Innovation Proesses
ClaudiaDiamantini,DomenioPotenaandEmanueleStorti
DipartimentodiIngegneriadell'Informazione,
UniversitàPoliteniadelleMarhe-viaBreeBianhe,60131Anona,Italy
{.diamantini,d.potena,e.sto rti} univp m.it
Abstrat. Being themoderneonomyonstantlyhangingand evolv-
ing, organizations are asked to develop a more exible, open and ol-
laborativemindset.Inpartiular,anattitude towardsontinuousprod-
ut/proessinnovationis seenas oneofthepotentialsolutionsapable
to eetively addressthe dynamism of the market. However, Business
Innovation(BI)still laks methodologies andbest pratiesapable to
eetivelydrivebusinessusersfromaninnovativeideatoitsrealization
andevaluation.This workinvestigates thepossibility to adopta prag-
matiandsystematiapproahtosupportbusinessusersinthemanage-
mentofaninnovationproess,withtheaimtoinreasetheontrolover
theproessandreduetherisksoffailure 1
.
1 Introdution
Profoundhangesineonomy,soietyandtehnologyarenowadaysdramatially
reshapingtheenvironmentinwhihompanies,nationsandpeopleareused to
live.Moreover,inlastyearsamoreopensoietyandeonomyisontributingto
teardownommerial barriers,allowingmorehighly ompetitivebusinesses to
join the global market.Being the modern eonomy ontinuouslyhangingand
evolving,organizationsare askedto developamoreexible, openand ollabo-
rativemindset.Inpartiular,innovationisseenasoneofthepotentialsolutions
apable to eetivelyaddress suh hallenges. Anyway, it is widely reognized
that BusinessInnovation (BI)isalso ariskyproesswhose outomesareoften
unpreditable, aeted by multiple internal and external variable onditions,
many of whih are non-observableand therefore annot be properly kept un-
derontrol.Forsuh reasons,designand managementof innovation proesses,
espeially in highly ollaborative Virtual Enterprises (VE) environments, are
hallenging tasks. This is the main reason why, in fat, there is still a lak of
methodologiesapabletoprovidediretionsandbestpratiestoinnovation,as
wellasatheoretial systematizationofthe notionsrelatedtoBI, oftenonsid-
eredmoreanart thanasiene. Inlast yearsseveraltoolsandheuristishave
1
This work has been partially funded by the European Commission through the
Projet BIVEE:Business Innovationand Virtual Enterprise Environment (Grant
are mainly based on suggestions and 10-best-rules lists derived by personal
experieneofbusiness expertsorinnovationguru. Suh attempts,althoughnot
always partiularly eetive, share the idea that business have to master the
variablesbehindtheinnovationproess.
Thiswork isaontributionto investigatethe adoption ofa pragmatiand
systematiapproahtosupportbusinessusersinthemanagementofaninnova-
tion proess, withthe aim to drive business innovation from theart towards
thesiene side,byalsoindiatingsolutionsthatarealreadyavailableforspe-
isientields, espeiallyin e-Siene.Inmoredetails,Setion 2disusses
themainsimilaritiesanddierenesbetweenasientiproessandaninnova-
tionproess,omparing theformulationof ahypothesis tothe denition ofan
innovativeidea,andproposingasientiapproahtoestimatetheeetiveness
ofthelatter;anopeninnovationperspetiveisintroduedintheontextofVir-
tualEnterprises. InSetion 3wereognize somefuntionaland non-funtional
requirementsforanideal BIframework,together withsomebasitehnologies
andtoolsthatanbeabletosupportit,whileinSetion4wemakerefereneto
somespeiexistingplatformssupportingexperimentationsine-Siene,whose
funtionalitiesanbereusedoradaptedto providemoreadvaned support for
BI.Finally,Setion5ontainssomenalremarks.
2 Sienti and open approah to Business Innovation
A rigorous and methodialapproah distinguishes siene from other forms of
explanationbeauseofitsrequirementofsystematiexperimentationandrepro-
duibility.Thesientimethodisreognizedasthebasiresearhparadigmfor
understandingthevalidityofahypothesis.Giventhephenomenontobestudied,
thisinludesthefollowingmaro-ativities,withpossibleiterations,overlapping
andparallelization:
Observation:theativityofgatheringfatsanddataaboutthephenomenon
understudy,oftendrivenbythereognitionofanopenproblemorthedraft
ofahypothesis.
Analysis: theativity of understanding, by meansof manual orautomati
tools,thegathereddata,inorder togaininsights,andpossiblynewknowl-
edgeapabletobetterexplainthephenomenon.
Formationofahypothesisoraonjetureapabletoexplainthephenomenon,
and the formulation of a testable predition. Note that the proess often
startswithadraftofsuhaonjeture.
Evaluation, whih inludes the planning of an experiment able to assess
whetherthepreditionoursornot.
Several elds of study and researh, although notdiretly denable assi-
entidisiplines,ndin thesientimethodanapproahto onsistentlysys-
entiapproah, basedonmethodialmanagementandanalysis ofdata, ould
provideavaluableimprovementforinnovationproessesintheevaluationofan
innovationidea[1℄.
Nowadays, suh aperspetive anbeeetively put in pratie[2℄.Infat,
massive volumes of data are produed by organizations daily: every produt,
task, ativity andproessthat isplanned orrealized anbepotentiallytraed
andlogged,andthisonstitutesthepreonditionsonwhihanobservationan
beperformed.Moreover,eetiveandmaturetehniquesareavailabletoanalyse
dataandto extratknowledgefromthem.
It is to be noted that innovation proesses, however, are in general muh
lessstruturedthansientiexperimentations,andoftenharaterizedbynon-
ontrollableornon-observablevariablesthatouldstronglyaetthenalresult.
Moreover,while sientiinvestigationisaimedto disoverthestatirulesun-
derlying some phenomenon in the physial world, innovation proesses has a
fousonthemarket,whihis dynamiand subjetto ontinuousandfrequent
hanges.Forsuhareason,there-exeutionofaBIproess,ingeneral,maynot
produe idential outomes. The sienti method relies on a set of praties
andformalizations whihonstitutesaommonbakgroundforsientists.This
inludes,amongothers,methodsandprotoolsforevaluationandanalysis,units
ofmeasurements,standardsandtheoriesthatrepresentatheoretialframework
forplanningand exeutionofasientiproess.Conversely,BusinessInnova-
tionis alessmaturedisipline,whih stilllaksenoughbakgroundknowledge
andtheoretialanalysisto depitaspei methodology.
Besidessuhdierenes, thetwotypesof proessesshare somesimilarities.
Thestartingpointoftheinvestigationisrepresentedbyanidea,orahypothe-
sis, whih oftenarisesfrom previousknowledgeand thereognitionof anopen
problem.Bothproesseshasadynami andriskynature,beausetheoutputis
notknowninadvane,andouldeitherontraditorvalidatetheidea(hypoth-
esis).Suessiveiterationsallows,inbothases,tomakeuseoftheurrentand
previousoutomesin ordertoomeoutwithabetterexplainedordenedidea
(hypothesis).
Aordingtosuhaperspetive,ageneralmeta-proess anbedevisedfor
innovationproesses,inludingthefollowingativities:
Observation, whih is driven by prior knowledge or the draft of the idea,
and inludes data trails aboutprevious relatedinnovation proesses,busi-
nessproesses,logsaboutinternalprodutsandtasks,togetherwithrelated
externaldatafrom themarket,lients,and suppliers.Dataaboutompeti-
torsandbakgroundknowledgeouldbeonsideredaswell.
Analysisof data in order to learly reognizeopenproblems and opportu-
nities.Infat,the properdenition ofan idearequires,atrst, to identify
theause-eetrelationsbetweentheopenissuestosolveandthestrutural
elementsof the produt/servie orproess at hand.Suh a systematiap-
proah ouldhelp to point outwhih internal variables anbe adjusted or
bythepreviousstep.
Planning of an implementation and experimentation proess, whih is fol-
lowedby anevaluationphaseaimed atassessing thevalidity oftheideain
termsofasetofindiatorsandmeasures.
Despiteits rigorousapproah,thesientiproessisfarfrom beinganau-
tomatable pre-dened proedure to follow, beause it strongly relies also on
imaginationandreativity,espeiallyforwhatonernsdataunderstanding,hy-
pothesis generation and experiment planning.Similarly, an innovation proess
requires adeep interationwith businessusers.As amatteroffat,therole of
reativity and human evaluation in the ontext of business innovation is even
moreimportantthaninsiene,beausetheproessismorestronglyaetedby
humandeision-making,andtheollaborativedimension(evenwithinthesame
ompany)ismuhmoreprominent.
Conventionally, the ahievement of innovation is based on the skills avail-
ablewithintheboundariesoftheompany,and everyimprovementandideais
onsidered a ompetitive advantage.Suh a perspetive, knownas losed inno-
vation, ultimatelyreferstoompaniesaslosedsystems,andstrongly relieson
theontrol andownership ofintelletualproperty.Reently,also thanksto the
improvementofITtehnologiesforommuniationandinformation/knowledge
sharing,anewparadigmofopeninnovationisemerging[3℄.Openinnovationis
basedontheusageofbothinternalandexternalresouresandideasapableto
reate opportunities for generating signiant value. It is based on thenotion
that knowledgeannotbeonstrainedwithin asingleompany,team,anduni-
versity:asamatteroffat,theavailabilityofpre-ompetitiveknowledgeproved
to be apable to reate amore dynami market.Open innovation pratiesin-
lude the exploitationof newollaborativebusiness models and strategieslike
o-produtionand o-reation,rowd-souring,peer prodution, aswell asthe
usageofsoialtehnologiestosupportandoordinateollaboration.
Companiesouldgreatlybenetfromexploitingbothasientiapproahin
theinnovationproessandamoreopenattitudetowardsollaboration.Infat,
ollaborativeenvironments,likeVirtualEnterprises,whereinformationandideas
anbeooperativelyolletedandorganized,arebothasoureandadriverfor
innovation. Then, the usage of proper tools and shared methodologies within
the VE, together with a sienti approah to experimentation, an enhane
thesuessrateofinnovationideasandprovideabasisusefulasareferenefor
future proessesin theVE.
3 Requirements for a BI support framework
Aordingto the data-driven/openperspetive introdued in the previousse-
tion,foreahofthemaro-ativityofaninnovationproessweidentifythemain
funtional requirements of an ideal BI framework,together with theavailable
storagefrom(possibly)multiple soures,whihallowto haveevidenesand
fatsatdisposalabouttheprodutorproessunderstudy.Usefultehnolo-
giesinlude,besidesdatabasesanddatawarehouses,CustomerRelationship
Management systems (CRM), Workow Management Systems, Enterprise
ResourePlanning,marketanalysis.
Dataanalysisanddenitionofaninnovationidea:theframeworkshouldin-
ludesupporttoolstoanalysetheolletedobservations,inordertoobtain
both a summarized view of them and to extrat possible relevant hidden
relations, patterns orregularities, useful to gain new orlearer knowledge
about the domain and its open issues or aws. Data Mining and Knowl-
edge Disovery in Databases (KDD) algorithms, together with statistial
methodsareeetivesolutionsforsuhapurpose.Systemsforollaborative
disussionsandknowledgesharing,then,allownewideasandsuggestionsto
emerge.
Experimentationandevaluation,whihrequiretoolsusefultosupportbusi-
nessusers in planning the innovation proess, inluding suggestionsabout
whih stepsoughtto betaken in givenirumstanes,and whih Key Per-
formaneIndiators(KPI)shouldbeusedtogaininsightsabouttheproess
status.Moreover,duringandaftertheexeution,toolsanbeusedtoollet
intermediateand output results, forinstane traing and loggingsystems,
CRMor surveysfor informationaboutustomersatisfationand feedbak,
systemstoanalysedatainordertoevaluatepreviouslydenedKPIs,apable
toathandshowtheimpatorthesuessoftheinnovation idea.
Giventhatin thiswork wereferespeiallytoenvironmentslikeVirtualEn-
terprise's,weenvisageinthefollowingthemosthallengingproblemsthatarise
fromthepeuliaritiesofsuhanopen,ollaborativeanddistributedsenario.On
suhabasisweontextuallydenenon-funtionalrequirementsforaframework
apabletosupport adata-driveninnovationproess:
Integration A distintivefeature of the sienti ommunity is theexistene
of asharedorpusof standards,norms, rules,aimed atproduing omparable,
measurableandreliableresults.Integrationofknowledgefromdierentsienti
eldsisfeasiblethankstotheusage(andthesharing)ofthesameommuniation
language,thesamemeasurementsunits andommonpratiesandmethodolo-
gies. Conversely, standards and praties for BI have not been identied yet.
Apartommon bakgroundknowledgelikelogisorstatistis,speibusiness
domains may requirespei solutions.Forsuh areason,aframeworkshould
providemeansto identify anddesribe resoureswithin theVirtual Enterprise
byreferringtothesameterminology,tooverometheheterogeneitiesamongthe
partners.
Complexity The lak of standardproedures and best pratiesaets also
theplanningandexeutionofaninnovationproess. Theframeworkshouldal-
hoie of the best output indiators. Complexity managementalso involves to
keeptrakofthestatusofaninnovationproess,itsvariablesandoutputs.Com-
monITtehnologiesinludedatamanagementsystems,optimizationalgorithms
andplanningtehniques.
Distribution Giventhedata-intensivedimensionofmodernsiene,espeially
in ertain elds, a reent trend is the onstitution of virtual laboratories, in
whihomputationofmassivedatasetsanbeperformedin adistributed man-
ner.Alsoaninnovationproessouldbepotentiallybasedonseveraldistributed
resoures,whih are to bemanaged throughspeitehnologies, espeiallyin
environmentslikeVirtualEnterprise's.Besidestraditionalommuniationinfras-
trutures likeinternet and the Web, spei instruments areneeded whenever
theenterprisefollowsamoreopenapproahtowardsinnovation,forinstanein
sharingofknowledge/data,ofdistributed toolsandevenof omputation,espe-
iallywheninnovationishighlydata-drivenorrequiressimulation.
Collaborationand oordination Sinetheooperativeplanningandexeu-
tionofaomplexproesstypiallyrequireseveralskills,bothtehnialandman-
agerial,ollaborationaneasilybeomeasoureofomplexityifnotsupported
by any kind of oordination.In last years thesientiommunity is showing
a ontinuously growing interest in tehnologies for data, model and workow
sharing(e.g., [4℄),whihonstitute thebakboneofamorenetworkedand ol-
laborativewaytosiene.Similarly,VirtualEnterprisesouldgreatlybenetof
systems to share information, data and ideas among the distributed partners,
and to support a virtual team by putting together diverse ompetenies and
apabilities,andprovidingmeanstomanageoordinationandtoo-operatively
performtasksandativities.
4 Tehnologies for a BI framework
InthissetionmorespeisolutionsforaBIframeworkareintrodued,taking
intoaountpreviouslyidentiedrequirementstoskethupthegeneralapproah
ofsuhasystem,aimedatsupportingbusiness innovationproesses.
Aspets of this proposal involve notonly the adoption of ertaintehnolo-
gies,butalsoseveralorganizationalhanges.Thisoftenrequirestheorganization
to reshapeitself, and adopt amore exible attitude towards revisionand im-
provementofinternalproessesandproedures,andtheoneptsaroundwhih
the enterprise is organized. In this sense,one of the emerging solutions is the
appliationofservie approahtoenterprises[5℄.
Servie orientation, in whih single tasks and ativities may be onsidered
as modular and (possible) distributed servies, is apable to improve exibil-
ityandeieny.Inordertofurther maximizemodularityandinteroperability,
apabilities and funtionalities. Suh an approah allowsto reuse some of the
methodologies and tools urrently implemented in SO frameworks, whih an
befruitfullyexploited to respond to somerequirements.One ofthe distintive
aspetsofSOAisrelatedtothedistintionamongserviepublisher(e.g.,inter-
nalorexternalsuppliers),servieonsumerandservieregistry,whereservies
holdingertainharateristisoraimedatertainfuntionalitiesanberetrieved
throughsearhingmehanisms.Withinthe business domain, suh arepository
ouldenablethedisoveryofbusinessserviesusefulinagivenstageof thein-
novationproessorforsupportingertainbusiness tasks,liketheevaluationof
aKPI,ortheoptimizationofabusiness proess.
Advaned funtionalities an rely both on servie and proess repositories
(1) to understand whih serviesare usually applied after a given one, or (2)
to providesuggestionsabout whih (typology of)servie is reommendedin a
ertainstage of theinnovationproess, and(3) to disoverythemostommon
pratiesofusageofertain servies.Moreover,thedesriptionof suhservies
byusingsemantitehnologiestodeneaommonterminology(atleast,shared
among themembersofanorganizationoramong thepartnersof aVE)allows
toaddressintegrationproblems.
Somegeneral-purpose tehnologies to support eah of the phasesof an in-
novation proesses have been introdued in the previous setion. Anyway, es-
peially in last years, several solutionshavebeeninvestigated in the sienti
ommunitytosolvesimilartasks. Inpartiularwereferto thosesientields
that are mostly onerned either with data-intensive omputation or ollabo-
rative issues, and that have at disposal advaned tools that ould be adapted
orreusedin theontextofBI.Amongthem:biologyandbioinformatisframe-
works,e.g. Taverna [6℄and Kepler[7℄, supportusers inthe designofproesses
and workows.Also theData Mining/KDD domainsare partiularly ativein
providingsupportfor userswith diverseompeteniesin designingandexeut-
ingadataanalysis/manipulationproessforknowledgeextration.Someofthe
frameworks,likeNeXT[8℄orKDDVM[9℄provideadvanedsupportforproess
semi-automati planningand algorithm/servie mathmaking, given that eah
appliativebrikoftheproessisdesribedthroughsomespeilanguage.KD-
DVMplatform,moreover,inludesaproessrepository,usefulforkeepingtrak
ofalltheproessesdevelopedinthepast,togetherwithalltheirtemporaryver-
sions. Suh arepository isused bothas areferenefor next projets, in order
to retrieve information and details about past exeutions, and also to under-
stand whih algorithm/servie's sequenesperformed better overertain data.
For what onerns ollaborative platforms, while
my
Experiment projet [4℄ is
aimedatproesssharingwithin aommunity,KDDVMprovidesteambuilding
funtionalitieswithfuntionalitiesforretrievinguserswithaspeisetofom-
peteniesorthatwereinvolvedin aertainpastprojet.Someofsuhsolutions
anbereusedoradapted forthispurpose,inpartiularthesupportforproess
The disussion provided in this work is aimed at analysing at what extent a
sientiandmethodialapproahanbeadoptedin theontextofinnovation
proessestoestimatetheeetivenessofaninnovativeidea,inreasingtheon-
trol over the proess and reduing the risks of failure. Currently, the lak of
methodologiesforBIrepresentsthemajorhindraneagainsttheatualapplia-
tion ofsuh priniples.Tothis aim, we proposed aset requirementsand teh-
nologialsolutions that an onstitute thebasis of a future framework,aimed
bothtoprovidesupporttoBIproessesdesignandmanagement,andameansto
deviseandtesttheoretialandpratialmodelsandmethodsforBI.Ultimately,
aBI frameworkould signiantlyhelp in betterdisriminating the best from
theworstpratiesinbusinessinnovationproesses,whihanbeonsideredas
therststeptowardsthedenitionof methodologiesforBI.Although itould
be useful to make innovation proesses moreeient/eetive within asingle
organization,thisisespeiallytrueinollaborativeenvironments,whereshared
methodologiesould beidentied startingfrom theinformation/proessesthat
are shared among the partners. As future work we would like bothto deepen
thetheoretialanalysisandtoproposeanarhitetureofsuhaBIframework.
Referenes
1. Thomke,S.: Experimentationmatters:Unlokingthepotentialofnewtehnologies
for innovation. HarvardBusinessShoolPressBooks(2003)
2. Kusiak, A., Tang, C.Y.: Data-inspired innovation model. In: Pro. of the 36th
InternationalComputersandIndustrialEngineeringConferene,C&IE2006.(June
2006)18
3. Tapsott,D.,Williams,A.: Wikinomis:HowMassCollaboration ChangesEvery-
thing. PortfolioHardover(2006)
4. Roure,D.D.,Goble,C.,Stevens,R.:Thedesignandrealisationofthemyexperiment
virtual researh environment for soial sharing of workows. Future Generation
ComputerSystems25(5)(2009)561567
5. Poulin,M.: LaddertoSOE:HowtoCreateResourefulandEientSolutionsfor
MarketChangeswithinBusinessandTehnology.TroubadorPublishingLtd(2009)
6. Hull,D.,Wolstenroft,K.,Stevens,R.,Goble,C.,Pook,M.,Li,P.,Oinn,T.: Tav-
erna:atoolforbuildingandrunningworkowsofservies. NuleiAidsResearh
34(2006)729732
7. Altintas, I., Berkley,C., Jaeger, E., Jones, M., Ludasher, B., Mok, S.: Kepler:
anextensiblesystem fordesignand exeutionof sientiworkows. In:Pro. of
16thInternationalConfereneonSientiandStatistial DatabaseManagement,
Santorini,Greee(June2004)423424
8. Bernstein,A.,Dänzer,M.: Thenextsystem:Towardstruedynamiadaptationsof
semantiwebservieompositions. In:Proeedingsofthe4thEuropeanonferene
onTheSemantiWeb:ResearhandAppliations. ESWC'07,Berlin, Heidelberg,
Springer-Verlag(2007)739748
9. Diamantini, C., Potena,D.,Storti, E.: ASemanti-AidedDesignerforKnowledge
Disovery. In:Pro.oftheIEEE InternationalSymposiumonCollaborative Teh-
nologies andSystems,Philadelphia,PA,USA,IEEE(May23-272011)8674
