
-Sequence diag ams
-Kanban
Pa icipan s in mee ings
All he s uden s
Numbe o mee ings
One weekly
P oblems
Communica ion
- P oblems wi h he sequence o
in o ma ion lows.
-Lack o communica ion be ween
g oups.
-Lack o a en ion om lea ne s.
-Lack o conside a ion o he needs o
o he s.
Da a
in e p e a ion
-Di icul y in unde s anding o eign
languages.
-Compu e e o s
Table 16. Si u a ion A p ojec bee po duc ion. Sou ce: sel made.
SITUATION B
Sample B consis s o only h ee s uden s in o al. Two o hem belong o he SAP g oup
and one o hem o he SPS eam. This yea he e is no MQTT eam so he communica ion
be ween SPS and SAP is done h ough online mee ings.
The communica ion is done di ec ly be ween he SPS and SAP de ices using he MQTT
p og amme, his is done wi h a b oke whe e all he in o ma ion is s o ed and whe e you
can selec he in o ma ion you wan o use. The managemen ools used a e he same as
he p e ious yea , wo weekly mee ings a e held in which he s uden s p esen hei
p og ess, he weekly objec i e hey se hemsel es and i hey ha e any p oblems in he
p og amming. Occasionally he e is an addi ional mee ing. This yea , he communica ion
p oblems o he p e ious yea ha e no been obse ed.
BEER PRODUCTION PROJECT
80
PROJECT CHARACTERISTICS
VARIABLES
CHARACTERISTICS
METHODOLOGY
Numbe o eams
Be ween 2 and 3 eams
AGILE
Size o eams
Be ween 1 un il 6
membe s
-
Possibili y o changes
du ing he execu ion
Yes
AGILE
De elopmen model*
E olu iona y/Held almos
ea ly a he beginning
AGILE
TRADITIONAL
Manage ial app oach
Flexible adap a i e
a iable/ igid, ocusing
on he ini ial plan
AGILE
TRADITIONAL
Wo k
Unp edic able, no
measu able, non-linea
and complex
AGILE
Re iews a e each
i e a ion
Yes
AGILE
Planning
No all is planned since de
beginning
AGILE
Cus ome in olmen
High
AGILE
Requi emen s*
Dynamic bu also well-
de ined be o e s a ing
AGILE
TRADITIONAL
Documen a ion
No as impo an
AGILE
Table 22. Me hodologies o be used acco ding o he cha ac e is ics i he p ojec . Sou ce: sel made
ollowing he li a a u e.
The e o e, as can be seen om s udying he cha ac e is ics o he p ojec and ollowing
wha has been s udied, he mos ecommendable me hodology o apply would be AGILE.
BEER PRODUCTION PROJECT
81
✓ A e iew o he cha ac e is ics o Indus y 4.0 p ojec s
As obse ed in he Table 20, al hough he a icles de e mine ha he e is no es ablished
me hodology ha can be applied in i s en i e y in Indus y 4.0 o ien ed p ojec s, AGILE
me hodologies a e he mos ecommended.
SUMARISE PROJECT 4.0 CHARACTERISTICS
CARATERISTIC
RESULT
AGILE OR
TRADITIONAL
P essu e on p ojec de elopmen
imes
▪ Time is a e y
impo an a iable
AGILE
▪ Need o inish he
p ojec quickly
Business model o ien a ion
▪ Physical ou come no
known un il he end o
he p ojec
AGILE
▪ Unp edic able
▪ T ial and e o
managemen
P ojec o he echnological
e olu ion a e complex in na u e
▪ Inno a ion
AGILE
Table 23. Suma ise p ojec 4.0 cha ac e is ics. Sou ce: Sel made.
BEER PRODUCTION PROJECT
82
4.3.2 CONCLUSION OF THE METHODOLOGY TO BE USED
The me hodologies o be implemen ed o he solu ion o communica ion and in o ma ion
low p oblems a e AGILE me hodologies.
The ou cases s udied ocus mo e on he use o agile me hodologies.
On he o he hand, and as has also been men ioned in p e ious opics, he ollowing
ci cums ances occu :
✓ The e is no ocused me hodology o p ojec s in a Sma ac o y, indus y.
✓ The e is no me hodology ha mee s all he necessa y equi emen s o his ype
o p ojec .
The e o e, in line wi h he p e ious poin , hyb id me hodologies a e mainly
ecommended and used.
F om his poin on, we ocus he s udy on inding solu ions o he p oblems wi h se e al
agile me hodologies, i.e. we will use a hyb id me hodology based on he di e en agile
me hodologies.
• POSSIBLE SOLUTION FOR THE COMMUNICATION AND
INFORMATION FLOW PROBLEMS:
As men ioned in he sec ion compa ing si ua ion A and si ua ion B, when he mee ings
we e made up o only a ew membe s, he communica ion p oblems we e p ac ically non-
exis en .
As a esul o his analysis, he i s solu ion o be es ablished is he ollowing:
INTER-GROUP MEETINGS WITH FEW PARTICIPANTS AND ROLE
The p esence o ew pa icipan s in mee ings will inc ease a en ion and communica ion.
In addi ion, in o de o de e mine who a e he people in each g oup who should a end
mee ings, a ole will ha e o be es ablished wi hin each eam.
These wo measu es will sol e he abo e men ioned p oblem o Si ua ion C in he
implemen a ion o AGILE me hodologies.
These mee ings will be weekly and will be used o discuss wi h he o he g oups wha has
been de eloped du ing he week, he u u e objec i es o be de eloped, he doub s and
BEER PRODUCTION PROJECT
83
p oblems ha ha e a isen and, inally, i he e is a need o help be ween eams, gi en
ha he da a a e in e ela ed.
Following he Lean me hodology on e ec i e mee ings:
• A ime limi should be se o he mee ing, which should no be exceeded. In he e en
ha issues a ise ha need o be add essed, discuss hem wi h hose in ol ed a ano he
ime.
• Comple e an ac ion plan, in his case a so wa e, o kan an me hodology, could be
used o es ablish wha asks a e o be ca ied ou , he ac ions aken and o ollow up
on wha has been discussed, so ha i can hen be passed on o he eams.
In summa y, he esponsibili y o he pe son in his ole will be o:
• Seconda ily o m pa o he o he eams.
• A end mee ings wi h he o he eam ep esen a i es.
• Repo on he asks ca ied ou du ing he week. And u u e asks.
• To expose he asks ha need o be epea ed and ha cause p oblems.
• Discussing doub s wi h o he eams.
• Be conce ned abou he ac i i ies o he o he eams.
• De e mine o whom he o he eams should u n o om hei own eam, o esol e
any doub s.
MEASURE
MEETINGS BETWEEN TEAMS WITH FEW
PARTICIPANTS
OBJECTIVE
▪ Inc eased communica ion
▪ Inc eased a en ion.
MEASURES
TAKEN
▪ Mee ings wi h ew pa icipan s. Ful illing he e ec i eness
o Lean mee ings. (LEAN).
▪ One ep esen a i e om each eam, eam leade .
EXPECTED
RESULT
▪ Reduc ion o in o ma ion low p oblems.
▪ Reduc ion o da a in e p e a ion p oblems.
▪ Reduc ion o was ed ime and duplica ed asks.
Table 24. Measu e solu ion 1, mee ings be ween eams. Sou ce: sel made ollowing he li e a u e.
BEER PRODUCTION PROJECT
84
GLOBAL DIVISION OF LABOUR IN PACKAGES
As was al eady done wi h he SCRUM me hodology in Si ua ion C, he global wo k will
be di ided in o small packages.
Wi h his measu e, we will be able o implemen he ollowing solu ion, a Kanban model
o suppo he Gan , which was o en no ul illed and did no p o ide he eams wi h a
ision.
The e o e, he objec i e o his measu e is o p o ide he eams wi h a ision o he
e olu ion o he wo k ca ied ou , wi h which hey can o ganise hemsel es, know wha
hey ha e done and wha emains o be done.
In addi ion, he esponsibili y o he pe son who has o ca y i ou is added o each ask,
which will inc ease he pa icipa ion o he membe s and con ol o e compliance; asks
will no be duplica ed o le undone, as was some imes he case.
MEASURE
DIVISION OF LABOUR INTO PACKAGES
OBJECTIVE
▪ Inc easing he ision o he p ojec .
MEASURES
TAKEN
▪ O e all di ision o wo k in o packages. (SCRUM)
▪ Es ablishmen o so wa e wi h Kanban philosophy
(KANBAN).
▪ Es ablishmen o esponsibili ies. (XP)
EXPECTED
RESULT
▪ Reduc ion o duplica ed asks.
▪ Elimina e he p oblem o un inished asks.
▪ Be e empo al o ganisa ion o he eams.
▪ Inc eased pa icipa ion o he membe s in he p ojec .
Table 25. Measu e solu ion 2, di ision o labou in o packages. Sou ce: sel made ollowing he
li e a u e.
ROLES WITHIN THE GROUP
Con inuing in line wi h he las commen : " o each ask is added he esponsibili y o he
pe son who has o ca y i ou , which will inc ease he pa icipa ion o he membe s and
he con ol o e compliance, asks will no be duplica ed o le undone, as happened on
ce ain occasions".
BEER PRODUCTION PROJECT
85
As a eam is made up o be ween 2 and 6 people o encou age he pa icipa ion o
e e yone in he wo k, i would be in e es ing o apply oles wi hin he g oup, i would be
in e es ing o apply some oles o he XP me hodology, since as was s udied in he
p e ious opic i is a e y use ul me hodology o eamwo k and collabo a ion among
p ojec membe s, especially o small eams o as ew as 9 people.
• One o hese oles would be he Big Boss, Manage , al eady men ioned o
communica ion wi h o he eams. This could be inc eased o wo ep esen a i es
pe eam and hey a e also in cha ge o suppo ing hei eam. I is e y impo an
ha hey know wha is being done.
• On he o he hand, he p og amme s.
• On he o he hand, he es e s could be es ablished o make su e ha wha is being
done wo ks.
• Suppo ole, acke o aine , one o he people who is p og amming o
es ing, mus also con ol ha all asks a e being ca ied ou and ha deadlines a e
me .
MEASURE
ROLES
OBJECTIVE
▪ Inc eased pa icipa ion and in e nal o ganisa ion o each
eam.
MEASURES
TAKEN
▪ Es ablishmen o esponsibili ies and oles (XP)
EXPECTED
RESULT
▪ Inc eased pa icipa ion and in e nal o ganisa ion o each
eam.
▪ Inc eased communica ion be ween di e en eams.
▪ Imp o ed collabo a ion and eamwo k.
Table 26. Measu e solu ion 3, Roles. Sou ce: sel made ollowing he li e a u e.
86
5 CONCLUSION
The e is no es ablished me hodology o p ojec s in he ou h indus ial e olu ion;
e e y hing will depend on di e en a iables such as he ype o p ojec , isk, size o
g oups, e c.
Howe e , i has been possible o es ablish guidelines and measu es on when i is ad isable
and when i is no ad isable o use he di e en me hodologies s udied. Mo eo e , i is
e y di icul o one me hodology o be 100% applicable.
Acco ding o wha has been s udied, hyb id me hodologies a e cu en ly he mos widely
used o his ype o p ojec . In o de o de e mine which ypes o me hodologies would
be used o make up he inal hyb id me hodology, we ha e based ou sel es on se e al
a iables, including he ac ha when de e mining he cha ac e is ics o 4.0 p ojec s, hey
es ablish he necessa y cha ac e is ics o agile me hodologies.
The e o e, in he p ojec de eloped by he Uni e si y o Albs ad -Sigma igen, i was
decided o apply a hyb id me hodology made up o agile me hodologies.
Finally, i should be no ed ha he p ojec managemen cu en ly used is e y much based
on ial and e o s udies, gi en ha any new a iable can a ec he measu es aken and
i is ad isable o con inue wi h a s udy p ocess o he con inuous imp o emen and
op imisa ion o he managemen .
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