Download - Information Management in Higher Education Institutionsduepublico.uni-duisburg-essen.de/.../M4_Information_Management... · Conseil Africain et Malgache pour l’Enseignement Supérieur

Transcript
Page 1: Information Management in Higher Education Institutionsduepublico.uni-duisburg-essen.de/.../M4_Information_Management... · Conseil Africain et Malgache pour l’Enseignement Supérieur

Der folgende Text wird über DuEPublico, den Dokumenten- und Publikationsserver der UniversitätDuisburg-Essen, zur Verfügung gestellt.

Diese auf DuEPublico veröffentlichte Version der E-Publikation kann von einer eventuell ebenfallsveröffentlichten Verlagsversion abweichen.

Randhahn, Solveig:

Information Management in Higher Education Institutions - Training on Internal QualityAssurance Series | Module 4

In: Training on Internal Quality Assurance Series

DOI: http://dx.doi.org/10.17185/duepublico/43225

URN: urn:nbn:de:hbz:464-20170215-102130-9

Link: http://duepublico.uni-duisburg-essen.de/servlets/DocumentServlet?id=43225

Lizenz:

Dieses Werk kann unter einer Creative Commons Namensnennung - Nicht kommerziell - KeineBearbeitungen 4.0 International Lizenz genutzt werden.

Page 2: Information Management in Higher Education Institutionsduepublico.uni-duisburg-essen.de/.../M4_Information_Management... · Conseil Africain et Malgache pour l’Enseignement Supérieur

Information Management in Higher Education Institutions

Solveig Randhahn

Training on Internal Quality Assurance Series | Module 4Solveig Randhahn and Frank Niedermeier (Eds.)

Page 3: Information Management in Higher Education Institutionsduepublico.uni-duisburg-essen.de/.../M4_Information_Management... · Conseil Africain et Malgache pour l’Enseignement Supérieur

With financial support from the

Imprint

This e-publication is part of the Training on Internal Quality Assurance Series which is also published as paperback (ISBN: 978-3-7345-7691-1) and distribut-ed in book shops worldwide. More information is available at http://www.trainiqa.org

Author: Solveig Randhahn

Editors: Solveig Randhahn and Frank Niedermeier

Reviewers: Karl-Heinz Stammen, Frank Niedermeier

Edition: First edition

Layout: Nikolaj Sokolowski, Randi Ramme

Publisher: DuEPublico, Duisburg/Essen, Germany

DOI: 10.17185/duepublico/43225

Copyright © 2017 Solveig Randhahn

This book is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND 4.0). https://creativecommons.org/licenses/by-nc-nd/4.0/

Please cite the use of our course book series in presentations, trainings, papers etc. according to scientific standards. You can cite this book as:

Randhahn, S. (2017). Information Management in Higher Education Institutions. Module 4. In Randhahn, S. & Niedermeier, F. (Eds.) Training on Internal Quality Assurance Series. Duisburg/Essen: DuEPublico. Retrieved from: http://dx.doi.org/10.17185/duepublico/43225

Page 4: Information Management in Higher Education Institutionsduepublico.uni-duisburg-essen.de/.../M4_Information_Management... · Conseil Africain et Malgache pour l’Enseignement Supérieur

Acknowledgment

Our modules and books have been prepared and written in a joint effort of the University of Duisburg-Essen

and the University of Potsdam under the DIES (Dialogue on Innovative Higher Education Strategies) Programme

conducted by the German Academic Exchange Service (DAAD) and the German Rectors’ Conference (HRK) with

funds from the Federal Ministry for Economic Cooperation and Development (BMZ). We take this opportunity

to thank the DIES Programme and all the partners from Africa, Europe and Southeast Asia who were involved

in the development process and express our deepest gratitude for the received support, without which the

modules and course books would not have been possible to realise.

We want to further express our sincere gratitude for the most valuable support and contributions from the

involved partners

Autorité Nationale d’Assurance Qualité de l’Enseignement Supérieur (ANAQ-Sup), Sénégal,

ASEAN Quality Assurance Network (AQAN),

ASEAN University Network (AUN),

Association of African Universities (AAU),

Conseil Africain et Malgache pour l’Enseignement Supérieur (CAMES),

European Association for Quality Assurance in Higher Education (ENQA),

National Accreditation Board (NAB), Ghana,

National Council for Tertiary Education (NCTE), Ghana,

National Universities Commission (NUC), Nigeria,

Southeast Asian Ministers of Education Organization Regional Centre for Higher Education and Develop-

ment (SEAMEO RIHED),

United Nations Educational, Scientific and Culutral Organization (UNESCO),

University of Professional Studies Accra (UPSA), Ghana

and especially from Prof. Dr. Shahrir Abdullah, Richard Adjei, Prof. Dr. Goski Bortiorkor Alabi, Prof. Dr. Bassey

Antia, Prof. Dr. Arnulfo Azcarraga, Gudrun Chazotte, Assoc. Prof. Dr. Tan Kay Chuan, Kwame Dattey, Prof. Dr.

Ong Duu Sheng, Prof. Zita Mohd. Fahmi, Mae Fastner, Assoc. Prof. Dr. Nantana Gajaseni, Robina Geupel, Josep

Grifoll, Juliane Hauschulz, Dr. Pascal Hoba, Dato’ Syed Hussein, Benjamin Jung, Prof. Abdel Karim Koumare,

Dr. Vipat Kuruchittham, Prof. Dr. Chiedu Mafiana, Prof. Dr. Duwiejua Mahama, Barbara Michalk, Prof. Dr. Le

Quang Minh, Nguyen My Ngoc, Johnson Ong Chee Bin, Concepcion V. Pijano, Prof. Dr. Philipp Pohlenz, Sonja

Pohlmann, Dr. Suleiman Ramon-Yusuf, Dr. Sylvia Ruschin, Dr. Chantavit Sujatanond, Dr. Oliver Vettori and Marc

Wilde.

The authors

Page 5: Information Management in Higher Education Institutionsduepublico.uni-duisburg-essen.de/.../M4_Information_Management... · Conseil Africain et Malgache pour l’Enseignement Supérieur
Page 6: Information Management in Higher Education Institutionsduepublico.uni-duisburg-essen.de/.../M4_Information_Management... · Conseil Africain et Malgache pour l’Enseignement Supérieur

Dr. Solveig RandhahnFaculty of Social Sciences

University of Duisburg-Essen, Germany

[email protected]

https://www.uni-due.de/gesellschaftswissenschaften/

Dr. Solveig Randhahn is Managing Director of the Faculty of

Social Sciences at the University of Duisburg-Essen (UDE) in

Germany. She studied Political Science, Spanish Philology and

Economic Policies at the University of Münster. She received

her PhD in Political Science, doing research on education and

social policy in Germany. Furthermore, she is a certified expert

in Education and Science Management.

Dr. Solveig Randhahn shows a wide range of work experience in

the field of quality management at higher education institutions.

She was responsible for the Service and Information Centre at

the Institute of Political Science and worked at the Department of

Quality Development in Teaching and Learning at the University

of Münster. Afterwards, she was employed at the University

of Applied Sciences in Aachen, coordinating the accreditation

processes of the University and advising the University leadership

in terms of higher educationpolicies in teaching and learning.

In January 2014, Dr. Randhahn took over the responsibility as

manager of the TrainIQA project (Training on Internal Quality

Assurance in West Africa), coordinated by the Centre for Higher

Education Development and Quality Enhancement (CHEDQE) at

UDE. The project aimed at developing capacity in the field of

internal quality assurance (IQA) in higher education institutions

by providing hands-on workshops for quality assurance officers

from higher education institutions in the West African region.

In March 2016, Dr. Randhahn switched to the Faculty of Social

Sciences as Managing Director. In addition, she was elected as

Vice-Dean for teaching and learning at the faculty.

Page 7: Information Management in Higher Education Institutionsduepublico.uni-duisburg-essen.de/.../M4_Information_Management... · Conseil Africain et Malgache pour l’Enseignement Supérieur
Page 8: Information Management in Higher Education Institutionsduepublico.uni-duisburg-essen.de/.../M4_Information_Management... · Conseil Africain et Malgache pour l’Enseignement Supérieur

List of Abbreviations

AAA

BA

BSC

CB

CEUS

CHE

EUNIS

HEI

IUCEA

MA

MSRE

PDCA

PhD

QA

Annual Academic Achievements

Bachelor

Balanced Scorecard

Course Book

Computerbasiertes Entscheidungsunterstützungssystem für die Hoch-

schulen in Bayern (computer-based management tool for the institu-

tions of higher education in Bavaria, Germany)

Centre for Higher Education

European University Information Systems

Higher Education Institutions

Inter-University Council for East AfricaUniversity of Duisburg-Essen

Master

Federal Ministry of Science, Research and Economy

Plan-Do-Check-Act or Plan-Do-Check-Adjust

Doctor of Philosophy

Quality Assurance

Page 9: Information Management in Higher Education Institutionsduepublico.uni-duisburg-essen.de/.../M4_Information_Management... · Conseil Africain et Malgache pour l’Enseignement Supérieur

8

Table of ContentsIntroduction to the Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10

Introduction to Information Management at Higher Education Insitutions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12

1 Introduction to Information Management at Higher Education Institutions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13

1.1 Why Should Higher Education Institutions Collect Data? . . . . . . . . . . . . . . . . . . 13

1.2 Characteristics of an Information Management System . . . . . . . . . . . . . . . . . . . . 16

Translation of Higher Education Objectives Into Numbers . . . . . . . . 30

2 Translation of Higher Education Objectives Into Numbers: Quantitative and Qualitative Indicators . . . . . . . . . . . . . . . . . . . . . . 31

2.1 Meaning and Function of Quantitative and Qualitative Indicators . . . . . . . . . . . 31

2.2 Determination and Operationalisation of Quantitative and Qualitative Indicators . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32

2.3 Using Indicators – Key Aspects to be Considered . . . . . . . . . . . . . . . . . . . . . . . . . 34

2.4 Challenges of Using Quantitative and Qualitative Indicators . . . . . . . . . . . . . . . . 39

Reporting: Presentation and Communication of Data and Information . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44

3 Reporting: Presentation and Communication of Data and Information . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45

3.1 Definition of Reporting Objectives for Different Target Groups . . . . . . . . . . . . . . 45

3.2 Content of Reporting . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46

3.3 Organisational Conditions for Reporting . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48

Page 10: Information Management in Higher Education Institutionsduepublico.uni-duisburg-essen.de/.../M4_Information_Management... · Conseil Africain et Malgache pour l’Enseignement Supérieur

9

Elaborated Information Systems - Examples for Data Sharing . . . . 52

4 Elaborated Information Systems – Examples for Data Sharing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53

4.1 Case Study of the ETH Zurich: Annual Academic Achievements Reporting . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53

4.2 Case Study of the University of Vienna: Course Controlling . . . . . . . . . . . . . . . . 55

4.3 Unidata – Facts and Figures at the Push of a Button – A Case Study from Austria . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56

References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 58

List of Tables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 62

List of Figures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63

Page 11: Information Management in Higher Education Institutionsduepublico.uni-duisburg-essen.de/.../M4_Information_Management... · Conseil Africain et Malgache pour l’Enseignement Supérieur

10

Preface

Introduction to the Module

Prerequisites for the Module Learnershaveabasicunderstandingandknowledgeofdifferentqualitymanagementapproaches(e.g.pro-

cess-andevaluation-based)inthehighereducationcontext(seecoursematerialModule1),

theyareabletousethePDCA-cycleasasystematicapproachtomanagingquality(seecoursematerial

Modules1and2),

theyhavebasic theoreticalknowledgeof thenewpublicmanagementapproachand its challenges for

highereducationinstitutions(HEI)(seecoursematerialModule1).

Intentions of the Module Establishingsystematicqualityassurancestructuresathighereducation institutionsrequiresawiderange

ofdecision-makingprocessesbydifferentstakeholders.Toimplementthederivingmeasuresandactivities

effectivelyandefficientlyandaccordingtothequalityobjectivesofthehighereducationinstitution,dataand

informationandtheirappropriatecirculationarenecessary.

Thismodulegivesanintroductiontothebasicdiscussionaboutinformationmanagementsystemsathigher

educationinstitutions.Itanalysesthequestionwhyuniversitiescollectdataanddiscusseskeycharacteristics

of informationmanagementsystemsatuniversities.Basedonthis, thecoursebook introducestheuseof

quantitativeandqualitativeindicatorsasameansofmeasuringandassessingobjectives.Itexplainshowto

determineandoperationaliseindicators,howtocriticallyreflectonthemandhowtousetheminaresponsi-

bleandappropriateway.ItpresentstheBalancedScorecardasamethodicalmanagementapproachtodeal

withindicatorsathighereducationinstitutions.

Furthermore,thecoursebookgivesan introductiononhowtoestablishadata-basedreportingsystemat

highereducationinstitutions.Itdealswiththeobjectivesofdifferentstakeholdergroupsandassesseshowto

considertheseappropriatelyinareportingsystem.Itgivesaninsightonthekeyconditionstobeconsidered

whengeneratingreports.

Finally,thecoursebookpresentsvariousexamplesofhowhighereducationinstitutionsdealwithinformation

byestablishingdifferent(technical)structuresandproceduresofcampus-widedatasharingandreporting..

Page 12: Information Management in Higher Education Institutionsduepublico.uni-duisburg-essen.de/.../M4_Information_Management... · Conseil Africain et Malgache pour l’Enseignement Supérieur

11

dealwith informationthat is relevant forplanningandcontrollingwithregardtoqualitydevelopment/

assurance/management,

developinternaldataandinformationchannels,consideringtherespectivetechnicalandstructuralframe-

workofhighereducationinstitutions,

defineandoperationalisequantitativeandqualitativeindicatorsathighereducationinstitutions,

recogniseandconsideropportunitiesandlimitationsofquantitativeandqualitativeindicatorsasmeasures

forqualityassuranceofprocessesathighereducationinstitutions,

developandmanagereportingsystemsfordifferenttargetgroupsbasedonatransparentsetofinternal/

externalcriteria.

On successful completion of the module, you should be able to…

Page 13: Information Management in Higher Education Institutionsduepublico.uni-duisburg-essen.de/.../M4_Information_Management... · Conseil Africain et Malgache pour l’Enseignement Supérieur

Chapter 1: Introduction to Information Management at Higher Education Insitutions

12

1 IntroductiontoInformationManagementat HigherEducationInstitutions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13

1.1 WhyShouldHigherEducationInstitutionsCollectData? . . . . . . . . . . . . . . . . . . 13

1.2 CharacteristicsofanInformationManagementSystem . . . . . . . . . . . . . . . . . . . . 16

identifythereasonsforhighereducationinstitutionstocollectdata,

recogniseanddifferentiatethelinkagesbetweeninformationmanagementandcontrollingprocessessuch

asplanning,managingormonitoring,

identifyelementarycharacteristicsofaninformationmanagementsystemandtodeducesystematicsteps

todealwithinformationatHEI(e.g.gatheringandacquisitionofinformationneeds,processingandstorage

ofinformationaswellascommunicationchannelsofinformation).

On successful completion of this chapter, you should be able to…

Chapter 1

Introduction to Information Management at Higher Education Insitutions

Page 14: Information Management in Higher Education Institutionsduepublico.uni-duisburg-essen.de/.../M4_Information_Management... · Conseil Africain et Malgache pour l’Enseignement Supérieur

Chapter 1: Introduction to Information Management at Higher Education Insitutions

13

1 Introduction to Information Management at Higher Education Institutions

1.1 Why Should Higher Education Institutions Collect Data?

Establishingsystematicinstitutionalqualityassurancestructuresrequiresabroadvarietyofinformationthat

isfundamentaltoenabledecision-making,communicationandorganisationalprocessesbetweendifferent

stakeholdersandtherealisationofactivities.

Informationcanbedefinedaspurposefuldatathat isrelatedtoaproblemandthat isusedtoachievean

objective(Wittmann1980).Wecantalkaboutknowledgewhenpeoplestarttoputinformationintoamean-

ingfulcontext(Gladen2003,2).

InformationisnecessaryforallorganisationalconcernsandobjectivesofaHEI:foreasingandoptimisingdeci-

sion-makingprocesses,forplanninganddevelopingrealisticsettings,forreportingandqualitydevelopment,

andwithitenhancingtheinstitutionalefficiencyandeffectiveness(Saupe1981).Highereducationresearcher

J.FrederickVolkweinsystemisesthesestrategicandoperativeobjectivesintofivefundamentalconcernsof

highereducationinstitutions(Volkwein1999):

1. Expensesforhighereducation(shortageoffinancialfunding)

2. Requiringanefficientmanagementandincreasingproductivityatthesametime

3. Effectivenessandsurplusvalueofhighereducationinstitutions(competitionandrighttoexistwithout

thenecessitytoproduceoutputwithregardtocontents)

4. Accesstohighereducationinstitutions(increasingnumberofstudentsasajustificationforadditional

funding)

5. Reporting

These fundamental concerns go alongwith various, constantly changingwhile simultaneously increasing

demandsforinformation.Thequestionishowhighereducationinstitutionscanrecognise,determine,pro-

ceedand,finally,copewiththeseinformationdemandsefficientlyandeffectivelyinthelightofavailablestaff,

materialandtechnical resources.Forexample, todeterminetheavailablecapacitiesofyour institutionto

establishanotherstudyprogramme,youhavetoconsiderandcalculatetheplannednumberofstudents,the

numberoflecturerswhoareavailable(intermsofworkinghours),aswellastheresultingcostsforstaffand

infrastructure.

Inorder tobeable todealwith such informationdemands,highereducation institutionshave started to

establishintegrateddata-basedinformationsystems.Thesearebaseduponexistingeconomicalapproaches

Information as“purpose- fulknowledge” (Wittmann 1980)

Page 15: Information Management in Higher Education Institutionsduepublico.uni-duisburg-essen.de/.../M4_Information_Management... · Conseil Africain et Malgache pour l’Enseignement Supérieur

Chapter 1: Introduction to Information Management at Higher Education Insitutions

14

forbusinessstrategiesandmanagementconcepts.Usingup-to-datedataand informationtechnologiesat

highereducationinstitutionsshouldcontributetoeffectiveandefficientprocessesinthehighereducation

organisation.

Inthiscontext,data canbedefinedasasetofqualitativeand/orquantitativevariablesthatbecomeinfor-

mationbyinterpretation.Dataarearesultofmeasurementsandcanbevisualisedbyusingtables,graphsor

images.Hence,datacanbeunderstoodasanabstractconceptfromwhichinformationandthenknowledge

arederived(BostonUniversity2015;DWBI2014;seealsoModule2).

Methodicalinformationmanagementservesaccountabilityandreportingpurposesintheinternalandexter-

nalcontextofhighereducation.Itcreatesperformanceandcosttransparencyandthereforeprovidesacen-

tralcontributionforqualityassuranceinresearch,teachingandsupportingservices:awell-establishedinfor-

mationsystemserves the formulationof institutionalobjectivesandthereforethe facilitationandoptimi-

sationofdecision-makingprocesses fora sustainable strategicplanning inhighereducation (Saupe1981;

Küpper,Friedl,Hofmann,Hofmann&Pedell2013).

“An information system can be understood as a coordinated arrangement of staff, organisational

and technical elements that provides decision-makers with purposeful knowledge for their task

fulfilment.”

(Eberhardt, 67 in Frese 1992)

Thekeypurposesofinformationmanagementincludeacloselinkagetomanagerialaccountingprocessesat

HEI.

Asaprimaltaskofmanagerialaccounting,wecanconsidertheoverallcoordinationofthemanagementsys-

temofahighereducationinstitution:

“Management must deal with the dynamics of change and provide coordination for the overall

system.”

(Kast & Rosenzweig 1974, 620 in Horváth 2011, 8)

AccordingtoHorváththemanagementsystemconsistsoffivesubsystems:planning,accounting,information

supply,organisationandhumanresourcemanagement(Hórvath2011,8;Küpperetal.2013,636).Concern-

ingtheinformationsupply,managerialaccountinghastocoordinateandaligntheaforementionedsubsys-

temswithregardtotheinformationneedsofdecision-makers.Ontheonehand,thisincludesthecoordina-

tionwithintheinformationsystem–thecollectionofnecessarydata,itssystematisation,storageand,finally,

itsallocation.Ontheotherhand,thisincludesthetransmissionofdatatotheaforementionedsubsystemsof

themanagementsystembysuitablereportingsystems.

Datacreate suitable

information fordecision-

making processes

Linkage between

information management

andmanagerial accounting

Page 16: Information Management in Higher Education Institutionsduepublico.uni-duisburg-essen.de/.../M4_Information_Management... · Conseil Africain et Malgache pour l’Enseignement Supérieur

Chapter 1: Introduction to Information Management at Higher Education Insitutions

15

Figure 1 Layer model for higher education institutions (Tropp 2002, 2)

Thedesignofinformationsystemsisorientedtowardstworeferencelevels.Theverticallevelreferstosuch

levelsathighereducationinstitutions,wheredecisionsaremadeandtasksarecarriedout,i.e.thetopman-

agement,faculties,institutesandchairs.Thehorizontallevelreferstothecoreprocessesofhighereducation,

i.e. research, teachingand services. These includevarious informationneeds thatgoalongwithdifferent

requirementsregardingthewayofsystematisationandallocationofinformation.Dependingonthelevelof

centralisedandde-centraliseddecision-makingprocessesbetweenthetopmanagement,faculties,institutes

andchairs,multi-dimensionalinformationsystemsareneeded(Küpperetal.2013,636).

Theincreasingcomplexityanddiversityofinformationleadtoverydifferentscopesofperformanceofthese

informationsystemsamonghighereducationinstitutions.Coreprocessesofthesocalled“studentlifecycle”1,

thatarefrequentlymanagedthroughprofessionalinformationtechnologies,aresuchasthefollowing:

application,assessmentandadmissionprocesses

studentadministration

planningandmanagementoflectures(universitywidecourseschedule,generalandindividualcourse

schemes,registrationandderegistrationofstudentsfromcourses/exams)

managementoflecturehallbooking

examinationmanagement(e.g.examregistrationandderegistration,transcriptofrecords,recognition,

archivalstorageoffinalexamination)

managementoforganisationaldata(buildingandlecturehallplans,e-mailandphoneindex)

1Thestudent-life-cycleincludesallrelevantactivitiesandfieldsforstudents,lecturersandadministratorsthathavetobecon- sideredduringtheacademiceducationprocess:e.g.application-->admission-->teachingandlearning-->assessment--> graduation-->alumni.

Page 17: Information Management in Higher Education Institutionsduepublico.uni-duisburg-essen.de/.../M4_Information_Management... · Conseil Africain et Malgache pour l’Enseignement Supérieur

Chapter 1: Introduction to Information Management at Higher Education Insitutions

16

Higher education institutions have started to integrate thiswidely ramified IT-landscape in complex data

warehousesystems.

Comingbacktothequalitymanager,wecanaskwhichareasofsuchacomplexdatasystemarerelevantto

her/him.Focussingonteachingandlearning,wecanthinkofaprofessionaldatamanagementofprocesses

suchasinternalandexternalevaluationsonfacultylevelorthehighereducationinstitutioningeneral,tracers

studies,oralsostaffdevelopmentinteaching.

Further Reading

Taylor,J.(2014).Informingordistracting?Guidingordriving?Theuseofperformanceindicatorsin

highereducation.InMenon,M.,Terkla,D.,Gibbs,P.(Ed.),Using data to improve higher education.

Research, policy and practice.Rotterdam:SensePublishers.

HigherEducationFundingCouncilforEngland(HEFCE)(2011).Performance indicators in higher ed-

ucation. First report of the performance indicators steering group (PISG).London:HEFCE.

Balasubramanian,K.(2009).ICTs for higher education. Background paper from the commonwealth

of learning.Paris:UNESCO;WorldConferenceonHigherEducation;CommonwealthofLearning.

1.2 Characteristics of an Information Management System

Whyshouldqualitymanagerscareaboutinformationmanagement?–Basically,qualitymanagershaveacon-

sultativefunctionwithregardtodifferentdecision-makingprocessesathighereducationinstitutions,beiton

managementlevel,onorganisational/administrationleveloronfacultylevel.Therefore,theyneedtobeable

togatherinformationrequirementscorrectlyandanalyseandevaluatethecollecteddataandinformation

accurately.

Examplesoftargetsinaninformationmanagementsystem,forwhichqualitymanagerscanplayakeysup-

portingrolecanbethefollowing:

Definition of Data Warehouse

“Adatawarehouseisacopyoftransactiondataspecificallystructuredforqueryingandreporting.”

Source: (Kimball 2002)

Page 18: Information Management in Higher Education Institutionsduepublico.uni-duisburg-essen.de/.../M4_Information_Management... · Conseil Africain et Malgache pour l’Enseignement Supérieur

Chapter 1: Introduction to Information Management at Higher Education Insitutions

17

Defineandestimateinformationneedsrequiredforcertaindecision-makingprocesses.

Prepareunderstandableandinterpretabledatafortherespectivetargetgroupsandavoidcontradictions.

Interfacefunctionwithregardtoinformationdistribution,inordertohelptoclosecommunicationand

informationgapsamongsendersandaddressees.Thatmeans,theycanexplainandclarifywhichinfor-

mationisavailableforwhichissues,orwhoneedswhichpartoftheexistingdataandinformation.

Supportforreading,analysingandinterpretingdatamaterial,consideringtherespectiveparticularcon-

text.

Contributetodevelopingmoretransparencyabouthowtheinformationflowsofahighereducationinsti-

tutionworkaccordingtodefinedqualitycriteria.

Insomehighereducationinstitutionsthesetargetscanbecloselyrelatedtomanagerialaccounting.2Toavoid

overlappingactivitiesbutachieveaneffectivetargetallocation,youshoulddefineandcoordinatetherespec-

tiveresponsibilitiesbetweenaqualitymanagerandaunitformanagerialaccountingclearly.

Takingthisintoconsideration,thewholefieldofinformationmanagementcontainsenoughquestionstobe

discussedinapropertrainingcourse.Thisiswhyinthiscoursebookwehavetolimitourfocusonsomepar-

ticularaspects.Inshort,wewillfocusonthelinkagesbetweeninformationandqualitymanagementandthe

roleofqualitymanagers.

Thecoursebookgivesanintroductiontomanagementrelevantdataandinformationwhichahigheredu-

cationinstitutionneedsforimproving,assuringandmanagingqualityinthecoreprocessesofteachingand

learning,researchandservices.Therefore,itgivesanoverviewonthekeycharacteristicsofinformationman-

agementsystemsanddiscussesthecriteriathatarenecessarytodevelopasystematiccollection,analysisand

interpretationofdataandinformationaccordingtotheneedsandrequirementsofspecifictargetgroups.3

Basedonthis,yougettoknowthemostimportantessentialstoassessandjudgeinhowfarstrategicand

operativeobjectivesofqualityassurancehavebeenreached.Youwill learnaboutthechallengesofdefin-

ingquantitativeandqualitative(keyperformance)indicators(Chapter2.1),howtocollectandanalysethem

(Chapter2.2),aswellashowtodealwithresistanceagainstdataandinformationandtoachieveacceptance

(Chapter2.3and2 .4).

AccordingtoHorváthamethodicalinformationmanagementsystemcanbestructuredintothethreefollow-

ingphases(Hórvath2011,308etseq.)

I. IdentifyinginformationneedsandgatheringrawmaterialatHEI

II. Datacollection,processingandanalysis

III.Datadissemination(workflowsbetweendisseminatorandreceiver)

2ForfurtherinformationonmanagerialaccountingandtherelationtoinformationanalysisseeDemski(198,2008). 3 MoreinformationonthisissuecanbefoundinCB2aswell.

Page 19: Information Management in Higher Education Institutionsduepublico.uni-duisburg-essen.de/.../M4_Information_Management... · Conseil Africain et Malgache pour l’Enseignement Supérieur

Chapter 1: Introduction to Information Management at Higher Education Insitutions

18

I. Identifying information requirements and gathering raw material at Higher Education Institutions

Tobeabletogather,classify,processandreportdataandinformationinaninformationsystem,firstofallyou

havetofindoutabouttherespectiveinformationrequirements.Decision-makersathighereducationinstitu-

tionshavedifferentinformationneedsaccordingtotheirrespectivestrategicobjectivesandtargets(seeTable

1).Theseinformationneedshavetobedefinedclearlyandunambiguouslytobeabletodeducesystematic

andeffectivedatacollectionanddistribution.

Information requirements can be defined as “the type, amount and quality of informationwhich a deci-

sion-makerneedstofulfilher/histargets”4(Koreimann1976,6;Gladen2003,4).

Wecandifferbetweenobjectiveandsubjectiveinformationneeds.Objectiveinformationrequirementsrefer

totheamountofinformationwhichissetinafactualcontexttosolveaproblem.Subjectiveneedsarethe

informationwhichadecision-makerconsiderstoberelevantforher/histargets(Küpper2013,218).

Basedonthis,aconcreteinformationdemandgenerallyincludesbothsubjectiveandobjectiveinformation

requirements.Veryoftendecision-makersarenotsufficientlyawareoftheirsubjectiveinformationneedsor

cannotformulatethemappropriately.Itmayalsohappenthattheyevenwanttohidetheirrealinformation

requirements(Nusselein2002,3).

Figure 2 Gathering information based on needs, supply and demand (translated based on Picot & Frank 1988, 608 in Hórvath 2011, 311)

4OwntranslationfromGermanintoEnglish.

Objective andsubjective

information requirements

Page 20: Information Management in Higher Education Institutionsduepublico.uni-duisburg-essen.de/.../M4_Information_Management... · Conseil Africain et Malgache pour l’Enseignement Supérieur

Chapter 1: Introduction to Information Management at Higher Education Insitutions

19

Thefollowingtableillustratespossibleinformationneedsofdifferentstakeholders,referringtostructuralcon-

ditions,resourcesorprocessesinteachingandlearningwhichcancomeupwhenestablishingqualityassur-

ancestructuresatanhighereducationinstitution.

Subject-matter Examples for information sources Examples for information requirements

Structuralframeofresearchandteaching

(National)lawonhighereduca-tion

StrategicplansofaHEI

Strategicplansoffaculties

HEIconstitutionandregulations

Examinationregulations

Regulationsfordoctoral

degreesandhabilitation

IstherearegulatoryobligationtoestablishaQA-unit?Ifso,whichrequirementshavetobefulfilled?

WhichobjectivesshallbeachievedwiththeQA-unit?(E.g.annualevaluationofstudypro-grammes;establishmentandcoordinationofqualitycyclesinteachingandlearning)

Whichinformationhastobedocumentedinanexaminationregulationtocomplywithinternal/externalqualitystandards?

ResourcesofaHEI(staff,facilities)

Dataonavailableresourcesandcashflows

Staffingperprofessor Third-partyfundsperprofessor Overviewonavailablestaffandresourcesatfaculties

Whoprovideswhichamountoffinancialresourc-esfortheset-upofaQA-unitandforwhatperi-od?Forwhichpurposescantheseresourcesbeused?(E.g.facilities,staff,IT)

WhatisthenumberofqualifiedstaffavailablefortheQA-unit,andforwhatperiod?

Whichadditionalqualityassuranceactivitiescanberealisedbasedonthird-partyfunds(e.g.additionallectures,tutorials,mentoringpro-grammes)?

Processman-agementofteachingandlearning

Input/outputdataofthepro-cessteachingandlearning(aggregationonprogrammelevel)

Dataoninternationalisation Qualityofgraduates Detaileddataonteachingandlearning(e.g.coursescheme,assessment,mentoring)

Capacitiesofprofessorshipinteachingandlearning

Whichdataisavailableonthenumberofappli-cationsperplaceinaprogramme,thenumberofstudents/graduatesperprogramme,thedrop-outratioetc.?Isthisdataconsistentwithinter-nal/externalqualityrequirements?Whichaddi-tionaldatamightbenecessary?

Howmanyincomingandoutgoingstudentsarethereonfaculty/programmelevel?

Isthereanyinformationavailableonthegradu-atesandtheircareerpaths?

Whichinterdisciplinarycoursesdowehave? Scopeofregularcoursesofferedperpro-gramme?Numberofparticipantsperlecture?

Numberofprofessorsperprogramme?Mentor-ingratioperprogramme?

Table 1 Information sources and requirements from different stakeholders (adapted from Nusselein 2002)

According to thedifferent subject-mattersmentioned in the table, theprioritiesof the listed information

requirementsdifferdependingontherespectivetargetgroup.Focussingonthestrategicframeinresearch

and teaching, forexample,a vice-chancellorneedsother information thanadeanoradeanof students.

Page 21: Information Management in Higher Education Institutionsduepublico.uni-duisburg-essen.de/.../M4_Information_Management... · Conseil Africain et Malgache pour l’Enseignement Supérieur

Chapter 1: Introduction to Information Management at Higher Education Insitutions

20

Theformerisespeciallyinterestedinstrategicplanningofthewholehighereducationinstitutionandconsid-

ersinformationaboutstrategicplanningonfacultylevel.Adeanofstudentshowever,isresponsibleforteach-

ingandlearning,focussingespeciallyonexaminationandprogrammeregulations.Yetforadean,information

onregulationsofthedoctorateorpost-doctorallecturequalificationsmightbemorerelevant.

Informationthatreferstothefinancial resourcesandcashflowsareespeciallyrelevantforthechancellor

(understoodasheadofadministration)whoisresponsibleforthebudgetofahighereducationinstitution.

However,theinformationrequirementsofthevice-chancellororthesenatemightfocusondataaboutstaff-

ingorthird-partyfundsperprofessorwhichcanbeusedasquantitativeindicatorsforresearchperformance.

Amongothers,theyneedthis informationforprofessorialappointmentprocedures.Afacultyneedsmore

detailedindicatorssuchastheavailablestaffingorfinancialresourcesofthefaculty.

Focussingontheprocessofteachingandlearning,thetopmanagementisusuallyinterestedininput/output

dataonprogrammelevel(e.g.numberofapplication,students,graduates,drop-outratioperprogramme).

Furthermore,dataoninternationalisationandthequalityofthegraduatesisrelevantinordertoanalyseand

interpretthesuccessofastudyprogramme.Deansofstudentsneedinformationthatdifferentiatesinmore

detailbetweenthewholestudyprocesses(e.g.dataontheorganisationofassessment,courses,andproce-

duresofrecognition).Finally,achancellorneedsdatatobeabletodeterminetherequiredresources(capac-

ities)inteachingandlearning.

Qualitymanagersshouldknowallthesedifferentperspectivesandtherespectiveinformationrequirements.

Basedonthis,theycancontributetothedistributionofinformationtothosewhoeffectivelyneedthem,but

alsosupportdecision-makingprocessesondifferentinstitutionallevels.

Questions & Assignments

1. Pleasestudythetableandthementionedexamplesofinformationrequirementsagain.Lookingat

yourown institution,whichof these informationrequirementsdothedecision-makersprioritise

andwhy?

2. Arethereanyadditionalinformationrequirementswithregardtoqualityimprovementinteaching

andlearningatyourhighereducationinstitution?Forwhomandwhy?Pleasegiveexamples.

Howcanqualitymanagersfindoutaboutthesedifferentinformationneedswithoutonlyraisingassumptions

orhypotheses?Therearedifferentwaysofgatheringinformationrequirements,whichcanbeseparatedinto

inductiveanddeductiveprocedures (Küpper2001,145). Inductivemethods focusontheconditionsofan

organisationasthefundamentforinformationrequirements.Basedonthis,youparticularlyidentifyinforma-

tionsupplyaswellassubjectiveinformationneeds.Examplesformethodologicalapproachesaresuchasthe

analysesoforganisationaldocumentsanddataorananalysisoftheorganisationorasurveybasedoninter-

viewsorquestionnaires.Deductivemethodsidentifyinformationinasystematicway:Basedonthestrategic

objectivesofanorganisation,theytrytofindoutabouttheobjectiveinformationneeds(Küpperetal.2013,

222;Nusselein2002,3).

Determination ofinformation requirements

basedon inductiveand

deductive procedures

Page 22: Information Management in Higher Education Institutionsduepublico.uni-duisburg-essen.de/.../M4_Information_Management... · Conseil Africain et Malgache pour l’Enseignement Supérieur

Chapter 1: Introduction to Information Management at Higher Education Insitutions

21

Togainamorecomprehensivepictureoftheinformationneeds–thatisbothobjectiveandsubjectiveinfor-

mationneeds–itisrecommendedtocombineboththeinductiveanddeductiveapproach.Thefollowing

procedureofananalysisofinformationneedsmayserveasanexample:

Integrated concept of an information needs analysis

Figure 3 Based on the project “Computer-based management tool for the institutions of higher education in Bavaria” (CEUS) (Nusselein 2002, 4)

Description of Figure 3:

Theorganisationanalysis focusesontherespectiveunitsofanorganisationunddeterminestargetsand

decision-makingcompetencesoftherespectivedecision-makers(inthecaseofhighereducationinstitu-

tionssuchas(vice)chancellor,highereducationboard,senate,chancellor,dean,deanofstudents).5

Theresultsoftheorganisationalanalysesarethebasisforthesubsequentinterviewswiththeabove-men-

tioneddecision-makers.Theinterviewshavetwopurposesinparticular:First,theycompletetheobjective

targetprofilebyaddingsubjectivelyconsideredtargets(seeabove,No.1);second,theygiveinformation

aboutthesubjectivelyconsideredinformationrequirementsforthedefinedsetoftargets.

Thedeductiveanalysisgathersobjective informationrequirementsandwith it completes thesubjective

informationneedsgainedbytheinterviews.

Followingthis,theresultsaretestedwithanothersurveybytheabove-mentioneddecision-makers.Based

onaquestionnaire,theyshallevaluateandnarrowdowntheinformationrequirementsaccordingtoprior-

ities(Küpper1997,133).IntheprojectCEUS,theoutlineofthequestionnairewasbasedontheaforemen-

tionedsubject-matters:a)structuralconditions,b)resources,c)processplanninginteachingandlearning,

d)processplanninginresearch(Nusselein2002,5).

Inaconcludingworkshopthesurveyresultsarediscussedwiththedecision-makersagain.Ifnecessary,fur-

theradaptionsoftheinformationneedsaretobeeffected.6

5 Thetypesofdecision-makersmaydifferdependingontheorganisationalstructureandhavetobeadaptedaccordingly.6 IntheCEUSprojectthismethodofgatheringinformationneedswasrealisedatseveralhighereducationinstitutions.Basedonthis itwaspossibletoachieveasufficientandcomparabledatabasis.

Page 23: Information Management in Higher Education Institutionsduepublico.uni-duisburg-essen.de/.../M4_Information_Management... · Conseil Africain et Malgache pour l’Enseignement Supérieur

Chapter 1: Introduction to Information Management at Higher Education Insitutions

22

Thedescribedwayofgatheringinformationrequirementsexemplifiestheprocedureatvarioushighereduca-

tioninstitutionsinGermany.Itisimportanttokeepinmindthatduetodifferentstructuralconditionsindiffer-

entcountriesandinstitutions,thedescribedmethodtoanalyseinformationrequirementshastobeadjusted,

dependingontheinternalandexternalparticularitiesofahighereducationinstitution.

Dependingonthepurposesoftheinformationistobeused,thecollectionofdatahastobemoreaggregated

ormoredetailed.Consideringtheabove-mentionedexamplesofinformationrequirementsofa(vice)chan-

cellor,achancellororrepresentativesfromfaculties,itcanbeconcludedthatthedetail-leveloftheprovid-

edinformationincreaseswithadecreasinghierarchylevel.Viceversa,theaggregationlevelofinformation

increasesfromthelowesttothetophierarchylevel.Inordertoprovidecomparabledataandinformationon

alllevels,theaggregationofinformationshouldalwaysrefertoacommonandstandardiseddata-basis(Eber-

hardt2003,73).

Furthermore,itcanbeconcludedthatingeneralitisnotpossibletocoverallinformationneeds.Establish-

inganddevelopingastructuredinformationsystemathighereducationinstitutionscanhelptocloseorat

leasttoreducethesegaps.Therefore,oneofthekeychallengesisnotknowingexactlywhichunitsofahigher

educationinstitutionprovidepromisinginformationsourcesandhowtoconnectandusetheseinformation

sourcesforthewholeinstitution.Sometimesthatisbecausetherespectiveinvolvedpartiesdonotwishsuch

“connections”.Sometimes,collectingspecificinformationneedsisjustnotpossible,beitbecauseofalackof

time,beitduetotechnicalrestraints,orbecausethereisnotenoughstafffortheprocessing.

Consideringthis,acontrollerwhoisresponsibleforgatheringinformation,firstofallhastoanswerthefol-

lowingquestions:

Doesmyinstitutionprovidetheinformationneeded?

Whichpossibilitiestogatherinformationtheinstitutiondoesnotyetprovideexist?

Howmuchtimeandeffortdoesittaketoprovidethisinformationandwhocandoit?

Whichqualitycriteriacanbeguaranteedfortheinformationtobeneededwithregardtobeingcomplete,

timely,comparableetc.(seeTable2)

Questions & Assignments

1. Howdoyouproceedwhengatheringinformationatyourinstitution?Whoisresponsibleforthis

task?

2. Howfardoestheprovidedinformationmeettheneedsofthetargetgroups?

3.Whichchallengesareyouconfrontedwithwhencollectingdataatyourinstitution?

Page 24: Information Management in Higher Education Institutionsduepublico.uni-duisburg-essen.de/.../M4_Information_Management... · Conseil Africain et Malgache pour l’Enseignement Supérieur

Chapter 1: Introduction to Information Management at Higher Education Insitutions

23

II. Data collection, processing and analysis

Havingcollectedthenecessarydatafortherespectiveinformationneeds,thisdatanowhastobeevaluated

andanalysedinatransparentandunderstandableway.Generallythisisdonebystafflocatedataunitfor

managerialaccounting.Butwithregardstodataanalysisaccordingtodefinedqualitycriteria(seeTable2),it

isrecommendabletoinvolvethequalitymanageraswell.Additionally,she/hecanhelptoillustratethetech-

nicaldatainsuchawaythattherespectivetargetgroupisabletoread,understandandinterpretitcorrectly.

Themaintaskforqualitymanagerswhoareresponsiblefortheevaluationandanalysesofdataandinforma-

tionistocheckwhichcharacteristicsanidealinformationshouldhavetosatisfythedesiredinformationneeds

asmuchaspossible(Hórvath2011,298etseqq.).Thisprocessofevaluationandanalysesincludesvarious

challenges.

Averycommonproblemis, forexample,thatdata isnotcurrent,butretrospective,that it istoodetailed

andextensive,orthatitisinconsistentandcontradictory.Basedontheserestrictions,thedatadoesnotgive

enoughsignificantinformationontherespectiverequirements.

Workingagainsttheserestrictionsandachievinggreaterprecisionofthecollecteddatawithregardtothe

respectiveinformationneeds,somecriteriaofsuccessshouldbeevaluated.

Thefollowingtableshowsexamplesofkeycriteriaofsuccesswhenevaluatingandanalysingdataandinfor-

mation.Itincludessomeimportantquestionsthatshouldbeansweredwhencheckingthesecriteria.

Criteria of success for data collection

Questions to be clarified Phrase to memorise

Typeofdata Isitquantitativeorqualitativedata? Whichinformationdoesthedatagive? Isthedatasignificantlyvaluable?

Thedataiscategorisedclearlyintoquantitativeorqualitativecategories.Thesignificanceofthedataisclearandcanbenamed.

Degreeofcom-pression

Arethereanyduplicationsthatcanbereduced? Howtoaggregateandsummarisedata?

Asmuchdataasnecessary,aslittledataaspossible.

Timelinessofdata Isthedataup-to-date? Istheperiodofdatacollectionandthereportingperiodcongruenttotherespectiveissueofinter-est?

Theperiodofdatacollectionreferstotherelatedissueofinterest.Theperiodofdatacollectionmatchesthereportingperiod.

Page 25: Information Management in Higher Education Institutionsduepublico.uni-duisburg-essen.de/.../M4_Information_Management... · Conseil Africain et Malgache pour l’Enseignement Supérieur

Chapter 1: Introduction to Information Management at Higher Education Insitutions

24

Criteria of success for data collection

Questions to be clarified Phrase to memorise

Layout Whichlayoutisappropriateforthetargetgroup?(e.g.writtenreport;tablesummary;graphic/visualisedlayout)

Doesthelayouttransfertheneededinformation? Doesthelayoutincludeasystematicandreada-bleoutline?

Thelayoutisappropriatefortheneedsofthetargetgroup.

Problem-solvingrelevance

Whichinformationvaluedoesthedatahaveforthetargetgroup?

Whichindicatorprovesthisvalueandwhodecidesaboutthisindicator?

Thecollecteddataisvaluablewithregardtotheissueofinterest.

Priorityandcol-lectionfrequency

Whenisthedataneededandwho/whatdecidesaboutthistimeframe?

Whatisthefrequencyofdatacollectionandreporting?

Whichconsequenceshavetobeconsideredwithregardtothescopeofdataevaluationandanaly-sesresultingfromshort-termorlong-terminfor-mationneeds?

Istheperiodofdatacollectioncoordinatedwiththedateofprovision?

Whichcontrolmechanismscanbeconsideredrespectivetotheavailabletime?

Isthecollectionfrequencysufficienttoachievesignificantinformationfromthedata?

Theperiodofdatacollectioniscoordinatedwiththedateofprovision.Thefrequencyofdatacollec-tionissufficienttoproducesignificantinformation.

Purposeofuse Isthedataonlyusedforonepurposeordoesitservevariouspurposes?

Doesthepurposerequireaspecialformofdataevaluationandanalyses?

Checkifdatacanbeusedfordifferentpurposes.

Amount Whichdataisrequiredtodelivertheinforma-tionneededfromtherespectivetargetgroupandwhichnot?

Howdetailedshoulddatabetodelivercertaininformation?

Thelevelofdetailandtheamountofdatamatchestheissuesofinterestandinforma-tionneededfromthetargetgroup.Basedonfiltering,comprehen-sionandcanalisationofdata,youshouldproducesignificantandunderstandableinforma-tion.

Page 26: Information Management in Higher Education Institutionsduepublico.uni-duisburg-essen.de/.../M4_Information_Management... · Conseil Africain et Malgache pour l’Enseignement Supérieur

Chapter 1: Introduction to Information Management at Higher Education Insitutions

25

Criteria of success for data collection

Questions to be clarified Phrase to memorise

Accuracy Whatisthelevelofaccuracyofthecollecteddata?

Doesthedatadelivercoherentandconsistentinformationordoesitincludecontradictoryordifferingpossibilitiesofinterpretation?Ifso,howfardoesthisreducethevalueofthegainedinfor-mation?

Reducecontradictoryformsofinterpretation,butproduceclearandunambiguousinfor-mationfromthedata.

Reliability Whatisthedatasource?Isthedatasourcereli-ablewithregardtotransparency,methodologyandmeasurability?

Thecollecteddataisobtainedfromareliabledatasource.

Measurability/plausibility

Whichcriteriahavebeendefinedtomeasurethedata?

Arethesecriteriatransparentandunderstanda-ble?

Defineclearandunderstanda-blecriteriaofmeasurability.

Costs Whichfinancial,stafformaterialcostsresultfromcollecting,analysingandreportingdata?

Clarifythecostsfordatacollec-tion,analysesandreporting.

Data-protection Whataretheproceduresofdocumentingandsavingdata?

Whichdataprotectionruleshavetobeconsid-eredwithregardtodataaccess?

Clarifyregulationsandpro-ceduresofdocumentingandsavingdata.

Communicationprocesses

Whichcommunicationflowsarenecessaryforcollecting,analysingandusingdata?

Whoisinvolvedindatacollectionandanalyses? Whohastobeinformedaboutthedatacollec-tionandanalysesandhow?

Arethesecommunicationflowsclearandtrans-parenttoallinvolvedstakeholders,andtowhatextentaretheyputintopractice?

Coordinateanddefinecom-municationchannelstocollect,analyseandusedata.

Table 2 Criteria of success for data collection

Questions & Assignments

Theseniormanagementofyourinstitutionwantsallfacultiestohandinareportaboutthecurrent

successoftheirstudyprogrammes.

1.Howdoyoureportthesuccessofstudyprogrammesatyourinstitution?

2.Whichinformationneedsdoyouconsidertoberelevantinthisregard?

3.Whichcriteriaofsuccessareimportanttobeconsideredinthedatacollectionprocess?

Page 27: Information Management in Higher Education Institutionsduepublico.uni-duisburg-essen.de/.../M4_Information_Management... · Conseil Africain et Malgache pour l’Enseignement Supérieur

Chapter 1: Introduction to Information Management at Higher Education Insitutions

26

III. Distribution of information

Aftercollectingandanalysingthedatathegainedinformationistobedistributedtotherespectiveaddress-

eesviareportingsystems.Thedesignofthesereportingsystemscanvarydependingonthetypeandthe

amountofinformation,aswellasthetargetgroupanditsobjectives.InChapter4wewilllearnaboutthe

reporting-issueinmoredetail.Therefore,thischapterwillonlygiveanoverviewontherequirementsofan

informationmanagementsystemwithregardtodistribution.

The key element of distributing information is the relation between the sender of information and the

addresseeandthequestionofhowtotransfertherelevantinformationappropriately.Thismeans,aninfor-

mationsenderhastoknowtowhomshe/hehastodelivertheinformationandinwhichform.Atthesame

time,addresseesofinformationshouldknowhowtoread,understandandusethereceivedinformationfor

thearticulatedneeds(Hórvath2011,354etseq.).

Suchcoordinationisnoteasytoachieveinpracticebutincludesvariouschallenges.Forexample,producers

ofinformationoftendonotknowsufficientlywhotheaddresseeofthecollecteddataisandwhatthedatais

neededfor.Ontheotherhand,forinformationusersitmightbeunclearwhichinformationcanbeprovided,

howtoreadandanalysecollecteddataconsideringtherespectivecontext.

Figure 4 Types of interferences during the process of information distribution (adapted from Küpper et al. 2013, 241)

Dealingwiththesechallenges,qualitymanagerscanplayanimportantrolebybeingacommunicationlinkage

betweenthedifferentstakeholdersandunitsofahighereducationinstitution.Theycanrevealcommunica-

tionandinformationgapsbetweensendersandaddresseesofinformationandreducethembyclarifyingthe

contentofthespecificdatainanunderstandablewayforthetargetgroups.Indoingsotheycontributeto

achievingmoretransparencyandworkinginformationflowsathighereducationinstitutions.

Page 28: Information Management in Higher Education Institutionsduepublico.uni-duisburg-essen.de/.../M4_Information_Management... · Conseil Africain et Malgache pour l’Enseignement Supérieur

Chapter 1: Introduction to Information Management at Higher Education Insitutions

27

Incidence Case: Students Newsletter

Theresultofasurveyatthe“African-University”wasthatthestudentsfeel insufficiently informed,

beitwithregardtoorganisationalproceduresandrelevantdeadlinesoftheirstudiesorwithregard

tocurrentdevelopmentsinresearch.Thevice-chancellorforacademicsaskedthequalitymanagerin

chargetodevelopanewsletter.Thepurposeofthisnewsletterwastoinformregularly(e.g.quarter-

ly)aboutrelevantorganisationalissues,deadlinesandfixeddates,newservices,orotherissuesthat

mightbeofinterest.Sinceanewsletteriscloselyrelatedtothetargetsofthedepartmentforpublic

relations, thequalitymanager informedthedepartmentabout thiswork task. Indoingso,healso

wantedtofindouthowfarthepublicrelationscolleagueswereabletosupporthimwithregardto

developinganddistributingthenewsletter.Aftertalkingtoeachother,thequalitymanagerdecided

topublishthenewsletterbothasaprintversionandasanonlinepdf-versionontheuniversityhome-

pagetoreachasmanyuniversitymembersaspossible.Thepublicrelationscolleaguesofferedtocare

fortheplacementofthedocumentonthewebsiteandtosendasufficientnumberofprintedcopies

toeachfacultyandunit.Furthermore,thequalitymanageraskedacolleaguefromthedepartmentof

dataandinformationmanagementtocreateamailinglist.Inthefuture,interesteduniversitymem-

berscansubscribetothismailinglistandwillreceivethenewsletterautomatically.

Concerningthecontentdesignofthenewsletter,thequalitymanagerwantstoproceedaccordingto

thefollowingoutline:

1. Didyoualreadyknowabout…?

Informationaboutinterestingevents

Importantdatesanddeadlines

Currentresearchprojectsattheuniversity

Miscellaneous

2. LibraryServices

3. ICTServices

4. Haveyoualreadyread?–Newpublicationsfromresearchersoftheuniversity

5. Portraitofauniversitymember(shortinterviewwith5-6questions)

Thequalitymanagerisveryenthusiasticabouthisprojectactionplanforthepublicationofthenews-

letter and already very excited about feedback from the students and the other universitymem-

bers.

Page 29: Information Management in Higher Education Institutionsduepublico.uni-duisburg-essen.de/.../M4_Information_Management... · Conseil Africain et Malgache pour l’Enseignement Supérieur

Chapter 1: Introduction to Information Management at Higher Education Insitutions

28

Further Reading

Alter,S.(1996).Information systems: A management perspective(2ndedition).MenloPark:

BenjaminCummingsPub.Co.

Questions & Assignments

Your vice-chancellor of academics asks you to develop a newsletter for the lecturers at your

university.

1.Whatmightbeinterestingandrelevantinformationforlecturers?Howandbywhomcouldyou

gathertheseinformationneeds?

2.Whichstepsdoyouhavetoconsidertodesignanddistributethisnewsletter?

Whichchallengesshouldbeconsideredinthisregard?Whichcriteriaofsuccessareimportanttobe

consideredinthedatacollectionprocess?

Page 30: Information Management in Higher Education Institutionsduepublico.uni-duisburg-essen.de/.../M4_Information_Management... · Conseil Africain et Malgache pour l’Enseignement Supérieur

Chapter 1: Introduction to Information Management at Higher Education Insitutions

29

Page 31: Information Management in Higher Education Institutionsduepublico.uni-duisburg-essen.de/.../M4_Information_Management... · Conseil Africain et Malgache pour l’Enseignement Supérieur

Chapter 2: Translation of Higher Education Objectives Into Numbers

30

2 TranslationofHigherEducationObjectivesInto Numbers:QuantitativeandQualitativeIndicators . . . 31

2.1 MeaningandFunctionofQuantitativeandQualitativeIndicators . . . . . . . . . . . 31

2.2 DeterminationandOperationalisationof QuantitativeandQualitativeIndicators . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32

2.3 UsingIndicators–KeyAspectstoBeConsidered . . . . . . . . . . . . . . . . . . . . . . . . . 34

2.3.1 RequirementstoDefineIndicators . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34

2.3.2 TheBalanced-Scorecard–AnInstrumenttoMonitorIndicators . . . . . . . . . . . . . 36

2.4 ChallengesofUsingQuantitativeandQualitativeIndicators . . . . . . . . . . . . . . . . 39

differentiatekeyfunctionsofusingquantitativeandqualitativeindicators,

determineandoperationalisequantitativeandqualitativeindicatorsbydeterminingcentralparameters

suchasthesample,thereferenceperiodorthenumericalvalue,

considerkeyconditionswhenusingquantitativeandqualitativeindicators(e.g.trade-offsbetweenrele-

vantandnon-relevantdata,validityofdata,sensitisationofthetargetgroup,expenditureincostandtime,

dataprotection),

dealwiththeconceptoftheacademicbalancedscorecard.Basedonthis,participantsareabletotranslate

HEIstrategiesintoobjectivesandfindsuitableindicatorstomeasureaperformanceleveltobereachedin

adefinedperiod.

On successful completion of this chapter, you should be able to…

Chapter 2

Translation of Higher Education Objectives Into Numbers

Page 32: Information Management in Higher Education Institutionsduepublico.uni-duisburg-essen.de/.../M4_Information_Management... · Conseil Africain et Malgache pour l’Enseignement Supérieur

Chapter 2: Translation of Higher Education Objectives Into Numbers

31

2 Translation of Higher Education Objectives Into Numbers: Quantitative and Qualitative Indicators

2.1 Meaning and Function of Quantitative and Qualitative Indicators

Inthepreviouschaptersyouhavelearnedthatthepurposesofinformationsystemsareto

supportdecision-makingprocesses,

achievetransparencyonstructuralprocesses,

increaseefficiencyandeffectivenessoftheprocessesathighereducationinstitutions.

Indicatorsplayanimportantroletoreachtheseobjectives.Theirtaskistosummariseaquantitativemeasur-

ablesituationandtoidentifyrelevantfactsandcorrelationsinasimpleandcondensedform.(Küpper2013,

476).

Focussingonhighereducationinstitutionsmeansmakinganyactivitiesreferringtodecision-making,organi-

sationalorplanningprocessestransparent.Theygiveaquantitativeoverviewaboutthestatusquoatahigher

educationinstitution.Indicatorsreducecomplexityandaggregateinformation,whichmeansthattheyinform

aspreciselyandbrieflyaspossibleaboutperformances.Indoingso,theyhelptoachieveanadequateinfor-

mationsupplyforhighereducationmanagement:theyallowanalysingthestatusquoaswellastoevaluating

theoutcomesofthespecificcoursesofactions.Fromaninternalperspectivetheyareafundamentalbasisof

managementandrelateddecision-makingprocesses.Fromanexternalperspective,highereducationinsti-

tutionscanbemeasured,compared(e.g.rankings)andevenmanaged(e.g.targetagreementswiththemin-

istry)basedonperformanceindicators.Basedonthis,indicatorsarealsocloselyrelatedtothequalityassur-

ancesystemofahighereducationinstitution.

If indicatorsareusedtodescribeperformancesorthesuccessofdefinedobjectivesofahighereducation

institution,weoftenusetheterm“keyperformanceindicators“or“performanceindicators“.Accordingto

theAnalyticQualityGlossary,

“Performance indicators are data, usually quantitative in form, that provide a measure of some

aspect of an individual’s or organisation’s performance against which changes in performance or

the performance of others can be compared.”

(Harvey 2004-14)

It shouldbeconsidered, thatalthoughperformance indicatorshavea relativelyprecisemeaning, there is

atendencytousethistermforanystatisticaldatarelatedtotheactivitiesofhighereducationinstitutions,

whetherornotitreallyreferstoperformanceorsuccess(Harvey2004-14).

Performance Indicators

Page 33: Information Management in Higher Education Institutionsduepublico.uni-duisburg-essen.de/.../M4_Information_Management... · Conseil Africain et Malgache pour l’Enseignement Supérieur

Chapter 2: Translation of Higher Education Objectives Into Numbers

32

Consideringthis,qualitymanagersshouldbeabletounderstandmeaningandfunctionof(performance)indi-

cators,usethemcorrectlyandexplainthemappropriatelytotherespectivetargetgroups.

AccordingtoGladen(2003,11)keyfunctionsofindicatorscan...

describecomplexandoperationalissues,structuresandprocessesinarathersimpleway,

guarantyacomprisingandquickoverview,

serveleadershipforspecificanalyses,

serveleadershipforcurrentplanning,decision-makingandmanagerialaccounting,

enableinformationreleasebyaggregationandselection,

describecriticalfactorsofsuccessandshortagesinthemanagementsystem.

2.2 Determination and Operationalisation of Quantitative and Qualitative Indicators

Indicatorscanbedescribedwiththreekeyparameters:

1. Theobject/target,theyaredescribing(what?).

2. Thetimeframe,whichtheyreferto(dateorperiod?).

3. Adefinednumericalvalueforquantification(howmuch?).

Indicatorscanbedifferentiatedintoquantitativeandqualitativeindicators.Quantitativeindicatorsdescribe

issuesandsituationswithaclearlydefinednumber.Basedonthereductiontothesubstantialsignificance,

existingindividualinformationiscondensedtoanobservableandmeasurablematteroffact(Gladen2003,

12).

Examplesincludeavailablethird-partyfundsofafaculty,numberofstudentsinacertainprogramme,number

ofPhDstudentsperprofessor,availableacademicstaffofafaculty,drop-outstudentsratiosetc.

“Qualitativeindicatorsareproxyparameters,whosecharacterorvaryingvaluehelpstoconcludethechar-

acterorvaryingvalueofanotherimportantparameter”(translatedfromGladen2003,15).Thatmeansthat

theydonotdescribedirectlymeasurablevariables,buttheyserveasasubstitutewhichiseasiertobemeas-

ured.Basedonthiswecananalyseperformancesthatcannotbequantifiedormeasureddirectly.Forexam-

ple,ifafacultyorachairwantstodescribeitsresearchperformancelevel,theyconsidervariousquantitative

indicatorssuchasnumberofpublications,patents,successfuldoctoratesortheamountofraisedthird-party

funds.Thesumoftheseindicatorsissupposedtohelpratingtheresearchperformance.

Theproblemofusingqualitative indicators is that theyonlyhavea limitedvalidity,becausethecause-ef-

fectrelationshipbetweentheoriginalandthesubstitutingindicatorisonlybasedonassumptions,butnot

Quantitative Indicators

Qualitative indicators

Page 34: Information Management in Higher Education Institutionsduepublico.uni-duisburg-essen.de/.../M4_Information_Management... · Conseil Africain et Malgache pour l’Enseignement Supérieur

Chapter 2: Translation of Higher Education Objectives Into Numbers

33

onexactdescriptions.Thismeansthatcause-effectrelationshipscanbebiasedormono-causalandwithit

incomplete(Küpper2013,480).7Thiscanprovokecontradictionswithregardtotheanalysisandinterpreta-

tionoftherespectivedata,asisshowninthefollowingexample:

Theseniormanagementofahighereducation institutionwantstoknowwhichthemostsuccessfulstudy

programmesof their faculties are. Therefore, theydefine thequantitative indicator “numberof achieved

degrees”.Viewedinisolation,thisindicatorisdefinitelyvalidsinceitdescribeswhatitismeanttodescribe

–thesuccessofstudyprogrammes,whichismirroredintherespectivenumberofdegrees.Nevertheless,

ifnotusedadequately,this indicatorcanentailwrongincentivesorundesiredside-effects.Forexample,a

target-settingbasedonthisindicatorcouldinducefacultiestoneglectexistingcriteriatopassfinalexamsin

ordertobeabletoachieveasmanysuccessfuldegreesaspossible.

Theexampleshowsthatwehavetobecarefulandmustdefineindicatorsdeliberatelywhenusingthemfor

managementpurposes(alsoconsiderChapter2.3.2focussingontheBalancedScorecard(BSC)).

Ifasuccessfulstudyprogrammeisnotonlydefinedbythenumberofgraduatesbutalsobyfulfillingprevi-

ouslydefinedminimumrequirementsinteachingandlearning,thismeansdifferentiatingandconcretising

consideredparametersinamorequalitativeway.Forexample,todescribeasuccessfulstudyprogrammewe

canconsiderevenmorequantitativeindicatorsthataresummarisedtoaqualitativeindicator(e.g.mentoring

student’sratio,drop-outstudent’sratio,numberofrepetitionoffinalexamsortheaveragetimeneededto

completeadegree).

Similarly,wecanrefertosuccessfulresearch:Thesuccessofascientificexperimentdependsonvariousinflu-

encingparameters,whicharesearcheroftenisnotabletocontrol.Thatmeans,weneedindicatorsthatare

abletoreduceinformationasymmetriesinsuchawaythattheaddressee(e.g.theseniormanagement)is

abletoconcludeonthefactualresearchactivitiesoftheresearcher.

Therefore, data cannot only be analysed quantitatively, but their qualitative characteristics and possible

resultingeffectshavetobeconsideredaswell.

Further Reading

Dealingwithnationalteachingperformanceindicators–thefollowingarticlegivesanexamplefrom

Australia:

Barrie,S.,&Ginns,P.(2007).Thelinkingofnationalteachingperformanceindicatorstoimprove-

mentsinteachingandlearninginclassrooms. Quality in Higher Education,13(3),205-286.

7Youfindmoreinformationonhowtodealwiththeissue“validity”inModule2,Chapter5.4.

Page 35: Information Management in Higher Education Institutionsduepublico.uni-duisburg-essen.de/.../M4_Information_Management... · Conseil Africain et Malgache pour l’Enseignement Supérieur

Chapter 2: Translation of Higher Education Objectives Into Numbers

34

Qualitymanagerscanplayanimportantroleinthiscontext.Theycanuncovercontradictionswhenusingindi-

cators,theycanmaketransparentandunderstandablecause-effectrelationships,andtheycanshowdeci-

sion-makerswaysofdealingwiththemappropriately.Todoso,qualitymanagersshouldknowandbeableto

dealwiththekeyrequirementsofindicators.Therefore,thefollowingchaptergivesanintroduction.

2.3 Using Indicators – Key Aspects to Be ConsideredThischapterdescribeskeyrequirementstobeconsideredtodefinevaluableindicators.Furthermore,wewill

gettoknowtheBalancedScorecardasanexampleofaninstrumenttouseanddealwithindicators.Thechap-

tertiesinwiththediscussionaboutthemethodologicalrealisationofsurveysinModule2.

2.3.1 Requirements to Define IndicatorsThefollowingfactorsshouldbeconsideredwhenaimingatdefiningpreciseindicators(Hórvath2011,542et

seq.;Tropp2002,57etseqq.)

1. Each indicator needs a concrete purpose

Tobesignificantanindicatorneedsaconcretepurposeandoneorseveral(butnotarbitraryselected)

addressees.

Tobeabletouseindicatorsforseveralpurposes,theyhavetobedefinedanddifferentiatedexactly.

Datacollection,thatisnecessarytodefineanindicator,hastoberelatedappropriatelytothepurposeof

theindicator.

Formalrequirements(e.g.law/politicalrequirements),whicharerelevantfordefininganindicator,have

tobeconsidered.

Key questions to be answered:

Whatisthesignificanceoftheindicator?

Whichnumericalvaluetranslatesthissignificance?

Whichinformationdoesthisnumericalvaluetakeintoaccountandwhichnot?

Whichformalrequirementshavetobeconsidered?

2. Validity of data: No quantitative data without additional qualitative information

Indicatorshavetobecontrolledwithregardtotheirvaliditytoavoidwrongincentivesorunexpected/

undesirableside-effects(seeexampleonsuccessfuldegrees).

Key questions to be answered:

Whatarethecontinualdatasourcesandwhocollectsthemtodefineanindicator?

Whataresuitablereferencevalues(benchmarks)tocontrolthevalidityofanindicator?

3. Trade-off between relevant and non-relevant data and information

Providedhigh-qualityvalidity,thescopeofdatatodefineindicatorsshouldbereducedasmuchaspossi-

ble.Anoverloadedlevelofdetailcanevenhinderstrategicmanagement.

Reductionofdatacollectionthatisnotrelevantforthedefinitionofindicatorsandwithitavoid“data

graveyards”.

Page 36: Information Management in Higher Education Institutionsduepublico.uni-duisburg-essen.de/.../M4_Information_Management... · Conseil Africain et Malgache pour l’Enseignement Supérieur

Chapter 2: Translation of Higher Education Objectives Into Numbers

35

Key questions to be answered:

Whichdataisnecessarytodefineacertainindicatorandwhichisnot?

Arethereanyirrelevantdatathatkeepbeingconsideredunnecessarily?

4. Considering feedback

Thenumericaldatashouldbealignedtotherealityoftheaffectedstakeholdersandevaluatedwith

regardtocontradictions.

Atthesametime,theaffectedstakeholderscanbeprovidedwiththeevaluatedandanalyseddatatobe

consideredforfurtheractionsanddevelopments.

Key questions to be answered:

Doesthecollecteddatareflectreality?

Arethereanyconstraints?

Dotheselectedindicatorsprovideanyadditionalbenefitsforimprovementandenhancement?

5. No isolated measurements

Whencollecting,analysinganddocumentingdata,itshouldnotbedoneinisolationbutcomparable

parametersshouldbeconsidered(e.g.descriptionofabsolute,relativeandaccumulatednumbers).

Datatobeusedtodefineindicatorsshouldbecollectedcontinuouslyoveralongerperiodinsteadofonly

onceandinisolation.Byconsideringalongerperiodthesignificanceofindicatorsincreasesanditfacili-

tatesamoreexactjudgementofaverageperformancelevels.

Key questions to be answered:

Whatisthedateofreferenceandtheperiodofreferenceforthedefinedindicator?

Inwhichintervalshouldtheindicatorsbelookedat?

6. Expenditure in cost and time

Collecting,analysingandpublishingdataandinformationrequiresfinancial,staffandalsomaterial

recourseswhichhavetobecalculatedintime.

Timeneededtogatherinformationistobecalculatedintimeandtobecoordinatedwithpossibledead-

lineswhichhavetobeconsidered.

Key questions to be answered:

Whichexpendituresonresources(staff,finances,IT-system,material)havetobeconsidered?

Whatisthetimeframetosubmittherequireddataandinformation?

Whatisthecost/benefit-ratiowithregardtoexpenditureofresourcesandtimeandtheadditional

benefitoftheprovidedinformation?

7. Data protection

Thecollectedandanalyseddataaretreatedresponsiblyandaccordingtogivendataprotectionguide-

lines.

Key questions to be answered:

Dodataandinformationcomplywiththerespectivedataprotectionguidelinesinforce?

Whathastobedonetomeetpersonaldataprotectionrightsandtoavoidmisuse?

Page 37: Information Management in Higher Education Institutionsduepublico.uni-duisburg-essen.de/.../M4_Information_Management... · Conseil Africain et Malgache pour l’Enseignement Supérieur

Chapter 2: Translation of Higher Education Objectives Into Numbers

36

8. Sensitisation of the target group to use edited data reports

Informingthegroupofaddresseesabouthowtointerpretindicatorsandwhattousethemfor.

Key questions to be answered:

Istheinformationoftheindicatortransparenttothegroupofaddressees?

Whichinformationdoesthegroupofaddresseesneedtobeabletousetheindicatorsappropriately?

Further Reading

Chalmers,D.(2008).Teaching and learning quality indicators in australian universities. Outcomes of

higher education: Quality relevance and impact.Paris:ProgrammeonInstitutionalManagementin

HigherEducation.

2.3.2 The Balanced-Scorecard – An Instrument to Monitor Indicators

Indicatorsthataredefinedunderstandablyandcomprehensivelycancontributetoreduceinformationasym-

metriesbetweendifferenttargetgroups.Theyspecifytherespectivedefinedobjectivesandthusfacilitate

thecoordinationofnecessaryprocessestoreachtheseobjectives(Küpper2013,500).Thiscanbecarriedout

eitherverticallyacrossthedifferenthierarchicallevelsofahighereducationinstitution,aimingatmanaging

itsmultipleunits (e.g.with targetperformanceagreements),orhorizontally tomanagedifferentdomains

basedondefinedtargetsforthesedomains(e.g.orientationofstudyprogrammesoninternationalstudents).

Oneexampleofaninstrumenttomonitorindicatorsathighereducationinstitutionareindicatorsystems.An

indicatorsystemis

“an arrangement of indicators in a systematic way, which means that the individual indicators

are linked in a meaningful way, that they complement each other, and that they are aligned to an

overriding common objective.”

(translated from Tropp 2002, 3 et seq.)

Questions & Assignments

1. Whichparticular conditionsdoesyour institutionhave toconsiderwhendealingwithdataand

information?Whichchallengesdosuchconditionscomewith?

Indicator system

Page 38: Information Management in Higher Education Institutionsduepublico.uni-duisburg-essen.de/.../M4_Information_Management... · Conseil Africain et Malgache pour l’Enseignement Supérieur

Chapter 2: Translation of Higher Education Objectives Into Numbers

37

Besides indicator systems, another strategicmanagement instrument is theBalanced Scorecard,which is

increasinginpopularityathighereducationinstitutions.

ABSCfacilitatesthelinkbetweenstrategicplanningandoperationalprocessestorenderperformanceassess-

ment.Otherthanindicatorsystems,aBSCisnotbasedonapredefinedsetofindicators,butenablesamore

precisechoiceofindicatorsfortherespectiveobjectiveswhicharetobeoperationalised.Therefore,aBSC

isveryusefulinmonitoringcomplexitiesandorganisationalparticularitiesofahighereducationinstitution,

suchasuncleartechnologiesofperformanceassessment,ambiguousandcomplextargetstructures,differing

memberships,staffexpertise,hierarchiesororganisationbasedonknowledge(Scheytt2007).

ABSCcancontributesignificantlytoachievemoretransparencyandclarityaboutthestrategicobjectivesof

ahighereducationinstitution.Basedonthis,suitableorganisationalprocessescanbedevelopedinorderto

reachthesedefinedobjectivescanbedeveloped(Röbken2003,4).

Theterm“balanced”signifiesthattheperspectivesthatarerelevanttorealiseastrategyareequallyweighted

inthescorecard(Kaplan/Norten,inRöbken2003).AccordingtoKaplanandNorten,typicalperspectivestobe

consideredinaBSCarethefollowingfour8:

1.customer

2.learningandgrowth(humanresourcesandorganisationaldevelopment)

3.financial

4.internalprocesses

Consideringtheseperspectives,wecandefineindicatorsforthestrategicobjectivesanddeterminetargetval-

uesthathelptomeasurehowfartheseobjectiveshavebeenreached.

Duetothebalancedconsiderationofthementionedperspectives,theBSC-approachtriestocopewiththe

challengingtaskofcomprisingdifferingcontextsandinfluencingfactorsofsubject-mattersandofanalysing

andinterpringoutcome-linkagesmoretransparentlyandclearly(Scheytt2007).

AccordingtoKaplanandNorton(1996)theimplementationofaBalancedScorecardcanbebasedonfivekey

steps(Scheytt2007):

1 . Definitionofthedifferentperspectiveswhichareoffundamentalimportancetothehighereducation

institution.ThesecandifferfromtheabovementionedeconomicalBSCmodel.

2. Deductionofobjectives,whichareparticularlyimportanttofollowthestrategicplan(operationalisation

ofobjectives).

3. Definitionofindicators,whichinformaboutcontent,extentandtimeframetoreachtheobjectivesand

thushelptomanagetheorganisationalprocessesofperformanceassessment.

8Theseperspectivescanbeadaptedtotherespectiveneedsofaninstitution.

ABSC translates thevision andthe strategyofa higher education institution intocoherent objectivesand indicators

Page 39: Information Management in Higher Education Institutionsduepublico.uni-duisburg-essen.de/.../M4_Information_Management... · Conseil Africain et Malgache pour l’Enseignement Supérieur

Chapter 2: Translation of Higher Education Objectives Into Numbers

38

4. Definitionoftargetvaluesbasedoninfluencingparameterstobereachedinacertainperiod(e.g.one

year).

5. Definitionofinitiatives/activitiestoberealisedinordertoreachtheobjectivesduringadefinedperiod.

Figure 5 System of a Balanced Scorecard (adapted from Scheytt 2007)

Themanagedprocessing,asitisdescribedintheillustration,istheparticularcharacteristicoftheBSC,alsoto

bedistinguishedfromotherconceptsofperformancemanagementsuchasindicatorsystems.Suchprocess

orientationfacilitatesthediscussionabouttarget-performancecomparisons:Onetheonehand,thecurrent

statusisdefinedbyanalysingthequestions“whodoeswhat,when,whereandhow?”Ontheotherhand,tar-

getvaluesandthequestionwhohastobeinvolvedandwhichinformationistobeneededfromwhomand

tillwhen(Scheytt2007)

Deducingindicatorsforthetotal“objectivehierarchy”ofahighereducationinstitutionaimsatguaranteeing

congruencebetweenthedifferentobjectivesandatcoordinatingstrategicplanningwiththeorganisational

processesofdailyperformanceassessment.Basedonthis,theBSCcansupportcommunicationprocesses

betweenthedifferentdepartmentsandstaffbydevelopingaframeworkthatenablesacontinuousprocess

ofself-evaluationandorganisationallearning(Röbken2003,4).Thisincludesaimingcontinuouslyatquality

enhancementandwithitestablishingandsystemisinginternalqualityassurancestructures.

Page 40: Information Management in Higher Education Institutionsduepublico.uni-duisburg-essen.de/.../M4_Information_Management... · Conseil Africain et Malgache pour l’Enseignement Supérieur

Chapter 2: Translation of Higher Education Objectives Into Numbers

39

2.4 Challenges of Using Quantitative and Qualitative Indicators

Whilecompaniesgenerallyhaveonebigstrategictargettobeachievedbyallemployees,athighereduca-

tioninstitutionswecanfinddifferentlooselycoupledtargetsystems,whicharenotrelevantforallmembers

oftheinstitutionbutonlyforpartialgroups.Thedifferentfaculties,theseniormanagement,aswellasthe

administrationofahighereducationinstitutioncanhaveratherdiffering,sometimesevenconflictingtargets

withdifferentpriorities.Forexample,aprofessorwhoisdoingresearchmightbeparticularlyinterestedin

gainingsufficientthird-partyfundstobeabletodoresearch.Atthesametime,fortheseniormanagement

third-partyfundsofferapossibilitytobalancebudgetdeficits.Furthermore,theystrengthenexternalinsti-

tutionalprofiling.Meanwhile,alecturermightbeespeciallyinterestedinadequateresourcestobeableto

facilitategoodteachingandlearningconditions.Thelatterisalsoakeyconcernofthestudentswhowantto

completetheirstudiessuccessfully.

Accordingtothis,anotherchallengetodealwithistheformulationofobjectives.Whatlevelofclarityand

precisiondoobjectivesneedinordertobemeasurable?Andwhichamplescopecantheyhavetoenable

a broadflexibilitywith regard to their design and implementationaccording to the academic freedom in

researchandteaching.

Basedonthis,anotherobstaclewhendefiningandusingindicatorsisthattheycannotbedefinedforseveral

objectivesatthesametime,butonlyforoneconcreteobjective.Duetothissingle-sidedfocus,itmayoccur

thatcausalitiesbetweendifferentobjectivesarenotconsideredandwithitentailcontradictoryorevenwrong

interpretationsfortakingfurtheractions.UsingaBSC,requiresconsideringsuchcausalitieswhencombining

differentindicatorsforanobjective.

Theproblemofcontradictoryconclusionscanalsobeaconsequenceofdifferentunderstandingsaboutindi-

catorsandtheirassumedprioritylevels.Thefollowingmetaphoricalcomparisoncouldhelptoillustratethis

problem:whentalkingaboutapples,wecanassumethatonepersonconsidersanappletobebig,sourand

Further Reading

Kaplan,R.S.(2011).StrategicperformancemeasurementandmanagementinNonprofitOrganiza-

tions.Nonprofit Management & Leadership, 11(3),353–370.

Kaplan,R.S.,&Norton,D.P.(1993).Puttingthebalancedscorecardtowork.Harvard Business Re-

view,71(5),134-147.

Kaplan,R.S.,&Norton,D.P.(1996).Usingthebalancedscorecardasastrategicmanagementsys-

tem.Harvard Business Review, 74(1),75-85.

Page 41: Information Management in Higher Education Institutionsduepublico.uni-duisburg-essen.de/.../M4_Information_Management... · Conseil Africain et Malgache pour l’Enseignement Supérieur

Chapter 2: Translation of Higher Education Objectives Into Numbers

40

green,meanwhileanotherthinksaboutsmall,crispandredapples.Translatingthistothehighereducation

contextmeans, forexample, that“goodteaching”at the facultyofmathematicscanbecharacteriseddif-

ferentlythanatthefacultyofsocialsciences9.Also,internationalpublicationstobeusedasanindicatorof

researchqualitycanberatherimportantinonefaculty,whileinanothertheyarenotasrelevant.

Thesedifferingunderstandingshavetobeconsideredandclarifiedwhendefiningindicators.Onlythen,are

weabletoachieveacommonbasisfortheiranalysisandinterpretationandcanthereforeavoidtheapple

comparisonbecomingacomparisonofapplesandpears.

Anotherprecedingchallengeisthathighereducationinstitutionsneedanoverarchingstrategyasabasisto

defineanduseindicators.Whatwecanobserveisthatstrategiesonlyexistonpaper,buttheydonotplaya

rolewithregardtooperationalisingprocessesandactivities.Ifhighereducationinstitutionswanttodealwith

indicators,strategicplanningisanobligatoryrequirement–itisthestrategythatistranslatedintoconcrete

operationalisedtargets(e.g.basedonaBSC)thataremeasuredbasedonappropriateindicators.Thatmeans,

theessentialprerequisiteforintroducingaBalancedScorecardisahighereducationinstitutiondetermining

itsstrategicorientation,documentingitandmakingittransparentamongthewholeorganisation,forexam-

plebydevelopingstrategicplansoninstitutionalorfacultylevel.

Furthermore,whenusingindicatorsdifferentcomparisondimensionshavetobeconsidered:forexample,for

internalpurposesindicatorsareoftenusedtocomparedatainahistoricaltimeframe.Thatmeans,theymon-

itorcertaindevelopmentsduringagivenperiodoftimeandserveasabasisforfutureperformancelevelsto

beachieved,andwhicharenegotiated,e.g.viatarget-performanceagreements(Röbken2003).Forexternal

purposes,indicatorscansupportthecomparisonofhighereducationinstitutions(orafaculty,aunitetc.)in

termsofrankingsorbenchmarking.

Focussingonthevalidityofindicatorsanotherchallengeisthatveryoftentheycannotbecontrolledcom-

parably,which lead to furtherdiffering interpretation frameworks. For example, higher education institu-

tionscanhardlyinfluenceinput-parametersbecausetheycannotinfluencetheprovisionofresources.This

changeswhenwelookatprocess-parameters:toensureandenhancethequalityofteachingandlearning,

weshouldnotonlyconsidertheprovidedresources,butfocusonaspectssuchascurriculumdesign,didac-

tics,programmeandassessmentmanagement,planningstudentinfrastructure,evaluationofchairsorother

teachingunits.

Thementionedchallengesindicatethatdealingwithindicatorsinvolvesahighworkloadandexpenditureof

time.Themorecomplicatedthemethodsandtechniquesforthedatacompilation,themoreriskofanincom-

pleteandnonpermanentdata-collection,andwithitindicatorsthatareneitherrelevantnorsignificant.Con-

sideringthis,wealsohavetoquestiontheintendedbenefitscomparedtotheintroducedcosts.Tocountervail

thisproblem,itisimportanttoreflectwhichdata-collectionmethodsandwhichdataisalreadyavailableto

describehighereducationprocesses,whichadditionalinformationmightbeusefulandtowhatextentexten-

sionsoradaptionsoftheexistingdata-systemmightbepossibleanduseful.

9Forfurtherexplanationsonhowtooperationalisethequalityof“goodteaching”pleaseconsiderModule2,Chapter5.2.

Page 42: Information Management in Higher Education Institutionsduepublico.uni-duisburg-essen.de/.../M4_Information_Management... · Conseil Africain et Malgache pour l’Enseignement Supérieur

Chapter 2: Translation of Higher Education Objectives Into Numbers

41

Furthermore,highworkloadwithregardtocollectingdataandthe followingdocumentationandcommu-

nicationflowscanresult inopposingandnegativeattitudesamongstaff.Toreducesuchoppositions, it is

veryimportanttoexplainandcommunicatetheadditionalbenefitandthepurposeoftheintroductionofan

instrumentliketheBSCorotherindicatorsystemsforahighereducationinstitution.

ThedescribedchallengesbringoutthenarrowlimitsofusingaBSCandindicatorsasameanstoimprovepro-

cessesandactivitiesthatservetoachievecertainobjectives.Wehavetokeeptheselimitsinmindandshould

notunderestimatethem,sinceitmightbecomeevenmoreproblematicandcomplicated,whencontradic-

tionsarenotclarified,butcontinuouslyproceeded.Inthiscase,theexpectedbenefitofworkingwithindica-

torsasaninstrumenttosystematiseandmanageprocesseswouldbenotberealised.

Consideringthis,whenoperationalising indicatorswecontinuouslyhavetocheckwhichindicatorcanpro-

videwhichcontributionandhowrelevantthiscontributioniswithregardtoachievingtheintendedstrategic

objective.

Comingbacktoqualityassuranceprocessesathighereducationinstitutions,qualitymanagersplayanimpor-

tantroleindealingwiththeabove-mentionedchallenges.Theycanhelptodefineappropriateindicatorsfor

thekeyprocesses,teachingandresearch.Furthermore,theyshouldrevealbothopportunitiesandalsolimits

ofusingindicatorsandmakethemtransparenttotherespectivetargetgroups.Basedonthis,theycanfacili-

tateacoordinatedandadequateinformationfundamentfordecision-makingprocesses.

Challenges when dealing with (performance) indicators

Example

AtHEItherearedifferentstakeholderswithmul-tiple,sometimescontradictoryobjectives.

Topmanagement:getthird-partyfundsforrea-sonsofcompetitionandcompensationofbudgetdeficits.

Professor:getsthird-partyfundstodomoreresearch.

Anindicatorcannotrepresentmultipleobjectives

butonlyonedefinedobjective.

Theindicator“third-partyfunds”ofafacultyreferstotheallocationofthird-partyfundsatafaculty.Itdoesnotrefertoresearchquality.

Adefinedstrategyisaprerequisitetouseabal-anced-scorecard.

HEIstrategy:toincreasetheinternationalisationofteachingandlearning.

Indicators: Numberofinternationalstudyprogrammes Numberofinternationalcollaborativeresearch

projects

Thecomparabilityofindicatorsmaydiffer(e.g.dependingontheirlongitudinalorinter-organi-sationaluse)

Longitudinaluse:comparedatawithregardtothedevelopmentofstudyprogrammesoveracertainperiod.

Inter-organisationaluse:comparetwofacultieswithregardtothenumberofgraduates.

Page 43: Information Management in Higher Education Institutionsduepublico.uni-duisburg-essen.de/.../M4_Information_Management... · Conseil Africain et Malgache pour l’Enseignement Supérieur

Chapter 2: Translation of Higher Education Objectives Into Numbers

42

Challenges when dealing with (performance) indicators

Example

Theinfluenceonthevalidityofindicatorsmaydiffer(e.g.inputvs.processindicators)

Indicatorsforthequalityofteachingandlearn- ing:

Inputindicators:resourceallocationthatis determinedbyexternalstakeholders(e.g.min- istry).HEIcanhardlyinfluencetheamountof resourceallocation.

Processindicators:curriculumdesign,didactics, managementofassessment/studentinfrastruc- ture,evaluationetc.HEIcaninfluencethequali- tyoftheseindicators.

Therelationbetweenexpenditureoftimewhencollectingdatafortheindicatorsandtheeffectsshouldbebalanced.

Whichadditionalinformationdoweexpectfrom students’drop-out-rates?Dowegetmoreinfor- mationthanwhatwealreadyknow?Isthis informationworthinvestingtimeonrespective datacollection?

Whichinformation/dataalreadyexistandwhichadditionalinformation/datashould/couldbeaddedoradjusted?

Both,administrationandfacultycollectdata aboutstudentswhogoabroadduringtheirstud- ies.Itshouldbecheckedinhowfarthesenum- bersarecoherenttoeachotherand/orcanbe matched.

Whichnotionsofresistanceamongstaffhavetobeconsidered?

Staffresistanceduetooverlappingresponsibil- ities

Table 3 Challenges of (performance) indicators

Page 44: Information Management in Higher Education Institutionsduepublico.uni-duisburg-essen.de/.../M4_Information_Management... · Conseil Africain et Malgache pour l’Enseignement Supérieur

Chapter 2: Translation of Higher Education Objectives Into Numbers

43

Page 45: Information Management in Higher Education Institutionsduepublico.uni-duisburg-essen.de/.../M4_Information_Management... · Conseil Africain et Malgache pour l’Enseignement Supérieur

Chapter 3: Reporting: Presentation and Communication of Data and Information

44

3 Reporting:PresentationandCommunicationof DataandInformation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45

3.1 DefinitionofReportingObjectivesforDifferentTargetGroups . . . . . . . . . . . . . . 45

3.2 ContentofReporting . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46

3.3 OrganisationalConditionsforReporting . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48

transfercollecteddataintoacoherentandtransparentreportingsystem,

define reporting objectives for different target groups (e.g. (internal) accountability, strategic decision-

making,qualityassurance),

setupareportstep-by-step,consideringaspectssuchastargetgroups,afundamentalplan/actualdata

analysis,andanappropriatecompositionofvalidandrelevantinformation,

supportthedevelopmentofareportsystematyourinstitution.Youwillbeabletodetermineresponsibili-

tiesandfunctions,defineworkflows,deadlinesandreportingfrequencies,aswellasanappropriateformat

ofreporting.

On successful completion of this chapter, you should be able to…

Chapter 3

Reporting: Presentation and Communication of Data and Information

Page 46: Information Management in Higher Education Institutionsduepublico.uni-duisburg-essen.de/.../M4_Information_Management... · Conseil Africain et Malgache pour l’Enseignement Supérieur

Chapter 3: Reporting: Presentation and Communication of Data and Information

45

3 Reporting: Presentation and Communication of Data and Information

3.1 Definition of Reporting Objectives for Different Target Groups

According toBlohm,a reportingsystem includesallunits, regulationsandactivitiesofahighereducation

institutionwhichsupportcollecting,analysingandcommunicatinginformationforinternalandexternaluse

(BlohminGrochla1980,316).Basedonthis,thedistributionandexchangeofinformationiscarriedoutby

reportswhich“includesummarisedinformationthatrefertoanoverridingaimandaninformationpurpose”

(translatedfromBlohm1974,15).

Therefore,reportsplayanimportantrolewithregardtoqualityassuranceandenhancementathigheredu-

cationinstitutions.Theyhelptodocumentevaluatedstatusquosandtodescribeopportunitiesandthreats

on theway to achieveexpectedperformance levels. Furthermore, they serve accountability purposeson

achievedoutputs-statusinthecorefieldsofteachingandlearning,researchorservicesbyprovidingafunda-

mentalbasisfordecision-makingprocesses.

Qualitymanagerscanbeassignedwithdevelopingsuchreportsorsupportingotherstaffmembersduringa

reportingprocess.Thisiswhytheyshouldhaveabasicunderstandingabouttheobjectivesofreportingto

thedifferenttargetgroups.Basedonthis,theyshouldbeabletodesignanadequatereportstepbystep(e.g.

coordinatingresponsibilities,workflows,deadlines,reportingfrequenciesorformats).

Inthefollowing,youwillgettoknowdifferenttypesofreportingthatcanbeusedfordifferentpurposesand

targetgroups.Basically,wecandifferentiatethreedifferenttypesofreporting:standardreports,reportson

demandanddeviationreports(Hórvath2011,535;Horváth2008,21etseq.;Küpperetal.2013,231etseq.;

Göpfert2007,3etseq).

Standardreportsarepublishedinregularlyfixedperiods.Theyarestandardisedinformandcontent,based

onadefinedsetofinformationneeds(e.g.standardisedteachingreports,reportforthetopmanagement/

ministry,evaluationreport).Generally,inthiscasetheaddresseehastoidentifyandselecttheinformation

thatisrelevanttoher/himfromthereportonher/hisown.Oneproblematicaspectofsuchstandardreports

isthequestionoftheirsignificancewithregardtoanoverarchingpurpose.Duetothestandardisationitcan

occur, thatcertain informationneedsofanaddresseearenotreportedcorrectly.Or,dependingonwhich

informationaddresseesselectfromthereport,theycaninterpretwrongorunclearcorrelations.

Consideringtheseproblems,reportsondemandaregainingrelevanceandcansubstitutestandardreports

withregardtocertainpurposes.Reportsondemandarenotbasedonstandardiseddata,butaredesigned

Distribution ofinformation basedon reporting

Page 47: Information Management in Higher Education Institutionsduepublico.uni-duisburg-essen.de/.../M4_Information_Management... · Conseil Africain et Malgache pour l’Enseignement Supérieur

Chapter 3: Reporting: Presentation and Communication of Data and Information

46

forspecificinformationdemandsoftheaddressees.Theydonothaveapre-fixedrhythmofbeinggenerated.

Basedonadatabasethatincludesallrelevantdataforhighereducationmanagement,theaddresseescan

generatetheindividualinformationneededontheirownwithdirectaccess.Therefore,theaddresseestake

onamoreactiverole,onlyselectingsuchinformationthatisrelevanttothem(e.g.informationtobeconsid-

eredinaself-reportofaself-evaluationinteachingandlearning/research).Usingsuchreportsrequiresthe

addresseestoknowhowtousethedatabaseinordertobeabletogeneratesuchinformationrequests.

Thethirdtype,deviationreports,servestofocusonplan-actual-deviationsofmanagementissuesthatexceed

orfallbelowcertaindefinedtolerancevalues.Suchreportsareonlyusedwhennormalprocessesareinter-

ruptedbyconspicuousdeviationsordisturbancestoreachtheexpectedoutcomes(e.g.non-predictablefallin

students’enrolment).Thecontentandformatofthesereportsarenotstandardisednormally.Theaddressees

can,forexample,bedeansoffaculties,acontrollerorthetopmanagement.

3.2 Content of ReportingHowcanhighereducationinstitutionsdesignandusereportsadequatelywithregardtotheirpurposesand

withjustifiableworkload?

Figure 6 Criteria to design reports (translated illustration adapted from Tropp 2002, 70)

In the following, it is suggested that some fundamental conditions shouldbe consideredwhendesigning

reportsforinformationtransferpurposes.

Designing reports

Purpose ofReporting

Page 48: Information Management in Higher Education Institutionsduepublico.uni-duisburg-essen.de/.../M4_Information_Management... · Conseil Africain et Malgache pour l’Enseignement Supérieur

Chapter 3: Reporting: Presentation and Communication of Data and Information

47

1. Why Reporting? (purpose)

Reportsareusedtofulfilpre-definedpurposesandthereforearenotanendinthemselves.Areport´spur-

poseisdeducedfromtheinformationneedsoftherespectivetargetgroup.Hence,areportcanbeusedfor

accountabilityanddocumentationreasons,bothfrominternalaswellasexternaladdressees(Küpperetal.

2013,230).Examplesincludeprotocols,listsofapproved/not-approvedexaminationsorself-reportsofinter-

nal/externalevaluation.Furthermore,reportsserveformanagementpurposesandwithitforpreparingand

controllingdecision-makingprocesses.Forexample,basedonareportoffinancialliquidity,theseniorman-

agementcandecideaboutthedistributionorcutbacksoffinancialresourcesindifferentfieldsoftheinstitu-

tion.Besidesservingformanagementandaccountabilityreasons,reportscanreleaseworkflows.Forexam-

ple,abudgetreportofacertainunitcanentailstartingarevisionoftheexpectedtargetsandresourcestobe

neededtoachievethesetargets.Concerningprojects,reportsareespeciallyusedtomonitortheprocessing

andtherespectivelevelsoftargetachievement.

2. What to Report?

Dependingonthepurpose,wehavetodecideonwhichinformationistobereported.Isitinformationtobe

usedforaccountingpurposesthatshouldreportonthecurrentstateofacertainarea?Willtheinformation

beusedforinternal/externalcomparability?Consideringthepurposeofareport,wehavetodecideabout

thescopeandthelevelofaccuracyandaggregationofinformation,sotheycanbeusedappropriately:Isthe

informationrelevantfortherespectivepurpose?Doestheinformationgiveadequateanswerstothedesired

informationneeds?Reportsshouldonlyincludesuchinformationthatisneeded,notmoreandnotless(“as

muchasnecessary,aslittleaspossible”).Thecollecteddatashouldsignificantlyhelptoanalyseandillustrate

thelevelofdefinedobjectives.Theillustrationofquantitativedataandindicatorsshouldbecompletedwith

qualitativedescriptionsandevaluationstobecomeasexactandunderstandableaspossible.Consideringindi-

vidualcontextsaswellasrelevantcorrelationsoroverlapswithotherobjectivesatahighereducationinsti-

tutionmayhelptodesignapictureofrealitythatisasexactandundistortedaspossible.Forexample,when

wecollectdataaboutteachingcapacities,itisnotenoughtocollectdatathatreferstotheteaching-workload

leveloflecturers.Eataaboutresearchworkloadoradministrativeobligationsshouldbeconsideredaswell.In

thefollowing,thisdatacollectionshouldbeanalysedbasedonaqualitativedescription.

Atthesametimewealwayshavetokeepinmindtobalancethenecessaryworkflows(includingstaffandtime

resourcesneeded)fortheexpectedinformationprovisionandtheexpectedresultsadequately,toavoiding

graveyards.

3. How to Report? (structure / format)

Aclearstructureaswellasthewayofpublishing(e.g.onlineorpaper-based)influencetheaddresseesand

how they are using the information. For example, by using visualisations and graphic illustrations special

issuesbecomeclearerora report iseasier toread.Furthermore, reportsshouldhaveastandardisedand

repeatingstructure,whichcanbeastandardisedheadingorthesameorderofindividualandaccumulated

information.Thismeans,thereportstructureshouldbechosenaccordingtotheneedsoftheaddresseesand

thusmakingsurethepresentedinformationisreadableandunderstandabletothem.

Page 49: Information Management in Higher Education Institutionsduepublico.uni-duisburg-essen.de/.../M4_Information_Management... · Conseil Africain et Malgache pour l’Enseignement Supérieur

Chapter 3: Reporting: Presentation and Communication of Data and Information

48

4. Who Reports to Whom? (sender / addressee)

Beforewritingareport,theaddresseehastobedefinedclearlyinordertobeabletoillustratethecontent

ofthereportaccordingtotheneedsofthetargetgroup.Thatdoesnotmeanpreparinganindividualreport

foreveryaddressee.Instead,reportscanbecomposedbyusingamodulestructure.Individualmodulescan

includeadditionalinformationforspecifictargetgroupsaccordingtotheirneeds.

Furthermoretheaddresseeshouldalsoknowaboutthesenderwhoisresponsibleforthereportingprocess.

Thisisimportanttoimprovethereportedinformation´stransparency.Thesenderfinallydecideswhichinfor-

mationistransmittedhowandensuresthatthereportisunderstoodandacceptedtobeusedwithregardto

itspurposes.

5. When to Report? (reporting periods and dates)

Focussingonthetimeframe,ithastobeclarifiedwhenareporthastobefinishedandwhetheritisaone-

timeoraregularandrepeatingreporting.Thisincludesdefiningthereferenceperiodofthereport,e.g,isthe

reportbasedondatacollectedforeachsemesterorforeachstudyyear?

Basedonthis,thetimeframesforthedifferentworkflowsofdesigningthereporthavetobedetermined,as

wellasthescopeofdataandinformationthatistobecollected,analysedandtransmittedduringthisperiod.

3.3 Organisational Conditions for ReportingDuetoincreasinginternalandexternalinformationneedsathighereducationinstitutions,thecoordination

ofinformationsupplysystemsbecomesincreasinglycomplex:Composingandaggregatingdifferingdata-for-

mats,data-sourcesaswellaspaper-basedtemplatesismoredifficultandwithitalsoerror-prone.Disturbing

parametersresultinincreasinginformationgaps,andthustheyreduce(orevenprevent)expectedoutcomes

(Koch1994,71inGladen2003,240etseq.).

Todealwiththisproblem,highereducationinstitutionshavestartedtouseprofessionalIT-softwarethatinte-

gratethedifferentcorefieldsinacompletecampusmanagementsystem10 .

Nevertheless,asweallknow,evenautomaticIT-systemsdonotworkwithoutpeoplewhopushtheelectronic

buttonsandwholinktechniqueswithhumanworkflowsandcommunicationflows.

Thisisthemomentwhenqualitymanagerscanplayanimportantroleagainbyhelpingtohandletheafore-

mentionedobstaclesofcomplexinformationsystems.Theycanfindoutaboutexistinginformationor/and

communicationdeficits.Togetherwiththerespectiveinvolvedpartiestheycandiscusshowtosolvethese

deficits.Ifnecessary,theycanalsocommunicatethesepossibilitiesandtheiraccompanyingadvantagesand

disadvantagestotherespectiveauthoritiestotakedecisions.

10 The EuropeanUniversity Information Systems (EUNIS) organisation offers an online platform for institutions to develop their IT landscapebysharingexperiencesandworkingtogether.http://www.eunis.org/

Implementing reporting systems

Page 50: Information Management in Higher Education Institutionsduepublico.uni-duisburg-essen.de/.../M4_Information_Management... · Conseil Africain et Malgache pour l’Enseignement Supérieur

Chapter 3: Reporting: Presentation and Communication of Data and Information

49

Thefollowinglistsummarisesfrequentshortcomingswhendesigningreports(basedonGleich,Horváth&

Michel2008,38)

Nosufficientorientationtowardtheaddressee(“Idon’thavetheinformationIneedtomanagethebusiness

effectively”(Axson2007,131inHorváth2008,36).

Reportsarebasedonavailabledataandinformation,butnotontheinformationneeded:Transferofnon-pur

posefulinformation.

Orientationonarigidandinflexibletimefrequency

One-sidedorientationonaccountingquantitativedata

Noclearlydefinedperiodofreference:Datacollectionreferstodifferingperiods/dates.

Competitionbetweenperiodoftime,levelofaggregationandscopeofdata:Ontheonehandtoomuch

unnecessaryandunclearinformationcanbetransferred.Ontheotherhandtoogeneralinformationcan

reducesignificanceaswell.

Misunderstandingsduetounclearlydefinedterminologiesandmissingqualitativeanalysesofthedata

material.Inthefollowing,theaddresseemightdevelopwronginterpretations.

Dataisoldandnotup-to-date.Thelessup-to-datethedata,themoredifficulttoguaranteeaccuracy.

Toreducesuchshortcomingswhenimplementingareportingsystem,someessentialcriteriashouldbecon-

sidered(Horváth2008):

1. Avoiding double data collections:Whencollectingandanalysingdataforreportingpurposesyoushould

makesurethattheyarecollectedonlyoncefromasinglesourceandmayinthefollowingbeusedfordif-

ferentpurposes.Forexample,veryoftenweneedthesamedataforinternalandexternalqualityassurance

purposesathighereducationinstitutions.Thatmeans,weusedata,collectedfromthesamedatasource

andonlyaggregateandcombineitaccordingtotherespectivepurposesandneeds.

2. Efficiency:Thecoordinationbetweennewdatademandsandalreadyexistingdatasourcesshouldbeeffi-

cient.Basicdataforspecificfieldscanbeprovidedtogiveanoverviewfor interestedstakeholders,e.g.

bypublishing themona (internal)website.Anothermoreelaboratedformofusingdataefficientlyare

so-called“data-warehouse-systems”,whichhavebecomeofincreasinginterestforhighereducationinsti-

tutions.Suchacentralonline-toolisabletointegratedifferentdatasetswithdifferentpossibilitiesofdata

retrieval,andwithitfacilitatesdiversesynergyeffectsathighereducationinstitutions.Usingsuchatool,

addresseesareabletogeneratemoreexactlytheinformationtheyneed.Nevertheless,itistobeconsid-

eredthatthereexistdataprotectionregulationsincludingspecificaccessrights–beitforinternalorexter-

naluseofspecificdataorinformation.

3. Comparability of data:Toachieveapurposefulandreasonableuseofdata,itisimportanttocomposethemin

astructured,clearandtransparentway.Thismeansthatyoushouldcoordinatestandardiseddefinitions,ter-

minologiesanddatacollectionprocedures.Thisisafundamentalrequirementforenablinginternal/external

comparisons(e.g.rankingorbenchmarkingofhighereducationinstitutions,(internal)facultiesorprogrammes).

Shortcomings inreporting

Page 51: Information Management in Higher Education Institutionsduepublico.uni-duisburg-essen.de/.../M4_Information_Management... · Conseil Africain et Malgache pour l’Enseignement Supérieur

Chapter 3: Reporting: Presentation and Communication of Data and Information

50

4. Reliability, validity and consistency: Followingthecriteriaofcomparability,youshouldalsocoordinate

ratherstandardisedmethodologicalproceduresofdatacollectiontopreventidenticaldatasamplesfrom

differingreferenceperiodsleadingtodifferingresultsandcreatingirritationsorequivocations.Tocontrol

datavalidity,theyshouldnotbeillustratedinisolationbutincombinationwithothercomparablevalues,

e.g.byindicatingabsolute,relativeoraccumulateddata.

5. Timeliness of data:Aprompt reportingona certain issue increases the significanceofdataand infor-

mation.Still,youshoulddifferentiatebetween“intermediatedatainrealtime”or“outcomedata”tobe

usedforspecificdefinedindicatorsandperiods.Informationthatisneededregularlyshouldbecollected

andprovidedperiodically.Tobeabletodosoandtomeetpredeterminedreportingperiodsrequiresthat

(internal)providersofdatatobeontimeaswell(e.g.submissionofassessmentresultsintoasystem).

6. Transparency:Toensuretransparencyandresponsibilitiesithastobeclear,whohasworkedonwhichdata

fromwhichdatasource.

Recommendations on How to Proceed When Designing Reports

(basedonastudyoftheCHEofthereportingsysteminSaxony-Anhalt,afederalstateinGermany:

Yorck,H.,Güttner,A.,&Müller,U.(2010)).

1. Coordinationbetweentheaddresseeandthesenderwithregardtothereportingstructureandits

elements.

2. Theinformationsystemforinternalprocessesatahighereducationinstitutionsshouldbethebasis

andfacilitatedecisionsonexternalreporting.Thismeansexternalreportsshouldbelinkedtoand

basedoninternalhighereducationmanagerialaccounting.

3. The content analyses in reports should be oriented on the objectives and thus outcome-/out-

put-based.

4. Data, indicators or parameters should be defined according to fixed and comparable stand-

ards.

5. Thereportingformatofinformationshouldincludethecollectedquantitativedata,comprisingof

somedescriptivequalitativetextwithvisualisations,tablesorotherillustrations.

6. Developmentof adata-pool for internal/externalpurposes (data-warehouse) tobeable todeal

withtheincreasingcomplexityofdatasourcesanddataformats.

7. Adhoc reports should only be based on data and information from internal data-sources.

8. Reportsforexternaluseshouldrefertoconcreteaddressees,andshouldbedesignedbasedona

modularstructurethatcanbeadjustedaccordingtotherespectiveinformationneeds.

Page 52: Information Management in Higher Education Institutionsduepublico.uni-duisburg-essen.de/.../M4_Information_Management... · Conseil Africain et Malgache pour l’Enseignement Supérieur

Chapter 3: Reporting: Presentation and Communication of Data and Information

51

9. Informationpyramid: Starting from internal reports fordecision-makingprocesses andmanage-

mentofthehighereducationinstitutions,theirlevelofdetaildecreaseswhenitcomestoamore

abstractpublicuse.

10.Theentirescopeofareportshouldbeshortandreadable(notmorethan20pages,ifpossible).

11.Coordinationofaregularreporting(e.g.forexternalpurposesannualreportingwithdatacollec-

tiononapredetermineddate).

12.Annualreportsrefertothepreviousyearandshouldincludeperspectivesonthefollowingyear.

13.Structuringareport:Clearseparationbetweenoverviewanddetaileddescriptions.Generalstruc-

ture according to compulsory requirements to be supplementedwith amore detailed outline

accordingtothespecificneedsofahighereducationinstitution(e.g.firstsummarisinginformation,

thandescriptionofparticularissuesanddetailedadditionalinformation).Anexample:

a. Executivesummary

b. Teaching,learningandfurthereducation

c. Researchandyoungscientists

d. Cooperationandknowledgetransfer

e. Qualityenhancementinteaching,researchandservices

f. Highereducationstrategicandfinancialplanning

14.Developingastandardisedsetofindicators(consideringregionalcompulsoryindicatorsystems)

a. Guaranteeingcomparability

b. Relevance-basedselection

c. Possibilityforindividualhighereducationinstitution-basedinterpretations

d. Describinghighereducationperformancesaccordingtotheirrespectivedimensions,e.g.

i. Research,teaching,services

ii. Monetaryvs.non-monetaryindicators

iii. Finances,processes,potentials,compatibility

Further Reading

The Commission on Institutions of Higher Education (CIHE) in New England has defined different

reportingguidelines:

CommisiononInstitutionsofHigherEducationNewEngland(CIHE).Reporting Guidelines.Retrieved

onJanuary25,2015,fromhttps://cihe.neasc.org/institutional-reports-resources/reporting-guide-

lines

Page 53: Information Management in Higher Education Institutionsduepublico.uni-duisburg-essen.de/.../M4_Information_Management... · Conseil Africain et Malgache pour l’Enseignement Supérieur

Chapter 4: Elaborated Information Systems – Examples for Data Sharing

52

4 ElaboratedInformationSystems– ExamplesforDataSharing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53

4.1 CaseStudyoftheETHZurich:AnnualAcademicAchievementsReporting . . . . 53

4.2 CaseStudyoftheUniversityofVienna:CourseControlling . . . . . . . . . . . . . . . . 55

4.3 Unidata–FactsandFiguresatthePushofaButton–ACaseStudyfromAustria 56

differentiateapproachesofusingdataathighereducationinstitutionsappropriately,

deduceappropriateareasandmechanismstostartwithwhendevelopinginformationmanagement

systemsatyourownhighereducationinstitution.

On successful completion of this chapter, you should be able to…

Chapter 4

Elaborated Information Systems – Examples for Data Sharing

Page 54: Information Management in Higher Education Institutionsduepublico.uni-duisburg-essen.de/.../M4_Information_Management... · Conseil Africain et Malgache pour l’Enseignement Supérieur

Chapter 4: Elaborated Information Systems – Examples for Data Sharing

53

4 Elaborated Information Systems – Examples for Data Sharing

4.1 Case Study of the ETH Zurich: Annual Academic Achievements Reporting

ThereportingsystemoftheETHZurich,theso-called“AnnualAcademicAchievements”(AAA)isanaca-

demicreportingofprofessors,facultiesandstudyprogrammes.Thereportsincludeinformationonthe

corefieldsofteaching,researchandservices.Theobjectivesrefertothreeessentialconcerns:

1. Collectionofmanagement informationbasedondecision-relevantdataandsignificantperformance

indicatorsforthefieldsofteaching,researchandservices,whichtheseniormanagementneedstofulfil

theirtasks.

2. Thereportsserveasacademicperformancecertificatesoftheprofessors.Theycompletetheregular

facultyevaluationsandsupportthedialoguewiththeseniormanagement.

3. Reportingtoexternalthird-parties(e.g.ETH-board,ministry).

Byusingthesamedatasetsforthesethreeconcerns,theETHtriestoreducedataandinformationasym-

metries.

TheAAAreportingsystemisdesignedasanelectroniconlineportal.Itcanbeunderstoodasabigpoolthat

importsandillustratesdatafromdifferentsystems,suchasthefollowing:

Teachingdatabase(lectures,assessments,completedBA/MAtheses,completeddoctoraltheses)

SAPR/3(stockforfinancialexpendituresandactivitiesoutsidetheuniversity)

Researchdatabase(researchprojects)

E-Citations(publications)

Hermes–database(patents,licences)

Databaseoftheorganisation(internalcommissions,functions)

Page 55: Information Management in Higher Education Institutionsduepublico.uni-duisburg-essen.de/.../M4_Information_Management... · Conseil Africain et Malgache pour l’Enseignement Supérieur

Chapter 4: Elaborated Information Systems – Examples for Data Sharing

54

Figure 7 Import and illustration of data from different data base systems at the ETH Zurich (ETH Zürich 2013)

TheinformationgatheredfromthesedatabasesistransferredautomaticallyintotheAAAportal,i.e.,they

donothavetobedouble-entered.Furthermore,insomefields,datathatwasenteredinapreviousyearis

transferredtothefollowingyearaswell.Thismeansusersonlyhavetoaddchangesmanually,ifapplicable.

Besidescollectingquantitativedata,usershavethepossibilityofaddingadditionalqualitativereportsthat

describetheiractivitiesinmoredetail(e.g.selectedpresentations,organisationofaconferenceetc.).

TheAAAportal isonly accessible from the internal ETHnetwork.Onlyheadsofunits that are subject to

reportshaveaccess.They,inturn,havethepossibilitytodelegatetheiraccessrightstofurtherstaffbyselect-

ingtheindividualnecessaryaccessrightsfromtheportal-menu.

Page 56: Information Management in Higher Education Institutionsduepublico.uni-duisburg-essen.de/.../M4_Information_Management... · Conseil Africain et Malgache pour l’Enseignement Supérieur

Chapter 4: Elaborated Information Systems – Examples for Data Sharing

55

4.2 Case Study of the University of Vienna: Course Controlling

AttheUniversityofViennateachingplanningisorganisedbyfocussingonthe(required)teachingload.The

teachingloadisdifferentiatedintothecategoriesinternalteaching,externalteachingandnon-paidteaching

andtutorials.Asquantitativenumericalvaluetheyexaminetheweightedteachingload.Dependingonthe

groupofpersonsandtherespectivepublicserviceslaw,theyusedifferentwages-codes.Theweightingfactors

helptoreduceresultingbias.

Thereportforteachingplanningisdesignedbythedepartmentoffinancesandmanagerialaccounting.They

providefourdifferenttypesofreportsfordifferentpurposes:

1. Overviewonactualteaching-performancewithcomparisonoftheprecedingyear(general/detailedsur-

vey),

2. Overviewonplan-actual-teaching-performanceattheendofthestudyyear,

3. Overviewonplan-actual-teaching-performanceduringastudyyear(general/detailedsurvey),

4. Overviewonactual-teaching-performanceonfacultylevel(includingteachingimport;general/detailed

overview).

Thefirstreportdeliversageneralsurveyofthedistributionofteachingload,differentiatedintodifferentstaff

categoriesduringastudyyear,includingacomparisontothepreviousstudyyear.

Thethirdreportdeliversanoverviewontheachievedteaching-performancelevelatadefineddateduringa

studyyear.Ithelpstoevaluatewhethertheteachingloadhasbeen/willbeaccomplished.

Thefourthreportisespeciallyusedforthesemesterplanningofafaculty,focussingonthedistributionand

theaccomplishmentofteachingload.

Thesecondreportfocusesontheplan-actual-comparisonofteaching-performanceattheendofastudyyear

andisusedasabasisfortarget-performance-agreementsinteachingbetweenseniormanagementandfac-

ulties.Therefore,theteachingload(inhours)isdefinedforthedifferentteachingcategories,asmentioned

intheillustrationbelow(internal/externalteaching,non-paidteaching,andtutorials).Inthefollowing,the

departmentoffinancesandmanagerialaccountingmatchtheagreedteachingloadresultsfortheteaching

categoriestotheteachingstaffavailable(professors,associateprofessors,academicassociates,tutorsetc.),

bygatheringthisinformationintheplan-actual-reports.Toachieveplanningvaluesfortheteachingloadthat

considerstheactualconditionsofcoordinatingthestudyprogrammes,theuniversityhasaninternalsetof

criteriawhichenablesrequiredshiftsbetweentheplannedvaluesofthedifferentteachingcategories(e.g.

whenlecturesofaprofessorhavetobecancelledduetoaresearchsemester).Suchshiftingproceduresare

usuallyalreadydiscussedbetweenthestudyprogrammecoordinatorandthedepartmentoffinancesand

managerialaccountingbeforehavingthetarget-performancetalksinordertochecktheshiftingpossibilities.

Page 57: Information Management in Higher Education Institutionsduepublico.uni-duisburg-essen.de/.../M4_Information_Management... · Conseil Africain et Malgache pour l’Enseignement Supérieur

Chapter 4: Elaborated Information Systems – Examples for Data Sharing

56

.

Table 4 Report for teaching planning at the University of Vienna (adapted from the course controlling of the University of Vienna)

4.3 Unidata – Facts and Figures at the Push of a Button – A Case Study from Austria

Unidata isthestatisticalhighereducationinformationsystemoftheFederalMinistryofScience,Research

andEconomy(MSRE)inAustria.Themainpurposeofthisreportingsystemistoproviderecentdataandfacts

abouttheAustrianhighereducationsystem.Unidataisaninternetportalthataddressesstudents,research-

ers, education experts, employers, and especially higher educationmanagers and decision-makers of the

MSRE.11

Dependingontheaccessrights,theportalgivescontinuousaccesstostatisticalinformationinfieldssuchas

budget,students,graduates,staffandfacilitymanagement,aswellasindicatorsforteachingandresearchof

universitiesanduniversitiesforappliedsciences.Furthermore,Unidatacomprisesacentralcollectionofpub-

licationsoftheMSREandhighereducationreporting.Thestatisticaldatacanberetrievedasdynamicstand-

ardreports,includingthepossibilitytoreducethemondetailedparameters.

11 MoreinformationonUnidatacanbefoundontheirwebsite:https://oravm13.noc-science.at/apex/f?p=103:36:0::NO

Page 58: Information Management in Higher Education Institutionsduepublico.uni-duisburg-essen.de/.../M4_Information_Management... · Conseil Africain et Malgache pour l’Enseignement Supérieur

Chapter 4: Elaborated Information Systems – Examples for Data Sharing

57

Thisdatapool includesaquantitativedocumentationofallhighereducationperformancesinthefieldsof

teaching,researchandservices.Therefore,ithelpstoprovidetransparentpossibilitiesofcomparinguniver-

sitiesordifferentdisciplinesinAustriatomonitorhighereducationtargetfields(e.g.gender,Bolognamon-

itoring).Furthermore,Unidata isavalidfundamentforevidence-baseddecision-makingprocessesandfor

deducingmanagementinformationandprogramme-initiativestoberealisedinthehighereducationarea.

Thepurposesofunidatarefertothefollowingkeyaspects(seeunidatawebsite)

FactsandfiguresabouttheAustrianhighereducationsector,

permanentaccessforrecentquantitativedataandqualitativeanalyses,

collectionofrelevantreportsandpublications,

freeinformationplatformforallinterestedusers,

decision-makinginstrumentfortarget-performance-agreements,aswellasmonitoringofquantitative

aspectsforperformance-agreementsandotherhighereducationtargetfields(BolognaProcess,gender

monitoringetc.),

implementationofaworkingplatformformutualdata-clearingbetweenhighereducationinstitutions

andtheministry.

Unidata,anditscentralisationoftheindividualinformationsystemsofAustrianhighereducationinstitutions

andtheministryhasinitiatedanddevelopedprocessesthatareessentialinhelpingincreasedataqualityin

highereducationstatistics.Forexample,datasourcesoftheministryandthehighereducationinstitutions

arenowsynchronisedviaanelectronicplatform.Before,thisprocessofdata-synchronisationwasregulated

bylaw.Thegainedstandardiseddatasetsshallcontributetoachievingmoreliabilityandreduceoutput-asym-

metriesbetweenhighereducationinstitutionsandtheministry.

Questions & Assignments

1.Pleasenameanddescribeaprocessinthefieldofteaching,researchorservicesatyourHEIthat

hasasystemisedinformationprocessing.Whichinformationiscollected,whatfor,bywhomand

inwhatperiod?Arethereanyinformationgapsthatyoucanobserveinthisinformationprocess?

Ifso,whatareyoudoingatyourHEItoclosesuchgaps?Areyou,asqualitymanager,involvedin

theseprocesses?

Page 59: Information Management in Higher Education Institutionsduepublico.uni-duisburg-essen.de/.../M4_Information_Management... · Conseil Africain et Malgache pour l’Enseignement Supérieur

References

Alter, S. (1996). Information systems. A management perspective (2nd edition). Menlo Park: Benjamin

Cummings Pub. Co.

Axson, D.A. (2007). Best practices in planning and performance management (2nd edition). Hoboken, NJ: John

Wiley & Sons.

Balasubramanian, K. (2009). ICTs for higher education. Background paper from the commonwealth of learning.

Paris: UNESCO; World Conference on Higher Education; Commonwealth of Learning.

Babbie, E. R. (2004). The practice of social research (10th edition). Southbank: Wadsworth.

Barrie, S. & Ginns, P. (2007). The linking of national teaching performance indicators to improvements in

teaching and learning in classrooms. Quality in Higher Education, 13(3), 205-286.

Beitz, A., Dharmawardena, K. & Sam Searle, S. (2012). Monash university research data management strategy

and strategic plan 2012 – 2015. Melbourne: Monash University.

Blohm, H. (1974). Organisation, Verwaltung und Arbeitswissenschaft. Die Gestaltung des betrieblichen

Berichtswesens als Problem der Leitungsorganisation (2nd revised edition). Herne: Verlag Neue

Wirtschafts-Briefe.

Boston University (2015). What is “research data”? Retrieved from http://www.bu.edu/datamanagement/

background/whatisdata/

Bundesministerium für Wissenschaft, Forschung und Wirtschaft Österreich (Ed.) (2015). Datawarehouse

Hochschulbereich. Unidata - Zahlen und Fakten auf Knopfdruck. Retrieved from https://oravm13.

noc-science.at/apex/f?p=103:36:::NO:::

Chalmers, D. (2008). Teaching and learning quality indicators in australian universities. Outcomes of higher

education: Quality relevance and impact. Paris: Programme on Institutional Management in Higher

Education.

Commision on Institutions of Higher Education New England (CIHE) (2015). Reporting guidelines. Retrieved

from https://cihe.neasc.org/institutional-reports-resources/reporting-guidelines

Data Warehousing and Business Intelligence Organization (2014). Classifying data for successful modeling.

Retrieved from http://dwbi.org/data-modelling/dimensional-model/16-classifying-data-for-

successful-modeling

Demski, J. (1980). Information analysis (2nd edition). New York: Addison-Wesley.

Demski, J. (2008). Managerial uses of accounting information (2nd edition). New York: Springer-Verlag.

ETH Zürich (2013). ETHIS-Schulung Annual Academic Achievements (AAA). Akademische Berichterstattung

der Professuren, Departemente und Studiengänge. Retrieved from https://www1.ethz.ch/sap/

applications/aaa/Folien

European University Information Systems (EUNIS). Retrieved from http://www.eunis.org/

Frese, E. (Ed.) (1992). Handwörterbuch der Organisation (3rd revised edition). Band 2 der Enzyklopädie der

Betriebswirtschaftslehre. Stuttgart: Schäffer-Poeschel Verlag.

Gladen, W. (2003). Kennzahlen- und Berichtssysteme. Grundlagen zum Performance Measurement (2nd

revised edition). Wiesbaden: Gabler.

References

58

Page 60: Information Management in Higher Education Institutionsduepublico.uni-duisburg-essen.de/.../M4_Information_Management... · Conseil Africain et Malgache pour l’Enseignement Supérieur

References

Gladen, W. (2011). Performance Measurement. Controlling mit Kennzahlen (5th revised edition). Wiesbaden:

Gabler Verlag / Springer Fachmedien Wiesbaden GmbH.

Gleich, R., Horváth, P. & Michel, U. (Ed.) (2008). Management Reporting: Grundlagen, Praxis und Perspektiven.

München: Rudolf Haufe Verlag.

Göpfert, I. (2007). Berichtswesen. In Küpper, H.-U. & Wagenhofer, A. (Ed.), EdBWL. Handwörterbuch

Unternehmensrechnung und Controlling. Stuttgart: Schäffer-Poeschel Verlag, 143–156.

Grochla, E. & Thom, N. (Ed.) (1980). Handwörterbuch der Organisation (2nd revised edition). Band 2 der

Enzyklopädie der Betriebswirtschaftslehre. Stuttgart: Schäffer-Poeschel Verlag.

Harvey, L. (2004-14). Analytic quality glossary. Resarch quality international. Retrieved from http://www.

qualityresearchinternational.com/glossary/performanceindicators.htm

Higher Education Funding Council for England (HEFCE) (2011). Performance indicators in higher education.

First report of the performance indicators steering group (PISG). London: HEFCE.

Horváth, P. (2008). Grundlagen des Management Reportings. In Gleich, R., Horváth, P. & Michel, U. (Ed.),

Management Reporting: Grundlagen, Praxis und Perspektiven. München: Rudolf Haufe Verlag, 15–

42.

Hórvath, P. (2011). Controlling (12th edition). München: Vahlen.

Horváth, P. & Michel, U. (Ed.) (2013). Controlling integriert und global. Erfolgreiche Steuerung von komplexen

Organisationen. Stuttgart: Schäffer-Poeschel Verlag.

Kaplan, R.S. (2011). Strategic performance measurement and management in Nonprofit Organizations.

Nonprofit Management & Leadership, 11(3), 353–370.

Kaplan, R.S. & Norton, D.P. (1993). Putting the balanced scorecard to work. Harvard Business Review, 71(5),

134-147.

Kaplan, R.S. & Norton, D.P. (1996). Using the balanced scorecard as a strategic management system. Harvard

Business Review, 74(1), 75-85.

Kimball, R. & Ross, M. (2002). The data warehouse toolkit. The complete guide to dimensional modeling (2nd

edition). New York: Wiley.

Koch, R. (1994). Betriebliches Berichtswesen als Informations- und Steuerungsinstrument. Frankfurt a.M.

[u.a.]: Verlag Peter Lang.

Koreimann, D.S. (1976): Methoden der Informationsbedarfsanalyse. Berlin, New York: De Gruyter.

Küpper, H.-U. (1997). Das Führungssystem als Ansatzpunkt für eine wettbewerbsorientierte Strukturreform

von Universitäten. Beiträge zur Hochschulforschung, 19(2), 123–149.

Küpper, H.-U. (2001). Rechnungslegung von Hochschulen. Betriebswirtschaftliche Forschung und Praxis, 53(6),

578–592.

Küpper, H.-U., Friedl, G., Hofmann, C., Hofmann, Y. & Pedell, B. (2013): Controlling. Konzeption, Aufgaben,

Instrumente (6th edition). Stuttgart: Schäffer-Poeschel Verlag.

Noé, M. (2010). Vom Qualitätsmanager zum internen Managementberater. Die neuen Anforderungen

souverän meistern. München: Hanser.

59

Page 61: Information Management in Higher Education Institutionsduepublico.uni-duisburg-essen.de/.../M4_Information_Management... · Conseil Africain et Malgache pour l’Enseignement Supérieur

References

Nusselein, M.A. (2002). Empirische Erkenntnisse einer Informationsbedarfsanalyse an bayerischen

Hochschulen. Beiträge zur Hochschulforschung, 24(1), 100-114.

Nusselein, M.A. (2003). Inhaltliche Gestaltung eines Data Warehouse-Systems am Beispiel einer Hochschule.

München: Bayerisches Staatsinstitut für Hochschulforschung und Hochschulplanung.

Organisation for Economic Co-operation and Development (2003). Education policy analysis - 2003 edition.

Paris: OECD.

Röbken, H. (2003). Balanced Scorecard als Instrument der Hochschulentwicklung. Projektergebnisse an der

Reykjavik University. Beiträge zur Hochschulforschung, 25(1), 102-120.

Saupe, J.L. (1981). The functions of institutional research. Tallahassee: Association for Institutional Research.

Schenker-Wicki, A. (1999). Moderne Prüfverfahren für komplexe Probleme. Evaluation und Performance-

Audits im Vergleich. Wiesbaden: Deutscher Universitätsverlag/Springer Fachmedien Wiesbaden.

Scheytt, T. (2007). Strategieorientiertes Performance Management in Hochschulen: Das Konzept der Balanced

Scorecard. Hochschulmanagement, 2007(1), 15–21.

Taylor, J. (2014). Informing or distracting? Guiding or driving? The use of performance indicators in higher

education. In Menon, M., Terkla, D., Gibbs, P. (Ed.), Using data to improve higher education. Research,

policy and practice. Rotterdam: Sense Publishers.

Tropp, G. (2002). Kennzahlensysteme des Hochschul-Controlling. Fundierung, Systematisierung, Anwendung.

München: Bayerisches Staatsinst. für Hochschulforschung u. Hochschulplanung.

Varghese, N.V. (2004): Incentives and institutional changes in higher education. Higher Education Management

and Policy, 16(4), 27–39.

Volkwein, J.F. (1999). What is institutional research all about? A critical and comprehensive assessment of the

profession. San Francisco: Jossey-Bass ( J-B IR Single Issue Institutional Research, Book 41).

Weilenmann, G. & Scheitlin, V. (1972): Informationstechnik für Führungskräfte. Moderne Information u.

Kommunikation in d. Unternehmung. Stuttgart: Schäffer-Poeschel Verlag.

Wittmann, W. (1980). Information. In Grochla, E. & Thom, N. (Ed.), Handwörterbuch der Organisation (2nd

revised edition). Band 2 der Enzyklopädie der Betriebswirtschaftslehre. Stuttgart: Schäffer-Poeschel

Verlag.

Yorck, H., Güttner, A., & Müller, U. (2010). Berichterstattung für Politik und Staat von Hochschulen im Land

Sachsen-Anhalt. Wittenberg: Wissenschaftszentrum Sachsen-Anhalt.

60

Page 62: Information Management in Higher Education Institutionsduepublico.uni-duisburg-essen.de/.../M4_Information_Management... · Conseil Africain et Malgache pour l’Enseignement Supérieur

61

Page 63: Information Management in Higher Education Institutionsduepublico.uni-duisburg-essen.de/.../M4_Information_Management... · Conseil Africain et Malgache pour l’Enseignement Supérieur

List of Tables

Table 1 Information sources and requirements from different stakeholders (adapted from Nusselein 2002). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19

Table 2 Criteria of success for data collection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25

Table 3 Challenges of (performance) indicators . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42

Table 4 Report for teaching planning at the University of Vienna (adapted from the course controlling of the University of Vienna) . . . . . . . . . 56

List of Tables

62

Page 64: Information Management in Higher Education Institutionsduepublico.uni-duisburg-essen.de/.../M4_Information_Management... · Conseil Africain et Malgache pour l’Enseignement Supérieur

List of Figures

Figure 1 Layer model for higher education institutions (Tropp 2002, 2) . . . . . . . . . . . 15

Figure 2 Gathering information based on needs, supply and demand (translated based on Picot & Frank 1988, 608 in Hórvath 2011, 311) . . . . . . . 18

Figure 3 Based on the project “Computer-based management tool for the institutions of higher education in Bavaria” (CEUS) (Nusselein 2002, 4) . . . . . . . . . . . . . . . 21

Figure 4 Types of interferences during the process of information distribution (adapted from Küpper et al. 2013, 241) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26

Figure 5 System of a Balanced Scorecard (adapted from Scheytt 2007) . . . . . . . . . . . . 38

Figure 6 Criteria to design reports (translated illustration adapted from Tropp 2002, 70) . . . . . . . . . . . . . . . . . . . 46

Figure 7 Import and illustration of data from different data base systems at the ETH Zurich (ETH Zürich 2013) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54

List of Figures

63

Page 65: Information Management in Higher Education Institutionsduepublico.uni-duisburg-essen.de/.../M4_Information_Management... · Conseil Africain et Malgache pour l’Enseignement Supérieur

With financial support from the Supported by