The development of a platform using digitalisation and networked modules for forecasting, planning and management to facilitate long-term success of SMEs in South Africa

Date
2023-12
Journal Title
Journal ISSN
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Publisher
Stellenbosch : Stellenbosch University
Abstract
ENGLISH ABSTRACT: The high attrition rate of Small and Medium Enterprises (SMEs) in South Africa, with a staggering 70% ceasing operations within their initial two years, is a pressing concern extensively highlighted in academic literature. This dissertation presents an innovative approach to support the growth and success of these SMEs by holistically addressing the multifaceted challenges they face, such as limited education, restricted _nancial access, and inadequate management skills. Current interventions often fall short due to their sector-speci_c focus, lack of adaptability to diverse user contexts, and scalability challenges, further exacerbated by low adoption rates among SMEs. To bridge the identi_ed gap in existing solutions, the study poses a central research question: How can a con_gurable, adaptable, and accessible platform be developed to holistically address the challenges faced by South African SMEs, thereby bolstering their prospects for long-term growth and success? The proposed platform is then developed into a prototype, which is validated in real-world use cases across the services, online retail, and subsistence agriculture sectors. The _ndings from these implementations underscore the platform's potential in facilitating long-term success. This research lays the foundation for further advancements aimed at strengthening the SME sector in South Africa, with the overarching ambition of fostering a vibrant and resilient national economy. This research introduces _ve unique contributions. Foremost is the development of a comprehensive set of networked modules, tailored specifically for South African SMEs. These modules holistically address the multifaceted challenges that SMEs encounter. Bolstering this is a novel platform design, informed by a synthesis of insights from earlier research objectives. This design serves as a roadmap for devising solutions essential to the long-term success of SMEs. The third contribution, inherent in the platform design, is the integration of strategic business management systems, machine learning, and digitalisation. This multi-pronged approach, drawing on the core tenets of industrial engineering, has culminated in a platform tailored to augment SME success in South Africa. Furthermore, the establishment of a database backend for operational planning and operations management dispels the conventional complexities SME stakeholders face, facilitating seamless business performance management. Lastly, building on these foundational elements, an automated mechanism for deriving use case-speci_c KPIs has been introduced. This mechanism leverages the intricate relationships among measures, sensors, and objectives, with machine learning serving as the catalyst for producing KPIs precisely attuned to speciFIc business objectives.
AFRIKAANSE OPSOMMING: Die hoë uitvalsyfer van Klein en Medium Ondernemings (KMO's) in Suid-Afrika, met 'n skokkende 70% wat hul bedrywighede staak binne hul aanvanklike twee jaar, is 'n dringende bekommernis wat breedweg in akademiese literatuur beklemtoon word. Hierdie proefskrif bied 'n innoverende benadering om die groei en sukses van hierdie KMO's te ondersteun deur die veelsydige uitdagings waarmee hulle te kampe het, soos beperkte onderwys, beperkte _nansiële toegang en ontoereikende bestuursvaardighede, holisties aan te spreek. Huidige intervensies skiet dikwels tekort as gevolg van hul sektor-spesi_eke fokus, gebrek aan aanpasbaarheid aan diverse gebruikerskontekste, en skalering uitdagings, wat verder vererger word deur lae aannemingskoerse onder KMO's. Om die geïdenti_seerde gaping in bestaande oplossings te oorbrug, stel die studie 'n sentrale navorsingsvraag: Hoe kan 'n kon_gureerbare, aanpasbare, en toeganklike platform ontwerp word om holisties die uitdagings waarmee Suid-Afrikaanse KMO's te kampe het, aan te spreek, en sodoende hul vooruitsigte vir langtermyn groei en sukses te versterk? Die voorgestelde platform word dan ontwikkel tot 'n prototipe, wat gevalideer word in werklike gebruikstoestande oor die dienste, aanlyn kleinhandel, en bestaanslandbou sektore. Die bevindinge van hierdie implementerings beklemtoon die platform se potensiaal in die fasilitering van langtermyn sukses. Hierdie navorsing lê die fondament vir verdere vorderings wat daarop gemik is om die KMOsektor in Suid-Afrika te versterk, met die oorkoepelende ambitie om 'n lewendige en veerkragtige nasionale ekonomie te bevorder. Hierdie navorsing stel vyf unieke bydraes voor. Voorop is die ontwikkeling van 'n omvattende stel van genetwerkte modules, spesi_ek aangepas vir Suid-Afrikaanse KMO's. Hierdie modules spreek die veelsydige uitdagings waarmee KMO's te kampe het, holisties aan. Hierdie bydrae word versterk deur 'n nuwe platformontwerp, geïnformeer deur 'n sintese van insigte uit vroeëre navorsingsdoelwitte. Hierdie ontwerp dien as 'n padkaart vir die ontwikkeling van oplossings wat noodsaaklik is vir die langtermyn-sukses van KMO's. Die derde bydrae, inherent aan die platformontwerp, is die integrasie van strategiese besigheidsbestuurstelsels, masjienleer en digitalisering. Hierdie veelkantige benadering, wat gebaseer is op die kernbeginsels van bedryfsingenieurswese, het uitgeloop op 'n platform wat aangepas is om die sukses van KMO's in Suid-Afrika te bevorder. Verder elimineer die totstandkoming van 'n databasis agterkant vir bedryfsbeplanning en bedryfsbestuur die konvensionele kompleksiteite waarmee hierdie KMO belanghebbendes te kampe het, en fasiliteer naadlose besigheidsprestasiebestuur. Laastens, gebou op hierdie grondslagelemente, is 'n outomatiese meganisme vir die a_eiding van geval-spesi_eke KPI's ingevoer. Hierdie meganisme maak gebruik van die ingewikkelde verhoudings tussen metings, sensors en doelwitte, met masjienleer as die katalisator vir die produksie van KPI's wat presies afgestem is op spesi_eke besigheidsdoelwitte.
Description
Thesis (PhD)--Stellenbosch University, 2023.
Keywords
Digitalisation, South African SMEs, forecasting, planning, management
Citation