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dc.contributor.advisorCoetzee, J.C.en_US
dc.contributor.authorPhaswana, K.en_US
dc.date.accessioned2021-09-16T05:49:34Z
dc.date.available2021-09-16T05:49:34Z
dc.date.issued2021en_US
dc.identifier.urihttps://orcid.org/0000-0002-3064-5614en_US
dc.identifier.urihttp://hdl.handle.net/10394/37440
dc.descriptionMBA, North-West University, Potchefstroom Campus
dc.description.abstractIt is widely recognised that the 4th industrial revolution (4th IR) will have an impact on job profiles and will require new approaches on human resources management and planning. The main challenge in the 4th IR context is to avoid technological unemployment and as such human capital investment (HCI) planning is crucial. Business leaders across all industries are called to formulate comprehensive human capital investment strategies ready to meet the challenges of the 4th IR while ensuring efficiency and avoiding technological unemployment. This study developed a framework that managers and strategists at National Statistics Offices (NSO) of the Southern Africa Customs Union (SACU) region can use to amplify human capital investment plans for the 4th IR era. In designing this framework, the study followed a qualitative research approach with semi-structured interviews being conducted with experts in the field of official statistics and the data revolution. The study presented the qualitative findings in reference to the existing literature. The results were analysed alongside the related literature review to identify areas of corroboration, disagreement, subtractions and additions between the results and the literature. The main additions to the results of the study were on the topic of the big-data maturity matrix. The literature highlighted the importance of the maturity matrix in NSOs, however the results of the study indicated that the topic has been discussed at international platforms but was not yet prioritized. Thus, NSOs in the SACU region may need to relook at the issue of maturity matrix. The results of this study further established that the currently used Generic Statistical Business Process Model (GSBPM) will still be fit to be used as a baseline operating model during the 4th IR era. However, the GSBPM will require modifications. This finding corroborated with the literature review, however the results of this study further suggested types of modifications that may be considered when modifying the GSBPM during the 4th IR era. This study also identified jobs that are at risk of automation at NSOs of the SACU region during the 4th IR era. The study furthermore suggested skills that will be demanded by NSOs of the SACU region during the 4th IR era. The strategic initiatives that NSO managers in the SACU region need to implement in order to acquire skills that would be demanded by the NSOs during the 4th IR era were also identified. These initiatives corroborated with the initiatives suggested in the literature, however this study added more initiatives to the themes that are dominant in the literature. The literature review further suggested that prior to initiating HCI programs; the NSOs in the SACU region will need to have the 4th IR strategy, as well as the maturity models to measure progress.
dc.language.isoenen_US
dc.publisherNorth-West University (South Africa)en_US
dc.subjectHuman Capital Investment
dc.subject4th Industrial Revolution
dc.subjectNational Statistics Office
dc.subjectGeneric Statistical Business Processing Model
dc.subjectSouthern African Customs Union
dc.subjectOfficial Statistics
dc.titleAmplifying human capital investment planning at National Statistics Offices in SACU region during the 4th Industrial revolutionen_US
dc.typeThesisen_US
dc.description.thesistypeMastersen_US
dc.contributor.researchID10306498 - Coetzee, Johannes Cornelius (Supervisor)en_US


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