Identifying quantitative relationships between Key Performance Indicators in support of Physical Asset Management decision-making processes
| dc.contributor.advisor | Jooste, J. L. | en_ZA |
| dc.contributor.author | Botha, Louis J. | en_ZA |
| dc.contributor.other | Stellenbosch University. Faculty of Engineering. Dept. of Industrial Engineering. | en_ZA |
| dc.date.accessioned | 2015-12-14T07:43:59Z | |
| dc.date.available | 2015-12-14T07:43:59Z | |
| dc.date.issued | 2015-12 | |
| dc.description | Thesis (MSc)--Stellenbosch University, 2015. | en_ZA |
| dc.description.abstract | ENGLISH ABSTRACT: Physical Asset Management (PAM) is increasingly being acknowledged by industry as an important contributor to the financial success of organisations, especially those who are dependent on their physical assets for organisational value creation. Amongst the PAM improvement opportunities identified by researchers and organisations is the derivation of additional, meaningful and innovative information from Key Performance Indicators (KPIs) for improved PAM decision-making process. The Quantitative Relationships at the Performance Measurement System (QRPMS) methodology is an existing methodology which objectively identifies and quantifies the relationships between a set of KPIs, and presents these relationships as additional information for PAM decision-making processes. QRPMS employs two mathematical techniques, Principal Components Analysis and Partial Least Squares regression, to identify and quantify inter-KPI relationships, respectively. The Guttman-Kaiser criteria (K1) is employed by QRPMS to determine the number of principal components (PCs) to retain for further assessment. However, the K1 criterion is found to be one of the least reliable and most inaccurate selection criteria available, with some publications using it without reservation. Therefore, the K1 criterion severely compromises the reliability and mathematical accuracy of the results obtained from QRPMS. This study proposes an improved methodology for the objective identification and quantification of inter-KPI relationships, called the Quantitative Identification of Inter-Performance Measure Relationships (QIIPMR) methodology. A comprehensive literature study is conducted, investigating the realms of PAM, Performance Management (PM), Performance Management Systems (PMS) and performance measures. Existing frameworks and methodologies which aim to identify relationships between performance elements are investigated, and their flaws identified. The literature study concludes with an investigation of PCA, PLS and selection criteria. The proposed QIIPMR methodology employs QRPMS as a foundational framework. Accurate and reliable alternatives to the K1 criterion are compared, and the most appropriate of these is incorporated into QIIPMR. A case study is conducted, comparing the results of QRPMS and QIIPMR using real-world KPI data from an open-pit, thermal coal mine in South Africa. The case study results substantiate the improvement made to QRPMS methodology. This study concludes with recommendations for future research. | en_ZA |
| dc.description.abstract | AFRIKAANSE OPSOMMING: Fisiese Batebestuur (FB) word toenemend deur die industrie erken as ’n belangrike bydraer tot die finansiële sukses van organisasies, veral diegene wat afhanklik is van hul fisiese bates vir organisatoriese waarde skepping. Van die FB verbetering geleenthede wat geïdentifiseer is deur navorsers en organisasies, is die toepassing van bykomende, betekenisvolle en innoverende inligting van Sleutel Prestasieaanwysers (SP) vir verbeterde FB besluitnemingsprosesse. Die Kwantitatiewe Verwantskappe in die Prestasiemeting Sisteem (KVPS) metodologie is ’n bestaande metodologie wat die verhoudinge tussen ’n stel SP objektief identifiseer en kwantifiseer, en bied hierdie verhoudinge aan as bykomende inligting vir FB besluitnemingsprosesse. KVPS gebruik twee wiskundige tegnieke, Hoof Komponente Analise (HKA) en Parsiële Kleinste Kwadraat (PKK) regressie, om die identifisering en kwantifisering van SP verhoudings onderskeidelik the bereken. KVPS neem die Guttman-Kaiser kriteria (K1) in diens om die aantal hoofkomponente (HKe) te bepaal wat behou moet word vir verdere assessering. Die K1 kriteria was egter gevind as een van die minste betroubaarste en mees onakkurate keuringskriteria beskikbaar, met ’n paar publikasies wat dit gebruik sonder voorbehoud. Dus, die K1 kriteria stel die betroubaarheid en wiskundige akkuraatheid van die KVPS metodologie in groot gevaar. Hierdie studie stel ’n verbeterde metodologie voor vir die identifisering en kwantifisering van SP verhoudings, genaamd die Kwantitatiewe Identifisering van Tussen-Prestasiemaatstaf Verhoudings (KITPV) metodologie. ’n Omvattende literatuurstudie is voltooi, en die areas van FB, Prestasiebestuur (PB), Prestasiebestuurstelsels (PBS) en prestasiemaatreëls is ondersoek. Bestaande raamwerke en metodologieë wat daarop gemik is om die verhoudinge tussen prestasie elemente te identifiseer is ook ondersoek, en hul foute is geïdentifiseer. Die literatuurstudie word afgesluit met ’n ondersoek van HKA, PKK en seleksie kriteria. Die voorgestelde KITPV metodologie neem KVPS in diens as ’n fundamentele raamwerk. Akkurate en betroubare alternatiewe vir die K1 kriteria word vergelyk, en die mees geskikte van hierdie kriteria is opgeneem in hierdie KITPV. ’n Gevallestudie is onderneem, en die resultate van KITPV en KVPS is vergelyk met die hulp van werklike wêreld SP data van ’n oop-put, termiese steenkool myn in Suid-Afrika. Hierdie gevallestudie resultate staaf die verbetering aan die QRPMS metodologie. Hierdie studie sluit af met aanbevelings vir toekomstige navorsing wat geloots kan word. | af_ZA |
| dc.format.extent | 185 pages : illustrations | en_ZA |
| dc.identifier.uri | http://hdl.handle.net/10019.1/98044 | |
| dc.language.iso | en_ZA | en_ZA |
| dc.publisher | Stellenbosch : Stellenbosch University | en_ZA |
| dc.rights.holder | Stellenbosch University | en_ZA |
| dc.subject | Physical Asset Management (PAM) | en_ZA |
| dc.subject | Key Performance Indicators (KPI) | en_ZA |
| dc.subject | Performance Management | en_ZA |
| dc.subject | Key Performance Indicator Relationships | en_ZA |
| dc.subject | UCTD | en_ZA |
| dc.title | Identifying quantitative relationships between Key Performance Indicators in support of Physical Asset Management decision-making processes | en_ZA |
| dc.type | Thesis | en_ZA |