Retirement Funds Quantification and Trustees Skills … Life to Ideas Directors: Emmanuel Damoulakis, Lundi Mbokodi, Lesego Molwantwa-Mbatha, Vuyolwethu Nogantshi, Lungile Thabo Twalo

Report

Date 30 June 2006

To INSETA Steering Commitee

From Endeleo Investments and Trading

Endeleo Investments and Trading CC.

Breathing Life to Ideas

CONFIDENTIAL

Retirement Funds Quantification

and

Trustees Skills Audit and Quantification

Steering Committee Report


Directors: Emmanuel Damoulakis, Lundi Mbokodi, Lesego Molwantwa-Mbatha, Vuyolwethu Nogantshi, Lungile Thabo Twalo Reg No. 2004/027360/23 Email: [email protected] Fax: +27 866 888 33 6 Postal address: P.O.Box 2106, Saxonwold, 2132, SOUTH AFRICA

2

Table of contents Table of contents ............................................................................................................................ 2 Index of tables ................................................................................................................................ 4 Index of figures ............................................................................................................................... 6 Executive Summary........................................................................................................................ 7 Introduction..................................................................................................................................... 9 Project objectives ......................................................................................................................... 10 Project plan................................................................................................................................... 11

Phase 1: Project Tendering Phase........................................................................................ 11 Phase 3: Project Training Phase........................................................................................... 13 Phase 4: Project Operational Phase ..................................................................................... 14 Phase 5: Project Close-Down Phase .................................................................................... 15

Methods........................................................................................................................................ 19 Distribution ................................................................................................................................ 19

Administrators ....................................................................................................................... 19 Financial Services Board....................................................................................................... 20 Media formats........................................................................................................................ 20 Affiliated bodies ..................................................................................................................... 20 Postal communication ........................................................................................................... 20 Skills Development Facilitators ............................................................................................. 21 General.................................................................................................................................. 21

Support Structures .................................................................................................................... 22 Weekly reporting meetings.................................................................................................... 22 Regular steering committee meeting..................................................................................... 22

Project contingencies ................................................................................................................... 23 Data .......................................................................................................................................... 23 Incentives.................................................................................................................................. 23

Project guidelines ......................................................................................................................... 25 Compile a list of all fund trustees .......................................................................................... 25 Identify each Trustee’s level of formal education and training .............................................. 25 Identify each Trustee’s years of experience as a trustee ...................................................... 25 Identify each fund’s economic sector, e.g. Construction, manufacturing, etc ....................... 25 Using a 30% sample of identified trustees (which sample shall fulfil the national demographic profile), quantify these trustees’ self-identified training needs............................................... 25

Project Scope Revision ................................................................................................................ 27 Key findings - Retirement Funds and Administration Methods..................................................... 28

Total funds by date of data and administration method ............................................................ 28 Total funds by administration method including funds not supervised under the Pension Funds Act............................................................................................................................................. 30 Geographic distribution of funds ............................................................................................... 32 Geographic distribution of fund administrators ......................................................................... 32 Distribution of fund economic sector......................................................................................... 34 Distribution of fund economic sector by province ..................................................................... 37

Key findings – Retirement Fund Trustees .................................................................................... 40 Analysis of explanatory data ..................................................................................................... 40

Index of variable coding: ....................................................................................................... 42 Summary statistics of trustees .............................................................................................. 43 Analysis of explanatory variables .......................................................................................... 54 Distributions of trustees – final results................................................................................. 103



3

Conclusions ................................................................................................................................ 137 Recommendations...................................................................................................................... 139 Appendix – Determining a suitable sample size and population ................................................ 140

Introduction ............................................................................................................................. 140 Sampling theory ...................................................................................................................... 140 Relevance to this project......................................................................................................... 141 Determining the total number of trustees................................................................................ 143 Conclusions ............................................................................................................................ 144

Appendix II – Endeleo Proposal ................................................................................................. 145 Executive Summary ................................................................................................................ 145 Endeleo Proposal.................................................................................................................... 146

General requirements for tender ......................................................................................... 146 Endeleo solution.................................................................................................................. 146 Notes on general requirements ........................................................................................... 147



4

Index of tables Table 1: Total funds by date of data and administration method.................................................. 28 Table 2: Total funds by administration method including funds not supervised under the Pension

Funds Act .............................................................................................................................. 30 Table 3: Total funds by administrator ........................................................................................... 31 Table 4: Geographic distribution of funds..................................................................................... 32 Table 5: Geographic distribution of fund administrators ............................................................... 32 Table 6: Distribution of fund economic sector .............................................................................. 34 Table 7: Distribution of fund economic sector by province ........................................................... 38 Table 8: 95.0% confidence intervals for each explanatory variable ............................................. 43 Table 9: Population group frequency table................................................................................... 45 Table 10: Correlations between explanatory variables................................................................. 50 Table 11: Principal Component analysis of the explanatory variables ......................................... 52 Table 12: Analysis of Variance for Legal Aspects and Legislation ............................................... 54 Table 13: Table of Least Squares Means for Legal Aspects and Legislation with 95.0 Percent

Confidence Intervals.............................................................................................................. 55 Table 14: Analysis of Variance for Benefits offered and membership.......................................... 58 Table 15: Table of Least Squares Means for Benefits Offered and Membership with 95.0 Percent

Confidence Intervals.............................................................................................................. 58 Table 16: Analysis of Variance for Service Providers................................................................... 61 Table 17: Table of Least Squares Means for Service Providers with 95.0 Percent Confidence

Intervals................................................................................................................................. 61 Table 18: Analysis of Variance for Investment Management ....................................................... 64 Table 19: Table of Least Squares Means for Investment Management with 95.0 Percent

Confidence Intervals.............................................................................................................. 64 Table 20: Analysis of Variance for Financial Aspects................................................................... 67 Table 21: Table of Least Squares Means for Financial Aspects with 95.0 Percent Confidence

Interval................................................................................................................................... 67 Table 22: Analysis of Variance for Dealing with Surplus and Legislation related to surplus ........ 70 Table 23: Table of Least Squares Means for Dealing with Surplus and Legislation related to

surplus with 95.0 Percent Confidence Intervals .................................................................... 70 Table 24: Analysis of Variance for Interpreting financial state...................................................... 73 Table 25: Table of Least Squares Means for Interpreting financial statements with 95.0 Percent

Confidence Intervals.............................................................................................................. 73 Table 26: Analysis of Variance for Retirement Fund governance ................................................ 76 Table 27: Table of Least Squares Means for Retirement Fund governance with 95.0 Percent

Confidence Intervals.............................................................................................................. 76 Table 28: Analysis of Variance for Legal Aspects and Legislation ............................................... 79 Table 29: Table of Least Squares Means for Legal Aspects and Legislation with 95.0 Percent

Confidence Intervals.............................................................................................................. 79 Table 30: Analysis of Variance for Benefits offered and membership.......................................... 82 Table 31: Table of Least Squares Means for Benefits Offered and Membership with 95.0 Percent

Confidence Intervals.............................................................................................................. 82 Table 32: Analysis of Variance for Service Providers................................................................... 85 Table 33: Table of Least Squares Means for Service Providers with 95.0 Percent Confidence

Intervals................................................................................................................................. 85 Table 34: Analysis of Variance for Investment Management ....................................................... 88 Table 35: Table of Least Squares Means for Investment Management with 95.0 Percent

Confidence Intervals.............................................................................................................. 88 Table 36: Analysis of Variance for Financial Aspects................................................................... 91



5

Table 37: Table of Least Squares Means for Financial Aspects with 95.0 Percent Confidence Interval................................................................................................................................... 91

Table 38: Analysis of Variance for Dealing with Surplus and Legislation related to surplus ........ 94 Table 39: Table of Least Squares Means for Dealing with Surplus and Legislation related to

surplus with 95.0 Percent Confidence Intervals .................................................................... 94 Table 40: Analysis of Variance for Interpreting financial statements............................................ 97 Table 41: Table of Least Squares Means for Interpreting financial statements with 95.0 Percent

Confidence Intervals.............................................................................................................. 97 Table 42: Analysis of Variance for Retirement Fund governance .............................................. 100 Table 43: Table of Least Squares Means for Retirement Fund governance with 95.0 Percent

Confidence Intervals............................................................................................................ 100 Table 44 - 139: Trustee skills and requirements distribution ...................................................... 105



6

Index of figures Figure 1: Distribution of funds by economic sector....................................................................... 35 Figure 2: Labour Force Survey (StatsSA) .................................................................................... 36 Figure 3: Population group bar chart ............................................................................................ 44 Figure 4: Trustee type pie chart.................................................................................................... 45 Figure 5: Trustee province bar graph ........................................................................................... 46 Figure 6: Trustee formal education graph .................................................................................... 47 Figure 7: Trustee experience graph ............................................................................................. 48 Figure 8: Experience vs. Formal Education bar graph ................................................................. 49 Figure 9: Scree plot of component eigenvalues ........................................................................... 53



7

Executive Summary

This is a final report of the findings of the Retirement Fund Trustees Training Survey and Skills

Audit conducted by Endeleo in the period beginning 1st May 2005 ending 30th June 2006.

The information presented in this document is as a result of a nationwide data collection

campaign through advertising and awareness campaigns focused on the retirement fund

community and securing the participation of stakeholder organisations.

Data was mainly collected in electronic format via Retirement Fund Administrators, Retirement

Fund Skills Development Facilitators and directly from the retirement funds. Presence on various

web sites and in print media has also aided data collection.

The data collected to-date with respect to the retirement funds and the retirement fund

administrators is comprehensive, although regular fluctuations in the industry will alter the profile.

The number of registered retirement funds in the South African Retirement Fund Industry was

taken to be 12,750 pension and provident funds and some 800 umbrella funds.

The data collected was also used to determine the size of the retirement fund trustee population

which is estimated to be approx 54,000 with more than half residing in the Gauteng province.

Due to industry, fund and trustee resistance, it was difficult to get large volumes of trustee data for

this survey. However, Endeleo was able to collect sufficient trustee data to make meaningful

analyses and inferences at a confidence level exceeding 90%.

The data collected to date resulted in a sample containing over 500 retirement funds and 1,400

trustee responses as at 12 June 2006.

The results were in line with intuitive thinking insofar as trends are concerned. Trustees with a

higher formal education tended to have higher levels of trustee related knowledge, as did trustees

with experience in trustee related activities. Both factors (education level & experience) were

observed to have a strong influence on trustee knowledge.

The ultimate aim of the project is to equip trustees with the tools they require to carry out their

duties effectively. It was therefore important to distinguish between the professional and



8

experienced trustees who do not require further training and trustees who may have not had an

opportunity to receive comprehensive training on or off the job in their experience as trustees.

The final set of results shown later in this report indicate the proportion of trustees that have a

certain level of training, but also go further to indicate the proportion of trustees requiring a certain

level of training given their current level. These proportions take into account the trustees not

requiring any further training.

An analysis of trustee training needs revealed that the majority required an intermediate level of

training, although, in some cases, this may have been less than their skill levels. This would

indicate a need for refresher training.

Further conclusions and recommendations based on the results are included in the final section

of the report.



9

Introduction In January of 2005, the INSETA issued a request for proposals for the Retirement Fund Trustee

Training - Quantification and Skills Audit. In April 2005 ENDELEO were officially appointed to

conduct this Retirement Fund Trustee Training - Quantification and Skills Audit on behalf of

INSETA.

The guidelines to be followed in the quantification and skills audit are listed below:

• Ascertain the retirement funds registered.

• Compile a list of all current registered retirement funds.

• Establish the number of fund trustees, both employer-nominated and employee-

nominated representatives per each individual fund.

• Compile a list of all fund Trustees.

• Identify each fund’s economic sector, e.g. Construction, manufacturing, etc.

• Identify who the fund administrators are per fund.

• Determine the physical location of both fund administrators and trustees per fund

(Employer- and employee- nominated).

• Compile fund Administrator’s contact details list per fund (Name, telephone/fax

number, e-mail, etc).

• Identify each Trustee’s level of formal education and training.

• Identify the level and extent of Trustee specific training that each trustee has

received.

• Identify each Trustee’s years of experience as a trustee.

• Using a 30% sample of identified trustees (which sample shall fulfil the national

demographic profile), quantify these trustees’ self-identified training needs.

This report aims to provide a final and comprehensive documentation of the methodologies,

challenges and results of Endeleo’s quantification and skills audit exercise.



10

Project objectives Retirement Fund and Trustee training was identified at the Growth and Development Summit

(GDS) as a specific and urgent priority for skills development. INSETA, as the Education and

Training Authority for Skills Development in the Insurance Sector, is tasked to conduct this urgent

skills need analysis.

The basic objective of this phase is:

To conduct the quantitative analysis of the Retirement Fund Trustee training requirements. Determine the Skills needs/requirements of the Retirement Fund trustees.

In order to achieve this objective, the guidelines given in the introduction were formulated. These

guidelines, if achieved, would enable the INSETA to proceed to the following phases of the

project, namely:

• The identification and development of any additional applicable Unit Standards

• Identification of suitable skills programmes

• Learning Materials Development

• Curriculum Development

• Quantification of the number of participants

• Appointment of a suitable Learning Provider for the delivery of skills programmes

• Retirement Fund and Trustee training pilot programme

• Review and updating of the Retirement Fund and Trustee training skill

programme



11

Project plan

Phase 1: Project Tendering Phase



12

Phase 2: Project Kick-off phase



13

Phase 3: Project Training Phase



14

Phase 4: Project Operational Phase



15

Phase 5: Project Close-Down Phase



16

1. Ascertain the retirement funds registered.

According to the Pension Funds Act, all funds are to be registered with the Pension Funds

Registrar. The Financial Services Board (FSB) maintains a database of all pension fund

administrators and most pension funds that includes contact information. The pension fund

administrators would have fairly detailed records of the pension funds administered. Pension

funds that are that are not supervised by the Pension Funds Registrar according to the act such

as parastatals will also form part of the scope of the analysis. These funds are supervised by the

National Treasurer. Details of other funds established in terms of the Labour Relations Act which

may not be registered with the pensions funds registrar will be obtained via the Department of

Labour and the relevant trade unions.

2. Compile a list of all current registered retirement funds

This process will be addressed in the operational phase of the project. Please see the process

flow chart above.

3. Establish the number of fund trustees, both employer-nominated and employee-nominated representatives per each individual fund.

A central registrar of trustees is maintained by the Institute of Retirement Funds. The information

can be obtained here or by way of e-mail, post and telephonic contact with funds.

4. Compile a list of all fund trustees

This is perhaps the most critical phase of the project and Endeleo recognises the fact that there

are a several obstacles that Endeleo will need to overcome in order to accomplish this aspect of

the project including ignorance and mistrust. Endeleo is aware that recent legislation has thrust a

lot additional players in the trusteeship of pension funds. The names and details of these

additional players may not have filtered through to the appropriate supervisory institutes. In order

to obtain this additional information it will be important to contact industry trade unions and other

employee representative bodies.

The amount of work involved will also depend on the number of details on each trustee that is

required. INSETA want a lot of detail per trustee as specified in sections 5 -11. In order to



17

properly stratify the population of pension fund trustees for the purposes of statistical analysis

information such as a race, gender, age etc. may also be required.

The strategy that Endeleo will adopt to deal with these requirements will be via direct contact with

the pension fund trustees as far as possible (through email, telephone, post etc.). As a result this

phase can be combined with the audit phase (see section 13 below).

5. Identify each fund’s economic sector


flow chart above.

6. Identify who the fund administrators are for each fund


Registrar. The Financial Services Board (FSB) maintains a database of all these funds and their

administrators. 7. Determine the physical location of both fund administrators and trustees per fund


Registrar. The Financial Services Board (FSB) maintains a database of all these funds. Funds

that are exempt from registration with the Pension Funds Registrar are supervised by other

bodies such as those mentioned in section 1 above. Within the operational phase, the above

requirements will be obtained.

8. Compile fund Administrator’s contact details list per fund


flow chart above.

9. Identify each Trustee’s level of formal education and training.


flow chart above.



18

10. Identify the level and extent of Trustee specific training that each trustee has received.


flow chart above.

11. Identify each Trustee’s years of experience as a trustee.


flow chart above.

12. Using a 30% sample of identified trustees (which sample shall fulfil the national demographic profile), quantify these trustees’ self-identified training needs.

The planned contact process as explained in section 3 above) aims to quantify the entire trustee

population’s collective training requirements. This will result in a sample greater than 30% being

assessed.



19

Methods

Distribution This project was identified as a particularly difficult one as a survey of this nature had never been

successfully carried out in this industry. Carrying out the project required an assessment of the

tools that were immediately available.

Each retirement fund is legally required to disclose its existence to the Financial Services Board

(FSB). Most funds have more stringent levels of reporting to the FSB, but there do exist some

funds that are governed by other acts (Telkom Funds, Transnet Funds, Post Office Fund,

Bargaining Council Funds and Official Funds). Funds are also expected to maintain a register of

current trustees together with other details at the fund’s registered office.

Approximately one quarter of all funds are self-administered. The remaining funds are

administered by professional administrators. These administrators maintain communication

channels with funds by way of trustees and were, therefore, in a position to have details of all

trustees in funds they administer.

Administrators also belong to certain prescriptive bodies.

Administrators

The results given in the key findings of this report show that 3 administrators dominate in each of

the fund administration methods (underwritten, private, umbrella) with various other

administrators competing for numbers. Key personnel within most of the larger administrators

were contacted and their participation secured in the project. These administrators were:

• Alexander Forbes

• Momentum

• Sanlam

• ABSA

• Old Mutual

Other smaller administrators were also contacted (Lekana, NBC, Wynne Jones), with only NBC

refusing to participate in the project.



20

Upon the agreement of the administrators to participate, they were then furnished with the

necessary material to formulate a communication to members (project description, questionnaire

,etc).

Financial Services Board

The FSB was able to provide details on all registered funds together with all registered

administrators.

The FSB also reinforced communications to administrators which was useful in generating a

large number of responses.

Media formats Media that went out directly to trustees and retirement funds included Today’s Trustee, Pensions

World magazine and fund administrator newsletters. Today’s trustee were able to include an

article together with a questionnaire for distribution to trustees. Pensions World magazine

included an editorial that directed trustees to various resources where the questionnaire could be

downloaded.

Affiliated bodies

The Institute of Retirement Funds maintained a membership of both funds and administrators.

Regular meetings with this body enabled good communication channels to be maintained.

The Principal Officers Association, a body that had membership of a number of fund principal

officers – mainly professional trustees.

The South African Financial Services Intermediaries Association maintained membership of over

75% of registered administrators. Communications to its members was achieved through regular

newsletters or bulletins.

The affiliated bodies above facilitated the distribution of project related material including the

questionnaire. This enabled a relatively large audience to be reached.

Postal communication

As each of the funds had a registered address with the FSB, postal communications together with

the questionnaire were sent to each fund’s principal officer for distribution within each fund. This

method achieved a very wide distribution across the country. Given that from the 13,000 funds

contacted, the survey only received a response from approximately 500 funds. A number of



21

respondents stated that their funds no longer existed because the company had closed down or

the fund was no longer active. This suggested that there is a need to update the FSB database.

On several occasions the addresses were outdated.

Skills Development Facilitators

As the key function of SDF’s is to facilitate skills development, they were critical contact points

within certain organisations. They were expected to have contact with trustees as well in any

training requirements that may arise.

These details were available from the various SETAs including the INSETA.

General

Most of the sources listed above also allowed the posting of articles or links on their websites

related to the project.



22

Support Structures

Weekly reporting meetings

Endeleo had a standing agreement with the INSETA where activity during each week was put

into a report and submitted to the Project Office. This report also contains issues, concerns and

possible solutions.

Following submission of this report, meetings were held between the INSETA and Endeleo where

the report was discussed.

Regular steering committee meeting

The steering committee meetings provided strategic direction to the project as a whole. Regular

meetings included participants in all active areas of the project so that synergies could be

identified.

The steering committee included members from union bodies, affiliated bodies, Endeleo and the

INSETA.



23

Project contingencies

Data The original project plan assumed that there would be data sources available from which trustee

contact details could be obtained. Also that these data sources would include fund administrators

information.

After a detailed investigation, it was been found that the FSB does not maintain any databases of

trustee data. The most suitable level of data the FSB holds is a register of funds together with the

fund physical locations.

Due to the highly competitive nature of the retirement fund administration industry, no

administrators were willing to provide any trustee data if they had any. However, it is most

probable that the administrators do possess the data. The most administrators were willing to do

was to distribute the project questionnaire to their fund contact points.

As a result of the above issues, the project had to rely on a number of secondary interfaces to

communicate with trustees. This restricted the frequency of reminders to trustees together with

any further communications to trustees.

Incentives The initial project communications did not include deadlines for responses. The reason for this

was to allow as many trustees to respond without a further need to redistribute the project

communications. A further reason was to avoid non-participation or complacency due to

inadequate deadlines.

However, although deadlines were a consideration, there was the further issue of incentives to

participate from trustees and administrators. Failure to respond to the communications cannot

and did not carry any penalty to trustees or administrators as none of the affiliated bodies have

any authority to compel participation.

Administrators and trustees may also have not realised the urgency or importance of the project

as a whole. The project is aimed at ensuring that those individuals who have been thrust into the

role of trusteeship as a result of changes in legislation are empowered with the requisite



24

information to carry out their duties. However for this initiative to succeed these individuals must

either be compelled to participate or must willingly take part in the project. The problem, as

Endeleo discovered is that the majority of the new entrants are not aware of the responsibilities

that come with this role and the knowledge required to mitigate any risks of personal liability. This

possibly lead to the relatively low participation rates.

Endeleo recommends that legislation be amended to compel that trustees have a minimum

competency before being entrusted with the responsibility of trusteeship. Failing this then it will be

crucial to embark on an extensive awareness campaign to ensure that that potential trustees are

well aware of their options when agreeing to become a trustee.



25

Project guidelines Through the life of the project, it has become clear that a number of guidelines may not

necessarily be the most effective method of meeting the project objectives. Some of these are

discussed below:

Compile a list of all fund trustees

This guideline aims to assess the possible extent of resources required given the training

requirements of trustees. However, by the simple use of sampling techniques, inferences can be

made upon the total population size based on sample statistics.

No lists of trustees exist in publicly available data sources and bodies that hold any trustee

specific data are very guarded with it.

Therefore, an appendix to this report details a suggested approach to determining the trustee

population.

Identify each Trustee’s level of formal education and training

This guideline aims to assess the level at which trustee training material should be set. Again,

using sampling techniques, it is possible to determine the distribution of these trustee specific

details and infer population statistics.

Identify each Trustee’s years of experience as a trustee

The aim of this guideline is similar to the guideline above. For the same reasons as above, it is

not necessary to conduct a census to make inferences on the population statistics.

Identify each fund’s economic sector, e.g. Construction, manufacturing, etc

Currently, over 50% of all funds have been categorised into their respective sectors. In meeting

with the objectives of the project, this is a suitably large sample to make inferences at the 99.9%

confidence level.

Using a 30% sample of identified trustees (which sample shall fulfil the national

demographic profile), quantify these trustees’ self-identified training needs

By taking into account sample variances, it is possible to determine a sample which will provide

results to a significant confidence level that is suitable for making inferences required in this



26

guideline. A 30% sample will achieve results that may be obtained using a much smaller sample.

Details of this are given in the appendix to this report.



27

Project Scope Revision Following on from the points listed in the previous section, a project scope revision was

suggested and the following guidelines adopted:

1. Ascertain the retirement funds registered.

2. Compile a list of all current registered retirement funds.

3. Establish the number of fund trustees, both employer-nominated and employee-


4. Identify each fund’s economic sector, e.g. Construction, manufacturing, etc.

5. Identify who the fund administrators are per fund.

6. Determine the physical location of both fund administrators and trustees per fund


7. Compile fund Administrator’s contact details list per fund (Name, telephone/fax number, e-

mail, etc).

8. Using an appropriate sample size of identified trustees (which sample shall fulfil the

national demographic profile)

Compile a list of sampled trustees.

Identify each Trustee’s years of experience as a trustee.

Identify each Trustee’s level of formal education and training.

Identify the level and extent of Trustee specific training that each trustee has

received.

Quantify these trustees’ self-identified training needs.



28

Key findings - Retirement Funds and Administration Methods The data in the previously mentioned database forms the basis for the following results:

Total funds by date of data and administration method

Table 1: Total funds by date of data and administration method

Data date Underwritten1 Private Umbrella2 Totals

21-Jan-05 10,068 3,337 603 14,008

18-May-05 9,995 3,365 798 14,158

31-May-06 9,645 3,107 798 13,550

The table above details the data in the database by the type of administration used by the fund

and the date on which the data was extracted. It is clear that a large number of funds choose to

be underwritten. Although the numbers of umbrella funds are relatively small, the structure of

these funds means that they have a higher number of members than the average fund. We can

expect to find a large number of professional trustees on the trustee boards of these funds.

Typically these will be the funds that see no need for further training.

ENDELEO has been able to source further data from the FSB detailing fund movements. The

following results have been obtained:

Fund status Totals

Curatorship 5

In transfer 1,708

Liquidated 2

Normal active 9,632

Preliminary registered 558

Process of liquidation 1,567

Query 13

Total Active Funds 10,190

1 Funds which operate exclusively by means of policies of insurance issued by registered insurers in the Republic. 2 Funds which invest their assets with institutions in the public or private sectors of the economy on their own behalf and to which the provisions of the Act apply



29

The “Total Active Funds” row only includes funds listed as active or preliminary registered. Funds

currently in transfer have been found to be categorically shifting into existing umbrella funds.

Those shifting into new umbrella funds are captured in the preliminary registered category.

Liquidated or liquidating funds are excluded, as are query funds. The result is the total number of

ordinary active funds.

Further to this, it has been found that a significant number of funds have combinations of

pension, provident and umbrella funds. This means that trustees may be members of multiple

funds. We have found over 1,200 funds with this occurrence. This analysis has not looked at

associated funds where trustees may also be on multiple trustee boards (eg. The Argus and The

Star funds, Amplats and MMR funds). Based on the above, we have estimated that the total

trustee numbers are at most 54,000. An analysis of this estimate follows later in the report.

Finally, trustees are also duplicated due to the presence of independent trustees (professional

trustees) that are present on multiple trustee boards. This is similar to trustees being on multiple

umbrella fund trustee boards.

Taking all the above factors into account together with the average trustee board size, it becomes

clear that trustee numbers are far less than originally anticipated.



30

Total funds by administration method including funds not

supervised under the Pension Funds Act3

In the table below the data has been broken down to exclude those fund which are not governed

under the Pension Funds Act

Table 2: Total funds by administration method including funds not supervised under the Pension Funds Act

Funds Private Umbrella Underwritten Total

Transnet Funds 2 0 6 8

Telkom Funds 6 0 2 8

Post Office Funds 0 0 2 2

Bargaining Council Funds 14 2 12 28

Supervised funds 3,085 796 9,623 13,504

Total 3,107 798 9,645 13,550

Further analysis of this data by administrator allows the identification of the most significant

administrators in the retirement funds sector. The table below shows in absolute number the

proportion of funds administered by each administrator. Due to sheer volumes of administrators,

we have only showed the top 10 administrators:

3 Funds that have been established by special laws for employees of the State and certain parastatal institutions. These funds are supervised by The National Treasury under the relevant laws (official funds). Other funds not supervised under the Pension Funds Act: Telkom Fund, Transnet Fund, Post Office Pension Fund and Bargaining Council Funds



31

Table 3: Total funds by administrator

Administrator Frequency

Relative

frequency

Cumulative

frequency

Cumulative

relative

frequency

LIBERTY GROUP LIMITED 3,076 22.64% 3,076 22.64%

INVESTEC EMPLOYEE BENEFITS LIMITED 2,786 20.51% 5,862 43.15%

MOMENTUM EMPLOYEE BENEFITS 1,261 9.28% 7,123 52.43%

SANLAM 1,218 8.97% 8,341 61.40%

ALEXANDER FORBES FINANCIAL SERVICES 941 6.93% 9,282 68.33%

METROPOLITAN LIFE LTD 740 5.45% 10,022 73.78%

OLD MUTUAL LIFE ASSURANCE COMPANY 535 3.94% 10,557 77.72%

SAGE LIFE LTD 320 2.36% 10,877 80.08%

GLENRAND MIB BENEFIT SERVICES 319 2.35% 11,196 82.43%

ABSA CONSULTANTS & ACTUARIES 254 1.87% 11,450 84.30%

Clearly the Liberty group is the dominant administrator in the industry. An interesting note is the

position of Investec in second place. However, this position will probably change following the

acquisition of Investec’s group business by 12th placed Capital Alliance. The sum of the two still

does not manage to displace Liberty in first place.

Another acquisition is that of Sage Life by the Momentum Group. This will most likely result in a

significant shift in Momentum’s portfolio of funds under management.

Of the administrators listed above, we have been able to obtain participation from trustees in

funds administered by all the administrators. The most co-operative administrators were Sanlam,

Alexander Forbes and ABSA Consultants and Actuaries. As can be seen, they jointly represent a

large segment of funds, yet the responses received do not appear to reflect this.



32

Geographic distribution of funds

Table 4: Geographic distribution of funds

Province Number of funds

GAUTENG 61.86%

MPUMALANGA 2.14%

LIMPOPO 0.64%

NORTH WEST 1.02%

KWAZULU-NATAL 11.67%

EASTERN CAPE 4.76%

WESTERN CAPE 15.87%

NORTHERN CAPE 0.59%

FREE STATE 1.45%

The table above shows the large bias of fund location towards Gauteng. The trends seen above

are closely followed by administrator locations.

Geographic distribution of fund administrators

Table 5: Geographic distribution of fund administrators

Province Number of administrators

EASTERN CAPE 4

FREE STATE 2

GAUTENG 137

KWAZULU-NATAL 12

MPUMALANGA 3

NORTH WEST 3

WESTERN CAPE 33

Total 194



33

It is quite clear from Table 5 above that the majority of fund administrators have their main office

located in the Gauteng province. The next most significant province is the Western Cape. Most

significant in the results is the absence of the Limpopo and Northern Cape provinces.

The two tables above are quite significant since they give a clear indication of the distribution of

trustees across South Africa. We would expect that the factors that determine the location of

administrators is trustee / fund proximity. However, in the next tables we will investigate the effect

of fund sector on location.



34

Distribution of fund economic sector

Table 6: Distribution of fund economic sector

Economic Sector Percentage of funds Financial and Accounting Services 3.77%Banking Services 0.82%Chemical Industries 2.17%Clothing, Textiles, Footwear and Leather Industries 3.52%Construction Industries 4.42%Diplomacy, Intelligence, Defence and Trade & Industry Services 0.06%Education, Training and Development Practices 3.29%Energy Industries 0.17%Food and Beverages Manufacturing Industries 4.15%Forest Industries 0.84%Information Systems, Electronics and Telecommunications Technology Industries 3.61%Insurance Services4 9.38%Local Government, Water and Related Services 2.19%Health and Welfare Services 4.34%Media, Advertising, Publishing, Printing and Packaging Services 4.32%Mining Industries 2.57%Manufacturing, Engineering and Related Services 14.60%Police, Private Security, Legal and Correctional Services 1.36%Primary Agricultural Industries 2.81%Public Services 1.01%Secondary Agricultural Industries 0.76%Service Industries 12.66%Tourism and Hospitality Industries 3.47%Transport Industries 4.60%Wholesale and Retail Industries 9.11%

The above data is based on over 50% of total funds. The trends follow an expected distribution of

funds within the economy. Based on the size of the sample, it can be inferred within a 99%

confidence interval that the population of funds will be distributed in a similar fashion.

4 This category also includes umbrella funds which may make the figure artificially higher than the actual insurance services industry.



35

The economic sectors shown above are determined according the distribution of Sectoral

Education Training Authorities (SETAs). Each fund was asked to select their relevant SETA in

order for the results to be categorised as above.

As is clear from the above, the manufacturing and services sectors are quite prominent with the

retail and insurance services sectors forming the second tier of prominence. The presence of

umbrella funds most likely distorts the relative weight of the insurance sector. If we assume a set

average trustee board, we can infer that trustees will also be similarly distributed (this can be

inferred with 99% confidence in the result).

Figure 1: Distribution of funds by economic sector

Economic Sector Pie Chart

Financial and Accounting Services Banking ServicesChemical Industries Clothing, Textiles, Footwear and Leather IndustriesConstruction Industries Diplomacy, Intelligence, Defence and Trade & Industry ServicesEducation, Training and Development Practices Energy IndustriesFood and Beverages Manufacturing Industries Forest IndustriesInformation Systems, Electronics and Telecommunications Technology Industries Insurance Services[1]Local Government, Water and Related Services Health and Welfare ServicesMedia, Advertising, Publishing, Printing and Packaging Services Mining IndustriesManufacturing, Engineering and Related Services Police, Private Security, Legal and Correctional ServicesPrimary Agricultural Industries Public ServicesSecondary Agricultural Industries Service IndustriesTourism and Hospitality Industries Transport IndustriesWholesale and Retail Industries

The graph above shows graphically the distribution of funds in their economic sectors. The larger

segments are taken by the manufacturing, retail, insurance and service industries. In order to



36

verify the findings, we have included a break-down of employment by sector from the 2005

Labour Force Survey produced by StatsSA.

Figure 2: Labour Force Survey (StatsSA)

Although the classifications of industry do not match the SETA classifications, it is clear that similar sectors as dominant in the above figure as is the case in the trustee population.



37

Distribution of fund economic sector by province The following tables are used to interpret the coded province and sector numbers below:

Coding Sector Coding Province

1 Financial and Accounting Services 1 Gauteng

2 Banking Services 2 Mpumalanga

3 Chemical Industries 3 Limpopo

4 Clothing, Textiles, Footwear and Leather Industries 4 North West

5 Construction Industries 5 Kwazulu-Natal

6

Diplomacy, Intelligence, Defence and Trade &

Industry Services

6 Eastern Cape

7 Education, Training and Development Practices 7 Western Cape

8 Energy Industries 8 Northern Cape

9 Food and Beverages Manufacturing Industries 9 Free State

10 Forest Industries

11

Information Systems, Electronics and

Telecommunications Technology Industries

12 Insurance Services

13 Local Government, Water and Related Services

14 Health and Welfare Services

15

Media, Advertising, Publishing, Printing and

Packaging Services

16 Mining Industries

17 Manufacturing, Engineering and Related Services

18

Police, Private Security, Legal and Correctional

Services

19 Primary Agricultural Industries

20 Public Services

21 Secondary Agricultural Industries

22 Service Industries

23 Tourism and Hospitality Industries

24 Transport Industries

25 Wholesale and Retail Industries

This table above is applicable to all tables where province and sector have been coded.



38

Table 7: Distribution of fund economic sector by province

Province 1 2 3 4 5 6 7 8 9

Sector

Total

Sector

1 72.0% 0.8% 0.4% 0.8% 5.0% 3.3% 15.9% 0.0% 1.7% 3.8%2 73.1% 1.9% 0.0% 0.0% 3.8% 7.7% 13.5% 0.0% 0.0% 0.8%3 72.1% 0.7% 0.0% 0.7% 9.6% 2.9% 14.0% 0.0% 0.0% 2.2%4 35.9% 0.9% 0.5% 0.0% 28.2% 10.9% 21.4% 0.0% 2.3% 3.5%5 55.4% 4.7% 0.7% 0.0% 14.9% 8.0% 13.8% 0.0% 2.5% 4.4%6 100.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.1%7 61.3% 1.0% 1.5% 1.5% 9.8% 10.8% 12.7% 0.0% 1.5% 3.3%8 72.7% 0.0% 0.0% 0.0% 18.2% 0.0% 9.1% 0.0% 0.0% 0.2%9 47.5% 3.4% 0.8% 0.0% 14.2% 5.0% 27.6% 0.8% 0.8% 4.2%10 47.2% 7.5% 1.9% 0.0% 20.8% 7.5% 15.1% 0.0% 0.0% 0.8%11 74.9% 0.5% 0.9% 1.4% 7.3% 3.7% 11.0% 0.0% 0.5% 3.5%12 70.4% 0.7% 0.3% 0.2% 2.5% 0.2% 24.5% 0.5% 0.7% 9.4%13 32.2% 2.1% 2.1% 4.9% 7.7% 16.1% 21.7% 4.2% 9.1% 2.3%14 67.4% 1.4% 0.0% 1.1% 11.2% 5.8% 12.0% 0.7% 0.4% 4.4%15 71.1% 0.8% 0.0% 0.8% 9.0% 1.5% 15.8% 0.0% 1.1% 4.3%16 76.3% 5.6% 0.6% 1.9% 3.8% 2.5% 4.4% 2.5% 2.5% 2.6%17 68.8% 1.8% 0.1% 0.6% 10.7% 5.1% 11.3% 0.5% 1.0% 14.9%18 72.3% 0.0% 1.2% 1.2% 10.8% 3.6% 9.6% 0.0% 1.2% 1.3%19 31.7% 3.7% 3.1% 1.2% 22.4% 7.5% 26.1% 1.2% 3.1% 2.6%20 62.5% 0.0% 0.0% 0.0% 15.6% 4.7% 14.1% 0.0% 3.1% 1.0%21 46.9% 12.2% 0.0% 2.0% 16.3% 0.0% 18.4% 2.0% 2.0% 0.8%22 64.0% 2.0% 0.8% 1.6% 13.1% 2.5% 13.8% 0.3% 1.9% 12.6%23 56.2% 4.3% 1.0% 0.5% 16.7% 5.7% 13.8% 0.5% 1.4% 3.4%24 54.1% 3.7% 0.7% 0.3% 15.0% 4.8% 17.7% 2.4% 1.4% 4.7%25 57.5% 2.1% 0.9% 2.5% 14.6% 5.2% 16.2% 0.4% 0.7% 9.0%

Province Total 61.9% 2.1% 0.6% 1.0% 11.7% 4.8% 15.9% 0.6% 1.5% 100%

The rows of each table show a particular provinces contribution to the total number of trustees in

each economic sector (eg. 73.1% of banking sector funds are Gauteng based). The sector total

column shows the contribution of each sector to the total population of funds. Similarly, the

province total shows the contribution of each province to the total population of funds.



39

Generally, Gauteng is the dominant province, but depending on the actual fund sector, other

provinces may become more significant. For instance, looking at local government funds (sector

13), we can see other provinces are more significant than in the other sectors shown. The test

below shows this dependence:

Tests of Independence

Test Statistic Df P-Value

Chi-Squared 859.981 192 0.0000

This table shows the results of a hypothesis test run to determine whether or not to reject the

hyposthesis that the row and column classifications are independent (ie. Is Province independent

of Sector?).

The P-Value column gives us an indication of the results of the test. The lower the P-Value, the

more likely that the hypothesis can be rejected. The P-Value gives the (100-p)% confidence level

of the conclusion. In this test, the hypothesis is that Province is independent of Sector and we

have defined p to be 5% (0.05). If the P-Value of the test is less than p, we can be 95% certain

that our conclusion is correct.

Since the P-value is less than 0.05, we can reject the hypothesis that rows and columns are

independent at the 95.0% confidence level. Therefore, the observed value of Economic Sector

for a particular case is related to its value for Province.



40

Key findings – Retirement Fund Trustees The main focus of INSETA’s work is to quantify the demographic profile and training needs of its

constituents, the retirement fund trustees. As such a number of summaries of the demographic

profile as well as the training requirements identified from the data collected to date are

presented below.

Analysis of explanatory data The questionnaire distributed to trustees collected data which included dependent and

explanatory variables. The following variables are dependent variables:

Trustee training, current and required, on:

• Legal aspects

• Benefits and membership

• Service providers

• Investment management

• Financial aspects

• Dealing with surpluses

• Interpreting financial statements

• Governance

The following variables are variables that explain the dependent variables:

• Province

• Trustee Age

• Trustee Formal Education

• Trustee Gender

• Trustee Language

• Trustee Population Group

• Trustee Type

• Trustee Years Experience

While it is desirable to have as much data as possible, it is possible, by statistical methods, to

achieve the same explaining power using fewer sample points. However, the parameters



41

required to determine the variables need to be known with some certainty or estimated from

collected data. From the sample size analysis shown later, it can be shown that based on the

data collected for this survey, the results carry a 90 – 95% confidence level. The results are

based on a sample size of 1420 trustees (implies the specified confidence level).

In order to better illustrate the important variables, a number of tests have been carried out

below. We have also shown the mean results for each of the dependent variables above.

To facilitate the analyses, the data had to be coded and each coded data set can be referenced

to the tables overleaf. The attached reference card can also be used for quick reference when

looking at each table.



42

Index of variable coding:

Age Code Experience Code

younger than 25 1 No experience 1

25 years to younger than 35

years 2 0 – 2 years 2


years 3 2 – 5 years 3


years 4 5 or more years 4


years 5

older than 65 years 6

Trustee Type Code Population Group Code

Pensioner Trustee 1 Black 1

Employer Appointed Trustee 2 Coloured 2

Member Elected Trustee 3 Indian 3

Independent Trustee 4 White 4

Other Trustee 5 Other 5

Language Code Gender Code

English 1 Female 1

Afrikaans 2 Male 2

Sepedi 3

Sesotho 4 Formal Education Code

Setswana 5

siSwati 6 Less than Matric Certificate (NQF < 4) 1

Tshivenda 7 Matric Certificate (NQF = 4) 2

Xitsonga 8 Undergraduate degree / Diploma (NQF = 5) 3

isiNdebele 9 Postgraduate degree (NQF > 5) 4

isiXhosa 10

isiZulu 11

Other 12



43

Summary statistics of trustees

Initially, we will study the distributions of trustees that responded in the survey. The table below

provides the mean levels of each of the explanatory variables giving 95% confidence intervals of

each variable:

Table 8: 95.0% confidence intervals for each explanatory variable

Variable Mean Standard Error Lower limit Upper limit

Age 3.89 0.034 3.83 3.96

Economic Sector 13.6 0.231 13.2 14.1

Experience 3.18 0.032 3.12 3.25

Formal Education 3.24 0.029 3.18 3.3

Gender 1.81 0.013 1.79 1.84

Language 1.25 0.020 1.21 1.29

Population Group 3.42 0.037 3.34 3.49

Province 3.48 0.088 3.31 3.65

Type 2.6 0.025 2.55 2.65

By reference to the table overleaf, we can see the mean levels of each of the variables. The 95%

confidence interval shows the interval that contains the true mean value of each variable with

95% confidence. However, as the variables are discrete, an application of categorical analysis is

required. This is shown below for each of the significant variables.



44

Population group

Figure 3: Population group bar chart

Barchart for Population Group

0 200 400 600 800 1000 1200frequency

1

2

3

4

5

The graph above shows the significant prevalence of trustees in the “white” population group.

The next most significant group is the “black” population group.



45

Table 9: Population group frequency table

Population

Group Class Frequency

Relative

frequency

Cumulative

frequency

Cumulative

relative frequency

Black 1 217 15.4% 217 15.4%

Coloured 2 58 4.1% 275 19.6%

Indian 3 27 1.9% 302 21.5%

White 4 1098 78.0% 1400 99.5%

Other 5 7 0.5% 1407 100.0%

The table above gives a numerical representation of the split of trustees within each population

group. It is clear that the significant groups are the “white” and “black” population groups with the

other groups forming marginal contributions to the numbers.

Trustee Type

Figure 4: Trustee type pie chart

Piechart for Type

Type12345

The pie chart above shows the approximate even split of employer (2) and employee (3)

nominated trustees. The other groups, made up by pensioner (1), independent (4) and other (5)

trustees, show very small proportions of the graph. Over 80% of trustees are either employee or

employer nominated.



46

Province

Figure 5: Trustee province bar graph

Barchart for ProvinceT

0 200 400 600 800frequency

123456789

Following the same labelling as in the retirement funds, Gauteng (1) again appears to be quite

dominant in trustee location. The trend of the other provinces is also similar to the retirement

funds and administrators.



47

Formal Education

Figure 6: Trustee formal education graph

Barchart for Formal Education

0 200 400 600 800frequency

1

2

3

4

This graph shows that most of the trustees that have responded are well educated (4). While this

would have been an expected result for independent trustees, it appears that most trustees are

well educated individuals. This result is perhaps not surprising as you would expect that the

majority of the employer-nominated trustees are most likely financially literate individuals such as

the Chief Financial Officer or Chief Operating Officer or even the Human Resources head.

Similarly the member elected trustees are likely to be those individuals within the company that

are seen to have the acumen, although they may not hold important positions as the employer

nominated trustees.

However, As in all investigations, it is important to be aware that bias may be introduced by the

method of sampling. If the sampling method predisposes certain trustees to responding, then that

will affect the results.



48

Experience

Figure 7: Trustee experience graph

Barchart for Experience

0 200 400 600 800frequency

1

2

3

4

Almost a mirror image of the formal education graph, experience also shows that more

experienced trustees responded to the survey when compared with inexperienced trustees. This

suggests that we may need to investigate the independence of formal education and experience.

If they are heavily correlated, it is possible to drop one of the two factors from the analysis as they

act in similar directions on the results.



49

Experience vs. Formal Education

Figure 8: Experience vs. Formal Education bar graph

0 100 200 300 400 500frequency

Exp

erie

nce

Barchart for Experience by Formal Education

1

2

3

4

Formal Education1234

The table above already suggests the positive correlation between experience and formal

education. With increasing experience, we note the increase in formal education. A more

comprehensive analysis of the correlations between all variables is examined next. It is

interesting to note that the differential between trustees’ formal education increases as trustee

experience increases.



50

Experience vs. Formal Education

Table 10: Correlations between explanatory variables

Age

Economic

Sector Experience

Formal

Education Gender Language

Population

Group Province Type

Age 0.00 0.38 -0.04 0.15 -0.09 0.23 -0.02 -0.19

0.95 0.00 0.28 0.00 0.00 0.00 0.51 0.00

Economic

Sector 0.00 -0.12 -0.10 -0.04 -0.04 0.02 0.09 -0.08

0.95 0.00 0.00 0.24 0.27 0.56 0.01 0.02

Experience 0.38 -0.12 0.13 0.20 -0.08 0.25 0.02 -0.15

0.00 0.00 0.00 0.00 0.02 0.00 0.58 0.00

Formal

Education -0.04 -0.10 0.13 0.07 0.00 0.34 -0.15 -0.09

0.28 0.00 0.00 0.02 0.91 0.00 0.00 0.01

Gender 0.15 -0.04 0.20 0.07 0.05 0.00 0.01 -0.12

0.00 0.24 0.00 0.02 0.11 1.00 0.77 0.00

Language -0.09 -0.04 -0.08 0.00 0.05 -0.02 0.00 0.05

0.00 0.27 0.02 0.91 0.11 0.56 0.93 0.15

Population

Group 0.23 0.02 0.25 0.34 0.00 -0.02 -0.02 -0.10

0.00 0.56 0.00 0.00 1.00 0.56 0.59 0.00

Province -0.02 0.09 0.02 -0.15 0.01 0.00 -0.02 0.02

0.51 0.01 0.58 0.00 0.77 0.93 0.59 0.57

Type -0.19 -0.08 -0.15 -0.09 -0.12 0.05 -0.10 0.02

0.00 0.02 0.00 0.01 0.00 0.15 0.00 0.57

The above table gives a cross-tabulation of each of the variables. The intersection gives the

relevant correlation (white cells) or p-value (red cells) of that correlation. As discussed before,

where the p-value is less than a pre-determined confidence level, the correlation is deemed

significant.

In this instance, we are looking for a 95% confidence level so a p-value of less than 5% (0.05) is

deemed significant. For example, Age vs. Experience has a p-value of 0.00. This suggests a

strong correlation between the two variables.

The sign of the correlation suggests whether the correlation is positive (ie. Increase in one results

in increase in other) or negative (increase in one results in decrease in other)



51

The table below provides a summary of pairs that have a significant correlation:

Pair Pair

Age and Experience Experience and Gender

Age and Gender Experience and Language

Age and Language Experience and Population Group

Age and Population Group Experience and Type

Age and Type Formal Education and Gender

Economic Sector and Experience Formal Education and Population Group

Economic Sector and Formal Education Formal Education and Province

Economic Sector and Province Formal Education and Type

Economic Sector and Type Gender and Type

Experience and Formal Education Population Group and Type



52

Principal Component Analysis

As we have already discussed, one can collect any number of data variables, but without data, it

can happen that some of the variables collected are redundant. Principal component analysis

looks at the components that are most critical in explaining the variability within the data. The

table below shows the results of the analysis:

Table 11: Principal Component analysis of the explanatory variables

Component Data Percent of Cumulative

Number Variable Eigenvalue Variance Percentage

1 Age 1.86 20.6% 20.6%

2 Economic Sector T 1.26 13.9% 34.6%

3 Experience 1.10 12.2% 46.8%

4 Formal Education 1.02 11.3% 58.2% 5 Gender 0.98 10.9% 69.1%

6 Language 0.87 9.7% 78.7%

7 Population Group 0.81 9.0% 87.7%

8 ProvinceT 0.59 6.6% 94.3%

9 Type 0.51 5.7% 100.0%

The purpose of the analysis is to obtain a small number of linear combinations of the 9 variables

which account for most of the variability in the data. In this case, 4 components have been

extracted, since 4 components had eigenvalues greater than or equal to 1.0. Together they

account for 58.2% of the variability in the original data. Figure 9 below shows the results

graphically:



53

Figure 9: Scree plot of component eigenvalues

Scree Plot

0 2 4 6 8 10Component

0

0.4

0.8

1.2

1.6

2E

igen

valu

e

What the graph and table above show is that the 4 components highlighted are most critical in

explaining the variability in any results that are obtained. It is important to examine the

interactions of all variables, though, to determine the best set of variables to determine each

dependent variable. This analysis follows the determination of the most significant explanatory

variables for each dependent variable.



54

Analysis of explanatory variables

Explanatory Variable Analysis of Variance (ANOVA) - Current

A multifactor analysis of variance (ANOVA) was carried out on each of the explanatory factors in

order to determine which variables have the most explaining power on the dependent variables.

The results of these analyses are shown below. The results are presented with training level

(current) shown first with training level (required) shown next. Each ANOVA table decomposes

the dependent variable into contributions due to each of the explanatory variables. As can be

seen below, TYPE III sums of squares have been used in the analysis. This has the effect of

removing the effect of all other factors. The P-value can then be used to test the significance of

each factor in isolation. Where the P-value is less than 5% (0.05), we can conclude that the factor

is a significant explanatory variable for that dependent variable.

Legal Aspects and Legislation – training (current)

Table 12: Analysis of Variance for Legal Aspects and Legislation

Source Sum of Squares Df

Mean

Square

F-

Ratio

P-

Value

MAIN EFFECTS

A:Age 10.80 5 2.170 1.810 0.107

B:Economic Sector 67.90 24 2.830 2.370 0.000

C:Experience 207.00 3 68.800 57.660 0.000

D:Formal Education 12.50 3 4.170 3.490 0.015

E:Gender 5.74 1 5.740 4.800 0.028

F:Language 24.20 5 4.830 4.050 0.001

G:Population Group 1.08 4 0.270 0.230 0.924

H:Province 7.33 8 0.916 0.770 0.632

I:Type 18.30 4 4.560 3.820 0.004

RESIDUAL 1,060 884 1

TOTAL (CORRECTED) 1,550 941

All F-ratios are based on the residual mean square error.



55

The following table shows the mean value of the legal aspects and legislation variable given each

explanatory variable. For example, trustees in economic sector 8 (energy industries) have a

mean current knowledge of legal aspects and legislation of an intermediate level. This table is

also shown for each of the dependent variables.

Table 13: Table of Least Squares Means for Legal Aspects and Legislation with 95.0 Percent Confidence Intervals

Table of Least Squares Means for Legal Aspects and Legislation with 95.0 Percent Confidence Intervals

Standard Lower Upper

Level Mean Error Limit Limit

Age

1 1.98 0.751 0.510 3.450

2 1.34 0.409 0.534 2.140

3 1.38 0.396 0.601 2.160

4 1.40 0.396 0.627 2.180

5 1.16 0.403 0.372 1.950

6 1.57 0.429 0.732 2.410

Economic Sector

1 1.68 0.428 0.840 2.520

2 1.20 0.442 0.329 2.060

3 1.67 0.430 0.824 2.510

4 1.49 0.471 0.569 2.420

5 1.09 0.452 0.205 1.980

6 0.75 1.180 -1.570 3.070

7 1.19 0.508 0.191 2.180

8 2.88 1.170 0.584 5.180

9 1.44 0.422 0.617 2.270

10 0.96 0.536 -0.089 2.010

11 1.65 0.461 0.749 2.560

12 1.81 0.410 1.000 2.610

13 1.96 0.412 1.150 2.760

14 1.08 0.468 0.160 1.990

15 1.98 0.461 1.070 2.880

16 1.36 0.442 0.496 2.230

17 1.24 0.414 0.427 2.050



56

18 2.20 0.642 0.937 3.450

19 1.38 0.609 0.190 2.580

20 1.39 0.454 0.499 2.280

21 1.45 0.516 0.439 2.460

22 1.39 0.455 0.501 2.290

23 0.98 0.512 -0.029 1.980

24 1.16 0.449 0.279 2.040

25 1.44 0.416 0.627 2.260

Experience

1 0.63 0.417 -0.189 1.440

2 1.13 0.416 0.316 1.940

3 1.81 0.411 1.000 2.610

4 2.33 0.406 1.530 3.120

Formal Education

1 1.46 0.435 0.608 2.310

2 1.26 0.408 0.456 2.060

3 1.58 0.410 0.774 2.380

4 1.59 0.409 0.791 2.390

Gender

1 1.36 0.410 0.559 2.170

2 1.58 0.403 0.791 2.370

Language

1 2.47 0.260 1.970 2.980

2 2.23 0.271 1.700 2.760

4 1.06 0.505 0.068 2.050

5 1.42 0.840 -0.222 3.070

9 0.19 1.160 -2.100 2.470

10 1.46 1.150 -0.787 3.700

Population Group

1 1.45 0.386 0.695 2.210

2 1.48 0.431 0.633 2.320

3 1.64 0.463 0.730 2.550

4 1.53 0.395 0.755 2.310

5 1.26 0.605 0.077 2.450

Province

1 1.58 0.364 0.872 2.300

2 1.34 0.513 0.333 2.350

3 1.35 1.190 -0.989 3.690

4 1.62 0.628 0.387 2.850



57

5 1.35 0.382 0.605 2.100

6 1.65 0.399 0.873 2.440

7 1.39 0.366 0.676 2.110

8 1.36 0.884 -0.377 3.090

9 1.60 0.564 0.494 2.700

Type

1 1.18 0.444 0.305 2.050

2 1.42 0.401 0.634 2.200

3 1.46 0.398 0.680 2.240

4 2.11 0.450 1.230 2.990

5 1.20 0.449 0.317 2.080



58

Benefits offered and membership – training (current)

Table 14: Analysis of Variance for Benefits offered and membership

Source

Sum of

Squares Df

Mean

Square F-Ratio P-Value

MAIN EFFECTS

A:Age 6.00 5 1.200 0.850 0.516


C:Experience 220.00 3 73.400 51.840 0.000


E:Gender 2.22 1 2.220 1.570 0.210

F:Language 35.90 5 7.180 5.070 0.000


H:Province 2.99 8 0.374 0.260 0.977

I:Type 14.70 4 3.670 2.590 0.035


TOTAL

(CORRECTED) 1.75E+03 939


Table 15: Table of Least Squares Means for Benefits Offered and Membership with 95.0 Percent Confidence Intervals



Age

1 2.37 0.818 0.764 3.970

2 1.53 0.446 0.660 2.410

3 1.62 0.432 0.778 2.470

4 1.59 0.431 0.744 2.430

5 1.52 0.439 0.657 2.380

6 1.86 0.467 0.943 2.770

Economic Sector

1 1.73 0.466 0.817 2.640

2 1.94 0.481 0.995 2.880

3 1.61 0.468 0.687 2.520



59

4 1.62 0.513 0.618 2.630

5 1.48 0.493 0.518 2.450

6 1.65 1.290 -0.873 4.180

7 1.84 0.554 0.759 2.930

8 2.66 1.280 0.161 5.170

9 1.74 0.460 0.843 2.650

10 1.69 0.584 0.541 2.830

11 1.90 0.502 0.918 2.890

12 1.82 0.446 0.943 2.690

13 2.12 0.448 1.240 3.000

14 1.28 0.508 0.283 2.270

15 2.10 0.503 1.120 3.090

16 1.60 0.482 0.653 2.540

17 1.51 0.451 0.629 2.400

18 2.17 0.699 0.799 3.540

19 1.66 0.663 0.357 2.960

20 1.46 0.495 0.489 2.430

21 1.52 0.562 0.415 2.620

22 1.91 0.496 0.935 2.880

23 1.67 0.558 0.572 2.760

24 1.40 0.489 0.444 2.360

25 1.62 0.453 0.732 2.510

Experience

1 0.85 0.454 -0.040 1.740

2 1.41 0.453 0.519 2.290

3 2.11 0.448 1.240 2.990

4 2.62 0.442 1.760 3.490

Formal Education

1 1.89 0.474 0.956 2.820

2 1.43 0.445 0.560 2.300

3 1.88 0.447 1.010 2.760

4 1.79 0.446 0.918 2.670

Gender

1 1.68 0.447 0.804 2.560

2 1.82 0.439 0.956 2.680

Language

1 3.01 0.283 2.460 3.570

2 2.71 0.295 2.140 3.290

4 1.41 0.551 0.330 2.490



60

5 1.49 0.915 -0.301 3.290

9 -0.04 1.270 -2.530 2.440

10 1.91 1.250 -0.538 4.350

Population Group

1 1.67 0.421 0.848 2.500

2 1.62 0.470 0.698 2.540

3 2.04 0.505 1.050 3.030

4 1.87 0.431 1.030 2.720

5 1.54 0.659 0.245 2.830

Province

1 1.76 0.396 0.982 2.540

2 1.92 0.560 0.819 3.010

3 1.38 1.300 -1.170 3.930

4 2.12 0.684 0.776 3.460

5 1.64 0.416 0.828 2.460

6 1.82 0.435 0.971 2.680

7 1.67 0.399 0.887 2.450

8 1.68 0.963 -0.207 3.570

9 1.75 0.614 0.544 2.950

Type

1 1.37 0.484 0.420 2.320

2 1.77 0.437 0.914 2.630

3 1.84 0.433 0.990 2.690

4 2.23 0.49 1.27 3.19

5 1.54 0.49 0.576 2.5



61

Service Providers – training (current)

Table 16: Analysis of Variance for Service Providers


Mean


MAIN EFFECTS

A:Age 10.20 5 2.050 1.520 0.180


C:Experience 207.00 3 69.000 51.430 0.000


E:Gender 8.38 1 8.380 6.240 0.013

F:Language 41.70 5 8.350 6.220 0.000


H:Province 9.93 8 1.240 0.920 0.495

I:Type 9.43 4 2.360 1.760 0.136


TOTAL

(CORRECTED) 1,720 939


Table 17: Table of Least Squares Means for Service Providers with 95.0 Percent Confidence Intervals



Age

1 2.70 0.797 1.130 4.260

2 1.59 0.434 0.744 2.440

3 1.64 0.420 0.817 2.460

4 1.74 0.419 0.915 2.560

5 1.57 0.427 0.735 2.410

6 1.97 0.455 1.070 2.860

Economic Sector

1 1.88 0.453 0.991 2.770

2 2.37 0.469 1.450 3.280

3 1.99 0.456 1.100 2.880



62

4 2.06 0.500 1.080 3.040

5 1.64 0.480 0.701 2.580

6 0.51 1.250 -1.950 2.960

7 2.02 0.539 0.966 3.080

8 2.81 1.240 0.373 5.240

9 1.94 0.447 1.070 2.820

10 1.41 0.568 0.296 2.520

11 2.24 0.489 1.290 3.200

12 2.15 0.434 1.300 3.000

13 2.22 0.437 1.370 3.080

14 1.21 0.494 0.238 2.180

15 2.20 0.489 1.240 3.160

16 1.96 0.469 1.040 2.880

17 1.76 0.439 0.901 2.620

18 2.10 0.681 0.766 3.430

19 2.24 0.645 0.979 3.510

20 1.60 0.482 0.660 2.550

21 1.63 0.548 0.559 2.710

22 1.94 0.483 0.997 2.890

23 1.72 0.543 0.654 2.780

24 1.42 0.476 0.490 2.360

25 1.65 0.441 0.783 2.510

Experience

1 0.87 0.442 0.005 1.740

2 1.63 0.441 0.765 2.490

3 2.27 0.436 1.420 3.120

4 2.70 0.430 1.860 3.540

Formal Education

1 1.75 0.462 0.841 2.650

2 1.64 0.433 0.788 2.490

3 2.01 0.435 1.160 2.870

4 2.07 0.434 1.220 2.920

Gender

1 1.74 0.435 0.883 2.590

2 2.00 0.427 1.160 2.840

Language

1 3.15 0.276 2.610 3.690

2 2.95 0.287 2.390 3.520

4 1.08 0.536 0.031 2.130



63

5 2.73 0.891 0.984 4.480

9 -0.56 1.240 -2.980 1.860

10 1.85 1.210 -0.533 4.230

Population Group

1 1.85 0.410 1.050 2.660

2 1.71 0.457 0.811 2.600

3 1.97 0.491 1.010 2.930

4 1.77 0.419 0.950 2.590

5 2.03 0.642 0.777 3.290

Province

1 1.84 0.386 1.090 2.600

2 1.25 0.545 0.185 2.320

3 1.04 1.270 -1.440 3.520

4 2.59 0.666 1.290 3.900

5 1.72 0.405 0.930 2.520

6 1.74 0.423 0.906 2.570

7 1.81 0.388 1.050 2.570

8 2.84 0.937 1.010 4.680

9 1.97 0.598 0.795 3.140

Type

1 1.77 0.471 0.852 2.700

2 1.91 0.425 1.080 2.740

3 1.93 0.422 1.100 2.760

4 2.24 0.477 1.300 3.170

5 1.48 0.477 0.549 2.420



64

Investment Management – training (current)

Table 18: Analysis of Variance for Investment Management

Source Sum of Squares Df Mean Square F-Ratio P-Value

MAIN EFFECTS

A:Age 15.70 5 3.150 1.410 0.217


C:Experience 195.00 3 65.000 29.170 0.000


E:Gender 23.50 1 23.500 10.530 0.001

F:Language 19.60 5 3.910 1.760 0.119


H:Province 12.30 8 1.540 0.690 0.700

I:Type 14.80 4 3.690 1.660 0.158


TOTAL



Table 19: Table of Least Squares Means for Investment Management with 95.0 Percent Confidence Intervals



Age

1 1.99 1.030 -0.022 4.000

2 1.42 0.559 0.323 2.510

3 1.39 0.542 0.329 2.450

4 1.62 0.540 0.559 2.680

5 1.41 0.550 0.327 2.480

6 1.90 0.586 0.751 3.050

Economic Sector

1 1.69 0.584 0.541 2.830

2 1.94 0.604 0.762 3.130

3 1.62 0.587 0.468 2.770

4 1.79 0.644 0.529 3.050



65

5 1.46 0.618 0.250 2.670

6 0.68 1.620 -2.490 3.850

7 1.72 0.695 0.355 3.080

8 2.64 1.600 -0.499 5.780

9 1.46 0.576 0.335 2.590

10 1.08 0.732 -0.355 2.510

11 2.03 0.629 0.792 3.260

12 1.95 0.560 0.857 3.050

13 1.77 0.562 0.666 2.870

14 0.86 0.637 -0.390 2.110

15 1.78 0.630 0.548 3.020

16 1.58 0.604 0.392 2.760

17 1.68 0.566 0.568 2.790

18 1.98 0.877 0.261 3.700

19 1.74 0.831 0.113 3.370

20 1.32 0.621 0.102 2.540

21 1.54 0.705 0.156 2.920

22 1.50 0.622 0.279 2.720

23 1.78 0.700 0.406 3.150

24 1.37 0.614 0.166 2.570

25 1.55 0.568 0.433 2.660

Experience

1 0.69 0.569 -0.422 1.810

2 1.33 0.568 0.216 2.440

3 2.04 0.561 0.942 3.140

4 2.41 0.554 1.330 3.500

Formal Education

1 1.19 0.595 0.026 2.360

2 1.37 0.558 0.278 2.470

3 1.81 0.561 0.708 2.910

4 2.11 0.559 1.010 3.200

Gender

1 1.40 0.561 0.300 2.500

2 1.84 0.550 0.762 2.920

Language

1 2.55 0.355 1.850 3.250

2 2.32 0.370 1.590 3.040

4 1.80 0.690 0.451 3.160

5 2.11 1.150 -0.140 4.360



66

9 -0.85 1.590 -3.970 2.270

10 1.79 1.560 -1.280 4.850

Population Group

1 1.28 0.528 0.250 2.320

2 1.63 0.589 0.480 2.790

3 1.93 0.633 0.687 3.170

4 1.61 0.540 0.555 2.670

5 1.64 0.827 0.019 3.260

Province

1 1.79 0.497 0.818 2.770

2 0.97 0.702 -0.402 2.350

3 1.53 1.630 -1.670 4.720

4 1.91 0.858 0.225 3.590

5 1.72 0.521 0.697 2.740

6 1.46 0.545 0.393 2.530

7 1.62 0.500 0.644 2.610

8 1.60 1.210 -0.762 3.970

9 1.97 0.770 0.458 3.480

Type

1 1.56 0.607 0.370 2.750

2 1.68 0.547 0.610 2.760

3 1.80 0.543 0.739 2.870

4 1.91 0.615 0.705 3.110

5 1.14 0.614 -0.060 2.350



67

Financial Aspects – training (current)

Table 20: Analysis of Variance for Financial Aspects

Source

Sum of

Squares Df

Mean


MAIN EFFECTS

A:Age 7.21 5 1.440 1.070 0.376


C:Experience 209.00 3 69.700 51.710 0.000


E:Gender 9.34 1 9.340 6.930 0.009

F:Language 21.10 5 4.220 3.130 0.008


H:Province 6.00 8 0.750 0.560 0.814

I:Type 10.70 4 2.670 1.980 0.095


TOTAL



Table 21: Table of Least Squares Means for Financial Aspects with 95.0 Percent Confidence Interval



Age

1 2.24 0.798 0.675 3.810

2 1.65 0.435 0.793 2.500

3 1.70 0.421 0.871 2.520

4 1.74 0.420 0.920 2.570

5 1.61 0.428 0.774 2.450

6 2.03 0.456 1.130 2.920

Economic Sector

1 2.13 0.454 1.240 3.020

2 2.18 0.470 1.260 3.100

3 1.62 0.458 0.725 2.520

4 1.77 0.501 0.792 2.760



68

5 1.54 0.481 0.596 2.480

6 1.06 1.260 -1.400 3.530

7 1.79 0.541 0.726 2.850

8 3.04 1.250 0.603 5.490

9 1.63 0.448 0.749 2.510

10 1.21 0.570 0.090 2.320

11 2.24 0.490 1.280 3.200

12 2.18 0.436 1.330 3.030

13 2.15 0.438 1.290 3.000

14 1.12 0.495 0.151 2.090

15 2.04 0.490 1.080 3.000

16 1.74 0.470 0.817 2.660

17 1.60 0.440 0.734 2.460

18 2.05 0.682 0.714 3.390

19 2.19 0.647 0.921 3.460

20 1.38 0.483 0.435 2.330

21 2.30 0.549 1.220 3.370

22 1.67 0.484 0.718 2.620

23 1.71 0.545 0.642 2.780

24 1.68 0.478 0.741 2.610

25 1.68 0.442 0.813 2.540

Experience

1 0.91 0.443 0.045 1.780

2 1.56 0.442 0.690 2.420

3 2.15 0.437 1.290 3.000

4 2.70 0.431 1.850 3.540

Formal Education

1 1.78 0.463 0.875 2.690

2 1.54 0.434 0.689 2.390

3 1.88 0.436 1.030 2.740

4 2.11 0.435 1.250 2.960

Gender

1 1.69 0.436 0.833 2.540

2 1.97 0.428 1.130 2.810

Language

1 2.74 0.277 2.200 3.290

2 2.59 0.288 2.030 3.160

4 1.39 0.537 0.340 2.450

5 2.40 0.893 0.649 4.150



69

9 -0.27 1.240 -2.700 2.150

10 2.11 1.220 -0.276 4.500

Population Group

1 1.48 0.411 0.674 2.280

2 1.95 0.458 1.060 2.850

3 1.94 0.492 0.977 2.910

4 1.79 0.421 0.967 2.620

5 1.97 0.643 0.710 3.230

Province

1 1.80 0.387 1.040 2.560

2 1.33 0.546 0.265 2.400

3 1.92 1.270 -0.570 4.400

4 2.54 0.668 1.230 3.850

5 1.69 0.406 0.899 2.490

6 1.70 0.424 0.870 2.530

7 1.76 0.389 1.000 2.530

8 1.65 0.940 -0.190 3.490

9 2.04 0.599 0.868 3.220

Type

1 1.63 0.472 0.708 2.560

2 1.95 0.426 1.110 2.780

3 1.92 0.423 1.090 2.750

4 2.17 0.478 1.230 3.110

5 1.47 0.478 0.528 2.400



70

Dealing with Surplus and Legislation related to surplus – training (current)

Table 22: Analysis of Variance for Dealing with Surplus and Legislation related to surplus

Source

Sum of

Squares Df

Mean


MAIN EFFECTS

A:Age 7.20 5 1.440 1.100 0.358


C:Experience 220.00 3 73.500 56.280 0.000


E:Gender 5.22 1 5.220 4.000 0.046

F:Language 15.30 5 3.050 2.340 0.040


H:Province 7.84 8 0.980 0.750 0.647

I:Type 12.20 4 3.040 2.330 0.054


TOTAL



Table 23: Table of Least Squares Means for Dealing with Surplus and Legislation related to surplus with 95.0 Percent Confidence Intervals



Age

1 2.49 0.786 0.951 4.030

2 1.66 0.428 0.825 2.500

3 1.75 0.415 0.936 2.560

4 1.72 0.414 0.906 2.530

5 1.55 0.421 0.730 2.380

6 1.86 0.448 0.976 2.730

Economic Sector

1 1.95 0.447 1.080 2.830

2 1.80 0.462 0.895 2.710

3 1.80 0.450 0.919 2.680



71

4 1.92 0.493 0.950 2.880

5 1.78 0.473 0.853 2.710

6 1.37 1.240 -1.050 3.800

7 1.47 0.532 0.429 2.510

8 3.32 1.230 0.917 5.720

9 1.69 0.441 0.824 2.550

10 1.52 0.561 0.424 2.620

11 2.13 0.482 1.190 3.080

12 2.12 0.429 1.280 2.960

13 2.05 0.431 1.200 2.890

14 1.16 0.487 0.206 2.120

15 2.24 0.483 1.300 3.190

16 1.60 0.462 0.697 2.510

17 1.77 0.433 0.924 2.620

18 1.99 0.671 0.674 3.310

19 2.12 0.637 0.877 3.370

20 1.70 0.475 0.773 2.640

21 1.50 0.540 0.442 2.560

22 1.97 0.476 1.040 2.900

23 1.44 0.536 0.385 2.490

24 1.71 0.470 0.787 2.630

25 1.81 0.435 0.963 2.670

Experience

1 0.92 0.435 0.062 1.770

2 1.60 0.435 0.751 2.460

3 2.09 0.430 1.240 2.930

4 2.75 0.424 1.920 3.580

Formal Education

1 1.76 0.455 0.870 2.650

2 1.59 0.427 0.750 2.420

3 1.95 0.429 1.110 2.790

4 2.06 0.428 1.220 2.890

Gender

1 1.73 0.429 0.893 2.580

2 1.94 0.421 1.120 2.770

Language

1 2.60 0.272 2.070 3.140

2 2.52 0.283 1.960 3.070

4 1.35 0.528 0.310 2.380



72

5 2.17 0.879 0.449 3.890

9 0.17 1.220 -2.220 2.560

10 2.22 1.200 -0.123 4.570

Population Group

1 1.60 0.404 0.812 2.400

2 1.79 0.451 0.911 2.680

3 2.17 0.484 1.220 3.120

4 1.84 0.414 1.030 2.650

5 1.78 0.633 0.544 3.020

Province

1 1.81 0.380 1.060 2.550

2 1.29 0.537 0.241 2.350

3 1.80 1.250 -0.646 4.250

4 2.46 0.657 1.180 3.750

5 1.83 0.399 1.050 2.610

6 1.59 0.418 0.775 2.410

7 1.73 0.383 0.979 2.480

8 2.39 0.925 0.576 4.200

9 1.64 0.590 0.482 2.790

Type

1 1.97 0.464 1.060 2.880

2 1.78 0.419 0.963 2.610

3 1.86 0.416 1.050 2.680

4 2.21 0.471 1.290 3.130

5 1.36 0.470 0.440 2.280



73

Interpreting financial statements – training (current)

Table 24: Analysis of Variance for Interpreting financial state

Source

Sum of

Squares Df

Mean


MAIN EFFECTS

A:Age 5.76 5 1.150 0.850 0.517


C:Experience 198.00 3 66.100 48.600 0.000


E:Gender 15.00 1 15.000 11.060 0.001

F:Language 21.10 5 4.210 3.100 0.009


H:Province 9.88 8 1.240 0.910 0.509

I:Type 18.40 4 4.590 3.370 0.010


TOTAL



Table 25: Table of Least Squares Means for Interpreting financial statements with 95.0 Percent Confidence Intervals



Age

1 2.05 0.802 0.475 3.620

2 1.69 0.437 0.834 2.550

3 1.60 0.423 0.772 2.430

4 1.67 0.422 0.839 2.490

5 1.50 0.430 0.661 2.350

6 1.82 0.458 0.919 2.710

Economic Sector

1 1.77 0.456 0.874 2.660

2 2.43 0.472 1.500 3.350

3 1.71 0.459 0.809 2.610



74

4 1.77 0.503 0.787 2.760

5 1.73 0.483 0.786 2.680

6 0.45 1.260 -2.030 2.920

7 1.77 0.543 0.703 2.830

8 2.55 1.250 0.097 5.000

9 1.55 0.450 0.670 2.440

10 0.90 0.572 -0.218 2.020

11 2.17 0.492 1.200 3.130

12 1.88 0.437 1.020 2.740

13 2.10 0.440 1.240 2.960

14 0.77 0.498 -0.208 1.740

15 1.97 0.493 1.000 2.930

16 1.58 0.472 0.658 2.510

17 1.65 0.442 0.788 2.520

18 1.99 0.685 0.652 3.340

19 2.40 0.650 1.130 3.680

20 1.50 0.485 0.554 2.460

21 2.02 0.551 0.937 3.100

22 1.69 0.488 0.735 2.650

23 1.55 0.547 0.474 2.620

24 1.40 0.480 0.457 2.340

25 1.71 0.444 0.844 2.580

Experience

1 0.74 0.445 -0.127 1.620

2 1.53 0.444 0.658 2.400

3 2.06 0.439 1.200 2.920

4 2.56 0.433 1.710 3.400

Formal Education

1 1.29 0.465 0.375 2.200

2 1.44 0.436 0.588 2.300

3 1.93 0.438 1.070 2.780

4 2.23 0.437 1.370 3.080

Gender

1 1.54 0.438 0.684 2.400

2 1.90 0.430 1.050 2.740

Language

1 2.64 0.278 2.090 3.180

2 2.41 0.289 1.850 2.980

4 1.89 0.539 0.835 2.950



75

5 2.59 0.897 0.829 4.340

9 -1.07 1.240 -3.510 1.370

10 1.86 1.220 -0.537 4.260

Population Group

1 1.23 0.413 0.418 2.040

2 1.67 0.460 0.767 2.570

3 1.84 0.495 0.875 2.810

4 1.59 0.422 0.766 2.420

5 2.27 0.646 1.000 3.530

Province

1 1.97 0.388 1.210 2.730

2 1.19 0.548 0.117 2.270

3 1.41 1.270 -1.090 3.910

4 2.30 0.671 0.984 3.610

5 1.86 0.407 1.060 2.650

6 1.81 0.426 0.979 2.650

7 1.82 0.391 1.050 2.590

8 1.24 0.944 -0.606 3.090

9 1.88 0.602 0.702 3.060

Type

1 1.40 0.474 0.476 2.330

2 1.97 0.428 1.130 2.800

3 1.86 0.425 1.030 2.690

4 2.04 0.480 1.100 2.980

5 1.33 0.480 0.392 2.270



76

Retirement Fund governance – training (current)

Table 26: Analysis of Variance for Retirement Fund governance


Mean


MAIN EFFECTS

A:Age 14.10 5 2.810 2.200 0.052


C:Experience 268.00 3 89.400 69.980 0.000


E:Gender 6.83 1 6.830 5.350 0.021

F:Language 22.00 5 4.400 3.440 0.004


H:Province 8.73 8 1.090 0.850 0.555

I:Type 14.30 4 3.580 2.800 0.025


TOTAL



Table 27: Table of Least Squares Means for Retirement Fund governance with 95.0 Percent Confidence Intervals



Age

1 2.38 0.777 0.854 3.900

2 1.54 0.423 0.709 2.370

3 1.66 0.410 0.852 2.460

4 1.77 0.409 0.970 2.570

5 1.52 0.417 0.708 2.340

6 1.99 0.443 1.120 2.850

Economic Sector

1 1.69 0.442 0.821 2.550

2 1.84 0.457 0.939 2.730

3 1.96 0.445 1.090 2.830



77

4 1.83 0.487 0.872 2.780

5 1.66 0.468 0.747 2.580

6 0.75 1.220 -1.650 3.140

7 1.97 0.526 0.940 3.000

8 2.69 1.210 0.311 5.060

9 1.66 0.436 0.803 2.510

10 1.51 0.554 0.423 2.600

11 2.02 0.477 1.090 2.950

12 1.96 0.424 1.130 2.790

13 2.20 0.426 1.370 3.040

14 1.20 0.482 0.251 2.140

15 2.30 0.477 1.370 3.240

16 1.92 0.457 1.020 2.810

17 1.66 0.428 0.824 2.500

18 2.14 0.664 0.834 3.440

19 1.90 0.630 0.664 3.130

20 1.81 0.470 0.889 2.730

21 2.08 0.534 1.030 3.130

22 1.83 0.473 0.903 2.760

23 1.36 0.530 0.326 2.400

24 1.53 0.465 0.617 2.440

25 1.77 0.430 0.927 2.610

Experience

1 0.65 0.431 -0.191 1.500

2 1.53 0.430 0.689 2.370

3 2.32 0.425 1.480 3.150

4 2.73 0.420 1.910 3.560

Formal Education

1 1.43 0.450 0.550 2.320

2 1.55 0.422 0.722 2.380

3 2.10 0.425 1.270 2.930

4 2.16 0.423 1.330 2.980

Gender

1 1.69 0.425 0.858 2.520

2 1.93 0.417 1.110 2.740

Language

1 2.68 0.269 2.150 3.210

2 2.47 0.280 1.920 3.020

4 1.45 0.522 0.426 2.470



78

5 2.68 0.869 0.980 4.390

9 -0.37 1.200 -2.740 1.990

10 1.94 1.180 -0.378 4.270

Population Group

1 1.54 0.400 0.751 2.320

2 1.87 0.446 0.993 2.740

3 1.98 0.479 1.040 2.920

4 1.76 0.409 0.960 2.560

5 1.90 0.626 0.672 3.130

Province

1 2.02 0.376 1.280 2.760

2 1.59 0.531 0.554 2.640

3 1.33 1.230 -1.090 3.750

4 2.49 0.650 1.220 3.760

5 1.95 0.395 1.180 2.730

6 1.86 0.413 1.050 2.670

7 1.82 0.379 1.070 2.560

8 1.44 0.915 -0.355 3.230

9 1.78 0.583 0.635 2.920

Type

1 1.73 0.459 0.825 2.630

2 1.79 0.414 0.977 2.600

3 1.87 0.411 1.060 2.670

4 2.29 0.465 1.380 3.200

5 1.37 0.465 0.461 2.280



79

Explanatory Variable Analysis of Variance (ANOVA) - Needs

Legal Aspects and Legislation – training (needs)

Table 28: Analysis of Variance for Legal Aspects and Legislation

Source

Sum of

Squares Df

Mean


MAIN EFFECTS

A:Age 9.95 5 1.99 0.95 0.45


C:Experience 133.00 3 44.30 21.06 0.00


E:Gender 12.30 1 12.30 5.82 0.02

F:Language 31.40 5 6.29 2.99 0.01


H:Province 17.60 8 2.20 1.04 0.40

I:Type 27.10 4 6.78 3.22 0.01


TOTAL



Table 29: Table of Least Squares Means for Legal Aspects and Legislation with 95.0 Percent Confidence Intervals



Age

1 2.020 0.998 0.059 3.970

2 1.450 0.545 0.381 2.520

3 1.490 0.528 0.452 2.520

4 1.610 0.527 0.577 2.640

5 1.350 0.536 0.304 2.400

6 1.690 0.571 0.568 2.810



80

Economic Sector

1 1.800 0.570 0.684 2.920

2 1.650 0.591 0.491 2.810

3 1.390 0.573 0.271 2.520

4 1.560 0.627 0.337 2.790

5 1.410 0.605 0.222 2.600

6 1.470 1.570 -1.610 4.550

7 0.814 0.677 -0.511 2.140

8 2.640 1.560 -0.409 5.700

9 1.190 0.562 0.087 2.290

10 1.570 0.713 0.169 2.960

11 1.820 0.613 0.622 3.030

12 1.970 0.546 0.897 3.040

13 1.780 0.548 0.703 2.850

14 1.030 0.620 -0.188 2.240

15 1.800 0.614 0.596 3.000

16 1.240 0.588 0.085 2.390

17 1.340 0.552 0.260 2.420

18 2.280 0.856 0.608 3.960

19 2.500 0.809 0.918 4.090

20 1.630 0.605 0.443 2.810

21 1.530 0.687 0.188 2.880

22 1.420 0.610 0.220 2.610

23 1.270 0.681 -0.068 2.600

24 1.710 0.599 0.532 2.880

25 1.190 0.553 0.106 2.280

Experience

1 0.729 0.554 -0.357 1.820

2 1.460 0.553 0.373 2.540

3 1.970 0.547 0.895 3.040

4 2.250 0.540 1.190 3.310

Formal Education

1 1.490 0.579 0.359 2.630

2 1.450 0.544 0.385 2.520

3 1.720 0.547 0.652 2.800

4 1.730 0.544 0.665 2.800

Gender

1 1.440 0.547 0.370 2.510



81

2 1.760 0.536 0.709 2.810

Language

1 2.790 0.346 2.110 3.470

2 2.530 0.360 1.830 3.240

4 1.200 0.672 -0.121 2.510

5 1.930 1.120 -0.257 4.120

9 -0.262 1.550 -3.300 2.780

10 1.410 1.520 -1.570 4.390

Population Group

1 1.770 0.514 0.762 2.780

2 1.510 0.574 0.387 2.640

3 1.440 0.616 0.234 2.650

4 1.840 0.527 0.811 2.880

5 1.430 0.804 -0.142 3.010

Province

1 1.630 0.484 0.684 2.580

2 1.310 0.684 -0.029 2.650

3 0.511 1.590 -2.600 3.620

4 2.470 0.836 0.827 4.100

5 1.450 0.508 0.448 2.440

6 1.410 0.532 0.366 2.450

7 1.830 0.488 0.874 2.790

8 2.220 1.170 -0.086 4.520

9 1.580 0.750 0.111 3.050

Type

1 1.550 0.592 0.396 2.710

2 1.550 0.533 0.505 2.590

3 1.660 0.529 0.624 2.700

4 2.280 0.604 1.100 3.460

5 0.956 0.600 -0.220 2.130



82

Benefits offered and membership – training (needs)

Table 30: Analysis of Variance for Benefits offered and membership

Source

Sum of

Squares Df

Mean


MAIN EFFECTS

A:Age 22.10 5 4.41 1.81 0.11


C:Experience 105.00 3 34.90 14.36 0.00


E:Gender 2.66 1 2.66 1.09 0.30

F:Language 26.70 5 5.33 2.19 0.05


H:Province 24.60 8 3.07 1.26 0.26

I:Type 37.60 4 9.41 3.87 0.00


TOTAL



Table 31: Table of Least Squares Means for Benefits Offered and Membership with 95.0 Percent Confidence Intervals



Age

1 3.250 1.070 1.150 5.360

2 1.790 0.588 0.636 2.940

3 1.780 0.569 0.665 2.900

4 2.000 0.568 0.890 3.120

5 1.730 0.579 0.595 2.860

6 1.420 0.617 0.209 2.630

Economic Sector

1 2.180 0.616 0.972 3.380

2 2.670 0.638 1.410 3.920



83

3 2.180 0.618 0.964 3.390

4 1.960 0.676 0.638 3.290

5 2.190 0.652 0.911 3.470

6 1.880 1.690 -1.430 5.190

7 1.310 0.728 -0.120 2.730

8 -1.700 1.680 -4.980 1.590

9 2.180 0.606 0.994 3.370

10 2.190 0.768 0.681 3.690

11 2.170 0.661 0.870 3.460

12 2.350 0.589 1.190 3.500

13 2.460 0.591 1.310 3.620

14 2.040 0.668 0.728 3.350

15 1.290 0.662 -0.002 2.590

16 2.240 0.635 0.994 3.480

17 2.070 0.595 0.903 3.240

18 2.900 0.922 1.090 4.710

19 3.070 0.871 1.360 4.770

20 2.020 0.652 0.743 3.300

21 2.280 0.740 0.829 3.730

22 1.930 0.655 0.647 3.220

23 2.200 0.734 0.763 3.640

24 2.290 0.646 1.030 3.560

25 1.550 0.597 0.382 2.720

Experience

1 1.130 0.598 -0.038 2.300

2 1.910 0.597 0.743 3.080

3 2.440 0.590 1.280 3.590

4 2.500 0.583 1.350 3.640

Formal Education

1 1.950 0.625 0.726 3.180

2 1.760 0.586 0.613 2.910

3 2.100 0.590 0.943 3.260

4 2.170 0.588 1.020 3.320

Gender

1 1.920 0.590 0.765 3.080

2 2.070 0.578 0.938 3.200

Language

1 3.120 0.375 2.390 3.860

2 2.930 0.389 2.170 3.690



84

4 1.670 0.725 0.245 3.090

5 2.660 1.200 0.305 5.020

9 -0.189 1.670 -3.460 3.080

10 1.780 1.640 -1.420 4.990

Population Group

1 1.850 0.554 0.761 2.930

2 1.980 0.619 0.769 3.200

3 2.080 0.664 0.776 3.380

4 2.070 0.568 0.959 3.190

5 2.000 0.867 0.300 3.700

Province

1 1.970 0.521 0.944 2.990

2 2.060 0.736 0.618 3.500

3 1.060 1.700 -2.280 4.400

4 3.200 0.966 1.300 5.090

5 1.650 0.548 0.576 2.720

6 1.850 0.573 0.728 2.970

7 2.180 0.525 1.150 3.210

8 2.300 1.260 -0.176 4.780

9 1.700 0.806 0.123 3.280

Type

1 2.130 0.638 0.883 3.380

2 1.830 0.575 0.703 2.960

3 1.930 0.571 0.815 3.050

4 2.830 0.651 1.550 4.100

5 1.260 0.647 -0.013 2.520



85

Service Providers – training (needs)

Table 32: Analysis of Variance for Service Providers


Mean


MAIN EFFECTS

A:Age 16.10 5 3.22 1.25 0.28


C:Experience 89.60 3 29.90 11.59 0.00


E:Gender 9.12 1 9.12 3.54 0.06

F:Language 26.00 5 5.20 2.02 0.07


H:Province 31.80 8 3.97 1.54 0.14

I:Type 37.10 4 9.28 3.60 0.01


TOTAL



Table 33: Table of Least Squares Means for Service Providers with 95.0 Percent Confidence Intervals



Age

1 2.530 1.110 0.366 4.700

2 1.870 0.605 0.686 3.060

3 1.550 0.586 0.403 2.700

4 1.780 0.585 0.633 2.920

5 1.510 0.596 0.342 2.680

6 1.700 0.635 0.452 2.940

Economic Sector

1 2.120 0.634 0.881 3.360

2 2.650 0.657 1.370 3.940

3 1.950 0.637 0.700 3.200



86

4 1.660 0.695 0.300 3.020

5 2.040 0.671 0.723 3.350

6 1.720 1.740 -1.690 5.130

7 1.100 0.749 -0.366 2.570

8 -1.700 1.720 -5.080 1.680

9 1.760 0.624 0.542 2.990

10 1.990 0.791 0.446 3.540

11 1.890 0.680 0.557 3.220

12 2.320 0.606 1.130 3.510

13 2.110 0.608 0.919 3.300

14 1.890 0.688 0.540 3.240

15 1.150 0.681 -0.183 2.490

16 2.140 0.653 0.857 3.420

17 1.850 0.613 0.653 3.050

18 1.830 0.948 -0.032 3.690

19 3.040 0.896 1.280 4.790

20 2.030 0.671 0.715 3.340

21 1.940 0.761 0.448 3.430

22 1.910 0.674 0.592 3.230

23 2.400 0.755 0.917 3.880

24 2.240 0.665 0.933 3.540

25 1.550 0.614 0.346 2.750

Experience

1 1.050 0.615 -0.159 2.250

2 1.730 0.614 0.523 2.930

3 2.230 0.607 1.040 3.420

4 2.290 0.599 1.120 3.470

Formal Education

1 1.870 0.643 0.607 3.130

2 1.650 0.603 0.468 2.830

3 1.910 0.607 0.722 3.100

4 1.870 0.605 0.680 3.050

Gender

1 1.680 0.607 0.496 2.870

2 1.960 0.595 0.796 3.130

Language

1 2.980 0.386 2.230 3.740

2 2.910 0.400 2.130 3.700

4 1.410 0.745 -0.050 2.870



87

5 2.230 1.240 -0.198 4.650

9 -0.299 1.720 -3.660 3.060

10 1.700 1.680 -1.600 5.010

Population Group

1 1.740 0.571 0.622 2.860

2 1.570 0.637 0.324 2.820

3 2.040 0.683 0.705 3.380

4 1.870 0.585 0.722 3.010

5 1.890 0.892 0.146 3.640

Province

1 1.810 0.536 0.762 2.860

2 0.855 0.757 -0.629 2.340

3 0.775 1.750 -2.660 4.210

4 3.140 0.994 1.190 5.090

5 1.730 0.564 0.630 2.840

6 1.930 0.589 0.776 3.090

7 2.160 0.541 1.100 3.220

8 2.170 1.300 -0.383 4.710

9 1.840 0.829 0.213 3.460

Type

1 1.950 0.656 0.662 3.230

2 1.680 0.592 0.519 2.840

3 1.780 0.587 0.631 2.930

4 2.640 0.669 1.330 3.950

5 1.070 0.666 -0.238 2.370



88

Investment Management – training (needs)

Table 34: Analysis of Variance for Investment Management

Source

Sum of

Squares Df

Mean


MAIN EFFECTS

A:Age 15.40 5 3.09 0.72 0.61


C:Experience 128.00 3 42.60 9.90 0.00


E:Gender 8.89 1 8.89 2.07 0.15

F:Language 26.80 5 5.35 1.24 0.29


H:Province 11.10 8 1.38 0.32 0.96

I:Type 50.40 4 12.60 2.93 0.02


TOTAL



Table 35: Table of Least Squares Means for Investment Management with 95.0 Percent Confidence Intervals



Age

1 2.640 1.430 -0.163 5.440

2 1.970 0.781 0.438 3.500

3 1.920 0.757 0.435 3.400

4 1.800 0.755 0.320 3.280

5 1.550 0.769 0.046 3.060

6 1.490 0.819 -0.112 3.100

Economic Sector

1 1.900 0.817 0.296 3.500

2 2.250 0.847 0.585 3.910

3 1.820 0.822 0.211 3.430



89

4 1.550 0.898 -0.207 3.310

5 1.620 0.867 -0.077 3.320

6 1.110 2.250 -3.290 5.520

7 0.910 0.967 -0.986 2.810

8 3.030 2.230 -1.330 7.400

9 1.960 0.805 0.381 3.540

10 2.550 1.020 0.546 4.550

11 2.110 0.878 0.386 3.830

12 2.110 0.783 0.572 3.640

13 2.180 0.785 0.639 3.720

14 1.310 0.888 -0.427 3.050

15 0.904 0.879 -0.819 2.630

16 1.940 0.843 0.284 3.590

17 1.810 0.791 0.258 3.360

18 2.640 1.220 0.244 5.040

19 2.790 1.160 0.523 5.060

20 1.770 0.866 0.077 3.470

21 1.340 0.984 -0.587 3.270

22 1.590 0.874 -0.121 3.310

23 2.210 0.975 0.300 4.120

24 2.340 0.859 0.653 4.020

25 1.630 0.793 0.074 3.180

Experience

1 1.060 0.794 -0.495 2.620

2 1.750 0.793 0.199 3.310

3 2.210 0.784 0.670 3.740

4 2.560 0.774 1.040 4.080

Formal Education

1 1.700 0.830 0.073 3.330

2 1.690 0.779 0.166 3.220

3 2.050 0.783 0.512 3.580

4 2.140 0.780 0.611 3.670

Gender

1 1.760 0.783 0.224 3.290

2 2.030 0.768 0.526 3.540

Language

1 2.840 0.498 1.860 3.810

2 2.590 0.516 1.580 3.600

4 1.340 0.962 -0.541 3.230



90

5 2.770 1.600 -0.366 5.900

9 -0.091 2.220 -4.440 4.250

10 1.920 2.180 -2.340 6.190

Population Group

1 1.570 0.737 0.125 3.010

2 1.900 0.822 0.289 3.510

3 1.820 0.882 0.087 3.540

4 2.290 0.755 0.807 3.770

5 1.900 1.150 -0.354 4.160

Province

1 1.890 0.693 0.535 3.250

2 1.020 0.978 -0.892 2.940

3 1.670 2.270 -2.770 6.120

4 2.080 1.280 -0.440 4.590

5 1.970 0.727 0.545 3.400

6 1.900 0.760 0.413 3.390

7 2.050 0.698 0.677 3.410

8 2.680 1.680 -0.613 5.970

9 1.790 1.070 -0.309 3.890

Type

1 2.130 0.848 0.464 3.790

2 1.670 0.764 0.175 3.170

3 2.010 0.758 0.527 3.500

4 2.560 0.864 0.869 4.260

5 1.100 0.862 -0.588 2.790



91

Financial Aspects – training (needs)

Table 36: Analysis of Variance for Financial Aspects

Source

Sum of

Squares Df

Mean


MAIN EFFECTS

A:Age 12.90 5 2.58 1.06 0.38


C:Experience 111.00 3 37.00 15.28 0.00


E:Gender 2.19 1 2.19 0.90 0.34

F:Language 17.60 5 3.52 1.45 0.20


H:Province 20.50 8 2.57 1.06 0.39

I:Type 42.80 4 10.70 4.42 0.00


TOTAL



Table 37: Table of Least Squares Means for Financial Aspects with 95.0 Percent Confidence Interval



Age

1 2.350 1.070 0.244 4.450

2 1.990 0.586 0.839 3.140

3 1.790 0.568 0.679 2.910

4 2.060 0.567 0.953 3.180

5 1.820 0.577 0.684 2.950

6 1.820 0.615 0.609 3.020

Economic Sector

1 2.130 0.613 0.929 3.330

2 2.530 0.636 1.280 3.780

3 1.750 0.618 0.538 2.960

4 1.620 0.674 0.299 2.940



92

5 1.780 0.651 0.502 3.050

6 0.931 1.690 -2.380 4.240

7 0.984 0.726 -0.439 2.410

8 3.210 1.670 -0.070 6.480

9 1.570 0.605 0.388 2.760

10 1.970 0.767 0.467 3.470

11 2.310 0.662 1.010 3.610

12 2.320 0.588 1.170 3.470

13 2.110 0.590 0.956 3.270

14 1.550 0.667 0.240 2.850

15 1.130 0.660 -0.164 2.420

16 1.990 0.633 0.749 3.230

17 1.770 0.594 0.610 2.940

18 2.850 0.876 1.130 4.560

19 3.090 0.869 1.390 4.800

20 1.940 0.650 0.663 3.210

21 1.850 0.739 0.399 3.290

22 1.710 0.654 0.424 2.990

23 2.210 0.732 0.775 3.650

24 2.440 0.647 1.180 3.710

25 1.510 0.596 0.346 2.680

Experience

1 1.140 0.596 -0.030 2.310

2 1.880 0.596 0.708 3.040

3 2.290 0.588 1.140 3.450

4 2.570 0.581 1.430 3.710

Formal Education

1 1.780 0.623 0.559 3.000

2 1.770 0.585 0.629 2.920

3 2.110 0.588 0.960 3.270

4 2.210 0.586 1.060 3.360

Gender

1 1.900 0.588 0.749 3.050

2 2.040 0.577 0.908 3.170

Language

1 2.920 0.374 2.190 3.660

2 2.790 0.388 2.030 3.550

4 1.930 0.723 0.515 3.350

5 2.580 1.200 0.227 4.930



93

9 -0.345 1.660 -3.610 2.920

10 1.940 1.630 -1.260 5.140

Population Group

1 1.710 0.553 0.625 2.790

2 2.030 0.617 0.823 3.240

3 2.150 0.663 0.851 3.450

4 2.040 0.567 0.930 3.150

5 1.920 0.865 0.222 3.610

Province

1 1.920 0.520 0.904 2.940

2 1.160 0.735 -0.281 2.600

3 1.220 1.700 -2.120 4.550

4 2.740 0.964 0.853 4.630

5 1.820 0.546 0.746 2.890

6 2.030 0.571 0.911 3.150

7 2.200 0.524 1.170 3.230

8 2.630 1.260 0.158 5.100

9 2.010 0.804 0.437 3.590

Type

1 2.130 0.637 0.878 3.370

2 1.880 0.573 0.755 3.000

3 2.060 0.569 0.941 3.170

4 2.710 0.649 1.440 3.980

5 1.080 0.646 -0.183 2.350



94

Dealing with Surplus and Legislation related to surplus – training (needs)

Table 38: Analysis of Variance for Dealing with Surplus and Legislation related to surplus

Source

Sum of

Squares Df

Mean


MAIN EFFECTS

A:Age 17.00 5 3.39 1.36 0.24


C:Experience 108.00 3 35.90 14.40 0.00


E:Gender 4.91 1 4.91 1.97 0.16

F:Language 21.10 5 4.21 1.69 0.13


H:Province 62.20 8 7.78 3.12 0.00

I:Type 26.20 4 6.54 2.62 0.03

RESIDUAL 2,130 854 2.5

TOTAL



Table 39: Table of Least Squares Means for Dealing with Surplus and Legislation related to surplus with 95.0 Percent Confidence Intervals



Age

1 2.810 1.090 0.675 4.940

2 1.870 0.594 0.701 3.030

3 1.800 0.576 0.670 2.930

4 2.050 0.575 0.927 3.180

5 1.740 0.586 0.596 2.890

6 1.690 0.624 0.466 2.910

Economic Sector

1 2.570 0.621 1.350 3.790

2 2.710 0.646 1.450 3.980

3 1.930 0.626 0.704 3.160



95

4 1.930 0.684 0.587 3.270

5 1.880 0.660 0.591 3.180

6 2.490 1.710 -0.865 5.840

7 0.999 0.737 -0.445 2.440

8 -1.750 1.700 -5.080 1.570

9 1.850 0.613 0.651 3.060

10 2.720 0.778 1.200 4.250

11 2.200 0.669 0.891 3.510

12 2.260 0.597 1.090 3.430

13 2.300 0.598 1.130 3.480

14 1.730 0.677 0.407 3.060

15 1.040 0.670 -0.273 2.350

16 2.120 0.642 0.859 3.380

17 2.010 0.603 0.826 3.190

18 3.030 0.888 1.290 4.770

19 3.230 0.882 1.500 4.960

20 2.190 0.659 0.896 3.480

21 2.020 0.749 0.547 3.480

22 2.060 0.663 0.756 3.350

23 2.360 0.743 0.900 3.810

24 2.310 0.656 1.030 3.600

25 1.650 0.604 0.465 2.830

Experience

1 1.130 0.605 -0.055 2.320

2 2.050 0.604 0.867 3.240

3 2.200 0.597 1.030 3.370

4 2.590 0.589 1.440 3.740

Formal Education

1 1.930 0.632 0.691 3.170

2 1.810 0.593 0.646 2.970

3 2.160 0.597 0.987 3.330

4 2.080 0.595 0.914 3.250

Gender

1 1.890 0.596 0.722 3.060

2 2.100 0.585 0.949 3.240

Language

1 2.920 0.379 2.170 3.660

2 2.670 0.393 1.900 3.440

4 1.860 0.734 0.419 3.290



96

5 2.720 1.220 0.336 5.110

9 -0.173 1.690 -3.480 3.140

10 1.970 1.660 -1.280 5.220

Population Group

1 1.700 0.561 0.601 2.800

2 1.850 0.626 0.626 3.080

3 2.300 0.672 0.980 3.610

4 2.080 0.575 0.958 3.210

5 2.030 0.877 0.313 3.750

Province

1 1.950 0.527 0.919 2.990

2 0.756 0.745 -0.704 2.220

3 0.934 1.730 -2.450 4.320

4 2.950 0.978 1.030 4.860

5 1.590 0.553 0.507 2.680

6 1.850 0.580 0.709 2.980

7 2.360 0.532 1.320 3.400

8 2.680 1.280 0.175 5.190

9 2.870 0.816 1.270 4.470

Type

1 2.080 0.646 0.820 3.350

2 1.850 0.582 0.711 2.990

3 1.930 0.577 0.803 3.070

4 2.700 0.658 1.410 3.990

5 1.390 0.655 0.111 2.680



97

Interpreting financial statements – training (needs)

Table 40: Analysis of Variance for Interpreting financial statements

Source

Sum of

Squares Df

Mean


MAIN EFFECTS

A:Age 21.10 5 4.22 1.59 0.16


C:Experience 108.00 3 35.90 13.53 0.00


E:Gender 0.37 1 0.37 0.14 0.71

F:Language 18.40 5 3.68 1.38 0.23


H:Province 19.10 8 2.39 0.90 0.52

I:Type 37.10 4 9.29 3.50 0.01


TOTAL



Table 41: Table of Least Squares Means for Interpreting financial statements with 95.0 Percent Confidence Intervals



Age

1 2.550 1.120 0.346 4.750

2 2.020 0.615 0.811 3.220

3 1.710 0.595 0.542 2.880

4 2.050 0.594 0.890 3.220

5 1.750 0.605 0.565 2.940

6 1.860 0.644 0.598 3.120

Economic Sector

1 2.250 0.644 0.992 3.510

2 2.900 0.672 1.580 4.220

3 2.260 0.647 0.988 3.520



98

4 1.500 0.707 0.119 2.890

5 2.160 0.682 0.824 3.500

6 0.697 1.770 -2.770 4.160

7 1.000 0.761 -0.492 2.490

8 -1.560 1.750 -4.990 1.870

9 2.000 0.634 0.760 3.250

10 1.960 0.803 0.384 3.530

11 2.010 0.691 0.651 3.360

12 2.550 0.617 1.340 3.760

13 2.320 0.618 1.110 3.530

14 1.800 0.699 0.427 3.170

15 1.350 0.692 -0.007 2.710

16 2.240 0.663 0.937 3.540

17 2.130 0.623 0.909 3.350

18 3.260 0.963 1.370 5.150

19 3.230 0.968 1.330 5.130

20 2.060 0.682 0.728 3.400

21 2.220 0.774 0.704 3.740

22 2.130 0.686 0.783 3.470

23 2.410 0.767 0.910 3.920

24 2.850 0.678 1.520 4.180

25 2.010 0.625 0.782 3.230

Experience

1 1.180 0.624 -0.049 2.400

2 1.890 0.624 0.662 3.110

3 2.320 0.616 1.110 3.520

4 2.580 0.609 1.390 3.770

Formal Education

1 1.850 0.653 0.574 3.130

2 1.710 0.612 0.513 2.910

3 2.150 0.616 0.944 3.360

4 2.240 0.614 1.040 3.440

Gender

1 2.020 0.616 0.810 3.220

2 1.960 0.604 0.777 3.150

Language

1 3.020 0.392 2.260 3.790

2 2.980 0.407 2.180 3.780

4 2.010 0.757 0.523 3.490



99

5 2.430 1.260 -0.035 4.890

9 -0.509 1.740 -3.930 2.910

10 2.000 1.710 -1.350 5.360

Population Group

1 1.800 0.579 0.661 2.930

2 1.860 0.646 0.598 3.130

3 2.050 0.694 0.694 3.420

4 1.890 0.594 0.728 3.060

5 2.340 0.905 0.565 4.110

Province

1 1.950 0.545 0.878 3.010

2 1.540 0.777 0.019 3.060

3 1.110 1.780 -2.380 4.610

4 2.470 1.010 0.489 4.450

5 1.760 0.572 0.639 2.880

6 2.150 0.598 0.975 3.320

7 2.220 0.549 1.140 3.290

8 2.460 1.320 -0.127 5.050

9 2.250 0.842 0.600 3.900

Type

1 2.170 0.666 0.860 3.470

2 1.860 0.601 0.687 3.040

3 1.950 0.596 0.779 3.120

4 2.790 0.680 1.450 4.120

5 1.180 0.678 -0.148 2.510



100

Retirement Fund governance – training (needs)

Table 42: Analysis of Variance for Retirement Fund governance

Source

Sum of

Squares Df

Mean


MAIN EFFECTS

A:Age 13.80 5 2.76 1.15 0.33


C:Experience 79.00 3 26.30 10.96 0.00


E:Gender 6.17 1 6.17 2.57 0.11

F:Language 14.50 5 2.91 1.21 0.30


H:Province 10.10 8 1.27 0.53 0.84

I:Type 44.40 4 11.10 4.62 0.00


TOTAL



Table 43: Table of Least Squares Means for Retirement Fund governance with 95.0 Percent Confidence Intervals



Age

1 2.850 1.070 0.754 4.940

2 2.240 0.584 1.100 3.390

3 2.310 0.565 1.210 3.420

4 2.500 0.564 1.390 3.600

5 2.180 0.574 1.050 3.300

6 2.240 0.611 1.040 3.440

Economic Sector

1 2.340 0.611 1.140 3.540

2 2.940 0.637 1.690 4.190

3 2.370 0.612 1.170 3.570



101

4 1.970 0.671 0.652 3.280

5 2.050 0.648 0.782 3.320

6 2.300 1.680 -0.995 5.590

7 1.640 0.724 0.226 3.060

8 3.400 1.660 0.143 6.670

9 2.000 0.602 0.825 3.180

10 2.850 0.763 1.360 4.350

11 2.210 0.656 0.923 3.500

12 2.640 0.584 1.490 3.780

13 2.510 0.587 1.360 3.660

14 1.830 0.663 0.529 3.130

15 1.460 0.657 0.177 2.750

16 2.280 0.630 1.040 3.510

17 2.060 0.591 0.906 3.220

18 3.240 0.915 1.450 5.030

19 3.190 0.864 1.500 4.880

20 2.230 0.647 0.961 3.500

21 2.100 0.735 0.657 3.540

22 2.390 0.653 1.110 3.670

23 2.960 0.754 1.480 4.440

24 2.680 0.641 1.420 3.940

25 2.000 0.593 0.836 3.160

Experience

1 1.640 0.593 0.480 2.800

2 2.350 0.592 1.190 3.510

3 2.690 0.585 1.540 3.830

4 2.870 0.578 1.740 4.000

Formal Education

1 2.120 0.620 0.910 3.340

2 2.220 0.581 1.080 3.360

3 2.610 0.585 1.460 3.750

4 2.590 0.582 1.450 3.730

Gender

1 2.270 0.585 1.130 3.420

2 2.500 0.573 1.380 3.620

Language

1 3.290 0.370 2.560 4.010

2 3.210 0.385 2.460 3.970

4 2.660 0.718 1.250 4.060



102

5 3.300 1.200 0.959 5.640

9 -0.087 1.660 -3.340 3.170

10 1.950 1.630 -1.240 5.130

Population Group

1 2.150 0.550 1.080 3.230

2 2.110 0.614 0.905 3.310

3 2.460 0.659 1.170 3.750

4 2.370 0.564 1.260 3.470

5 2.840 0.860 1.160 4.530

Province

1 2.310 0.518 1.290 3.320

2 2.110 0.733 0.676 3.550

3 1.220 1.690 -2.110 4.540

4 3.000 0.893 1.250 4.750

5 2.290 0.544 1.220 3.350

6 2.350 0.569 1.240 3.470

7 2.520 0.522 1.490 3.540

8 2.940 1.260 0.479 5.400

9 2.750 0.801 1.180 4.320

Type

1 2.600 0.633 1.360 3.840

2 2.250 0.570 1.130 3.370

3 2.320 0.565 1.210 3.420

4 3.260 0.646 1.990 4.530

5 1.510 0.642 0.251 2.770



103

Distributions of trustees – final results

This section uses a tabular format to give an indication of how the trustees actually responded in

the survey. Each of the questions posed to the trustees are the same as those listed in the ‘Key

Findings – Retirement Fund Trustees’ section. To recap, these questions asked each trustee to

rank their current skill level and their self-assessed training required on that particular level. The

questions covered the following areas:

• Legal aspects

• Benefits and membership

• Service providers

• Investment management

• Financial aspects

• Dealing with surpluses

• Interpreting financial statements

• Retirement Fund Governance

Answers to the questions were given as options between 1 and 5; 1 representing a basic

knowledge of the topic and 5 representing an advanced knowledge of the topic. The tables that

follow below examine the responses with respect to 5 of the more significant variables, those

being:

• Province

• Population group

• Trustee type

• Formal education

• Experience

In this type of analysis, it is important to have a minimum number of trustees in each field to give

the desired level of confidence in results. This has limited the number of variables available for

analysis to the set of 5 given above. Certain fields in the province table may show null values

since there may be no trustees in that category (especially for Northern Cape and Limpopo

provinces).



104

Again, the index of variable coding refers to each of the coded variables. The first table for each

of the areas of knowledge gives an overall distribution of trustees across all of the levels.

Each of the other tables will provide a distribution of trustees across the variable (eg. the

percentages given are percentages of the row total (ie. 21.4% of Gauteng trustees are at a basic

level of knowledge on Legal Aspects of retirement funds)).

Each table is labelled on the upper left corner in bold.



105

Table 44 - 139: Trustee skills and requirements distribution

Legal Aspects and Legislation

Current training

Level Overall 1 2 3 4 5

Total 21.8% 11.4% 35.1% 18.7% 11.2%

Level Province 1 2 3 4 5

1 21.4% 10.5% 35.2% 19.9% 11.6%

2 30.0% 3.3% 26.7% 26.7% 6.7%

3 33.3% 33.3% 33.3% 0.0% 0.0%

4 0.0% 20.0% 20.0% 60.0% 0.0%

5 15.3% 8.2% 42.4% 17.6% 14.1%

6 12.9% 15.7% 34.3% 22.9% 11.4%

7 25.2% 14.8% 29.9% 17.4% 11.1%

8 0.0% 0.0% 100.0% 0.0% 0.0%

9 23.1% 30.8% 30.8% 7.7% 7.7%

Population Level Group 1 2 3 4 5

1 30.0% 12.9% 33.6% 11.5% 8.8%

2 22.4% 24.1% 39.7% 6.9% 1.7%

3 22.2% 14.8% 44.4% 11.1% 7.4%

4 20.2% 10.5% 34.6% 21.0% 12.4%

5 14.3% 0.0% 71.4% 0.0% 0.0%



106

Trustee Level Type 1 2 3 4 5

1 22.0% 8.0% 30.0% 22.0% 16.0%

2 21.8% 9.7% 33.5% 22.7% 10.8%

3 22.1% 14.0% 40.0% 14.5% 7.8%

4 9.3% 3.7% 13.0% 22.2% 50.0%

5 25.0% 11.5% 23.1% 19.2% 15.4%

Formal Level Education 1 2 3 4 5

1 29.7% 9.4% 40.6% 10.9% 3.1%

2 26.8% 14.2% 40.7% 11.0% 5.3%

3 22.4% 13.2% 30.3% 21.0% 11.2%

4 19.2% 9.7% 35.3% 21.0% 13.7%

Trustee Level Experience 1 2 3 4 5

1 59.6% 18.3% 11.5% 1.0% 1.9%

2 38.4% 19.7% 34.1% 5.2% 2.6%

3 19.1% 13.7% 45.9% 13.7% 6.6%

4 12.7% 6.9% 33.3% 28.3% 17.8%

Self-assessed required training level


Total 13.4% 6.9% 23.7% 17.8% 29.3%



107

Level

Province 1 2 3 4 5

1 14.0% 6.5% 21.2% 17.9% 31.4%

2 6.7% 3.3% 50.0% 20.0% 16.7%

3 33.3% 66.7% 0.0% 0.0% 0.0%

4 0.0% 0.0% 20.0% 40.0% 40.0%

5 5.9% 6.5% 30.0% 18.8% 26.5%

6 11.4% 8.6% 31.4% 12.9% 25.7%

7 14.1% 9.1% 20.5% 18.5% 29.5%

8 0.0% 0.0% 50.0% 0.0% 50.0%

9 15.4% 0.0% 38.5% 23.1% 23.1%


1 23.5% 10.1% 24.9% 12.9% 23.0%

2 24.1% 17.2% 15.5% 20.7% 13.8%

3 14.8% 11.1% 25.9% 14.8% 25.9%

4 10.9% 5.4% 23.7% 18.9% 31.8%

5 0.0% 28.6% 42.9% 14.3% 0.0%


1 16.0% 6.0% 20.0% 16.0% 40.0%

2 11.3% 6.0% 21.8% 18.2% 31.8%

3 15.7% 8.4% 28.0% 18.4% 23.8%

4 1.9% 3.7% 5.6% 7.4% 66.7%

5 11.5% 1.9% 17.3% 21.2% 23.1%



108


1 23.4% 12.5% 25.0% 17.2% 15.6%

2 19.5% 10.2% 26.8% 16.3% 21.5%

3 15.1% 8.1% 21.0% 16.5% 29.7%

4 9.6% 4.6% 24.1% 19.2% 33.0%


1 52.9% 12.5% 8.7% 9.6% 10.6%

2 25.3% 14.0% 29.7% 13.5% 14.4%

3 10.3% 8.0% 33.9% 18.8% 21.9%

4 5.6% 3.2% 19.0% 20.2% 40.6%



109

Benefits offered and membership

Current training


Total 15.9% 7.7% 26.9% 25.3% 21.7%


1 16.1% 7.6% 24.6% 27.9% 21.8%

2 10.0% 0.0% 46.7% 13.3% 23.3%

3 0.0% 33.3% 66.7% 0.0% 0.0%

4 0.0% 0.0% 20.0% 60.0% 20.0%

5 6.5% 11.2% 28.2% 25.3% 26.5%

6 8.6% 8.6% 28.6% 30.0% 21.4%

7 20.1% 6.7% 29.9% 19.5% 20.8%

8 0.0% 0.0% 50.0% 50.0% 0.0%

9 23.1% 15.4% 30.8% 23.1% 7.7%


1 23.0% 10.6% 25.8% 19.8% 16.1%

2 20.7% 17.2% 37.9% 6.9% 12.1%

3 11.1% 14.8% 37.0% 11.1% 25.9%

4 14.5% 6.5% 26.0% 27.8% 23.4%

5 0.0% 14.3% 42.9% 28.6% 0.0%



110


1 14.0% 8.0% 26.0% 16.0% 32.0%

2 14.7% 7.5% 25.3% 27.7% 22.5%

3 16.5% 8.7% 31.3% 24.1% 17.4%

4 9.3% 1.9% 5.6% 25.9% 55.6%

5 25.0% 5.8% 13.5% 21.2% 26.9%


1 29.7% 3.1% 35.9% 7.8% 18.8%

2 20.7% 9.3% 35.4% 19.1% 11.8%

3 15.7% 10.1% 20.4% 26.3% 25.2%

4 13.4% 6.4% 26.3% 28.7% 23.5%


1 54.8% 13.5% 12.5% 8.7% 1.9%

2 28.4% 17.9% 32.8% 15.7% 4.8%

3 10.5% 9.1% 42.7% 22.8% 13.1%

4 9.2% 2.8% 19.5% 31.9% 34.7%



Total 9.3% 5.5% 22.5% 16.7% 33.2%



111

Level

Province 1 2 3 4 5

1 9.9% 4.5% 20.5% 17.0% 35.2%

2 3.3% 0.0% 36.7% 3.3% 46.7%

3 0.0% 66.7% 33.3% 0.0% 0.0%

4 0.0% 0.0% 20.0% 0.0% 60.0%

5 4.1% 6.5% 23.5% 16.5% 31.8%

6 8.6% 7.1% 20.0% 27.1% 27.1%

7 8.7% 7.0% 24.2% 17.8% 31.2%

8 0.0% 0.0% 50.0% 0.0% 50.0%

9 23.1% 7.7% 15.4% 23.1% 30.8%


1 22.1% 7.8% 19.8% 12.9% 29.0%

2 15.5% 13.8% 32.8% 12.1% 19.0%

3 11.1% 11.1% 25.9% 11.1% 33.3%

4 6.6% 4.6% 21.9% 18.0% 35.1%

5 0.0% 0.0% 71.4% 14.3% 0.0%


1 8.0% 4.0% 22.0% 14.0% 42.0%

2 6.3% 6.0% 19.8% 17.0% 33.8%

3 12.1% 5.9% 26.9% 18.0% 28.8%

4 1.9% 0.0% 5.6% 7.4% 74.1%

5 11.5% 3.8% 19.2% 9.6% 32.7%



112


1 23.4% 7.8% 23.4% 12.5% 26.6%

2 14.2% 9.3% 31.3% 13.8% 22.8%

3 11.5% 5.6% 19.6% 16.8% 32.8%

4 5.5% 3.8% 21.0% 18.3% 37.5%


1 43.3% 15.4% 15.4% 4.8% 14.4%

2 17.5% 11.4% 33.6% 13.5% 17.9%

3 5.4% 4.3% 35.3% 19.4% 27.6%

4 3.9% 2.7% 13.9% 18.3% 43.7%



113

Service Providers

Current training


Total 14.4% 7.2% 23.6% 27.6% 24.4%


1 14.2% 8.3% 21.2% 28.3% 25.9%

2 13.3% 0.0% 36.7% 36.7% 6.7%

3 0.0% 33.3% 33.3% 0.0% 33.3%

4 0.0% 0.0% 0.0% 40.0% 60.0%

5 7.1% 7.1% 25.9% 31.2% 26.5%

6 10.0% 4.3% 32.9% 34.3% 15.7%

7 18.5% 6.7% 21.8% 24.8% 24.5%

8 0.0% 0.0% 0.0% 50.0% 50.0%

9 30.8% 0.0% 15.4% 46.2% 7.7%


1 19.4% 13.4% 20.7% 26.7% 16.1%

2 15.5% 15.5% 41.4% 10.3% 12.1%

3 11.1% 14.8% 22.2% 25.9% 25.9%

4 13.6% 5.5% 23.2% 28.9% 26.8%

5 0.0% 0.0% 57.1% 14.3% 14.3%



114


1 12.0% 6.0% 20.0% 18.0% 42.0%

2 13.5% 5.2% 23.2% 30.2% 26.0%

3 14.6% 9.5% 28.0% 27.7% 18.0%

4 11.1% 1.9% 3.7% 13.0% 68.5%

5 23.1% 9.6% 5.8% 23.1% 28.8%


1 21.9% 14.1% 25.0% 18.8% 14.1%

2 17.1% 9.3% 36.2% 25.6% 8.5%

3 14.0% 7.3% 21.0% 29.4% 25.2%

4 13.3% 5.7% 20.6% 28.4% 30.3%


1 50.0% 14.4% 13.5% 9.6% 1.9%

2 23.6% 14.8% 34.5% 17.9% 8.3%

3 9.1% 9.7% 34.2% 29.3% 16.0%

4 9.2% 2.4% 16.8% 32.6% 37.5%



Total 9.7% 5.7% 21.8% 18.2% 30.9%



115

Level

Province 1 2 3 4 5

1 10.0% 5.7% 21.7% 16.7% 31.8%

2 0.0% 16.7% 23.3% 33.3% 16.7%

3 0.0% 33.3% 33.3% 0.0% 33.3%

4 0.0% 0.0% 20.0% 0.0% 60.0%

5 3.5% 4.7% 22.4% 12.4% 37.1%

6 10.0% 5.7% 21.4% 25.7% 27.1%

7 9.7% 6.4% 21.5% 21.8% 28.5%

8 0.0% 0.0% 50.0% 0.0% 50.0%

9 23.1% 0.0% 15.4% 30.8% 30.8%


1 21.7% 11.1% 17.5% 18.9% 24.0%

2 15.5% 10.3% 39.7% 6.9% 17.2%

3 7.4% 11.1% 22.2% 11.1% 37.0%

4 7.1% 4.4% 21.6% 18.6% 33.2%

5 0.0% 0.0% 57.1% 28.6% 0.0%


1 8.0% 2.0% 20.0% 18.0% 44.0%

2 7.7% 5.8% 19.0% 19.8% 30.8%

3 11.4% 6.7% 26.3% 18.4% 27.1%

4 1.9% 0.0% 9.3% 5.6% 68.5%

5 13.5% 1.9% 15.4% 11.5% 32.7%



116


1 18.8% 9.4% 21.9% 23.4% 20.3%

2 15.0% 8.5% 30.9% 15.9% 21.1%

3 11.5% 5.0% 20.2% 18.8% 30.0%

4 6.4% 4.6% 19.6% 18.4% 35.7%


1 43.3% 13.5% 16.3% 7.7% 12.5%

2 16.2% 13.5% 31.4% 17.9% 14.4%

3 6.6% 4.0% 31.9% 19.7% 27.1%

4 4.5% 2.9% 14.7% 19.0% 41.0%



117

Investment Management

Current training


Total 15.8% 8.8% 25.2% 25.2% 22.4%


1 16.1% 8.4% 22.2% 26.5% 24.6%

2 10.0% 23.3% 23.3% 20.0% 16.7%

3 0.0% 33.3% 66.7% 0.0% 0.0%

4 0.0% 0.0% 20.0% 60.0% 20.0%

5 8.8% 4.1% 27.6% 25.9% 31.2%

6 8.6% 10.0% 38.6% 27.1% 12.9%

7 19.1% 11.7% 27.5% 20.8% 17.8%

8 0.0% 0.0% 100.0% 0.0% 0.0%

9 30.8% 7.7% 23.1% 23.1% 15.4%


1 25.8% 14.7% 34.1% 15.7% 6.0%

2 19.0% 19.0% 37.9% 13.8% 5.2%

3 11.1% 18.5% 22.2% 22.2% 25.9%

4 13.9% 6.9% 22.7% 27.8% 26.8%

5 0.0% 0.0% 85.7% 0.0% 0.0%



118


1 10.0% 10.0% 20.0% 20.0% 38.0%

2 13.8% 6.5% 22.5% 29.3% 25.7%

3 17.4% 10.9% 30.2% 23.5% 16.2%

4 11.1% 3.7% 11.1% 20.4% 51.9%

5 25.0% 13.5% 19.2% 13.5% 21.2%


1 37.5% 12.5% 25.0% 15.6% 3.1%

2 19.9% 13.8% 37.0% 20.3% 5.7%

3 16.5% 9.0% 24.4% 26.9% 20.7%

4 12.3% 6.6% 21.8% 27.1% 30.4%


1 51.9% 18.3% 11.5% 5.8% 1.9%

2 28.4% 15.7% 35.4% 14.0% 5.7%

3 13.1% 13.1% 35.9% 22.8% 14.0%

4 8.3% 2.9% 19.3% 32.9% 35.2%



Total 11.8% 6.9% 19.4% 17.5% 34.1%



119

Level

Province 1 2 3 4 5

1 12.4% 7.4% 16.3% 16.9% 36.6%

2 3.3% 20.0% 16.7% 26.7% 23.3%

3 0.0% 33.3% 66.7% 0.0% 0.0%

4 0.0% 0.0% 20.0% 60.0% 0.0%

5 5.9% 4.1% 23.5% 18.2% 33.5%

6 8.6% 10.0% 21.4% 20.0% 32.9%

7 12.4% 6.7% 23.2% 13.8% 35.2%

8 0.0% 0.0% 50.0% 0.0% 50.0%

9 23.1% 0.0% 15.4% 23.1% 38.5%


1 28.6% 14.3% 18.4% 15.2% 18.9%

2 24.1% 12.1% 27.6% 10.3% 19.0%

3 7.4% 18.5% 18.5% 14.8% 29.6%

4 8.0% 4.9% 18.9% 18.5% 38.3%

5 0.0% 14.3% 57.1% 0.0% 14.3%


1 8.0% 0.0% 30.0% 18.0% 40.0%

2 10.0% 6.0% 16.3% 19.7% 35.2%

3 13.8% 9.0% 23.3% 16.8% 29.7%

4 1.9% 3.7% 7.4% 5.6% 74.1%

5 11.5% 3.8% 11.5% 13.5% 32.7%



120


1 31.3% 4.7% 20.3% 18.8% 20.3%

2 18.3% 11.0% 29.7% 13.4% 22.8%

3 13.4% 5.6% 20.4% 16.8% 32.8%

4 7.0% 6.4% 15.4% 19.4% 39.9%


1 51.9% 14.4% 4.8% 7.7% 15.4%

2 23.6% 11.4% 27.9% 13.5% 20.1%

3 8.0% 10.5% 27.6% 20.2% 27.4%

4 4.3% 2.8% 14.8% 18.8% 44.8%



121

Financial Aspects

Current training


Total 18.8% 10.2% 26.1% 24.3% 17.5%


1 19.2% 10.0% 24.3% 25.4% 18.8%

2 10.0% 6.7% 50.0% 20.0% 6.7%

3 0.0% 33.3% 33.3% 0.0% 33.3%

4 0.0% 20.0% 0.0% 20.0% 60.0%

5 10.6% 11.2% 24.7% 31.2% 19.4%

6 15.7% 5.7% 34.3% 28.6% 10.0%

7 22.8% 11.4% 27.2% 18.1% 16.8%

8 0.0% 0.0% 50.0% 50.0% 0.0%

9 23.1% 23.1% 7.7% 38.5% 7.7%


1 30.0% 16.1% 24.9% 16.1% 6.9%

2 24.1% 13.8% 32.8% 17.2% 6.9%

3 14.8% 22.2% 25.9% 18.5% 18.5%

4 16.6% 8.6% 26.0% 26.6% 20.1%

5 0.0% 14.3% 42.9% 14.3% 14.3%



122


1 14.0% 8.0% 28.0% 26.0% 22.0%

2 15.8% 9.3% 24.2% 28.3% 19.8%

3 21.3% 12.0% 30.9% 20.7% 12.4%

4 11.1% 3.7% 9.3% 27.8% 46.3%

5 28.8% 7.7% 13.5% 21.2% 21.2%


1 31.3% 9.4% 32.8% 9.4% 9.4%

2 26.8% 14.6% 30.9% 16.3% 6.5%

3 19.9% 11.2% 25.5% 24.9% 16.2%

4 14.5% 8.1% 24.5% 28.3% 22.5%


1 61.5% 9.6% 9.6% 3.8% 3.8%

2 34.5% 17.5% 27.9% 15.7% 2.6%

3 15.1% 14.2% 40.5% 19.7% 8.8%

4 9.8% 6.0% 21.0% 32.8% 28.9%



Total 12.9% 7.3% 20.5% 16.5% 30.5%



123

Level

Province 1 2 3 4 5

1 13.7% 6.4% 19.0% 15.7% 33.3%

2 3.3% 23.3% 16.7% 30.0% 16.7%

3 0.0% 66.7% 0.0% 0.0% 33.3%

4 0.0% 0.0% 20.0% 40.0% 20.0%

5 6.5% 11.2% 21.8% 16.5% 29.4%

6 10.0% 7.1% 30.0% 14.3% 30.0%

7 13.8% 6.0% 22.1% 17.4% 28.9%

8 0.0% 0.0% 50.0% 0.0% 50.0%

9 15.4% 15.4% 7.7% 23.1% 38.5%


1 32.3% 8.8% 19.4% 10.6% 21.7%

2 24.1% 8.6% 29.3% 12.1% 19.0%

3 7.4% 11.1% 25.9% 11.1% 33.3%

4 8.7% 6.8% 20.0% 17.9% 33.2%

5 0.0% 28.6% 28.6% 28.6% 0.0%


1 10.0% 8.0% 22.0% 16.0% 38.0%

2 10.3% 6.3% 19.2% 16.3% 31.7%

3 15.7% 8.7% 23.5% 18.4% 25.8%

4 1.9% 3.7% 11.1% 5.6% 70.4%

5 15.4% 5.8% 11.5% 9.6% 32.7%



124


1 34.4% 4.7% 20.3% 17.2% 18.8%

2 19.5% 12.6% 25.6% 13.4% 19.9%

3 14.8% 5.9% 20.7% 16.5% 29.7%

4 7.8% 6.5% 18.8% 17.7% 35.7%


1 57.7% 12.5% 3.8% 3.8% 16.3%

2 24.9% 13.1% 26.6% 14.0% 16.6%

3 9.4% 8.5% 31.6% 19.4% 21.7%

4 4.5% 4.3% 15.5% 18.1% 41.7%



125

Dealing with surplus and Legislation related to surplus

Current training


Total 21.3% 12.5% 28.2% 22.8% 12.1%


1 21.7% 11.3% 27.9% 23.3% 13.4%

2 16.7% 40.0% 16.7% 13.3% 6.7%

3 0.0% 66.7% 0.0% 0.0% 33.3%

4 0.0% 20.0% 0.0% 40.0% 40.0%

5 11.8% 14.1% 28.2% 30.6% 12.9%

6 18.6% 12.9% 37.1% 18.6% 8.6%

7 24.8% 12.4% 28.5% 19.1% 11.1%

8 0.0% 0.0% 50.0% 50.0% 0.0%

9 38.5% 23.1% 15.4% 7.7% 15.4%


1 32.7% 17.5% 27.6% 12.0% 4.6%

2 27.6% 22.4% 27.6% 15.5% 1.7%

3 22.2% 11.1% 33.3% 18.5% 14.8%

4 18.9% 11.1% 28.3% 25.5% 14.0%

5 14.3% 14.3% 42.9% 0.0% 14.3%



126


1 18.0% 4.0% 26.0% 26.0% 24.0%

2 19.2% 12.5% 27.2% 26.8% 12.0%

3 23.3% 14.2% 32.3% 18.5% 9.0%

4 11.1% 5.6% 11.1% 27.8% 40.7%

5 30.8% 7.7% 17.3% 23.1% 13.5%


1 32.8% 14.1% 32.8% 4.7% 7.8%

2 30.5% 16.3% 29.3% 16.3% 3.3%

3 23.0% 12.3% 24.4% 24.9% 12.6%

4 16.4% 11.2% 29.5% 25.7% 15.2%


1 62.5% 11.5% 9.6% 2.9% 1.0%

2 39.7% 15.7% 32.3% 9.6% 1.7%

3 17.7% 20.8% 37.6% 17.9% 4.6%

4 11.8% 7.7% 24.9% 32.8% 21.0%



Total 14.9% 7.8% 21.8% 15.7% 27.8%



127

Level

Province 1 2 3 4 5

1 14.4% 7.4% 20.5% 16.1% 28.8%

2 20.0% 6.7% 30.0% 16.7% 16.7%

3 0.0% 66.7% 0.0% 0.0% 33.3%

4 0.0% 0.0% 20.0% 40.0% 20.0%

5 14.1% 8.2% 27.1% 15.3% 22.4%

6 14.3% 10.0% 24.3% 14.3% 27.1%

7 13.4% 8.7% 22.5% 13.8% 31.9%

8 0.0% 0.0% 50.0% 0.0% 50.0%

9 23.1% 0.0% 30.8% 7.7% 30.8%


1 33.2% 11.1% 18.4% 12.9% 18.4%

2 22.4% 12.1% 32.8% 6.9% 17.2%

3 11.1% 11.1% 29.6% 7.4% 33.3%

4 11.2% 6.8% 21.6% 17.0% 30.1%

5 0.0% 28.6% 42.9% 0.0% 14.3%


1 12.0% 6.0% 18.0% 20.0% 36.0%

2 12.7% 6.3% 21.0% 16.8% 27.3%

3 17.7% 10.0% 24.7% 15.4% 24.4%

4 3.7% 3.7% 7.4% 11.1% 66.7%

5 17.3% 5.8% 17.3% 7.7% 32.7%



128


1 31.3% 9.4% 20.3% 12.5% 20.3%

2 22.8% 12.6% 25.2% 11.8% 17.5%

3 16.2% 5.9% 20.2% 16.8% 28.3%

4 10.1% 7.0% 21.8% 16.9% 31.8%


1 57.7% 10.6% 6.7% 4.8% 14.4%

2 24.9% 14.4% 30.1% 10.9% 16.2%

3 13.1% 10.3% 32.2% 19.1% 17.7%

4 6.6% 4.3% 16.4% 17.4% 38.7%



129

Interpreting Financial Statements

Current training


Total 15.5% 8.1% 22.4% 21.1% 29.8%


1 16.1% 7.4% 20.2% 20.8% 33.1%

2 10.0% 3.3% 40.0% 33.3% 6.7%

3 0.0% 66.7% 33.3% 0.0% 0.0%

4 0.0% 0.0% 20.0% 40.0% 40.0%

5 7.6% 7.1% 22.9% 24.1% 35.3%

6 12.9% 4.3% 28.6% 21.4% 28.6%

7 17.8% 11.1% 23.5% 20.1% 23.8%

8 0.0% 0.0% 100.0% 0.0% 0.0%

9 23.1% 7.7% 23.1% 30.8% 15.4%


1 28.6% 13.4% 21.2% 16.6% 14.3%

2 20.7% 17.2% 29.3% 8.6% 19.0%

3 18.5% 14.8% 14.8% 11.1% 40.7%

4 12.8% 6.5% 22.5% 23.0% 33.3%

5 0.0% 0.0% 42.9% 14.3% 28.6%



130


1 12.0% 8.0% 26.0% 28.0% 24.0%

2 12.5% 5.8% 20.8% 21.3% 36.8%

3 17.9% 10.9% 25.8% 20.4% 22.9%

4 9.3% 1.9% 13.0% 29.6% 44.4%

5 25.0% 7.7% 9.6% 15.4% 32.7%


1 37.5% 9.4% 25.0% 10.9% 9.4%

2 22.0% 13.4% 34.6% 16.3% 9.8%

3 16.2% 7.8% 24.1% 23.2% 26.1%

4 11.1% 6.4% 17.3% 22.7% 40.3%


1 48.1% 15.4% 14.4% 4.8% 3.8%

2 27.5% 18.3% 25.3% 14.4% 14.0%

3 14.0% 9.1% 34.5% 21.4% 19.9%

4 8.1% 3.2% 17.1% 25.5% 44.3%



Total 11.1% 6.4% 18.4% 15.2% 34.8%



131

Level

Province 1 2 3 4 5

1 11.0% 6.5% 17.2% 13.2% 37.5%

2 0.0% 3.3% 26.7% 40.0% 20.0%

3 33.3% 33.3% 33.3% 0.0% 0.0%

4 0.0% 0.0% 40.0% 20.0% 20.0%

5 6.5% 4.1% 19.4% 19.4% 32.4%

6 10.0% 2.9% 20.0% 18.6% 37.1%

7 12.4% 7.0% 20.1% 14.1% 34.2%

8 0.0% 0.0% 50.0% 0.0% 50.0%

9 15.4% 7.7% 15.4% 23.1% 38.5%


1 29.5% 10.6% 14.7% 12.0% 28.6%

2 17.2% 15.5% 29.3% 8.6% 20.7%

3 11.1% 11.1% 29.6% 7.4% 33.3%

4 7.2% 5.1% 18.2% 16.3% 37.1%

5 0.0% 0.0% 42.9% 28.6% 14.3%


1 6.0% 2.0% 26.0% 20.0% 38.0%

2 9.0% 5.3% 15.2% 14.5% 37.8%

3 13.5% 8.6% 22.9% 16.3% 29.2%

4 1.9% 1.9% 3.7% 11.1% 72.2%

5 13.5% 1.9% 13.5% 9.6% 32.7%



132


1 29.7% 6.3% 23.4% 9.4% 26.6%

2 17.1% 11.8% 29.3% 14.2% 19.5%

3 12.0% 4.8% 19.3% 19.3% 30.8%

4 7.2% 5.3% 13.9% 14.2% 42.8%


1 46.2% 14.4% 9.6% 8.7% 14.4%

2 21.0% 14.0% 26.6% 14.4% 17.9%

3 8.0% 6.8% 29.3% 17.9% 27.9%

4 4.6% 2.7% 11.9% 15.1% 46.9%



133

Retirement Fund Governance

Current training


Total 16.7% 7.0% 23.5% 27.2% 22.9%


1 17.0% 6.4% 22.2% 26.9% 25.1%

2 10.0% 6.7% 43.3% 26.7% 6.7%

3 0.0% 33.3% 66.7% 0.0% 0.0%

4 0.0% 0.0% 0.0% 60.0% 40.0%

5 7.6% 7.1% 23.5% 31.8% 27.6%

6 17.1% 4.3% 24.3% 34.3% 15.7%

7 19.5% 10.4% 23.8% 22.1% 21.1%

8 0.0% 0.0% 100.0% 0.0% 0.0%

9 23.1% 15.4% 23.1% 30.8% 7.7%


1 30.4% 9.2% 25.8% 18.0% 12.0%

2 24.1% 10.3% 29.3% 20.7% 10.3%

3 11.1% 22.2% 25.9% 7.4% 33.3%

4 13.8% 6.1% 22.6% 30.0% 25.6%

5 0.0% 0.0% 57.1% 28.6% 0.0%



134


1 14.0% 0.0% 26.0% 24.0% 34.0%

2 13.7% 5.5% 24.8% 30.5% 23.3%

3 19.0% 9.0% 25.2% 26.6% 17.9%

4 9.3% 1.9% 7.4% 13.0% 66.7%

5 26.9% 13.5% 7.7% 17.3% 28.8%


1 34.4% 3.1% 35.9% 14.1% 6.3%

2 24.0% 12.2% 32.1% 18.3% 10.6%

3 17.4% 5.9% 19.3% 30.5% 24.4%

4 12.3% 6.1% 21.5% 30.0% 27.9%


1 55.8% 17.3% 9.6% 4.8% 1.0%

2 31.4% 13.5% 31.9% 18.3% 4.4%

3 13.1% 8.8% 33.3% 27.6% 16.0%

4 8.4% 2.5% 18.1% 33.6% 35.7%



Total 11.0% 4.9% 21.1% 17.6% 33.4%



135

Level

Province 1 2 3 4 5

1 10.8% 6.1% 18.3% 17.2% 35.0%

2 3.3% 0.0% 26.7% 13.3% 46.7%

3 0.0% 66.7% 33.3% 0.0% 0.0%

4 0.0% 0.0% 20.0% 40.0% 40.0%

5 6.5% 2.4% 22.9% 19.4% 34.1%

6 8.6% 2.9% 35.7% 17.1% 27.1%

7 12.4% 5.0% 23.2% 15.8% 32.9%

8 0.0% 0.0% 50.0% 0.0% 50.0%

9 15.4% 0.0% 7.7% 38.5% 38.5%


1 26.3% 11.1% 18.9% 12.0% 26.3%

2 22.4% 13.8% 25.9% 10.3% 20.7%

3 14.8% 7.4% 25.9% 3.7% 40.7%

4 7.5% 3.3% 21.1% 19.3% 35.6%

5 0.0% 0.0% 42.9% 28.6% 14.3%


1 8.0% 0.0% 28.0% 18.0% 40.0%

2 7.8% 4.8% 20.0% 18.7% 34.5%

3 14.3% 5.9% 24.3% 17.9% 29.2%

4 1.9% 0.0% 1.9% 7.4% 74.1%

5 15.4% 3.8% 13.5% 11.5% 32.7%



136


1 29.7% 10.9% 23.4% 6.3% 23.4%

2 17.9% 8.1% 28.9% 16.7% 21.5%

3 11.2% 3.9% 20.7% 17.9% 33.1%

4 7.0% 3.8% 18.5% 18.9% 38.7%


1 45.2% 12.5% 14.4% 6.7% 15.4%

2 22.7% 8.7% 30.1% 16.2% 18.8%

3 8.5% 5.4% 31.6% 20.2% 25.9%

4 3.8% 2.4% 14.3% 18.5% 44.8%



137

Conclusions The results thus far are quite well explained in the relevant sections above. Specifically the

number of trustees, the location of the trustees, the demographic profile of the trustees and the

areas of required training for the trustees.

The final section enables the determination of the split of trustees according to their needs and

current knowledge. The most significant results from the tables above show that trustees are at

an intermediate level on most topics, but the areas of:

• Legal aspects and Legislation, and

• Dealing with surplus and Legislation related to surplus

show a markedly lower level of competence among the trustees. It would be useful to focus

training on these areas at the correct levels.

While these results are useful, it is important to note the significance of the results. The current

set of results has been indicated to have a 90% - 95% level of confidence. We would conclude

that the results of this part of the project are sufficient to continue with the subsequent phases on

the project.

The main problems associated with this project are those of interest and participation. Far too

many projects have been targeted at this industry and trustees have become complacent in their

participation at this stage. We have been made aware numerous times that this project is

voluntary and trustees cannot be pushed to respond in any way. As such, there is no

accountability by any party and the recommendations section of this report suggest ways in which

better participation can be achieved for later phases of this project.

A further problem is also that of industry co-operation. While the project has aimed to include as

many stakeholders as possible, important stakeholders were not included at the inception of the

project. As such, these stakeholders have refused to participate in the project, citing non-

consultation as a reason. Most notably, NBC has refused to participate, while the latest results

produced communication from the mining funds indicating that they had unilaterally taken the

decision not to participate in the survey.



138

However, in spite of the problems highlighted in this report and above, this project has certainly

created a very widespread awareness of the INSETA and its goals. A lot of skills development

facilitators, trustees and administrators in a number of sectors are excited to see this initiative

take place. They also appreciate the difficulty of the project and are quite eager to assist in any

way they can to facilitate the success of the project.

We would encourage the INSETA and subsequent service providers to take full advantage of this

together with all contacts developed in the initial phase of this project.

Bibliography Statistical package used to analyse was S-Plus

Trustee data used was collected from the survey conducted by Endeleo

Fund data use was obtained from the FSB



139

Recommendations This initial phase of the project has taught us many lessons and it is important that these lessons

are carried forward in this survey.

The retirement fund industry is a very complex and sensitive industry. With the amendments to

the Pensions Funds Act, combined with issues around fund surplus apportionment, compounded

by concerns around the integrity of trustees and fund administrators, funds and trustees have

sufficient concerns to only focus on the single aspect of trustee training. While it is important to

secure the backing of umbrella bodies, it is also important to understand that communications

with trustees may be inefficient using this channel since this may require lengthy processes and

also not have direct contact.

As such, we would recommend that the INSETA and other associated bodies engage ground

level retirement fund bodies such as the Institute of Retirement Funds, The Principal Officers

Association, The Pensions Lawyers Association and The South African Financial Services

Intermediaries Association. Also important are the administrators and unions related to each

industry sector.

Of course the above represents a much larger project, but it does appear necessary. The current

project assumed co-operation of many of the above bodies. When it was discovered that they

were not as informed on the project as was optimal, it was difficult to change their view on

participation after having been excluded from the initial planning of all the project phases.

Therefore it is important that the recommendation of engagement is followed. The larger bodies

can be captured by direct contact, while the administrator bodies may be targeted through use of

localised sessions.

We feel that the once the participation of the bodies above has been obtained, the further phases

of this project will be much more efficiently achieved in terms of cost, time and thoroughness.

Quantifying numbers of participants will be easier done, pilot studies will produce more relevant

results and the materials produced will be pitched at the correct levels. As a result, less of the

work will have to be outsourced as it can be provided by the bodies mentioned above, resulting in

a significant savings in costs.



140

Appendix – Determining a suitable sample size and population

Introduction Endeleo has been commissioned by the INSETA to determine the distribution of various

parameters that relate to trustees in the South African Retirement Funds industry. Areas of

serious doubt include:

• The total number of trustees in the population of trustees

• A suitable sample size required in order to estimate the population parameters

What this report aims to do is to answer the questions above within a reasonable confidence

level.

Sampling theory In answering the question, “How large should a sample be?”, one will need to be familiar with the

random variation (σ) surrounding the parameter to be estimated. At the extreme, given a variation

of zero, the sample size would be sufficient at one observation to estimate the mean of the

population. However, we are aware that variation exists in most observed parameters and the

extent of this variation (together with the confidence required) determines the sample size

needed to estimate parameters.

In order to understand the theory that we are putting forth, we will need to make an assumption of

normality; that is:

• Each parameter mean is normally distributed with a mean µ and a standard deviation σ/√n



141

Given this, we can surmise that for any parameter (say γ) that is distributed as above, there is a

100(1- α %) chance that this parameter will be found in the interval:

γ ± z α/2 (σ/√n)

where zα/2 is the z-value from the standard normal distribution Z that gives Pr{Z≤zα/2} = α/2

Now if we want this 100(1- α %) confidence interval to be no larger than ε %, we can equate it to ε

and then we can conclude that the sample size required to maintain the conditions given is the

solution to the equation:

ε = z α/2 (σ/√n)

therefore:

n = z α/22* σ2 / ε2

We can refer to ε as the maximum desired error of the estimate.

Relevance to this project While total trustee population is important, the size of the population does not really affect the

appropriate sample size required to make inferences on the population. The important factor in

determining population size is a mean trustee board size conditional on certain members being

present on multiple boards/

From the above data, we have been able to assess that the mean number of trustees per fund

sits at a figure of around 6. This figure is used later in this appendix.

In calculating a suitable sample size, we need to make a number of assumptions.

If we assume we want a 95% confidence interval, and we wish to be incorrect by at most a

margin of 10% on our average trustee response, we then need to assess the typical standard

deviation of the responses of trustees overall. From our data we have found that the maximum

standard deviation of responses and other data points is around 1.5. For prudence, we have

chosen to work with a figure of 2.



142

Using this figure of σ = 2, we arrive at a sample size of 1,600 trustee responses required to

assess the mean trustee responses within a 95% confidence interval, allowing for a maximum

parameter error of 10%, for a population of 54,000 trustees (population size does not really

matter when we are dealing with a population of this size. It only really factors in when the

population is quite small).

Relating this back to the project, over 1,400 trustees have been sampled. Using the same

parameters above, we can assess that the confidence level is approximately 92.5%.



143

Determining the total number of trustees Endeleo has so far received responses from over 1,400 trustees representing more than 500

pension funds. However from the responses received responses there were too few pension

funds had a 100% response rate; in other words, all the trustees of that pension fund responding.

Therefore in order to be able to obtain an estimate of the average number of trustees per fund

Endeleo called the principal officers of over 320 funds to determine the total number of trustees in

their respective funds.

From the funds sampled we received responses from over 270 funds with numbers ranging from

4 to 40. The funds with many trustees were the funds for large corporates such as Goldfields, VW

etc. The average number of trustees per fund based on the sample was 9 members.

We also found that a most companies had at least a pension fund and a provident fund and the

trustees of these two funds often overlapped. For example AMPLATS which has 8 registered

funds has 2 principal officers. This meant that the estimate of the average number determined

above was very conservative.

An analysis of the fund data revealed that 1,236 companies had at least 2 funds.

# funds per

company

# of companies

with ‘X’ funds

# of funds Avg. # of trustees

per fund

Total # of trustees

1 11,251 11,251 6 67,506

2 950 1,900 6 5,700

3 83 249 6 498

4 20 80 6 120

5 12 60 6 72

6 1 6 6 6

7 1 7 6 6

Total 12,318 13,553 73,908

However there are funds which fall outside the scope of this project because they are not normal

active. The table below gives a summary of the different types of funds:



144

Fund status Totals

Curatorship 5

In transfer 1,708

Liquidated 2

Normal active 9,632

Preliminary registered 558

Process of liquidation 1,567

Query 13

Total Active Funds 10,190

This then means that some 3,282 funds are to be excluded from the analysis, resulting in a total

estimate of 54,216 trustees.

Conclusions Using the theory developed above we have been able to conclude on the solutions to the two

areas of doubt listed above.

In summary, we have maintained that the trustee population must number 54,000 at most and

that the obtained sample size of over 1,400 will result in estimates of parameters on this

population within a 92.5% confidence interval with a maximum error margin of 10%.

It is important to note that these figures are upper limits. If there are more ‘overlapping’ trustees in

certain related funds than is estimated above, the total number of trustees is most likely to

decrease, thus ultimately decreasing the sample size too.



145

Appendix II – Endeleo Proposal

Executive Summary It has been discovered that a severe lack of formal training among South African pension fund

trustees exists. As the current legislative environment within this industry changes, INSETA has

been tasked with the assessment of the skills of trustees and the development of programmes

aimed at rectifying this skills gap.

This tender aims to achieve the following objectives identified by INSETA:

• The quantification and analysis of the Retirement Fund and Trustee training needs

• Skills audit of all Retirement Fund trustees

• Quantification of the number of participants

Endeleo, with its expertise in the Financial, Actuarial and Engineering fields, is equipped to

ensure that INSETA achieves these objectives by utilising a carefully managed 5-phase process.

Endeleo aims to breathe life into a sustainable partnership with INSETA to meet the educational

needs of the Retirement Fund industry.

This is essentially a statistical exercise and Endeleo have the know how to ensure a quality

product. Secondly, this exercise, while not complex, is administratively intensive and thus can be

very expensive. However, through careful management and the appropriate use of technology,

efficiencies can be derived. Endeleo have devised a detailed project plan (outlined below) to

facilitate the management of the exercise. Moreover Endeleo has the skill to develop, test and

implement the specialised technologies required for such an undertaking. Finally this is an

exercise in dealing with people and without the appropriate etiquette the quality of the information

gathered is compromised. Endeleo will use only able, Endeleo trained staff to conduct all survey

related activities.

Endeleo is a young, dynamic, black company that lives the ideal that one plus one can equal

three.



146

Endeleo Proposal

General requirements for tender

To conduct the quantification analysis of the Retirement Fund Trustee training requirements

Determine the Skill needs/requirements of the Retirement Fund trustees

The following tasks will render the objectives complete:

• Ascertain the retirement funds registered.

• Compile a list of all current registered retirement funds.

• Establish the number of fund trustees, both employer-nominated and employee-


• Compile a list of all fund Trustees.

• Identify each fund’s economic sector, e.g. Construction, manufacturing, etc.

• Identify who the fund administrators are per fund.

• Determine the physical location of both fund administrators and trustees per fund


• Compile fund Administrator’s contact details list per fund (Name, telephone/fax

number, e-mail, etc).

• Identify each Trustee’s level of formal education and training.

• Identify the level and extent of Trustee specific training that each trustee has received.

• Identify each Trustee’s years of experience as a trustee.

• Using a 30% sample of identified trustees (which sample shall fulfil the national

demographic profile), quantify these trustees’ self-identified training needs.

Endeleo solution

Due to this task being a short-term project, any participating service provider will be required to

allocate additional resources, over and above current functional requirements, in order to

complete the task. The following process flow diagram indicates how Endeleo proposes the

project is to be completed. The process outlines the dates and budget relevant to each phase of

the project. (see project plan in the main body of the document)



147

Notes on general requirements

Critical to the success of the project will be the relationship established between Endeleo and

INSETA. Input from both sides key in ensuring that the final product is a quality product. It would

therefore be a requirement of the project that both parties Endeleo and INSETA commit to a

close working relationship as both parties have a vested interest in the success of this project.

Specifically Endeleo aims to quantify the pension fund trustees and conduct the skills Audit in

overlapping phases. This can be achieved by simplifying the skills audit process to make it easy

to incorporate it into the quantification exercise and thus making the process as a whole more

time and cost effective.

Therefore the final product that Endeleo will deliver to INSETA will exceed the mandate without

sacrificing quality or making it costly.

And that is how Endeleo can make one plus one equal three

Documents

Retirement Funds Quantification and Trustees Skills … Life to Ideas Directors: Emmanuel Damoulakis, Lundi Mbokodi, Lesego Molwantwa-Mbatha, Vuyolwethu Nogantshi, Lungile Thabo Twalo