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PIREP
Programa Integrado de la Reforma de Educacao Profissional
MAPUTO / MOZAMBIQUE
GTZ‐PN: 2008.2048.0‐005.00
VN: 81109257
Needs study and competency analysis for skilled workers in the metal - mechanical sector of
Mozambican industries
Draft Firm Survey Report
Prepared by
Hans Stingl and Peter R. Beck, and with collaboration of Vasco Cuna and Rainer Reidenbach,
Maputo, May 2011
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Contents
List of Acronyms
Introduction
Objectives
Methodology
Definition of research approach – research instruments and techniques
Sampling approach and procedures – defining sample size and unit selection
Polling plan – data collection strategy
Data collection – how did it go
Findings
Introduction
Quantitative Aspects of Labor demand – vacancies now and then
Qualitative Aspects of labor demand – technical and general skills
Firm Observation sheet
Interpreting the results
Conclusions
Recommendations
Bibliography
Annex
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List of Acronyms
CEREP German support to PIREP for metal and electrician occupations
CIP Project Investment Centre
CIREP Inter‐ministerial Commission of professional education reform
COREP Educational Reform Executive Commission
DINET National Directorate for technical education
GTZ/GIZ German Cooperation agency
INE National Statistical Institute
PIREP LEVEL 5 Highest qualification level for non academic technical education
MIC Ministry of Industry and Commerce
MEC Education Ministry
MPD Planning and Development Ministry
PIREP Integrated professional educational reform project
REP Professional education Reform
TVET Technical Vocational Education and Training
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Introduction: Rationale and Objectives
1.1. Context and Rationale
The Government of Mozambique is presently involved in process for reforming the national system of technical and vocational education and training (TVET) which is known locally as ‘ Reforma da Educação Profissional’ (REP), of which PIREP constitutes the first phase.
PIREP is managed by the Executive Commission for the Professional Education Reform of (COREP), co‐chaired by Education and Labor Minister, and composed by government representatives and various stakeholders from the civil society.
German technical assistance in the reform of the technical and vocational training (TVET) system in Mozambique is aligned to the same vision, objectives, principles and methodological approach defined and applied by PIREP.
The German (GIZ) support is to be provided by long term international advisers and short term national, regional and international advisers/consultants in the following areas:
o the development of qualifications, standards, curriculum, modules, lesson plans, training curriculum including examining and certifying within the area of the industrial occupations in metal and electro‐technology (renewable energies and IT),
o Implementation of new competency‐based training courses for up to eight qualifications in the sectors of Industrial Maintenance (electrical and mechanical trades) in two DINET schools and two INEFP training centres.
o support for in‐service training for the teachers/trainers,
o Quality management at pilot school level for the planning, quality control and implementation of these new courses in two DINET schools and two INEFP training centres.
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1.2. Objectives
In order to strengthen PIREP’s demand lead philosophy, the ToR defined the following objectives of this survey:
• To establish the demand of technically skilled workers in the metal‐mechanical area in a few selected and representative companies in the metal‐mechanical area;
• To collected data about the skilled workers employed, their skills, knowledge and other competences required as well a projection for future needs to establish Job‐Profiles for the detected skilled worker needs in the specialized areas
By clarifying these objectives it was agreed to research labor and skills demand in quantitative and qualitative terms: The quantitative data would support decision making of TVET output quantity; from qualitative ‘skills profile’ data are expected hints for curricula design and teaching styles.
We also added two more objectives, that is: assessing firm readiness for active participation in quality improvement of TVET provision and professional education reform; and, last but not least, using this survey as a test for further data collection in enterprises run by national agencies (DINET/ANEP etc.)
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2. Methodological Approach
2.1. Definition of research approach
A survey research approach based upon questionnaire backed interviewing was applied. Other possible options such as indirect data collection through mailed questionnaires have been rejected for the following reasons:
• Possible loss of accuracy
• Incomplete and delayed data transmission
• Overall risk of low reliability and validity of information,
• The impossibility of visiting (and documenting) firm facilities; and, most of all the
• High risk of low return rates.1 Experiences in prior studies have confirmed this risk2
The interviewing options, on the other hand, offers the advantages of collecting more complete, accurate and valid information, and of achieving higher rates of return.3
1 Delbert C. Miller & Neil J. Salkind (2002) Handbook of Research Design &Social Measurement, Sage Publications, Thousand Oakes, page 318 2 Gtz (2009) Jobs & occupational skills in Mozambican Industry – Firm survey report, elaborated by Peter R. Beck, with collaboration of José Bambo, Maputo. This low‐cost industry firm survey was obliged to using a mailing strategy (fax, email) with the result that none of the addressed firms ever returned any questionnaire despite repetitive calling. Indeed this experience was reproduced here, fortunately on a smaller scale though. During the field phases in Sofala, Nampula and Tete province the realization of interviews it was not always possible, basically because no appointment could be made. Even though the five firms in question offered to return a filled questionnaire by mail, this did not happen in a single case. 3 Miller/Salkind (2002) ibid.
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2.1.1. Design of instruments – questionnaire and firm observation sheet
In a first step, and as a means to operationalize the ToR objectives, have been defined the key research variables:
• current and projected job demand by occupational skills profile in numbers
• (ranked) relevance assessment of skills by each of the five metal mechanical occupational profile
• Readiness to actively support quality TVET provision and reform, and
• Overall assessment of technological set up.
In a second step, and based on these variables a draft questionnaire and a brief firm observation sheet was designed.
2.1.2. Interview techniques and data documentation:
In parallel with the definition of key research variables the following components were designed and defined:
- data research techniques
- instrument design
- questionnaire for semi‐structured interviews
- firm observation sheet
- a basic research protocol as a guiding tool
2.1.3. Pretesting of instruments and data collection strategy
Pre testing followed as the next step. Pre‐testing is a necessary tool for controlling the performance of questionnaire instruments – clarity and order of questions;
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interview duration etc., as well as to familiarize the interview team with the use of instruments and with the interview situation, including interview conducting and documentation of information.
For this purpose it was possible to conduct the pretest in three Maputo based firms (2 small and one medium sized).
The outcome of the pretesting exercise made it possible to finalize the questionnaire design4, but made it also necessary to organize a brief training session for interviewers with the participation of project and DINET staff:
A training session with further instructions regarding research protocol use, and basic principles of interview based data collection techniques. In particular:
• how to use the questionnaire for conducting interviews and collecting data, and the firm sheet for documenting ‘observation;
• how to avoid data entry errors (non sampling errors)5, and
• how to conduct an interview, of what is an interview bias and how to avoid it, and of the necessity of standardized routines etc.
2.2. Sampling approach and procedures:
A sampling approach was developed at the same time as the instrument design. Two criteria have been used:
• the definition of the activity sectors that employ the five occupational skill profiles; and of
• four geographic regions (Maputo, Sofala, Nampula and Tete provinces) that would compose the firm sample frame.
4 See questionnaire in Annex 1 5 Everything not related with sampling process; for example unclear responses, erroneous recordings, data entry errors, etc.
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2.2.1. Setting a sample frame
The resulting sample frame was built upon two firm data bases procured from Ministry of Commerce and Industry, and from Investment Promotion Agency (CPI), a total of ca. 7.000 units.
2.2.2. Sample size and unit selection
Sample size: Original sample size was, as has been mentioned above, defined with reference to nonprobability methods,6 as a convenience sample. Sample size was at about 200 firms, which was considered sufficient (1) in order to produce relevant information and (2) for the purpose of data analysis requirements. 7
Unit selection: On the background of existing information and studies8 have been set following selection criteria for defining the sample list:
• Firm size, with strong focus on big and medium sized firms9
6 See Annex 2. Nonprobability sampling designs “any technique in which samples are selected in some way not suggested by probability theory.“ Earl Babbie (2004) The Practice of Social Research, Thomson Wagsworth, page G7 7 According to Bouma and Atkinson the minimum size requirement for a nonprobability sample lays by 30 in order to allow descriptive statistical data analysis. This number may increase depending on the number of research variables. Gary D. Bouma/G.B.J. Atkinson (1996) A Handbook of social research, Oxford University Press, page 152ff. In this case the revised sample size of 96 (plus those added up through snowball sampling technique in Tete province) match these minimum requirements; (three dependent variables and firm size as an independent variable. Of this point see: Ministry of Planning/National Directorate of studies and policy analysis: Enterprise development in Mozambique‐ Results Based on Surveys Conducted in 2002 and 2006, Maputo 2006. MPD (2006). Although we do not consider ‘geographic location’ as an independent variable it will be included into analysis. With regard now to the minimum requirement compared with ‘effective sample’ (n=38) only small firm category dissatisfies this minimum criteria by only 3 units selected. 8 Actually only few studies are available. In particular: MPD (2006). 9 According to MPD (2006) study, job turnover is very low in small industry firms, and highest in big enterprises. On the other hand have to be taken into account market situation, complexity of products and technological equipment requiring capital investment rates that lay beyond investment capacities of
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• Activity sector with strong presence and demand of metal mechanic occupational skills according to the five occupational skills profiles selected, that is PIREP level 5’ metal mechanics
• Geographic location
Due to changes in the expected number of researchers – originally it was expected that DINET staff could join in order to get to total of six interviewers organized in three independent research teams – that cut down research teams to one, decision was taken to cut down the sample size to about 100, which was still seen as a realistic target.
As a result sample size was set at ninety‐six (96) firms, applying the same criteria method for unit selection, mentioned above.10 Through snowball sampling technique used in Tete province another 18 firms had been added to sample list, putting sample size at a total of 114 units
The effective sample size, in terms of firms visited and that contributed with valid information to data analysis, amounts to thirty‐eight (38). We shall deal with these matters again in the Finding chapter.
2.3. Polling plan/Data collection plan
According to research approach – data collection by interview teams – and right after the realization of the pre‐test and the brief training session on proper use of instrument and research techniques, was developed a ‘first’ polling plan that foresaw the employment of three polling teams composed by two interviewers – one for conducting an interview and the other for documenting information. A
most small and medium sized firms, and are not considered necessary to survive on the market niche they are dominantly populating. 10 See sample list in Annex 3
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logic and timing plan was also developed and polling started at ERDMOTO Ltd, Maputo on 23 March 2011
However due to the already mentioned fact that the promised interviewers from DINET were not available as planned, interviewing was done by a single team composed of two project staff, actually one international consultant and CEREP project assistant.
Table 1 resumes how activities unrolled
Table 1 Activity Time table: Activity
Week 1 2 3 4 5 6 7 8 9 10 11 Defining Research strategy including data analysis and reporting format
Define key research variables Draft instruments: questionnaire Draft instruments: firm observation sheet
Define data collection techniques and set up basic protocol
Define sampling procedure Procure firm list Assess available resources Define sample size Set criteria for selecting sample units Draw sample list Execute Pré‐test Assess pre‐test Finalize instruments Field phase Maputo province Field phase Sofala province Field phase Nampula province Field phase Tete province Field phase Maputo province Prepare data analysis Run data analysis Draft study report (methodology & tables
Finalize survey report Translate report into Portuguese Submit final reports
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2.4. Data collection process, how did it go (strong points and weak points)
Before we start with presenting the results of data analysis, some short remarks of the data collection process.
In order to prepare data collection, all selected firms have been contacted in advance, with support from DINET, by phone or fax in order to fix interview dates. In addition letters of introduction accompanied by DINET signed Credentials have been sent. With some few exceptions (Coca Cola) this proved a very efficient strategy In particular in Maputo province.
In the remaining three provinces data collection was supported by staff from provincial directorates of Ministry of Industry and Commerce, and from DINET.
Data collection in Tete province, in particular in Moatize Industry Park had to face a particular problem. Newly created firms that fell under the relevance criteria hadn’t yet been included in procured firm data bases from neither CPI nor Industry Ministry. Field research team referred to snowball sampling technique, where every visited unit turned into a information source for identifying other – non listed – units for interviewing.11
From a general point of view data collection outside Maputo province was characterized by some difficulties, in particular in terms of
• Less viable forehand information, for example:
• Localization of listed firms, due to outdated address data or changed firm names;
• Activity change which turned listed firms ‘irrelevant’ for the purpose of this survey;
• Time consuming distances
11 See also Babbie (2004) ibid., page G11.
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Last but not least, and due to the fact that data collection was basically shouldered by a single research team – composed of two – it was necessary to extend data collection phase for another week in order to include Maputo based large firms, such as ‘Mozal’ and ‘MacMahon Beer factory’ where interviews could not be concluded within the projected timeframe. (see table 1)
3. Findings
3.1. Introduction: Data analysis approach and procedures
Data analysis strategy was developed with regard to the key research variables established. Data analysis should include simple basic operations of descriptive statistics, like frequencies, frequency distributions etc.12
It was further agreed to use familiar programs such as EXCEL, which was considered sufficiently sophisticated for this type of simple data analysis. On the other hand would it also facilitate the expected and intended ex‐post appropriation by DINET.
3.1.1. Planned vs. effective sample and sample composition
As has been reported above from the final sample size of 96 listed firms (we do not include the firms added up in Tete), a total of forty‐seven (47) firms have been visited. Out of this 47 firms visited only thirty‐eight (38) produced questionnaire data suitable for data analysis, while nine (9) failed to provide this 12 Descriptive statistical operations are used for describing sample characteristics and relationships among variables in a sample. It “merely summarizes a set of sample observations, whereas inferential statistics move beyond description” to make statements about a larger population, from which the sample was drawn. Babbie (2004) ibid., page G3.
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type of information. Due to this fact, the rate of firms that contributed with valid data suitable for analysis dropped from initially 49% to slightly under 40%.13
In the following we shall concentrate on data collected from these 38 firms. Table 2 resumes how these 38 firms distribute by province and size.
Table 2 Sample distribution by province and size of firms provided data
Province Numbers by firm size (# of employees) Total Big ‹100 Medium 10‐99 Small ›10
Maputo 9 9 1 19Sofala 3 2 0 5Tete 2 4 2 8Nampula 3 3 0 6Total 17 18 3 38
Graph 1 Geographic distribution (n=38)
In terms of geographic sample distribution Maputo province accounts for 50% of surveyed firms, the other 50% almost equally distributed in each of the other
13 The actual rate lies by 39.6%“.According to Babbie, in case of representative surveys a response rate of 50% would still be “adequate for analysis and reporting”. Babbie (2004) ibid., page 261In our case we consider the it still within the limits set by Bouma and Atkinson (1996).
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three provinces, with the exception of Sofala province, where only 5 firms could be surveyed (sample percentage of 13%).
Next we look at the sample distribution for the independent ‘firm size’ variable (Table 3). Here we find an almost equal distribution between big and medium sized firms. The under representation of small firms is justified by the research premises, exposed above, as well as by access problems.
Table 3 Sample distribution by firm size (n=38)
Firm Size Units
Big 17
medium sized 18
Small 3
Graph 2 Sample composition by firm size in % (n=38)
Based on MPD (2006) study we part from the hypothesis that size, and not geographic location, is the decisive independent variable for the demand of skilled labor.
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Labor demand distribution analysis that follows will provide an answer if this hypothesis is valid. But before we come to this, a short remark on the signficance of this data analysis.
3.1.2. Non response issues
Before we deal with the statistical significance of results a brief remark on non response issue is necessary. Non response affected most of all quantitative variables, notably information on current employment and skills structure, where non response was so paramount that it was not possible to include this variable. But it also impacted negatively on the job vacancy variable, where only 24 of the 38 sampled firms provided information for data analysis.14
Quite on the contrary though, qualitative variables dealing with skills relevance assessment ranking showed little up to no non response issues.
This fact may be explained by the more sensitive nature of the first variable type compared to the second.
3.1.3. The statistical significance of the results
In every study that applies to a scientific methodology the range of significance of the results must be clarified.15 As we opted for in favor of non‐statistical sampling methods, ‐ for the reasons indicated above – it is not possible to formulate inference statistical conclusion.
Nevertheless the nonprobability sampling method created the opportunity to select a maximum – only limited by scarcity of available time, financial and human resources – of relevant firms into the sample.
14 This includes some however fortunately rare cases of data documentation issues. 15 See: Peter R. Beck (2011) Roteiro da pesquisa empírica, Eduardo Mondlane University, Departament of Sociology, Maputo, Mozambique
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On the one hand, some of those relevant firms would have risked remaining outside if a random selection procedure would have been used.
On the other hand, and considering that the industrial firm sector is still quite small,16 with very modest growth rates, at least in terms of employment17 we can legitimately say that the results have a high degree of plausibility and draw a rather valid and truthful picture of current and project employment demand for workers with the respective skills profiles.
We believe therefore that the produced result data, even so of no statistical relevance, provide a rather sound basis for estimating labor and skills demand in the near future, and can be used for training provision output planning and curricula development.
3.2. Quantitative Aspects of Labor demand
In a first step analysis focus on the quantitative expression of labor demand for these five occupational profiles, in terms of current vacancies (1); of projected demand (2) and in terms of recruitment conditions (3).
3.2.1. Current vacancies and trends
3.2.1.1. Current Firm vacancies
We shall look at this variable under different angles. We first start showing the current numbers of job vacancies for each of the five professions (Table 3) and will then further desegregate this information by i) firm size, and ii) by geographic location.
It is important to remind that ‘Non response rate’ for this variable was quite high with a total of 11 firms (1 in Nampula and Sofala each, and 9 in Maputo province. 16 See National Statistical Institute ( INE) (2004): CEMPRE 2002, Source: www.ine.gov.mz 17 INE: monthly economic activity indicators; Source: www.ine.gov.mz
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1 Maputo questionnaire was useless due to a data error). That means that these data are based on an actual sample size of n1=24. N = 38 only indicates that a total of 38 firms have been surveyed on this item, but only 24 of them delivered valid responses for data analysis.
Table 4 labor demand for the five occupational profiles in # and % (n1=24)
Occupational skills Profile Current Job vacancies Percentage Machinist 44 12.60%Fitter (Industrial Mechanic) 125 35.70%Metal Construction Mechanic 78 22.30%Agricultural Machinery Mechanic 32 9%Construction Machinery Mechanic 71 20.30%total vacancies 350 100%
Demand for Agricultural Machinery Mechanics is at a low 9% and comes exclusively from firms located in Maputo province. None of the firms surveyed that are located in the other three provinces issued vacancies for workers with this occupational type.
Graph 3 below shows the vacancy distribution of the five occupation qualifications in percentages
Graph 3 labor demand by profession in percentages
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When we take a look at the distribution of job vacancies in the sampled firms (Graph 3), we can easily notice that ‘Fitters’ are on top of the demand list, followed by ‘Metal Construction Mechanics’ and ‘Metal Machinery Mechanics’. ‘Machinists’ and ‘Agricultural Machinery Mechanics’ meanwhile remain at the bottom of the demand list of the firms surveyed. Nevertheless a demand is still notable, although demand for ‘Agricultural Machinery Mechanics’ is only expressed by firms located in Maputo province.
Next we document current and projected vacancies for each profession by disaggregated by the firm size variable (Table 4).
Table 4 current and projected vacancies by occupational type (n=38/n1=24)
Firm size Occupational profile (Level 5)
Current Job vacancies
Future labor demand by frequency of votes
big firms Machinist 34 6 Fitter 107 8 Metal Mechanic 50 6
Agricultural Machinery Mechanic 30 1
Diesel Mechanic 64 3Subtotal 285 24medium sized firms Machinist 10 9 Fitter 18 9 Metal Mechanic 28 8
Agricultural Machinery Mechanic 2 2
Diesel Mechanic 7 4Subtotal 65 32small firms Machinist 0 0 Fitter 0 0 Metal Mechanic 0 0
Agricultural Machinery Mechanic 0 0
Diesel Mechanic 0 0Subtotal 0 0
Grand Total 350 56
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None of surveyed (n=3) small firms issued any job vacancy for one of these five professions. 81.5% of job vacancies for these professions are issued by big firms compared to 19.5% by medium sized firms. These numbers, again, confirm what we already knew about big firms importance for skilled labor market demand.
Graph 4 below is reporting the composition of vacancies for each of the five mechanical skills profiles in big firms only.
Graph 4 Current Vacancies by firm type – big firms (n=17)
While in the surveyed big firms Industrial Mechanics (Fitters) account for 37.5% of job vacancies, graph 5 below show that the demand for Metal Mechanics (43.1%) is higher in medium sized firms compared to ‘Fitters’ coming second with 27.7% of reported current job vacancies.
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Graph 5 Current vacancies in medium sized firms (n=18)
Table 5 in the following reveals vacancy distribution by firm size variable, underlining the big influence of big firms over medium sized and small firms when it comes to hiring.18 Graph 6 below underlines this fact.
Table 5 Job vacancy distribution by size in total numbers and percentages
Firm Size Job vacancies fo skilled labour Percentage
Big 285 81.40%
medium 65 18.60%
Small 0 0.00%
Total 350 100%
18 2006 MPD study already asserted that “the only firms hiring substantial numbers of new employees are large firms, implying greater and more frequent dealings with labour regulations and thus perhaps a higher level of perceived constraint. As the table indicates, micro enterprises hired an average of 0.2 workers in 2005, compared to 1.3 for small firms, 5.5 for medium firms and 34.8 for large firms.” Cited in: gtz (2009) Taking stock: Labor Market statistics and instruments in Mozambique – now and then; desk study elaborated by Peter R. Beck, with collaboration of José Bambo, Maputo, page 31.
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Graph 6 Percentage Distribution of vacancies by firm size
Indeed these results confirm our initial hypothesis that demand for skilled labor is causally linked with firm size, formulated on the grounds of quoted 2006 MPD study.
We shall now present surveyed data that is comparing job vacancy distribution with geographic firm location in the four provinces.
Table 6 Current job vacancy distribution by province and firm size
Province Big ‹100 Medium 10‐99 Small ›10 Total
Firm # Current vacancies
Maputo 9 177 9 35 1 0 19 212
Sofala 3 22 2 14 0 0 5 36
Tete 2 46 4 14 2 0 8 60
Nampula 3 40 3 2 0 0 6 40
Total 17 285 18 65 3 0 38 350
The table 6 above shows the dominant weight of size over geographic location with respect to skilled labor demand asserted above.
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Table 6 and most of all Graph 7 below, show that based on the sample, over 60% of all vacancies for skilled labor stem from firms located in Maputo province. Tete based firms are the second largest contributors but come well behind with only 17% of job vacancies.
What concerns the firms located in Maputo province, 83% of current skilled labor demand, expressed by job vacancies are issued by nine big firms, compared to 17% issued by medium sizes firms.
The following graph 7 illustrates these numbers
Graph 7 Current job vacancies by occupational skills profile
When we look at the distribution of vacancies by occupational skills profile, every third vacancy in average (35%) are issued for Industrial Mechanics, followed by Metal Construction Mechanics (22%) and Construction Machinery Mechanics with (20%).
3.2.1.2. Projected vacancies for 2011 by frequency of expressed intentions
We start with a summary presentation of reported labor demand estimates in the near future, and if it is ‘increasing, stagnating or decreasing’.
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Graph 8: future labor demand estimates by firm size.
Considering that the sample distribution of big and medium sized firms is almost equal and that big firms accounting for about 80% of job vacancies, the intention to hire in the next coming months is more frequently expressed by medium sized firms compared to big firms.
This may surprise; nevertheless, and not excluding non response issues, this result does not conflict with the fact that big firms surveyed have an – over four times higher – impact on labor demand, measured in terms of current vacancies, compared to medium sized firms.
It should be noted that none of the – however underrepresented ‐ small firms surveyed did express any increased labor demand in the near future.
We are now presenting labor demand this disaggregated by the five mechanical skills profiles.
Graph 9: demand by mechanical occupational type
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Firm estimates indicate a tendential increase in demand in particular for Fitters, Machinists and Metal Construction workers, and in a slightly less amount for Diesel Mechanics and Agricultural Machinery workers.
We conclude this chapter in comparing intentions to recruit by firm size and occupational, mechanical type. We start summarizing the situation presented for big firms (Graph 10).
Graph 10 # of Big Firms indicating ‘increasing labor demand in near future’
Now we shall report the same variables for sampled medium sized firms (Graph 11 below).
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Graph 11 # of medium sized Firms with intention to recruit in near future
If we compare now the intended recruitments for job vacancies that may materialize in 2011, in addition to the reported ‘current vacancies’ we may conclude that demand is highest for fitters, followed by Metal Construction Mechanics, and Construction Machinery Mechanics, independently of firm size. Machinists and Agricultural Machinery Mechanics come always last and in the same order.
Further analysis on this issue however will need to take into account additional variables that are closely linked to ‘size’ variable and actually expressed by it, that is: technological set up; product market situation; and firm strategy.19 The dominant position of size variable is contextual: in a context of an economy like Mozambique, with a low degree of industrialization and industrial specialization size is an indicator for capital investment and an important entry conditions for competing product markets that require a minimum degree of skills specialization, rational work organization and bureaucratic firm structure. On the
19 For example William Richard Scott (1998) Organizations – rational, natural, and open systems, Prentice Hall, Upper Saddle River, pages 131ff
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other hand, as we have shown elsewhere, firm size enhances negotiation power with the institutional political and legal environments20
3.2.2. Labor market efficiency and recruitment strategies
In the following we report responses to the question by which channels companies look for suitable candidates for job vacancies. Multiple answers were possible. Again, we use size and geographic location as independent variables:
Table 7 Recruitment strategies
Province Maputo* Sofala** Tete Nampula
Recruitment strategy
big med small big med small big med small big Med small
Newspaper Add
6 3 1 2 2 3 1 1 2
Social Networks
6 4 2 1 3 2 2 1
Employment Center
1 2 1 2
Other 1
*Among the Maputo sample we have two non‐responses, plus 1 data entry error
**Two non responses in Sofala sample
Graph 11 below sums up the recruitment strategy options reported. It confirms that firms prefer, in equal terms, using either newspaper ads and/or social networks when it comes to hiring, rather than addressing to Employment Centers.
Graph 11: reported recruitment channels in percentages
20 Peter R. Beck (2011 forthcoming) Sociological Challenges for labor market monitoring, analysis and research, University Eduardo Mondlane, Department of Sociology, page 17
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This topic concludes the so called ‘quantitative’ data analysis on vacancies and labor demand; in the next chapter we shall deal with more ‘qualitative’ aspects related with skills profiles and relevance ranking.
3.3. Qualitative aspects of labor demand – occupational skills’ profiles in demand
We turn now our attention to qualitative aspects of skills and present the results of the reported relevance assessment of occupational skills for the five mechanical occupations.
Interest in skills relevance assessment parts from the ‘human capital’ premise that investment in professional market skills development increases return of investment for individual workers and improves their market conditions; on the other hand firms benefit from higher productivity and product quality enhancing firm competitiveness.21
21 Beck (2011 forthcoming, ibid., page 12f
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This analysis of technical skills relevance will be completed by a brief remark to the result of ‘problem‐solving’, and social skills relevance assessments.
It should be noted that the competency skills assessment refers to PIREP level 5 qualifications and data from this analysis will be included into curricula development for these occupations.
In the following we resume the current skills profile definitions for each of the five mechanical professions:
Fitter (also known as Industrial mechanic)
Fitters produce components for assemblies and production machinery according to engineering drawings. They use machine tools and apply manual work techniques for the manufacturing processes.
Fitters monitor and optimize production processes and in case of breakdowns they locate and analyze the trouble and rectify the errors. Fitters find employment in many industrial sectors: e.g. the metal working industry, food industry, textile industry, vehicle manufacturing plants, power plants, electrical engineering companies, cement industry.
Metal Construction Mechanic (also known as boiler maker in South Africa or as steel work
fabricator in the U.S.A)
Metal Construction Mechanics produce steel structures such as girders, lattice frameworks, pillars, metal stairs, gates and roofing for large industrial buildings. They build conveyors, lifts and escalators and they assemble metal components by various joining methods: welding, soldering, riveting, bolting, bonding etc.
Metal Construction Mechanics manufacture sheet metal constructions such as tanks, boilers, ducts and sheathings using special sheet metal processing machines.
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They find employment in the metal fabrication industry, construction industry, dockyards and in vehicle manufacturing plants.
Machine Tool Operator (also known as machinist)
Machinists produce precision parts according to engineering drawings using machine tools such as lathe, milling machine, drilling machine, surface and cylindrical grinding machines.
They set up their machine tools, monitor the production processes and inspect the machined parts for correct size and geometric shape. In case of CNC machine tools they write the NC programs and simulate the cutting processes before machining takes place.
Machinists find work in mechanical workshops, foundries and in vehicle manufacturing plants.
Construction Machinery Mechanic (in South Africa also known as Diesel Mechanic)
Construction Machinery Mechanics maintain and repair construction machinery such as caterpillars, excavators, graders, trucks etc. They also maintain and repair mining equipment. Construction Machinery Mechanics find employment in construction companies, in construction machines and equipment leasing companies and in the mining industry.
Agricultural Machine Mechanic
Agricultural machine Mechanics maintain and repair agricultural machinery such as tractors, plows, sowing machines, harvesters, threshers, spraying equipment etc.
They can find employment in agricultural machinery leasing companies, agricultural co‐operatives and in repair workshops.
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3.3.1. Technical competency assessment
We turn now our attention to the ‘skills relevance assessments’. With regard to the reported results, it is not always clear if the relevance assessments were meant to describe and rank essential skills for the profession in question, or are reflecting the specific skills needs of the firm in terms of its products and its technological set up. Questionnaire used a ‘Likert scale’ type scaling scheme with five evaluation criteria, ranging from very low relevancy (0) to highly relevant (4). Nevertheless, considering that these ranking intervals have not been thoroughly defined, and for the purpose of analysis and better readability of results, we condensed information from the five scale model into a three scale model, composed by not ‘low relevance’, ‘relevant’, and ‘highly relevant’.
It was for the same reasons that we decided to condense the skills indicators into larger skills categories, which offers the advantage to reduce the large number of indicators that can attain more then 20/ occupational profile, to 3 to 5 categories. In case a more detailed analysis would be necessary, for example for curricula development purposes, nothing is standing in the way to get back to the raw data.
In the following we present the results for each of the five occupational types. Because we continue maintaining ‘size’ as an independent variable, following ‘skills relevance assessments’ will be distinctly presented for big firms and for medium sized firms.
Note: skills relevance assessments refer to those occupational profiles that are actually in demand or employed in respective firms. Not all firms assessed all skill profiles.
Legend: 1= highly relevant; 2 = relevant; 3 = non relevant skills
Table 8 skills relevance assessment for ‘Machinist’
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Table 9 skills relevance assessment for ‘Fitters’
Occupational key competences ranking by relevance voting
big firms medium sized firms
1 2 3 1 2 3
Fitter Inspection & Repair of production machinery 1 10 2 11
Assemble, test and commission production machinery 2 9 2 11
Control engineering pneumatics & hydraulics & testing 1 7 4 5 4 4
Others: high voltage up to 400 V 1 0 0 0
Total: skills relevance voting 1 11 23 5 8 26
Table 10 skills relevance assessment for ‘Metal Construction Mechanic’
Occupational key competences ranking by relevance voting
big firms medium sized firms
1 2 3 1 2 3
Metal Construction Mechanic Manufacture parts prior to machinery assembly 1 7 0 0 11
Dominate and apply welding technologies 2 6 1 10
Construction jobs for buildings 2 4 2 1 3 7
Treatment of metal surfaces, work planning and safety 3 5 1 10
Total: skills relevance voting 2 10 21 1 4 38
Table 11 skills relevance assessment for ‘Agricultural Machinery Mechanic’
Occupational key competences ranking by relevance voting
big firms Medium sized firms
1 2 3 1 2 3
Machinist
Reading & Reproducing engineering drawings 4 7 2 4 6
Quality control 4 7 12
Tuning, milling & grinding of work pieces 4 6 12
Work planning & setting up machine tools 3 8 3 2 7
Quality Machinery maintenance 5 6 4 1 7
Total: skills relevance voting 20 34 9 7 44
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Occupational key competences ranking by relevance voting
big firms medium sized firms
1 2 3 1 2 3
Agricultural Machinery Mechanic Machinery Quality control, diagnosis and maintenance 2 2
Control engineering pneumatics & hydraulics & testing 2 1 1 0
Testing & repair electrical circuits and customer care 2 1 1 0
Others: general repairs 1 2
Total: skills relevance voting 0 0 7 2 2 4
Table 12 skills relevance assessment for ‘Agricultural Machinery Mechanic’
Occupational key competences ranking by relevance voting
big firms medium sized firms
1 2 3 1 2 3
Diesel Mechanic Inspection maintenance & Repair of heavy machinery 1 7 0 0 4
Control engineering pneumatics & hydraulics & testing 3 4 0 0 4
testing & repair electrical circuits and customer care 3 5 0 2 2
Total: skills relevance voting 1 6 16 0 2 10
Fitters and Machinists followed by Metal Construction Mechanics got most frequent assessments. We suggest interpreting this fact as an indicator underlining the importance of these occupations for Mozambican Industry.
Table 13: Number of assessments of occupational skills profiles
Occupational skills # of Assessments ‐ big firms
# of Assessments ‐ medium sized firms
# of Assessments ‐ small firms Total
Machinist 54 60 1 115
Fitter 35 39 74
Metal Construction Mechanic
33 43 2 78
Agricultural Machinery Mechanic
7 8 15
Diesel Mechanic 23 12 35
Total 152 162 3 317
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Graph 12: Frequency of skills relevance assessment by occupational type
We should add the three small firms sampled assessed the (market) relevance of machinist (1 assessment) and of Metal Construction Mechanic (2 assessments). Both assessments do not reveal significant differences to the skills relevance assessments presented above. Indeed we can use the firm skills relevance assessment as an indicator of the relevance of the skills description used in the questionnaire. Such and evaluation is important for curricula development.
Graph 13 Relevance of skills description used in questionnaire22
22 big and medium sized firms only
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In 93% of cases skills description was considered relevant or very relevant by firm interlocutors, and only in 7% of cases was it considered as ‘not relevant’. Again we must take into account that firms will assess competencies with regard to their individual firm needs, rather than with regard to TVET provision. This underlines even more that the skills description can be seen as relevant for supporting curricula development.
Note: the relevance assessments of social and problem solving skills are not presented by using any tables or graphs for the simple fact that the approval rate of the relevance of these skills for professional behavior was widespread, and bringing up this item was apparently understood more like a rhetorical question.
3.3.2. Firm Observation sheet
As has been mentioned in the Methodology chapter has been created, in addition to the questionnaire – the main information gathering instrument – a firm observation sheet for quick assessments of firm and work facilities documenting general impression, workshop conditions and labor security provisions in terms of ‘good’, ‘normal’ and ‘problematic’.
Visits have been allowed in 27 of sampled 38 firms, and observation sheets were filled out in 1 small, 17 medium sized and 9 big companies. Table 14 resumes evaluation indicators and results
Table 14 firm observation sheet results on firm conditions ‐ # of observations
Firm size Small firms Medium sized firms Big firms Evaluation criteria
good normal insufficient good normal insufficient good normal insufficient
General impression
1 7 10 3 5
Workshop conditions
1 8 8 1 4 4
Security arrangements
1 7 9 1 3 3 2
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Indeed insufficient ratings are actually very low, but when they were made they were made in key areas such as work security (three cases) and workshop conditions (one case). On the other hand good ratings have been attributed in 32 cases: in twelve cases workshop conditions received this rating; work security in 10 cases. The other ratings can be studied directly in table 14.
3. Interpreting the results – method applied and findings
3.1. Brief assessment of the Methodological approach
With regard to the chosen methodology it has been confirmed that firm data collection should be done by using interview techniques. In case data collection will be done by non professional interviewers a sound training and pretesting is vital.
The relatively low effective, compared to planned sample size, was due to the fact that human resources have not been made available as planned. We evaluate the chosen pre‐interview contacting strategy and the actual access to sampled firms, as a good success.
With respect to sample frame, we would suggest that future surveys make use of International Statistical Institute’s Firm data base (FUE) in order to make sure that sample is complete and is containing all CAE numbers for a better identification of economic activity sectors and segments and a better over‐all comparability, with other surveys.
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Research Instruments and techniques have been judged relevant by all firm interlocutors. Even though the primary research objective was to assess current and future labor demand in the five occupations selected, we also wanted to know about current employment structure and skills levels. Firms revealed some severe reserves in providing information, which lead to the non‐consideration of these variables in data analysis.
The information of the quantitative aspects of labor demand was satisfactory, as well as the information gathered on behalf of the qualitative skills relevance assessment.
Nevertheless and in order to strengthen data analysis on this issue, we would suggest to rephrase the question and to using different data collection format: instead of using a Likert scale for capturing firms assessments, it is thinkable to use a hierarchical ranking model, where firm representatives would rank all presented skills by the order of their importance.
We also recommend making sure that a clear understanding of the question is guaranteed, by clarifying if relevance ranking of level 5 mechanical skills profile is referring to specific firm needs; or referring to the general ‘ideal typical’ skills profile of a Fitter for example.
If the latter is intended, the risk however still will be that the responses will in a high degree be tautological compared to the proposed list, insofar as this list already captures the relevant skill profile of this specific level 5 occupational type.
We suggest that these aspects should be given additional thoughts.
Data analysis was built on the comparison between what was considered independent and dependent variables, allowing putting labor demand and skills needs into a perspective with basic firm characteristics. As activity sectors and segments criteria was used for sample selection, we defined firm size as one
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independent variable – a choice that was supported by existing information (MPD 2006) – and geographic location as the other.
We found that only firm size can be confirmed as an independent variable allowing to cautiously establishing relationships of causality with labor and skills demand and assessment. Further explanations can be found in the ‘findings’ chapter.
3.2. Brief evaluation of survey results and its significance for TVET provision and curricula planning
The interview team was in all cases cordially received by the representatives of the companies. Considering the fact that the interviewees, in all cases technical directors, workshop managers or owners of companies are always under time stress it is remarkable and it cannot be appreciated enough that they took the time that was necessary to answer always all the questions of the interviewers.
In many cases (n=27) the interviewers had the opportunity to visit the workshops and they were allowed to take photographs.
Not all questions regarding details about the companies however were answered. In all cases the total number of staff was known however the distribution to administration, sales, production and gender could not always be answered. The same accounts for the structure of workforce being unskilled, semi‐skilled or skilled.
As analyzed in chapter 3 of this report a clear ranking of the labor demand was identified in the metal working and servicing area starting with the fitters (35,7%), followed by the metal construction mechanics (22,3%), construction machinery mechanics (20,3%), machinists (12,6%) and agricultural machinery mechanics (9%).
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Besides the data collected with the help of the questionnaires a lot of additional information was given, which was both interesting as well as relevant for the study. Some of the remarks of the interviewees were in many cases identical and are as follows:
practical skills on behalf of the graduates from technical schools are missing because the schools do not have the equipment (machines, tools, labs, computers..) to train the practical skills
curricula are outdated and do not reflect the level of technology in the industrial enterprises
technical teachers do often not have an industrial background, they are technical school or university graduates and can therefore not teach workshop practice
Co‐operation between school and industry does ‐ in many cases ‐ not exist however the representatives of the enterprises expressed their willingness to participate actively in the development of vocational schools i.e. training programs, curricula, internships etc.
social competences and problem solving abilities such as bearing responsibility, developing initiative, insight in further training and lifelong learning, discipline, care and cleanliness for equipment, cost‐conscientiousness, to name but a few, should also be part of the curriculum and be taught in school
In various technical sectors, especially in welding, a certification of the skills on behalf of the qualified worker is required by the enterprises in order to be able to quote for orders from abroad. In such cases the enterprise has to send its workers to South Africa to get the necessary certificate which is issued by the S.A. Certification Authority. The process is costly and the entrepreneurs wish that a certification authority would be established in Mozambique.
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Some companies are in the process of modernization – wired control must be replaced by PLC’s ‐ therefore there is a big demand for qualified staff in electric and electronic fields that can ‐ at the moment ‐ not be met.
The awareness for quality of work, initiative and autonomy on behalf of the trainees must be raised and also included in the training programs.
Several companies are in the process of establishing their own training centers because the graduates from technical schools lack practical experience as well as subject knowledge.
Fitters should be in a position to carry out simple electrical installations such as connecting electric motors and switches, changing fuses and contactors etc.
The relation between workshop practice / applied theory in the technical school should be about 70% / 30% and not vice versa.
Equipment, teaching aids, labs in technical schools should reflect the level of technology in the enterprises.
Revision of the curriculum should take place at least every five years in order to keep pace with the advance of new technologies and the changing needs of industry.
Technical schools must pay more attention to virtues such as punctuality, discipline, orderliness and cleanliness and introduce in this regard a zero tolerance approach as done in some of the industries.
In some cases the interviewers were informed that there was an urgent demand for labor in the automotive trades and for the electric/electronic professions. Whether similar studies should be undertaken for these occupational families remains to be considered.
We are proposing some adjustments for future firm surveys, as follow:
Revise the questionnaire by summarizing and shortening the number of technical skills and competences
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shorten the relevance scale from 5 elements to 3 elements: (1) unimportant, (2) important, (3) very important
do not mail questionnaires to companies and hope for return, they will not be returned personal interviews are indispensable
do not leave questionnaires at firms to be collected later, they may be wrongly filled in
4. Conclusions
The interviews and discussions in the firms revealed awareness for the necessity for well organized and well equipped vocational training centers and highly qualified training staff. As the demand for qualified personnel in the metal ‐ mechanical sector is very big in some parts of Mozambique, e.g. in Tete province some enterprises try to overcome the manpower shortage by establishing their own training centers.
Others are trying to attract staff from the neighboring states, South Africa, Zimbabwe, Malawi or even from Portugal and Brazil.
These developments show in an impressive way the importance of improvement and further development of VET in Mozambique.
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5. Recommendations
The results of the survey in the firms belonging to the metal / mechanical sector will enable the vocational planners to develop curricula, in this case for vocational level 5, to meet the skill needs of the industry. Furthermore important information was gathered regarding the design of training programs and equipment to be provided for training.
During the visits to the workshops of the firms no CNC machine tools were seen in use, only conventional machine tools were operated.
However TVET must be planned in a future oriented manner and as advanced technology does not stop at frontiers the provision of CNC machine tools for the vocational training schools should be considered to provide for future developments in industry.
Often very old machines were in use and in most cases HSS tools were used for the cutting processes.
Only in one case indexible carbide inserts were used on a lathe to machine the contact surfaces of the wagon wheels at the railway maintenance workshop in Maputo.
In case of milling only HSS cutting tools were seen to be used i.e. no high cutting speeds could be selected in the cutting processes and no high efficiency, precision and performance could be achieved. In order to remain competitive in the machining area it will be indispensable to use carbide tipped tool and for this purpose the provision of such tools for the vocational schools is a must.
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In the area of fabrication (boiler makers, metal constructions, sheet metal fabrication) all major welding methods were applied in industry: Oxy‐acetylene welding and cutting, manual electric arc welding, MIG‐welding and TIG‐welding.
The inclusion of all these welding techniques in the curriculum and its practical training in the welding workshops is therefore absolutely essential.
Further activities required for the development and modernization of the vocational schools:
Continuing teacher training activities Continuing the curriculum development work for level V, including lesson planning
Installing new equipment (machine tools, labs, teaching aids) in
the pilot schools Development of training programs, project work, CBT training
Development of concepts for interconnected PC school
networks and internet connection
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6. Bibliography
Delbert C. Miller & Neil J. Salkind (2002) Handbook of Research Design &Social Measurement, Sage Publications, Thousand Oakes
gtz (2009) Jobs & occupational skills in Mozambican Industry – Firm survey report, elaborated by Peter R. Beck, with collaboration of José Bambo, Maputo
gtz (2009) Taking stock: Labor Market statistics and instruments in Mozambique – now and then; desk study elaborated by Peter R. Beck, with collaboration of José Bambo, Maputo
Earl Babbie (2004) The Practice of Social Research, Thomson Wagsworth
Gary D. Bouma/G.B.J. Atkinson (1996) A Handbook of social research, Oxford University Press
Ministry of Planning/National Directorate of studies and policy analysis: Enterprise development in Mozambique‐ Results Based on Surveys Conducted in 2002 and 2006, Maputo 2006. MPD (2006)
Peter R. Beck (2011) Roteiro da pesquisa empírica, Eduardo Mondlane University, Departament of Sociology, Maputo, Mozambique
INE: monthly economic activity indicators; Source: www.ine.gov.mz
National Statistical Institute ( INE) (2004): CEMPRE 2002, Source: www.ine.gov.mz
William Richard Scott (1998) Organizations – rational, natural, and open systems, Prentice Hall, Upper Saddle River
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Peter R. Beck (2011 forthcoming) Sociological Challenges for labor market monitoring, analysis and research, University Eduardo Mondlane, Department of Sociology,
7. Annexes will be provided in separate documents
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