Modular manufacturing experience in the South African clothing industry: Lessons learned

This paper provides the lessons learned from an attempt by the South African Department of Science and Technology (DST) and the Council for Scientific and Industrial Research (CSIR) to develop a National Information Society Learnership in Ecological Informatics (NISL: EI). Ten unemployed graduates were selected in 2004 to be part of two years NISL: EI learnership programme. The results show that the programme had succeeded in making candidates employable, with 90 percent of the learners working in different science and technology sectors, and two Honours degrees having been awarded. Challenges for higher level learnership development and implementation are identified and possible solutions are discussed.

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Factors Affecting Demand Planning in the South African Clothing Industry

Journal of Economics and Behavioral Studies ◽

10.22610/jebs.v8i5(j).1443 ◽

2016 ◽

Vol 8 (5(J)) ◽

pp. 194-210

Author(s):

NJ Matsoma ◽

IM Ambe

Keyword(s):

South Africa ◽

South African ◽

Time Management ◽

Clothing Industry ◽

Specific Reference ◽

Key Factors ◽

The South ◽

Factors Affecting ◽

Demand Planning ◽

Analyse Data

The decline in the number of clothing manufacturers and the effect of globalisation have contributed to complexities in estimations and the scheduling of demand, as well as lead time management in the South African clothing industry. This article explores demand planning factors affecting the South African clothing industry, with specific reference to Gauteng. The study was necessitated due to demand planning challenges facing the South African clothing industry as well as economic factors which contribute to inaccuracies in clothing demand planning. The study makes an impact in the garment production factories of Gauteng in South Africa and adds to the philosophy of demand planning practices. It uncovers key factors affecting demand planning practices in the Gauteng clothing industry, South Africa. The study is explorative and descriptive in nature and it uses SPSS to analyse data. The findings revealed that there were factors affecting how demand planning practices were conducted in the clothing industry. The factors that have a significant influence on clothing demand planning include the scheduling of the manufacturing of customersâ€™ orders, planning for fashion clothes, the use of the POS system, clothing imports, estimating future clothing requirements, recession and the effect of the late arrival of clothes. Therefore, clothing industry stakeholders should take these factors into consideration when planning for their demand to ensure customer needs can be fully met, thus improving the performance of the clothing industry.

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Employment Protection in South Africa

Employment Protection Legislation in Emerging Economies - Advances in Finance, Accounting, and Economics ◽

10.4018/978-1-5225-4134-9.ch007 ◽

2018 ◽

pp. 140-156

Author(s):

Avinash Govindjee

Keyword(s):

Best Practices ◽

South African ◽

Work Force ◽

Lessons Learned ◽

International Standards ◽

Employment Protection ◽

Public Works ◽

Policy Framework ◽

The South ◽

African Experience

This chapter tests the existing (labour and social security-related) legislation against the South African constitutional framework, as well as international and regional standards. The issues to be addressed specifically include the following: 1) Is the existing legislation pertaining to employment protection, unemployment, and work constitutionally compliant? 2) Is it correct to expect legislation (and state policy) to regulate matters such as job-retention and work creation (for example, by activating the work force and through the creation of public works programmes), and if so, does the present statutory and policy framework address this expectation adequately? 3) To what extent is the legislation compliant with international standards and best practices, and are there fresh approaches to address the present malaise, perhaps emanating from regional standards and experiences? 4) Finally, are there any best practices or lessons learned through the South African experience that should influence developments in other emerging economies?

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