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A multi-objective method to align human resource allocation with university strategy

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A multi-objective method to align human resource allocation with university strategy
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  Full Terms & Conditions of access and use can be found athttp://www.tandfonline.com/action/journalInformation?journalCode=tpsp20 Download by:  [Archives & Bibliothèques de l'ULB] Date:  11 November 2015, At: 22:55 Perspectives: Policy and Practice in Higher Education ISSN: 1360-3108 (Print) 1460-7018 (Online) Journal homepage: http://www.tandfonline.com/loi/tpsp20 A multi-objective method to align human resourceallocation with university strategy Philippe Bouillard To cite this article:  Philippe Bouillard (2015): A multi-objective method to align humanresource allocation with university strategy, Perspectives: Policy and Practice in HigherEducation, DOI: 10.1080/13603108.2015.1081303 To link to this article: http://dx.doi.org/10.1080/13603108.2015.1081303 Published online: 21 Oct 2015.Submit your article to this journal Article views: 11View related articles View Crossmark data  perspective A multi-objective method to alignhuman resource allocation withuniversity strategy Philippe Bouillard  a,b a  School of Engineering, Nazarbayev University, Kabanbay batyr Ave., 53 Astana, 010000, Kazakhstan and   b  BATir dept., Universite ´  Libre de Bruxelles (U.L.B.), F. D. Roosevelt Av., 50, CP 194/2–1050,Brussels, Belgium  Universities are currently under considerable pressure to reach their stakeholders’ expectations. Man-agement tools that use strategic plans, key performance indicators and quality assurance methods areincreasingly deployed. This paper aims to demonstrate how resource allocation can be aligned withinstitutional strategic plans with a very simple multi-objective optimisation method. The method hasbeen tested and successfully implemented at the Universite´ Libre de Bruxelles. It has been designedfor a certain specific context (public university with human resources managed at the institutionallevel) but could be easily adapted for other contexts. Keywords:  university management; resource allocation; strategy; multi-objective method; multi-criteriamethod Introduction Higher education institutions face a very challenging,and constantly changing, environment (Kezar andEckel 2004). Simultaneously, the budgets of many uni-versities are under significant pressure, characterised bydecreasingpublicfundingalongsidegrowingstakeholder expectations, particularly in terms of accountability andefficiency. New management tools have therefore beenadopted by most universities: for example, managementcharts monitoring, strategic planning, quality manage-ment systems, international policies, etc (Agasiti, Arna-boldi, and Azzone 2008, Barr  2009, Sporn 2001). Most of the time, such tools have been developed andimplemented independently. They have rarely been Philippe Bouillard  holds an MSc in civil engineering(Universite´ Libre de Bruxelles ULB, Belgium, 1990), aPhD in Engineering (ULB, 1997) and Hab. (Paris VI,France, 2004). He began his career as a workmanager for major French contractors, before startingan academic career by a teaching and researchassistant position at the Ecole Polytechnique deBruxelles (ULB). He was promoted full professor in2005. Philippe Bouillard has occupied many senior management positions at ULB from Head of Department of Civil Engineering to Pro Vice-Chancellor for Academic Affairs. During a sabbaticalleave, he was Vice-Dean for Teaching and Learning for theSchool of Engineering atNazarbayev University (2014–2015). He developed anexpertise in Quality Assuranceand Bologna process and isacting as an expert for many agencies. His mainresearch activity was computational structuralmechanics but he recently redirected his researchinterest towards sustainable urban planning. He hasco-edited 3 books, is co-author of 53 refereed journalpapers, 6 chapters of books and more than 100conference proceedings. He supervised several PhDtheses (18) and research projects. He is a member of the editorial board of the ‘European Journal of Computational Mechanics’. He received the BelgianNational Science Foundation (FNRS) De Waele Awardin 2000 and the Wernaers Award in 2012 for his effortto scientific dissemination towards a large public. Onteaching point of view, Philippe Bouillard is deeplyinvolved in the active learning student-centred learningreforms and he received the ULB Socrates Teaching Award (2008). Address for correspondence: BATir dept., Universite´ Libre de Bruxelles (U.L.B.), F. D.Roosevelt Av., 50, CP 194/2–050 Brussels, Belgium.Email: philippe.bouillard@ulb.ac.be # 2015 Taylor & Francis PERSPECTIVES: POLICY AND PRACTICE IN HIGHER EDUCATION, 2015http://dx.doi.org/10.1080/13603108.2015.1081303 1    D  o  w  n   l  o  a   d  e   d   b  y   [   A  r  c   h   i  v  e  s   &    B   i   b   l   i  o   t   h   è  q  u  e  s   d  e   l   '   U   L   B   ]  a   t   2   2  :   5   5   1   1   N  o  v  e  m   b  e  r   2   0   1   5  integrated into a comprehensive management toolallowing senior managers to take fast and efficient bud-getary decisions.As human resources are, in every university, thelargest expenditure category (Stewart 1996), thispaper will focus on how to align (human) resourcesallocation and university strategy.Interest in the resource allocation system in univer-sities is not new (Ball 1980, Gonza Lopez 2006, Santos 2007). In a very early analysis, Clark (1983) pro- posed to classify the higher education systems into twocategories: ‘market-oriented systems’ where a largeproportion of funding comes from private sourcesand ‘state-oriented system’ where the funding islargely public and governance is mostly driven by gov-ernmental directives. In ‘market-oriented systems’ theresource allocation has been linked to performanceaffecting directly individual faculty members (Liefner 2003). In ‘state-oriented system’, there was a huge ten-dency to be less responsive to changes in demand andmore conservative in terms of organisations and struc-tures (Liefner  2003). The use of performance indicatorsto drive the resource allocation in such systems appearsonly recently (Caballero et al. 2001, 2004) and clearly depends on institutional autonomy and fundingsources (Casper and Henry 2001). However, a veryrecent study undertaken by the European UniversityAssociation (Claeys-Kulik and Estermann 2015)shows that many governments have now introduced,to a certain extent, a link between public funding andinstitutional performance. Even if this report demon-strates the limitation of such approaches, funding meth-odologies that incorporate performance outcomes arebound to impact significantly on university strategies.In state-oriented systems, without any performanceindicators, resource allocation is usually very stable,and incremental changes will only occur when facultymembers retire or resign (Liefner  2003). This canresult in huge discrepancies between institutionalneed and resources allocated. This was characteristicof Universite´ Libre de Bruxelles (ULB), our case-study institution, in 2006 when the idea to introducea performance-based approach emerged. In thispaper, we describe a resource allocation method thatis aligned with university strategy and uses a simplemulti-objective or multi-criteria optimisation methodbased on performance indicators whilst taking sourcesof income into account (Mustafa and Goh 1996,Datta, Fonseca, and Deb 2008). The advantage of themethod is clearly to make the decisions transparentand to allow the Schools first and individual facultynext, to understand university strategy and what isexpected from them. Based on a merit system wherethe Schools best aligned to the university strategy willbe rewarded, the system has the advantage of equity(same rule applied to all Schools) and transparency(simple function of the performance indicators). Ithas already been reported that such alignment, byincentivising behaviours that contribute to the achieve-ment of strategic targets, results in an improved effi-ciency (Dunworth and Cook 1976; Tangian 2004). It also allows Schools to reflect institutional policy (withflexibility to vary the extent) and to develop their local strategies and resource allocation methods(Wood 1990).This method has been applied in the context of anautonomous university, mostly publicly funded. Itcould, however, be applied  mutatis mutandis  to anyautonomous organisation as long as the context andstrategy are clearly identified first. The case study of this paper is the ULB where the author was Vice-Rector for Academic Affairs (Pro-Vice-Chancellor)when the method was designed and implemented. Strategy To make resource allocation transparent, it is necessaryfirst to elucidate institutional mission and strategythrough a plan that defines objectives. As an example,the objectives listed in the ULB strategic plan approvedby the University Board in April 2008 are listed inTable 1.Ideally, the strategic plan should state the key per-formance indicators (KPIs) related to the objectives.As this was the first attempt to adopt a strategic planat ULB, KPIs were not initially included. They werederived in the context of the development of theresource allocation method. The French-speaking Communityof Belgium context (Belgium-FR) Since 1980, the Belgian constitution has devoted theresponsibility of education (from early childhood tohigher education) to the ‘Community’. This paper,analysing the study case of the ‘ULB’, will focus onthe French-speaking Community of Belgium(denoted Belgium-FR below) context. It is important (1) Evaluate our own research and increase research withan international high-quality output.(2) Increase research income, particularly for fundamentalresearch(3) Increase participation in research programmes(4) Develop research valorisation(5) Give students real chances of success in Bachelor’sprogrammes.(6) Deliver high-quality Bachelor’s programmes(7) Organise internationally attractive Master’sprogrammes(8) Encourage staff to be more friendly and welcomingtowards international students(9) Participate in the European construction process(10) Contribute to social debate Table 1. ULB strategic objectives (April2008) PHILIPPE BOUILLARD2    D  o  w  n   l  o  a   d  e   d   b  y   [   A  r  c   h   i  v  e  s   &    B   i   b   l   i  o   t   h   è  q  u  e  s   d  e   l   '   U   L   B   ]  a   t   2   2  :   5   5   1   1   N  o  v  e  m   b  e  r   2   0   1   5  to notice that, since this splitting, both Flemish andFrench-speaking communities have evolved indepen-dently and the higher education systems are nowclearly different, though both compatible with theBologna process. Funding system for the universities in theBelgium-FR (Bayenet and Bosteels 1998 ;Detroux  2009  ) The current funding law is still mainly based on prin-ciples adopted by a former (Federal) law in 1971(27th July) where the equal treatment of students anduniversity institutions were fully guaranteed. Onlysince then, public and ‘free’ universities were governedbyexactly the same regulations and rules. In return, the1971 funding law defines a list of eligible universitieswhich receive an annual allowance. Allocations aremostly based on the number of students, even if theyare supposed to cover the three traditional duties of teaching, research and service to the society expectedfrom research-based universities. The allowancecovers working and staffing costs but not studentsocial expenses, fundamental research funding or infra-structure investments, which are covered by specificlaws or agencies.The annual allowance is, however, not strictly pro-portional to the number of students. Since the 2004decree restructuring the higher education in Belgium-FR to integrate the European Area, known as the‘Bologna’ decree, the allowance is divided into twoparts: one fixed amount representing more or less 25%of the total allowance, and one variable amount pro-portional to the weighted number of funded students(WNFS). 1 The weights are intended to reflect theactual costs of a curriculum, roughly speaking 1 for the social sciences and humanities programmes, 2 for the hard sciences programmes and 3 for the medicalor engineering graduate programmes. It has to benoted that every European Union citizen student willbe taken into account to determine the WNFS.Since 1998, the total allowance provided to univer-sities has been determined by a decree to a fixedamount. Therefore, income may decline even if thenumber of students increases. In a fixed budgetsystem, if the number of students in one university isconstant but it increases all others, the allowance willdecrease. According to the statistical office of theBelgium-FR (Etnic 2007), since the number of stu-dents is continuously growing, the actual universitypublic allowances have decreased by 6% between1998 and 2008. The same trend is still observed inmore recent years.Finally, it has to be noted that no significant changeshave been made to the funding mechanism in theFrench-speaking Community of Belgium. Accordingto Claeys-Kulik and Estermann (2015, Table 5,p. 30), despite the emergence of many performance-based systems throughout Europe, the Belgium-FRfunding law still relies on three indicators (number of BA/MA students, doctoral students and doctoraldegrees awarded) among a list of possible thirtyobserved. Key performance indicators KPIs can be derived from the objectives defined inTable 1. As a first attempt, it is preferable to defineonly a few indicators (manageable and understandable),based on easilyaccessible data and representative for anydiscipline. ULB is indeed a comprehensive universitywith the full range of disciplines from social sciencesand humanities to medicine and engineering.Evaluate ourown research and increase research withan international high-quality output: Proposed KPI N  Th : the number of thesis. We were looking for an indicator representativefor all disciplines and therefore excluded defi-nition of research outputs in terms of journalpapers since standards could not be easily com-pared across disciplines. (Browman and Stergiou2008; Bray 2008) Increase research income, particularly for fundamen-tal research: Proposed KPI N  FNRS  : the number of FNRS fellow-ships except at doctoral level (to avoid redundancywith NTh). The objective was mainly about fundamentalresearch which is mostly funded by the FNRS(Fond National de la Recherche Scientifique-National Research Foundation) in theBelgium-FR. There are other funding mechan-isms (European Research Council grants, spon-sorship) for fundamental research but they havebeen considered less significant at this stage (interms of relative budget figures) for our purpose.Increase participation in research programmes: Proposed KPI N  INC  : research incomes from private or  public contracts, except FNRS (to avoid redundancywith FNRS indicator) All research income can be considered (Europe,Belgium federal state, regions or communities,companies, etc.)Develop research valorisation: No indicator proposed. Tentative indicators were considered relating topatents and/or spin-offs. However, after severalbrainstorming sessions, we decided to excludethese because the numbers were small and the PERSPECTIVE 3    D  o  w  n   l  o  a   d  e   d   b  y   [   A  r  c   h   i  v  e  s   &    B   i   b   l   i  o   t   h   è  q  u  e  s   d  e   l   '   U   L   B   ]  a   t   2   2  :   5   5   1   1   N  o  v  e  m   b  e  r   2   0   1   5  indicator was not appropriate for all disciplines.Most of the spin-offs were in hard or medicalsciences.Give students real chances of success in Bachelor’sprogrammes: Proposed KPI N  Soc  : the number of students receiving asocial allowance. This indicator has been clearly debated as it is notreally a performance indicator. Actually, it ismore a ‘positive discrimination’ mechanism, asimplemented in secondary schools in Belgium(Demeuse 2000) where the idea is to provideadditional staff where ‘less favoured’ students arebeing taught. Although not a performance indi-cator, it was agreed because inclusive policy is amajor concern of ULB.Deliver high-quality Bachelor’s programmes: Proposed KPI N  WNFS  : weighted number of funded students Here we decided to adopt the funding law indi-cator NWNFS for two reasons. First, the insti-tution must be aligned with the funding law.Second, the number of students can be inter-preted as a programme success indicator reflect-ing perceived quality.Organise internationally attractive Master’sprogrammes: Proposed KPI N  Int  : the number of international stu-dents enrolled in our Master’s programmes (excluding Erasmus mobility exchanges). The number of international students enrolledwas here a self-evident indicator. The onlydebate was about including, or not, Erasmusexchange students. Even if they are an indicator of the international attractiveness of the pro-grammes, they do not have any impact on theuniversity income and were therefore excluded.This was obviously controversial and is stilldebated.Encourage staff to be more friendly and welcomingtowards international students.Participate in the European construction process.Contribute to social debate:No indicators were used for the last 3 objectivesat this stage. Resource allocation method  The proposed method is based on one of the simplestmodel of the so-called Multi-attribute Utility Theory(Bouyssou et al. 2006). A function  R   aggregates allthe  n  criteria  N  i   (the KPIs) using weighting factors  w  i  reflecting the relative importance given to each criteria(Equation (1)). Here, it is important to note that thecriteria are expressed in relative terms (as part of thetotal university budget) in order to avoid any scalingissue and they are averaged over a period of 5 years tosmooth local unexpected fluctuations. R   =  ni  = 1 w  i  N  i  .  ( 1 ) The method consists in minimising the distancebetween this objective function  R   and the current situ-ation  S  . The weighting factors can be used to reinforcethe relative importance of the corresponding criteria. Case study: ULB Initial situation Table 2 presents the human resource distributionamong the eleven Schools (data from 2008) for threecategories of personnel: lecturers (full-time or part-time, whatever their rank), teaching and research assist-ants (TAs - full-time or part-time) and staff (administra-tive or technicians). The data are expressed in relativeterms to the total amount of full-time equivalents(FTEs) budgeted for the whole university. The totalcolumn is obtained by multiplying the FTEs with anaverage cost per category then divided by the totalbudget. The distribution of human resources amongthe schools can be explained by their different sizes interms of students but also with their history. The distri-bution difference between the three categories can alsobe explained by different needs in terms of assistants or lab technicians for instance. FTE distribution among Schools as in 2008School Lecturers TAs Staff Total A 15.2% 13.0% 6.9% 13.0%B 6.8% 8.0% 3.6% 6.4%C 14.1% 22.9% 11.0% 15.2%D 4.7% 5.7% 3.7% 4.7%E 21.5% 14.2% 24.7% 20.7%F 11.1% 13.9% 15.9% 12.7%G 17.2% 11.6% 23.2% 17.3%H 2.8% 1.3% 2.2% 2.4%I 2.8% 3.9% 4.6% 3.4% J 2.1% 4.5% 2.2% 2.6%K 1.7% 1.0% 1.9% 16%Total 100.0% 100.0% 100.0% 100.0% Table 2. ULB case study: distribution of thehuman resources among the Schools as in2008. The total is obtained by multiplyingthe FTEs with an average cost per category PHILIPPE BOUILLARD4    D  o  w  n   l  o  a   d  e   d   b  y   [   A  r  c   h   i  v  e  s   &    B   i   b   l   i  o   t   h   è  q  u  e  s   d  e   l   '   U   L   B   ]  a   t   2   2  :   5   5   1   1   N  o  v  e  m   b  e  r   2   0   1   5
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