The Truth about Employment Equity in South Africa

 

 

 

Executive summary

 

The Truth about Employment Equity is an attempt to provide a more balanced view of employment equity in South Africa.

 

It opens with a critical analysis of the Employment Equity Commission’s report. The reason for taking such a critical look is the fact that this report is currently being used as an objective – and the only – basis for measuring employment equity in our country.

 

The main problem with reports by the Employment Equity Commission is the way in which employers provide information.

 

The most definitive criticism on the use of employment equity reports to draw conclusion regarding representation of the designated group in the workplace comes from the Employment Equity Report itself: “It is of great concern to the Commission that such a large number (3 835) of reports could not be included in the sample because they did not meet the minimum requirements for inclusion in the analysis. The effect of this is that the sample size has been diminished considerably. This may distort any interpretation and conclusions made about representation of the designated group in the workforce.”

 

The inclusion of this comment probably rendered this report superfluous from the outset, but it was deemed advisable to investigate the reason for the cited distortions and why data provided by the Employment Equity Report should be treated with circumspection.

 

These anomalies are identified in numerous graphs. In some years, there are spurious achievers or declines for which no explanation can be found. Coincidentally, the representation of white women in 2006 is one such anomaly. More about that later.

 

Comparisons cannot be drawn from the data sets for the various years. In the first place, small employers only submit reports every second year, while larger employers submit annual reports. This makes comparison difficult. In addition, the number of reports submitted every second year varies by between 30% and 195%.

 

Further proof of the radical variations in employers who submit annual reports is provided by the fact that 2,5 times as many reports were submitted in 2006 as in 2005, but 0,4% of employees (6 876 reports from a total of 164 1179 received) are covered in the 2006 report.

 

Only around 28% - or approximately 1 540 of the average of 5 478 submitted reports – relate to the same employers. If a scientific comparison were to be drawn, it must be based on the 1 540 companies that submitted reports every year, and the conclusions would be based on those same companies.

 

The Employment Equity Reports only cover 1,6 million workers - or 9,82% - out of the 16,7 million strong South African labour force. The reports cannot possible be representative of the entire labour force.

 

Another serious problem is the non-submission of reports by employers. In 2005 (the latest data available) 25 municipalities (including large metropolitan councils like Tshwane and Johannesburg), 13 provincial government departments and 9 national government departments failed to submit reports. Among other institutions that did not submit reports are the South African parliament and the director of public prosecutions.

 

If employers whose transformation is far advanced to not deem it necessary to submit reports, the Employment Equity Reports will be skewed and black representation will be underestimated.

 

African representation in the public service provides a good example. National representation at senior management level stands at 75%. In the Eastern Cape the figure is 80%, in the Free State 60%, in Gauteng 66%, in KwaZulu-Natal 77%, in Limpopo 92%, in Mpumalanga 88%, in North West 84%, in the Northern Cape 83% and in the Western Cape the figure is 52%. If these employers do no submit reports, the eventual employment equity profile will be seriously distorted.

 

As long ago as 2005 the Public Service Commission reported that racial targets had largely been achieved. The 2006 reports indicate that more than half the provincial department now have to apply affirmative action measures to render whites, coloureds and Indians representative: Africans are over-represented.

 

Numerous technical and computation errors have also been identified.

 

In spite of its failings, the Report is still being used as an objective means to measure the progress of employment equity. The progress is used very selectively.

 

This report used the data contained in the Service Equity Reports to determine changes in terms of the data in the reports. Even the deficient information provided in the Employment Equity Reports shows that far more had been achieved than is generally accepted.

 

Table 1

Top Management Employees % change

 

Male

Female

 

African

Coloured

Indian

Total Black

White

African

Coloured

Indian

Total Black

White

2001-2006

55,99%

21,95%

45,06%

45,80%

-22,85%

94,35%

545,43%

433,00%

210,87%

60,31%

 

Apart from the shifts demonstrated above, it appears that the number of black South Africans in senior management positions has also been underestimated.

 

An analysis of 367 JSE-listed companies shows that 1 023 of the 4 311 (or 24%) of company directors are black.

 

Statistics South Africa’s Household Survey found that 42% of legislators, senior officials and managers are black.

 

According to the South African Advertising Research Foundation (AMPS Surveys from 1997-2006), there have been significant shifts in senior positions in South Africa. Between 1997 and 2006 the number of black senior incumbents has grown from 8 766 to 28 658 – a 230% increase. White top management representation, on the other hand, has declined from 30 876 to 22 758, representing a 26,29% decrease.

 

Additional shifts are identified below:

 

Table 2

Senior Management Employees % change

 

 

Male

Female

 

African

Coloured

Indian

Total Black

White

African

Coloured

Indian

Total Black

White

2001-2006

44,05%

24,97%

85,34%

49,03%

-25,32%

71,23%

134,37%

277,55%

121,50%

34,49%

 

 

Table 3

Professionally Qualified and Experienced Specialists and Mid-Management Employees % change

 

Male

Female

 

African

Coloured

Indian

Total Black

White

African

Coloured

Indian

Total Black

White

2001-2006

44,14%

17,82%

29,60%

34,60%

-24,17%

90,13%

27,80%

98,91%

71,17%

-0,86%

 

 

Table 4

Skilled Technical and Academically Qualified Workers, Junior Management, Supervisors, Foremen, and Superintendents Employees % change

 

Male

Female

 

African

Coloured

Indian

Total Black

White

African

Coloured

Indian

Total Black

White

2001-2006

51,79%

54,85%

-17,86%

40,88%

5,92%

-54,81%

30,34%

-37,91%

-40,25%

-8,40%

 

 

 

Table 5

Semi-Skilled and Discretionary Decision Making Employees % change

 

Male

Female

 

African

Coloured

Indian

Total Black

White

African

Coloured

Indian

Total Black

White

2001-2006

14,46%

1,50%

-20,38%

11,17%

-23,46%

-16,18%

-16,13%

2,69%

-14,78%

-42,25%

 

Table 6

Unskilled and Defined Decision Making Employees % change

 

Male

Female

 

African

Coloured

Indian

Total Black

White

African

Coloured

Indian

Total Black

White

2001-2006

-25,55%

26,86%

-5,91%

-22,62%

-22,30%

53,54%

38,60%

-4,94%

49,03%

-36,98%

 

The number of white males declined in all categories, and bar one category the decline was more than 20%.

 

The tables above also cast a different light in the position of white females than the current perception. The number of white females declined by almost 25%. At the upper levels, where an increase in white female representation took place, the increase was considerably smaller than that of other races. Throughout the lower levels white female representation declined.

 

The South African Advertising Research Foundation (AMPS Surveys from 1997-2006) also found that whites in the labour market declined by 18%, and by more than 20% in the majority of categories.

 

The most definitive proof of the success of affirmative success is to be found in the growth of the black middle class.

 

The status of the black middle class can be summarised in the following 15 points:

 

  1. South Africa’s black middle class, increasingly referred to as “black diamonds”, has grown by an astonishing 30%. “Black diamonds” now comprise of an estimated 2,6million, as opposed to 2 million in 2005. This represents 12% of the country’s black population.
  2. There are more “black diamonds” in South Africa than working whites.
  3. It must be kept in mind that the total black population has only grown by 1, 82%, while the other population groups have shown no growth at all.
  4. Looking at the international situation, it is clear that the middle class populations of the world are generally a third or fourth generation, while South Africa’s black population has a first generation middle class as a result of BEE as the primary force, and second as a result of economic growth.
  5. “Black diamonds” are worth R180 billion, which is 28% of the total South African buying power.
  6. The buying power of the total SA population in the first quarter of 2007 was R640 billion, as opposed to the figure of R600 billion in the last quarter of 2005. This represents an increase of 6,67%.
  7. The figure for whites improved minimally, from R230 billion to R235 billion, or 2,17%.
  8. The total for black South Africans grew from R300 billion to R335 billion, representing an 11,67% increase.
  9. At the cutting edge of economic progress, the buying power of “black   diamonds” during the same period grew from R130 billion to R180 billion – an astonishing 38%. This demonstrates a significant move in the “black diamond” segment.
  10. The reason why this growth is regarded as so astonishing is that the number of “black diamonds” only grew by 30% in the same period. The higher growth in the buying power simply results from the fact that the “black diamonds” are getting better jobs, together with better salaries because of BEE and AA.
  11. “Black diamonds” (12% of all blacks) now account for 54% of black buying power.
  12. The “black diamonds”, who account for 9% of the total population and are worth R180 billion, are already responsible for 28% of South Africa’s total spending. 
  13. It is estimated that by 2009 the “black diamonds” will have overtaken white spending (now estimated at R235 billion).
  14. According to the “Black Diamond” Survey, more than 12 000 “black diamond” families – or 50 000 people – are moving from the townships to the suburbs of South Africa’s metro areas every month.
  15. The total number of “black diamonds” currently living in suburbia comes to approximately 1,2 million people and is likely to increase.

 

 

 

 

The truth about employment equity in South Africa

                                                                                                             

1. Introduction

 

All over the world affirmative action is an emotive issue that can divide communities. In countries like Malaysia, India and Sri Lanka people died as a result of affirmative action programmes gone wrong.

 

The issue must therefore always be handled with care.

 

In the newsletter ANC Today of July 20th, 2007, President Thabo Mbeki refers to Solidarity’s doubts about the validity of the Employment Equity Commission’s statistics as a basis for the determination of national policy.

 

In response to Solidarity’s criticism of the Employment Equity Report, Mr Mbeki said that South Africans cannot even sing from the same hymn sheet about the bare facts of affirmative action. 

 

He then proceeds to quote freely from the Employment Equity Commission’s report and refers, among other things, to the over-representation of white females mentioned in the Report. Mbeki also proposed that white females should no longer be included in the non-designated group.

 

The President in other words uses the Employment Equity Commission’ report as “an objective source” (as he calls it) to measure the progress of affirmative action in South Africa.

 

This document serves to motivate Solidarity’s criticism of the Employment Equity Commission’s report as an objective and sole source of information on the progress of affirmative action in South Africa.

 

It is important that national policy will be based on factually correct information.

 

This document shows the numerous deficiencies in the Employment Equity Report and its consequent inadmissibility as a yardstick to determine the progress of affirmative action.

 

The document shows that comparisons contained in the Employment Equity Report are not drawn from scientifically verifiable data; that submission is unreliable to the degree that it cannot reflect the national profile of the country and that it most probably underestimates black representation.

 

Solidarity’s document uses a number of other databases to arrive at a more comprehensive view on the progress of employment equity in South Africa.

 

2. Reports by the Employment Equity Commission as a basis for national policy

 

The Employment Equity Commission’s reports as used as a basis for the formulation of national policy. The most recent example is the debate on white females. On the grounds of the Employment Equity Commission’s reports, it is being said that white females should no longer be included in the designated group. One also often hears that no progress is being made with affirmative action. This conclusion is derived from the Employment Equity Commission’s reports. It is even said that stricter legislation is needed – all on the strength of the Employment Equity Commission’s reports. Since these reports play such a crucial part in the formulation of national policy regarding employment equity, it is extremely important to establish whether the Employment Equity Commission’s report are indeed a true reflection of the national status of employment equity.

 

It is clear from the outset that the Employment Equity Commission’s report does not reflect the true state of affairs. The report seems to underestimate black representation and the reports for several years contain inexplicable anomalies. Graphs to compare the various years show unnatural highs that do not reflect logical trends. A detailed investigation was done on the report and a number of problems have been identified with the way in which the report arrives at comparisons.

 

2.1 Manner of reporting

 

The Employment Equity Commission itself admits that there are problems regarding the reporting. According to the Commission, any interpretations or inferences regarding representation of the designated group can be distorted by the way in which companies submit their reports.

 

Reaching conclusions and determining national policy on the strength of reports that are – by the Commission’s own admission – scientifically flawed, is highly irresponsible.

 

In the 2004 report itself, on page 26, it is stated:

 

“It is of great concern to the Commission that such a large number (3 835) of reports could not be included in the sample because they did not meet the minimum requirements for inclusion in the analysis. The effect of this is that the sample size has been diminished considerably. This may distort any interpretation and conclusions made about representation of the designated group in the workforce. Nevertheless, analysis was made based on the available sample. It is recommended that these anomalies be corrected so that future reports do not suffer the same limitations.”

 

Die 2004 report is crucial, since it forms the basis on which the 2006 comparisons are drawn. The 2006 report also contain several comparisons with 2004 and the authors of the report do exactly that against which the 2004 report cautions.

 

2.2 Anomalies

 

The problem is further illustrated by the three graphs below. Dozens of examples exist, but these three have been selected as indicative of the problem.

 

The first graph shows the number of white females in top management positions. Note the unnatural increase in 2006. First there is a logical graphic line, and then a sudden upward move. No explanation for this phenomenon is offered. Since the databases differ significantly from year to year (see discussion later), many possible explanations exist other than the one that more white women were employed. The immediate reaction of the chairperson of the Employment Equity Commission in numerous media interviews was that white females should no longer form part of the designated group. There is also an unnatural decline in the number of black females, once again without any explanation being given. The reason is most likely to be found in the statistics, rather than in the workplace. There are no certainties, however, and national policy cannot be formulated on the strength of these statistics.

 

 

The next two graphics also illustrate the illogical nature of the statistics, which renders them practically useless. Additional explanations will be offered later.

 

 

 

2.3 Non-comparable data sets

 

Most of the statistical anomalies can probably be explained by the non-comparability of the data sets. Apples should be compared with apples. In this case, apples are compared with oranges and everyone is astonished with the orange apples.

 

Small employers (50 to 150 employees) submit every second year only, while large employers (150+) have to submit reports annually. This renders comparisons virtually impossible.

 

Even when the comparison is done for every second year, the databases show huge differences.

 

The number of reports is shown below:

 

Table 11

Year

Number of reports received

Number of reports analysed

2001

2 369

1 782

2002

6 990

6 990

2003

4 897

3 252

2004

8 974

5 554

2005

2 762

2 085

2006

6 876

4 394

 

Table 12

Years

% change in reports received

% change in reports analysed

2001-2002

195,06%

292,26%

2002-2003

-29,94%

-53,48%

2003-2004

83,26%

70,79%

2004-2005

-69,22%

-62,46%

2005-2006

148,95%

110,74%

 

A graphic representation provides a clear demonstration:

 

 

One element that does not hold up is the fact that the number of employees covered from 2001 to 2006 stayed relatively constant. This suggests that different companies made submission in the different years.

 

 

A glance at the figures for the number of employees covered and the number of reports received and analysed shows that these two factors are not nearly related. For example, in 2005 more employees were covered than in 2006, but fewer reports were received and analysed. This poses as a big problem when it comes to analysing and interpreting the data contained in the reports.

 

In 2006 two-and-half times as many reports as in 2005 were submitted, but they relate to 30,61% fewer employees.

 

Another inconsistency is that of the average 5 478 reports received from 2001 to 2006, only an estimated 1 540 companies were the same for each year from 2002 to 2005 (the Employment Equity Registers for 2001 and 2006 were not even released).

 

Only 28,11% of the reports can therefore be used for purposes of comparison.

 

The only way in which comparisons can be drawn, is to compare the 1 540 annually submitted reports and the results of the comparison will only apply to these reports. 

 

2.4 Non-submission by employers

As shown above, many large companies fail to submit or submit irregularly. The question arises how these companies are constituted. It is sometimes assumed that companies that want to circumvent the Employment Equity Act fail to submit reports, but the 2005 list of non-submitting employers shows that they are the transformed institutions.

 

If this is indeed the case, it will distort and underestimate black workplace representation.

 

A list of non-submitting companies in 2005, provided by the Labour Department, is given below:

 

Municipalities


1. Abaqulus Municipality
2. Amatole District Municipality
3. Ba-Phalaborwa Municipality
4. Butterworth Municipality
5. City of Johannesburg Municipality
6. City of Tshwane Metropolitan Council
7. Emfuleni Local Municipality
8. Emnambithi/Ladysmith Municipality
9. Govan Mbeki Municipality
10. Highland Municipality
11. Local Municipality of Lekwa
12. Makana Municipality
13. Maluti Phofung Municipality
14. Mamusa Local Municipality
15. Mbombela Local Municipality
16. Messina Municipality
17. Mnquma Local Municipality
18. Modimole Municipality
19. Municipality of Piketberg
20. Naledi Municipality
21. Nama Khoi Municipality
22. Nkomazi Municipality
23. Romothshere Moiloa Local Municipality
24. Sakhisizwe Municipality
25. Setsoto Municipality

State Departments ( Provincial)
1. Department of Agriculture: Western Cape
2. Department of Education and Training: Western Cape Area
3. Department of Health: KwaZulu-Natal
4. Department of Social Development: Eastern Cape
5. Department of Transport: Eastern Cape
6. Department of Transport: Polokwane
7. Department of Agriculture: Western Cape
8. Free State Department of Health
9. Free State Provincial Treasury
10. KZN Treasury
11. KZN Department of Labour
12. Mpumalanga Department of Housing & Land Administration
13. North West Provincial Government: Department of Transport

State Departments (National)
1. Department of Agriculture
2. Department of Agriculture: Conservation and Environment
3. Department of Finance & Economic Affairs
4. Department of Health
5. Department of Housing
6. Department of Justice Head Office
7. Department of Sport, Arts and Culture
8. Department of Health and Welfare
9. Department of Public Works, Roads and Transport

Other:
1. Director of Public Prosecutions
2. Eastern Cape Development Corporation
3. Eastern Cape Tourism Board
4. Gauteng Office of the Premier
5. Klerksdorp City Council
6. KwaZulu-Natal Provincial Administration
7. KZN Office of the Premier
8. National Research Foundation
9. Parliament of the RSA
10. SABS
11. SABC Strategic Human Resources
12. The Parliamentary Service
13. Transnet
14. Transnet Pension Fund

 

Non-submission by these institutions can have a major effect on the figures in the Employment Equity Reports. Municipalities have largely achieved 70%-80% (and even more) black representation.  

 

A glance at the progress made with employment equity in the public service will illustrate the effect of institutional non-submission on the final Employment Equity Report.


Page 61 of the Public Service Commission’s
2007 State of the Public Service Report carries a table that sets out the “workplace representivity” (i.e. racial breakdown) of the Senior Management Service (SMS) in the public service at national and provincial level as at October 31st, 2006.

 

Table 13

 

Total African

%

Total SMS members

National

2 437

71

3 452

 

 

 

 

Provincial

 

 

 

  1. Eastern Cape

351

80

439

  1. Free State

184

60

310

  1. Gauteng

465

66

713

  1. KwaZulu –Natal

471

77

608

  1. Limpopo

349

92

381

  1. Mpumalanga

220

88

249

  1. North West

233

84

276

  1. Northern Cape

121

83

145

  1. Western Cape

185

52

357


In 2000, Africans accounted for only 54% of senior management positions in the public service, compared to 71% in 2006. This represents a 31,48% increase
.

 

As long ago 2005, the Public Service Commission report acknowledged at racial targets had largely been reached. The 2006 report shows that more than half of provincial departments are now obliged to practice affirmative action to benefit whites, coloured and Indians in order to be representative – African are over-represented.

 

(The Employment Equity Act identifies four racial categories: African, White, Coloured and Indian. One must assume that, in reporting on the public service’s employment equity status, the Public Service Commission used the same categories and, therefore, that ‘African’ excludes coloured and Indian people.)

 

If these state departments do not reports, one can safely assume that black representation is underestimated.

 

2.5 Technical and computation errors

 

Technical and computation errors have also been identified in the reports, and these can obviously affect the statistical outcome.

 

The Employment Equity reports that were received and analysed do not always differentiate between large and small companies and the data in the reports and registers varies. The following shows the year to year differences in the reports:

 

 

Table 14

Reports

Some discrepancy explanations

2001

  • Report showed large employers ONLY and the data from the 2002 report differ from 2001 report when they were compared in the 2002 report.

2002

  • Did distinguish between large and small companies BUT the 2003 report only showed large companies for a comparison in 2002.

2003

  • Large employers ONLY

2004

  • Did distinguish between large and small companies

2005

  • Did not distinguish between large and small companies

2006

  • Did not distinguish between large and small companies

 

 

Mathematical and calculation errors in Employment Equity Reports from 2001 to 2006:

 

2001:

  • 2001 Report did NOT contain a table for the total number of recruited employees differentiated by occupational category, race and gender

2002:

  • Total number of employees by occupational category, race and gender data table. (All employers) the totals differ from real totals. (Addition error)
  • Total number of employees recruited by occupational category, race and gender data table does NOT show non-permanent employees and totals provided differ from real totals. (Addition error)
  • Total number of employees promoted by occupational category, race and gender data table does NOT show non-permanent employees and totals provided differ from real totals. (Addition error)
  • Total number of employees trained by occupational category, race and gender data table – the totals provided differ from real totals.(Addition error)

 

2003:

  • Total number of employees recruited by occupational category, race and gender data table does NOT show non-permanent employees.
  • Total number of employees promoted by occupational category, race and gender data table does NOT show non-permanent employees.

2004:

  • Total number of employees by occupational category, race and gender data table NOT given in 2004 report (There were no figures).
  • Total number of employees recruited by occupational category, race and gender data table does NOT show non-permanent employees.
  • Total number of employees promoted by occupational category, race and gender data table does NOT show non-permanent employees.

 

 

2005:

  • Total number of employees recruited by occupational category, race and gender data table does NOT show non-permanent employees.
  • Total number of employees promoted by occupational category, race and gender data table does NOT show non-permanent employees.

2006:

  • Total number of employees recruited by occupational category, race and gender data table - totals provided differ from real totals.(Addition error)

 

All the reports from 2001 to 2006 contain numerous computation and numerical errors, but this report uses only the actual data (none any of the totals and percentages in the Employment Equity Reports) and new totals and percentages were calculated to eliminate all the mistakes shown above.

 

In addition to the mathematical inconsistencies, the reports contain numerous other inconsistencies. In the first place, the reports from 2001 to 2006 did not use the same format and used different Occupational Level categories. For example, an analysis of the Employment Equity Reports does not allow for comparisons from 2001 to 2006, because some of the reports use different types of data or different types of data sets.

 

 

3. Comparisons from Employment Equity Reports from 2001 to 2006

 

As indicated above, it is virtually impossible to extrapolate comparisons from the Employment Equity Reports – but the Employment Equity Commission nevertheless continues to do so. Even the way in which the Commission uses the statistics is selective. What follows is a look at the Employment Equity Reports, warts and all.

 

3.1 Top management employees

 

The percentages below apply to males and females per race of the total number of employees in this occupational group.  

 

 

Table 15

Top Management Employees

 

Male

Female

 

African

Coloured

Indian

Total Black

White

African

Coloured

Indian

Total Black

White

2001

5,37%

2,20%

3,10%

10,67%

78,04%

1,50%

0,31%

0,31%

2,13%

9,17%

2002

7,96%

2,74%

4,40%

15,10%

71,05%

2,04%

0,74%

0,65%

3,43%

10,42%

2003

11,22%

3,07%

4,20%

18,49%

67,48%

3,66%

0,85%

0,74%

5,25%

8,78%

2005

13,25%

2,72%

4,71%

20,68%

62,74%

4,67%

1,03%

0,94%

6,64%

9,94%

2006

8,37%

2,68%

4,50%

15,55%

60,21%

2,91%

2,02%

1,67%

6,61%

14,70%

 

Total black representation at top management level in 2006 is therefore approximately 22%.

 

Analysing information from 367 JSE-listed companies shows that 1 023 out of 4 311 (or 24%) of company directors are black.

 

Statistics South Africa’s Household Survey shows that 42% of legislators, senior officials and managers are black.

 

According to the African Advertising Research Foundation (AMPS Surveys from 1997-2006), there have been huge changes in senior positions in South Africa.

 

Table 16

Occupation

African

Coloured

Indian

White

1997

Private sector top management

8 766

1 238

2118

30 876

Registered engineer

0

0

0

33 751

2006

Private sector top management

28 658

4 779

1 279

22 758

Registered engineer

2 937

446

0

10 154

  Source: SAARF (1997 and 2006)

This table shows tremendous growth in African representation at senior levels in the private sector. In number terms, the private sector saw, between 1997 and 2006, an increase in senior black management from 8 766 tot 28 658. This represents 230% growth. White senior management in the private sector declined from 30 876 to 22 758, representing a 26,29% decline.

·         Top management employees % change from 2001-2006 (EE reports)

 

White female top management employees: From 2001 to 2006, the number of white females grew by 60,31%, with the only big change coming in 2006 when white female top management grew from 9,94% (2005) to 14,7% (2006) of the total number of top management employees. In real terms this equals roughly 1 200 females. (See Table 17)

 

Total black top management employees: The total number of black females increased by 210,87% from 2001 to 2006. (Table 17)

 

White male top management employees: White male representation decreased by 22,85% between 2001 and 2006. (Table 17)  

 

Total black male top management employees: The total number of black males increased by 45,80% from 2001 to 2006. (Table 17)

 

Table 17

Top Management Employees % change

 

Male

Female

 

African

Coloured

Indian

Total Black

White

African

Coloured

Indian

Total Black

White

2001-2006

55,99%

21,95%

45,06%

45,80%

-22,85%

94,35%

545,43%

433,00%

210,87%

60,31%

 

 

 

 

 

3.2 Senior management employees

The percentages below are those of males and females per race of the total number of employees (male and female) in this occupational group.

 

 

 

 

Table 18

Senior Management Employees

 

Male

Female

 

African

Coloured

Indian

Total Black

White

African

Coloured

Indian

Total Black

White

2001

6,83%

2,99%

2,92%

12,73%

69,53%

2,12%

0,92%

0,61%

3,64%

14,10%

2002

8,19%

3,69%

5,02%

16,90%

61,58%

2,57%

1,39%

1,27%

5,23%

16,29%

2003

10,18%

4,35%

5,35%

19,88%

57,76%

4,00%

2,02%

1,40%

7,42%

14,94%

2005

10,29%

4,34%

5,42%

20,04%

56,32%

4,20%

1,72%

1,60%

7,52%

16,12%

2006

9,84%

3,73%

5,41%

18,97%

51,92%

3,62%

2,14%

2,29%

8,06%

18,97%

 

 

White female senior management employees: The number of white females increased by 34,39% from 2001 to 2006. (See table 18;19)

 

Total black female senior management employees: Total number of black females increased by 121,50% during the same period (from 2001 to 2006). (See Table 18;19)

 

White male senior management employees: The number of white males declined by 25,32% between 2001 and 2006.  (See Table 18;19)

 

Total black male senior management employees: Total number of black males increased by 49,03% during the same period. (See Table 18;19)

 

 

Table 19

Senior Management Employees % change

 

Male

Female

 

African

Coloured

Indian

Total Black

White

African

Coloured

Indian

Total Black

White

2001-2006

44,05%

24,97%

85,34%

49,03%

-25,32%

71,23%

134,37%

277,55%

121,50%

34,49%

 

 

 

 


 

 

 

 

3.3. Professionally qualified and experienced specialists and mid-management employees

 

The percentages below are those for males and females (per race) of the total number of employees (male and female) in this occupational group.  

 

Table 20

Professionally Qualified and Experienced Specialists and Mid-Management Employees

 

Male

Female

 

African

Coloured

Indian

Total Black

White

African

Coloured

Indian

Total Black

White

2001

8,99%

3,94%

3,92%

16,84%

52,84%

3,78%

2,68%

1,61%

8,06%

22,26%

2002

11,30%

5,41%

4,92%

21,63%

47,42%

4,92%

2,81%

2,11%

9,84%

21,11%

2003

21,31%

3,91%

3,92%

29,15%

34,35%

17,74%

2,21%

1,64%

2,58%

14,92%

2005

14,58%

5,89%

5,31%

25,79%

41,47%

6,86%

3,40%

2,64%

12,90%

19,85%

2006

12,96%

4,64%

5,08%

22,67%

40,07%

7,18%

3,42%

3,20%

13,80%

22,07%

 

 

 

·         Professionally qualified and experienced specialists and mid-management employees, % change from 2001-2006 (EE reports):

 

White female professionally qualified and experienced specialists and mid-management employees: The number of white females declined by 0,86% from 2001 to 2006. (See Table 20;21)

 

Total black female professionally qualified and experienced specialists and mid-management employees: Total number of black females increased by 71,17% from 2001 to 2006. (See Table 20;21)

 

White male professionally qualified and experienced specialists and mid-management employees: White male numbers decreased by 24,17% from 2001 to 2006. (See Table 20;21)

 

Total black male professionally qualified and experienced specialists and mid-management employees: Total representation of black males increased by 34,60% from 2001 to 2006. (See Table 20;21)

 

 

 

 

 

Table 21

Professionally Qualified and Experienced Specialists and Mid-Management Employees % change

 

Male

Female

 

African

Coloured

Indian

Total Black

White

African

Coloured

Indian

Total Black

White

2001-2006

44,14%

17,82%

29,60%

34,60%

-24,17%

90,13%

27,80%

98,91%

71,17%

-0,86%

 

 

 

 

3.4. Skilled technical and academically qualified workers, junior management, supervisors, foremen, and superintending employees:

 

The percentages below are those for males and females (per race) of the total number of employees in this occupational group.  

 

Table 22

Skilled Technical and Academically Qualified Workers, Junior Management, Supervisors, Foremen, and Superintendents Employees

 

Male

Female

 

African

Coloured

Indian

Total Black

White

African

Coloured

Indian

Total Black

White

2001

19,26%

4,41%

4,62%

28,29%

21,90%

22,19%

4,43%

4,45%

31,06%

18,75%

2002

20,72%

7,33%

4,30%

32,34%

24,02%

15,09%

6,75%

2,71%

24,56%

19,08%

2003

23,39%

6,59%

3,90%

33,89%

21,93%

18,70%

6,33%

2,87%

27,90%

16,29%

2005

23,44%

8,37%

3,79%

35,59%

21,24%

15,39%

8,64%

2,45%

26,48%

16,69%

2006

29,23%

6,82%

3,80%

39,85%

23,20%

10,03%

5,77%

2,76%

18,56%

17,18%

 

·         Skilled technical and academically qualified workers, junior management, supervisors, foremen and superintending employees, % change from 2001-2006:

 

White female skilled technical and academically qualified workers, junior management, supervisors, foremen, and superintending employees: White female representation declined by 8,40% from 2001 to 2006. (See Table 22;23)

 

 

Total black female skilled technical and academically qualified workers, junior management, supervisors, foremen and superintending employees: Total black female representation declined by 40,25% from 2001 to 2006. In spite of this substantial decline, black females still comprised a larger proportion of the total skilled technical and academically qualified workers, junior management, supervisors, foremen, and superintending employees than the white females. (See Table 22;23)

 

White male skilled technical and academically qualified workers, junior management, supervisors, foremen and superintending employees: White male representation increased by 5,92% from 2001 to 2006. (See Table 22;23)

 

Total black male skilled technical and academically qualified workers, junior management, supervisors, foremen and superintending employees: Total black male representation increased by 40,88% from 2001 to 2006, but still constituted a larger proportion of the total skilled technical and academically qualified workers, junior management, supervisors, foremen, and superintending employees than the white men. (See Table 22;23)

 

Table 23

Skilled Technical and Academically Qualified Workers, Junior Management, Supervisors, Foremen, and Superintendents Employees % change

 

Male

Female

 

African

Coloured

Indian

Total Black

White

African

Coloured

Indian

Total Black

White

2001-2006

51,79%

54,85%

-17,86%

40,88%

5,92%

-54,81%

30,34%

-37,91%

-40,25%

-8,40%

 

 

 

3.5   Semi-skilled and discretionary decision-making employees:

 

The percentages seen below are those for males and females (per race) of the total number of employees in this occupational group.  

 

Table 24

Semi-Skilled and Discretionary Decision Making Employees

 

Male

Female

 

African

Coloured

Indian

Total Black

White

African

Coloured

Indian

Total Black

White

2001

42,26%

6,59%

2,38%

51,23%

5,51%

19,02%

8,76%

2,20%

29,98%

13,27%

2002

45,97%

8,17%

2,89%

57,03%

6,84%

15,92%

7,70%

2,37%

25,99%

10,13%

2003

47,98%

7,91%

2,84%

58,73%

5,92%

15,49%

8,12%

2,45%

26,06%

9,29%

2005

46,09%

8,33%

2,66%

57,08%

6,27%

16,54%

8,82%

2,45%

27,80%

8,85%

2006

48,37%

6,69%

1,90%

56,96%

4,22%

15,94%

7,35%

2,25%

25,54%

7,67%

 

·         Semi-skilled and discretionary decision-making employees’ % change from 2001-2006:

 

White female semi-skilled and discretionary decision-making employees: White female representation declined by 42,25% from 2001 to 2006. (See Table 24;25)

 

Total black female semi-skilled and discretionary decision-making employees: Total black female representation declined by 14,78% from 2001 to 2006, although the group still constituted a much larger proportion of the total semi-skilled and discretionary decision-making employees than the white females. (See Table 24;25)

 

White male semi-skilled and discretionary decision-making employees: White male representation declined by 23,46% from 2001 to 2006. (See Table 24;25)

 

Total black male semi-skilled and discretionary decision-making employees: Total black male representation increased by 11,17% from 2001 to 2006, but this group still constitutes a much larger proportion of the total semi-skilled and discretionary decision-making employees than white males. (See Table 24;25)

 

Table 25

Semi-Skilled and Discretionary Decision-Making Employees % change

 

Male

Female

 

African

Coloured

Indian

Total Black

White

African

Coloured

Indian

Total Black

White

2001-2006

14,46%

1,50%

-20,38%

11,17%

-23,46%

-16,18%

-16,13%

2,69%

-14,78%

-42,25%

 

 

 

3.6   Unskilled and defined decision-making employees:

 

The percentages below are those for males and females (per race) of the total number of employees in this occupational group.  

 

 

 

Table 26

Unskilled and Defined Decision-Making Employees

 

Male

Female

 

African

Coloured

Indian

Total Black

White

African

Coloured

Indian

Total Black

White

2001

73,61%

4,18%

0,53%

78,32%

1,12%

15,14%

4,21%

0,45%

19,80%

0,77%

2002

61,47%

6,16%

0,91%

68,54%

1,35%

22,61%

5,78%

0,81%

29,20%

0,90%

2003

62,12%

5,81%

1,13%

69,06%

1,41%

21,92%

5,74%

0,93%

28,59%

0,94%

2005

59,77%

6,41%

0,5%

67,03%

1,09%

23,47%

6,87%

0,83%

31,16%

0,71%

2006

54,80%

5,31%

0,50%

60,61%

0,87%

23,24%

5,83%

0,43%

29,50%

0,48%

 

 

 

 

·         Unskilled and defined decision-making employees % change from 2001-2006:

 

White female unskilled and defined decision-making employees: White female representation declined by 36,98%. (See Table 26;27)

 

Total black female unskilled and defined decision-making employees: Total black female representation increased by 49,03% from 2001 to 2006 and this group constitutes a much larger proportion of the total unskilled and defined decision-making employees than white females. (See Table 26;27)

 

White male unskilled and defined decision-making employees: White male representation declined by 22,30% from 2001 to 2006. (See Table 26;27)

 

Total black male unskilled and defined decision-making employees: Total black male representation declined by 22,62% from 2001 to 2006 (almost the same percentage as that of white males), although the group still constitutes a much larger proportion of the total unskilled and defined decision-making employees than white males. (See Table 26;27)

 

Table 27

Unskilled and Defined Decision-Making Employees % change

 

Male

Female

 

African

Coloured

Indian

Total Black

White

African

Coloured

Indian

Total Black

White

2001-2006

-25,55%

26,86%

-5,91%

-22,62%

-22,30%

53,54%

38,60%

-4,94%

49,03%

-36,98%

 

 

 

 

 

 

3.7 Grand total of all employees

 

The percentages below are those for males and females (per race) of the total number of employees in this occupational group.  

 

 

 

 

Table 28

Grand Total Employees

 

Male

Female

 

African

Coloured

Indian

Total Black

White

African

Coloured

Indian

Total Black

White

2001

39,65%

5,13%

2,66%

47,44%

13,95%

17,92%

5,98%

2,30%

26,19%

12,42%

2002

40,29%

7,09%

2,81%

50,19%

13,18%

17,56%

6,80%

1,98%

26,35%

10,29%

2003

40,89%

6,63%

2,89%

50,40%

12,56%

18,76%

6,64%

2,12%

27,52%

9,52%

2005

40,95%

7,60%

2,63%

51,18%

11,22%

18,69%

7,88%

1,98%

28,55%

9,05%

2006

40,71%

6,08%

2,27%

49,06%

11,69%

17,42%

6,14%

1,95%

25,51%

9,34%

 

 

 

·         Grand total of employees % change from 2001-2006:

 

Female grand total (all occupations): White female representation declined by 24,83% from 2001 to 2006 and total black female representation declined by only 2,75% during the same period. Total black female representation constitutes a much larger proportion of the grand total of employees than white female representation. (See Table 28;29)

 

Male grand total (all occupations): White male representation declined by 16,6% and total black male representation increased by 3,42% from 2001 to 2006. Total black male representation constituted a much larger proportion of the grand total of employees than white men. (See Table 28;29)

 

Table 29

Grand Total Employees % change

 

Male

Female

 

African

Coloured

Indian

Total Black

White

African

Coloured

Indian

Total Black

White

2001-2006

2,68%

18,65%

-14,80%

3,42%

-16,16%

-2,75%

2,64%

-15,31%

-2,62%

-24,83%

 

 

:

 

 

4. Other databases

 

Other databases were also analysed in an attempt to measure the progress of employment equity in South Africa.

 

4.1 South African Advertising Research Foundation (AMPS Surveys from 1997-2006)

 

The AMPS survey is national survey that represents the profile of the major demographic breakdowns and is based on personal interviews (CAPI: Computer Assisted Personal Interviews) with citizens of 16 years and older. These databases exhibit exactly the same trends as those in the Employment Equity Report, i.e. a strong decline in white representation.

 

4.1.1          Total Occupations % of all employees:

 

The percentages below are the percentages for males and females (per race) of the total number of employees.  

 

Table 30

Male & Female

Total Occupation

 

1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

African

65,47%

66,09%

66,48%

68,06%

62,00%

65,89%

66,65%

67,15%

67,59%

68,75%

Coloured

10,13%

10,21%

9,56%

9,64%

12,49%

10,93%

10,58%

10,83%

11,05%

10,76%

Indian/Asian

2,99%

2,81%

3,04%

3,05%

3,27%

3,03%

3,07%

3,05%

3,07%

2,91%

White

21,41%

20,89%

20,92%

19,25%

22,24%

20,14%

19,70%

18,96%

18,29%

17,58%

Total Black

78,59%

79,11%

79,08%

80,75%

77,76%

79,86%

80,30%

81,04%

81,71%

82,42%

 

 

·         Total occupations % change 1997-2006:

 

White male & female all occupations: White males and females declined by 17,90% from 1997 to 2006. (See Table 30)

 

Total black male & female all occupations: Black males and females increased by 4,88% from 1997 to 2006 and constituted a much larger proportion of all employees in all occupations than white males and females. (See Table 30)

 

 

4.1.2          Professional technical occupations % of all employees:

 

The percentages below are those for males and females (per race) of the total number of employees in this occupational group.  

 

Table 31

Male & Female

Professional Technical  Occupation

 

1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

African

48,92%

48,46%

49,39%

54,46%

54,95%

53,24%

52,30%

53,94%

57,98%

57.94%

Coloured

8,74%

7,88%

7,52%

7,96%

8,63%

10,76%

8,90%

8,94%

9.60%

9.65%

Indian/Asian

3,53%

4,23%

3,52%

3,54%

3,51%

3,31%

3,19%

3,86%

3.31%

3.54%

White

38,81%

39,42%

39,57%

34,05%

32,91%

32,69%

35,61%

33,26%

29.12%

28.87%

Total Black

61,19%

60,58%

60,43%

65,95%

67,09%

67,31%

64,39%

66,74%

70.88%

71.13%

 

 

4.1.3          Professional technical occupations % change 1997-2006:

 

White male and female professional technical employees: White males and females declined by 25,61% from 1997 to 2006.  (See Table 31)

 

Total black male & female professional technical employees: Total black male and female representation increased by 16,25% from 1997 to 2006 and constitute a much larger proportion of the total professional technical employees than white males and females.  (See Table 31)

 

 

 

4.1.4          Administrative managerial occupations % of all employees:

 

The percentages below are those for males and females (per race) of the total number of employees in this occupational group.  

 

 

 

 

Table 32

Male & Female

Administrative Managerial Occupations

 

1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

African

24,08%

16,82%

13,84%

20,35%

19,61%

28,48%

25,11%

26,19%

30,37%

35,38%

Coloured

5,38%

6,85%

7,55%

8,26%

6,91%

7,83%

6,05%

6,90%

7,53%

10,99%

Indian/Asian

6,80%

5,92%

7,23%

7,67%

8,29%

6,74%

5,61%

6,19%

6,85%

6,89%

White

63,74%

70,40%

71,38%

63,72%

65,19%

56,96%

63,23%

60,71%

55,25%

46,74%

Total Black

36,26%

29,60%

28,62%

36,28%

34,81%

43,04%

36,77%

39,29%

44,75%

53,26%

 

4.1.5          Administrative managerial occupations % change 1997-2006:

 

White male and female administrative managerial employees: White male and female representation declined by 26,67% from 1997 to 2006. (See Table 32)

 

Total black male & female administrative managerial employees: Black male and female representation increased by 46,88% from 1997 to 2006 and they constituted a much larger proportion of the total number of administrative managerial employees than white males or females in 2006. (See Table 32)

 

 

4.1.6          Clerical occupations % of all employees:

 

The percentages below are those for males and females (per race) of the total number of employees in this occupational group.  

 

Table 33

Male & Female

Clerical Occupation

 

1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

African

60,76%

62,68%

64,22%

67,00%

63,72%

63,01%

66,54%

66,16%

64,99%

65,53%

Coloured

7,56%

7,62%

7,59%

7,85%

8,44%

9,59%

8,12%

8,24%

8,92%

9,24%

Indian/Asian

4,20%

3,92%

4,06%

3,87%

4,75%

4,13%

3,97%

4,06%

4,72%

4,31%

White

27,49%

25,78%

24,13%

21,28%

23,09%

23,27%

21,37%

21,54%

21,37%

20,92%

Total Black

72,51%

74,22%

75,87%

78,72%

76,91%

76,73%

78,63%

78,46%

78,63%

79,08%

 

4.1.7          Clerical occupations % change 1997-2006:

 

White male and female clerical employees: White men & women declined by 23,89% from 1997 to 2006. (See Table 33)

 

Total black male and female clerical employees: Representation by black males and females increased by 9,06% from 1997 to 2006 and this group constituted a much larger proportion of the total number or employees in clerical occupations than white males and females in 2006. (See Table 33)

 

 

 

 

 

 

5.1 “black diamonds” on the move in 2007

 

If any doubts remain about the success of affirmative action, a look at the growth of the black middle class will quickly dispel them. The reference data was drawn from a comprehensive study of the black middle class, undertaken by UCT/Unilever Institute of Strategic Marketing and TNS Research Surveys.

 

 

 

 

 

5.2.1 What is a “black diamond”?

 

“Black diamonds” are essentially:

 

(i)                   black South Africans only;

(ii)                 wealthy/salaried, in “suitable” occupations;

(iii)                well-educated;

(iv)                also young people living in middle class circumstances;

(v)                  own/acquiring homes, cars, household goods;

(vi)                aspirations, confidence in the future;

(vii)               creditworthiness[1]

 

5.2.2 Numbers

 

“Black diamond” numbers are:

 

 

 

Graph 1: (Source “black diamonds” on the move survey 2007)

 

  • South Africa’s black middle class, increasingly referred to as “black diamonds”, has grown by an astonishing 30%. “Black diamonds” now comprise an estimated 2,6 million people, against 2 million in 2005. “Black diamonds” constitute 12% of the country’s black population.
  • It should be kept in mind that the total black population has only grown by 1, 82%, while the other population groups have not shown any growth.
  • The conclusion is that there has been a tremendous shift in regard to the growth of the “black diamond” population in such a short period of time.

 

Why the fast growth in the numbers of “black diamonds”?

 

  • BEE is one of the primary forces driving “black diamonds” growth.
  • As a result of BEE and AA, they have grown rich overnight and have found it easier to achieve high positions.

 

General:

 

  • Worldwide, middle class populations are mainly third or fourth generation, while South Africa’s black population has a first generation middle class as a result of BEE as the primary force, and of economic growth.
  • It is important to bear in mind that these 2,6 million made a huge leap from poverty to riches.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

5.2.3 The value

 

Value of buying power:

 

Graph 2: Annual claimed buying power based on the last quarter of 2005 and first quarter of 2007.

Source: Black diamond on the move survey.

 

                                                                                                                                          

Graph 3: Percentage of buying power based on the last quarter of 2005 and first quarter of 2007.

Source: Black diamond on the move survey.

 

 

 

 

Interpretation of the buying power data:

 

  • “black diamonds” are worth R180 billion, or 28% of the total South Africa buying power
  • The buying power of the total SA population in the first quarter of 2007 was R640 billion a year, against R600 billion in the last quarter of 2005. This reflects growth of 6,7%.
  • The figure for whites improved only minimally, from R230 billion to R235 billion (2,17%).
  • The total for all blacks grew from R300 billion to R335 billion, or 11,67%
  • At the cutting edge of economic progress, the buying power of “black diamonds” grew from R130 billion to R180 billion in this period, or an astonishing 38%.  

 

(i)                  The reason why this growth is so astonishing is that the numbers of “black diamonds” only increased by 30% in the same period. The reason for the higher growth in the buying power is simply that the “black diamonds” are getting better jobs and better salaries because of BEE  and AA.

 

·         “Black diamonds” (12% of all blacks) now account for 54% of black buying power.

·         In 2005, 10%  were  responsible for 43% of black buying power

·          The “black diamonds” are responsible for the 28% of South Africa’s total spending. 

·         It is thought that by 2009, the “black diamonds” will have overtaken white spending (currently estimated at R235 billion).

 

5.2.4 Income

 

Value of income:

Graph 4: Average monthly personal income based on the last quarter of 2005 and first quarter of 2007.

Source: Black diamond on the move survey.

 

Graph 5: Percentage change in average monthly personal income based on the last quarter of 2005, and first quarter of 2007.

Source: Black diamond on the move survey.

 

·         Although relatively affluent and well-educated, the “black diamonds” earn an average monthly personal income (after tax) of R6 100. [2]

·         The figures do not tell the whole story of the average monthly income of “black diamonds”. Consider the following: [3]

 

(i)                   The average loan registered at the deeds office is worth about R500 000. The monthly

repayment, at an average 12,5% mortgage rate, would be just under R5 700, according to Standard Bank.

(ii)                  The bank would grant a loan of this size only to a household earning at least 

R16 000 a month, according to the bank’s economist, Elna Moolman.

(iii)                Bear in mind that most households have more than one income

(iv)                 According to the study, 70% of households have more than one breadwinner, and 

20% have more than two contributors to household income.

(v)      7% of households consist of five people – two adults and three dependents who have to be clothed, fed, educated, transported etc.

(vi)    From the above information, let us assume this household has an

average monthly income of R11 200 after tax. Keep in mind that a household earning R12 000 would be able to afford a R340 000 bond.

 

·         The above scenario is not far-fetched if one considers that the more established of the “black diamonds” earn more than R15 000 per month and have shown a definite move towards the suburb from the township.

·         One can therefore conclude that the “black diamonds” earn between R6 100 and R15 000 per month.

 

5.4.5          Moving to the suburbs

 

Graph 6: Based on 2005 and 2006.

Source: Black diamonds on the move survey.

 

 

Graph 7: Based on 2005 and 2006.

Source: Black diamond on the move survey

 

  • A closer look at graphs 6 and 7 shows accelerated movement of “black diamonds” to the suburbs, from the last quarter of 2005 until the first quarter of 2007.
  • More than 12 000 black diamond families – or 50 000 people – are moving from the townships to the suburbs of South Africa’s metro areas each month, according to the black diamond survey.
  • Although “black diamonds” remain fiercely loyal to township life and communities, they move to the suburbs to show that they have succeeded and as an investment. This is also reflected in the survey, in which 85% of “black diamonds” said that it was important to buy property in an expensive area as an investment.

 

5.2.5 Segmentation of “black diamonds”

 

According to the study, “black diamonds” can be divided in four categories:

 

(i)   Mzansi Youth;

(i)      Start-me-ups;

(ii)    Young families;

(iii)   Established people

 

Black Diamond Segmentation

 

Mzansi Youth

Start-me-ups

Young families

Established

Value:

 

R7 billion

 

Value:

 

R37 billion

Value:

 

R49 billion

Value:

 

R87 billion

Figures:

 

470 000

 

Figures:

 

490 000

Figures:

 

710 000

Figures:

 

940 000

Percentage of “black diamonds”’:

 

18%

 

Percentage of “black diamonds”’:

 

19%

 

Percentage of “black diamonds”’:

 

27%

 

Percentage of “black diamonds”’:

 

36%

 

Description:

 

Young females and females still living at home

Description:

 

Young ambitious single professionals – mostly males

 

Description:

 

Parents of young children – female bias

 

Description:

 

Older, stable family men and women, who are generally married.

 

 

Table 2: Segmentation of “black diamonds” (Source: Black diamond on the move survey)

 

 

In the period under review all segments have grown in actual numbers:

 

(i)                   Mzansi Youth are up from 350 000 to 470 000, or  34% growth ;

(ii)                 Start-me-ups have gone from 430 000 to 490 000, or 13,95% growth ;

(iii)                Young families up from 440 000 to 710 000, or 61,36% growth ;

(iv)                The established group remains the biggest group and has gone from 780 000 to

940 000 or 20,51%.

 

5.2.6 Conclusion:

 

  • The conclusion is that the “black diamonds” are alive and growing at a pace that no one could have imagined. The “black diamond” middle class is also beginning to mature.
  • The numbers are growing from outside, while their value is growing from within (thanks to better positions and salaries).
  • For the government and country as a whole this is a positive development in terms of economic growth and the redistribution of wealth, considering that the “black diamonds” have come out of poverty and are already a force to be reckoned with, thanks to BEE and affirmative action.
  • There is also an identity construction taking place in South Africa. The current struggle is about race, but in the near future the struggle will be about class. Remember that the majority of the black population is supposed to benefit, and not just a small group.

 

7. Sources

 

  • Commission for Employment Equity. Annual Report 2001/2002. Department of Labour.
  • Commission for Employment Equity. Annual Report 2002/2003. Department of Labour.
  • Commission for Employment Equity. Annual Report 2004/2005. Department of Labour.
  • Commission for Employment Equity. Annual Report 2005/2006. Department of Labour.
  • Commission for Employment Equity. Annual Report 2006/2007. Department of Labour.

 

  • Employment Equity Registry 2002. Department of Labour.
  • Employment Equity Registry 2003. Department of Labour.
  • Employment Equity Registry 2004. Department of Labour.
  • Employment Equity Registry 2005. Department of Labour.

 

  • General Household Survey 2002.
  • General Household Survey 2003.
  • General Household Survey 2004.
  • General Household Survey 2005.
  • General Household Survey 2006.

 

  • SAARF and AMPS Survey

 

  • “Black Diamonds” on the Move Survey

 

  • Public Service Commission: 2007 State of the Public Service Report
  • Public Service Commission: 2000 State of Representativeness in the Public Service
  • Statistics South Africa
  • McGregor BFA

 

 

Research and data compiled by: Dr Dirk Herman (Solidarity: Research & Development Department)

                                                              Tiaan Du Plooy (Solidarity: Economics Department)

                                                              Francois Calldo (Solidarity: Labour Relations Department)

 

 

 

 

 

 

 

 

 


 

 



[1] Allows the “black diamonds” to play catch-up with their white counterparts.

[2] The survey that was done is net broad and includes lower-paid white collar civil servants.

 

[3] Source: Business Report, 28 May 2007