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Data-driven decision-making in local governments : a case study of a Zambian local government
Thesis (MPhil)--Stellenbosch University, 2023.
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| Format: | Thesis |
| Language: | en_ZA |
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Stellenbosch : Stellenbosch University
2023
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| _version_ | 1867613956935254016 |
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| access_status_str | Open Access |
| author | Kalaba, Chiyesu Joseph |
| author2 | Maasdorp, Christiaan |
| author_browse | Kalaba, Chiyesu Joseph Maasdorp, Christiaan |
| author_facet | Maasdorp, Christiaan Kalaba, Chiyesu Joseph |
| author_sort | Kalaba, Chiyesu Joseph |
| collection | Thesis |
| dc_rights_str_mv | Stellenbosch University |
| description | Thesis (MPhil)--Stellenbosch University, 2023. |
| format | Thesis |
| id | oai:scholar.sun.ac.za:10019.1/128917 |
| institution | Stellenbosch University (South Africa) |
| language | en_ZA |
| last_indexed | 2026-06-10T12:44:23.606Z |
| license_str | Other — see source repository |
| provenance_str_mv | Harvested via OAI-PMH from SUNScholar — Stellenbosch University Repository |
| publishDate | 2023 |
| publishDateRange | 2023 |
| publishDateSort | 2023 |
| publisher | Stellenbosch : Stellenbosch University |
| publisherStr | Stellenbosch : Stellenbosch University |
| record_format | dspace |
| source_str | SUNScholar — Stellenbosch University Repository |
| spelling | oai:scholar.sun.ac.za:10019.1/128917 Data-driven decision-making in local governments : a case study of a Zambian local government Kalaba, Chiyesu Joseph Maasdorp, Christiaan Stellenbosch University. Faculty of Arts and Social Sciences. Dept. of Information Science. Local government -- Data processing Decision making -- Government Decision making -- Data processing -- Government Local government -- Technological innovations UCTD Thesis (MPhil)--Stellenbosch University, 2023. ENGLISH SUMMARY: Informed decisions at local government level are difficult to achieve in developing countries because of problems around the availability of actionable data. The thesis investigates the issues that affect decision making and identifies the necessary conditions for data-driven decision making processes at local government level in such a developing country context. The research was conducted by examining March's frameworks for decision making, and Anderson’s work on the prerequisites for constructing, operating, and leveraging comprehensive data platforms for decision making, forecasting, and operational functionalities. Symons' empirical findings on innovative, data-driven practices in local governmental settings in the United Kingdom are described as a developed country benchmark against which to contrast the developing country case. Using a mixed-methods approach, staff with decision-making responsibilities at a Zambian municipality were asked about the data they need and the tools and skills they need to analyse that data effectively. The quantitative analysis identified the data analysis skills levels, and the qualitative research delve into the decision-making processes and the challenges experienced by staff members. Secondary sources such as government legislation, policies, and websites were consulted. The research stages comprised reviewing documentation, interviewing local government decision-makers, surveying the data analysis skills of decision-makers and support staff, assessing the efficacy of current data tools and IT infrastructure, and an interview with the human resources officer regarding training in data analysis. The findings reveal that decision making in the case organisation is primarily driven by intuition and political considerations rather than data. Drawing comparisons with the UK Local Government, where data-driven approaches yielded effective decision making across varied political landscapes and with limited funding, the research suggests that similar strategies can significantly improve decision quality and accountability in Zambian local administrations. However, the adoption of such methodologies in Zambia is hampered by challenges, including insufficient IT infrastructure, limited data literacy, and a weak culture of data-driven decision making. To overcome these barriers, a multifaceted approach is needed to improve IT infrastructure and data literacy, coupled with funding for digitalisation initiatives. AFRIKAANSE OPSOMMING: In ontwikkelende lande is dit moeilik om ingeligte besluite op plaaslike regeringsvlak te neem as gevolg van die onbeskikbaarheid van data. Die tesis ondersoek die kwessies wat besluitneming raak en identifiseer die nodige voorwaardes vir data-gedrewe besluitnemingsprosesse op plaaslike regeringsvlak in so 'n ontwikkelende land konteks. As agtergrond word March se besluitnemingsraamwerke bestudeer, en Anderson se werk oor die voorvereistes vir die bou, bedryf en benutting van omvattende dataplatforms vir besluitneming, vooruitskatting en operasionele funksionaliteite. Symons se empiriese bevindinge oor innoverende, data-gedrewe praktyke in plaaslike regeringsomgewings in die Verenigde Koninkryk word beskryf as maatstaf uit 'n ontwikkelde land waarteen die gevallestudie in die ontwikkelende land gekontrasteer kan word. Deur 'n gemengde-metode-benadering te gebruik, is personeel met besluitnemingsverantwoordelikhede by 'n Zambiese munisipaliteit gevra oor die data wat hulle benodig en die tegnologie en vaardighede wat hulle nodig het om daardie data effektief te ontleed. Die kwantitatiewe analise het die data-analise-vaardigheidsvlakke geidentifiseer, en die kwalitatiewe navorsing delf in die besluitnemingsprosesse en die uitdagings wat personeellede ervaar. Sekondere bronne soos regeringswetgewing, beleide en webwerwe is ook geraadpleeg. Die dokumentasie is geanaliseer, onderhoude is gevoer met plaaslike regeringsbesluitnemers, 'n opname van die data-ontledingsvaardighede van besluitnemers en ondersteuningspersoneel is gemaak, die doeltreffendheid van huidige datahulpmiddels en IT-infrastruktuur is geassesseer, en 'n onderhoud is met die menslikehulpbronbeampte gevoer oor opleiding in data ontleding. Daar is bevind dat besluitneming in die Zambiese munisipaliteit hoofsaaklik deur intuisie en politieke oorwegings eerder as data gedryf word. Deur vergelykings te tref met die Britse plaaslike regering, waar datagedrewe benaderings effektiewe besluitneming oor verskillende politieke landskappe en met beperkte befondsing opgelewer het, dui die navorsing daarop dat soortgelyke strategiee besluitkwaliteit en aanspreeklikheid in Zambiese plaaslike administrasies aansienlik kan verbeter. Die aanvaarding van sulke metodologiee in Zambie word egter belemmer deur verskeie uitdagings, onder andere onvoldoende IT-infrastruktuur, beperkte datageletterdheid en 'n swak kultuur van data-gedrewe besluitneming. Om hierdie struikelblokke te oorkom, is 'n veelvlakkige benadering nodig om IT-infrastruktuur en datageletterdheid te verbeter, tesame met befondsing vir digitaliseringsinisiatiewe. Masters 2023-11-29T14:10:22Z 2024-01-08T15:44:39Z 2023-11-29T14:10:22Z 2024-01-08T15:44:39Z 2023-12 Thesis https://scholar.sun.ac.za/handle/10019.1/128917 en_ZA Stellenbosch University xiii, 146 pages : illustrations, includes annexures application/pdf Stellenbosch : Stellenbosch University |
| spellingShingle | Local government -- Data processing Decision making -- Government Decision making -- Data processing -- Government Local government -- Technological innovations UCTD Kalaba, Chiyesu Joseph Data-driven decision-making in local governments : a case study of a Zambian local government |
| title | Data-driven decision-making in local governments : a case study of a Zambian local government |
| title_full | Data-driven decision-making in local governments : a case study of a Zambian local government |
| title_fullStr | Data-driven decision-making in local governments : a case study of a Zambian local government |
| title_full_unstemmed | Data-driven decision-making in local governments : a case study of a Zambian local government |
| title_short | Data-driven decision-making in local governments : a case study of a Zambian local government |
| title_sort | data driven decision making in local governments a case study of a zambian local government |
| topic | Local government -- Data processing Decision making -- Government Decision making -- Data processing -- Government Local government -- Technological innovations UCTD |
| url | https://scholar.sun.ac.za/handle/10019.1/128917 |
| work_keys_str_mv | AT kalabachiyesujoseph datadrivendecisionmakinginlocalgovernmentsacasestudyofazambianlocalgovernment |