LMA & HR demand forecasting

Decent Work for All ASIAN DECENT WORK DECADE 2006-2015

Dr Sorab Sadri and Prof. jayashree Sadri

Labour Market Analysis and Human Resource Demand Forecasting in Developing Economies

Presentation Outline

1. Uses of skills demand analysis /labour market information (LMI)

2. Drivers of change for skills demands

3. Examples of methodologies

4. National examples

Uses of LMI & Skills Demand Data

• Policymakers: identify high demand skills, inform planning & resource allocation

• Training Institutions: schedule training programs, review/update course content & trainer skills, provide guidance to trainees

• Employers: understand changing business environments, respond to future skills shortages and gaps, identify enterprise and sector wide training priorities

• Workers: identify priority types and levels of skills upgrading for workers, inform employment and wage trends

• Community, civil society groups: improve advice and targeted training for vulnerable groups to access labor markets

• New entrants and returnees to LM: career guidance

Common Approaches to LMI

• Econometric modelling• Signalling• Job opportunity index• Use of administrative data• Enterprise surveys• Special studies (eg: cost-benefit, tracer)• Sector studies• Stakeholder driven forums

Sparreboom, T. & Powell, M. (2009) Labour Market Information and Analysis for Skills Development, ILO: Geneva.

Drivers of change for Skills Demand

Policy/regulationChange

e.g. Change inPriority sectors

Markets

Technology change

Demographic change

Environmental change

Migration

Business strategy,Competition

(e.g. growth of high/low Skills jobs)

Skills demand

Overview of Quantitative and Qualitative LMIS

Quantitative Qualitative

SectorStudies

EconometricModeling

Signalling

Job Opportunit

y Index

Enterprise Survey

Special Studies(Tracer/Rateof Return)

StakeholderDrivenForums

Use ofAdministrative

Data

LMIS: Quantitative and Qualitative Approaches

L E

V E

L O

F A

C C

U R

A C

Y

COMPLEXITY AND RESOURCE REQUIREMENT

SectorStudies

EconometricModeling

Signalling

Job Opportunit

y Index

Enterprise TrainingSurvey



Use of Administrative

Data

Quantitative Approaches to Labor Market Information

Sim

ple

st

Mo

st

Co

mp

lex

L E

V E

L O

F C

O M

P L

E X

I T Y

Approach Benefit Limitation Output Resources

Enterprise Survey

More specific,

enterprise level data

Limited to sectors, costly

Specific skills needs

of enterprises

Expertise in

specialized methods

EconometricModeling

Consistent overview

and forecast

Data dependent,

Costly, Time

consuming

Projections of demand &supply by occupation/

industry

Expertise in econo-

metrics,LFS data

Signalling

Simple, Easy to do and update

Data dependent Difficult to

interpret

General trends in

skills demand

and supply

Statistical knowledge

Time series

Source:

Sparreboom and Powell, Labor Market information and analysis for skills development, ILO Employment Trends Unit

Use ofAdministrative

Data

little cost, readily

available data

#of enterprises, employed, unemploye

d

Limited to available

data

Man hours for

collation, admin data

Job Opportunit

y Index

Gives insight into changing demand

Limited coverage, resource intensive

Newspaper accounts

List of skills

demand based on vacancies

Sim

ple

st

Mo

st

Co

mp

lex

L E

V E

L O

F C

O M

P L

E X

I T Y

Approach Benefit Limitation Output Resources

Source:


Quantitative Approaches to Labor Market Information

Qualitative Approaches to Labor Market InformationS

imp

les

tM

os

t C

om

ple

x

L E

V E

L O

F C

O M

P L

E X

I T Y

Approach Benefit Limitation Output Resource


More specific

information vis D&S factors

Subject specific/

qualitative D&S

factors

Expertise in

specialized studies

Partial view, costly

Source:


SectorStudies

Comprehen-sive vis

sector D&S factors

Sector specific data on demand

and supply

Expertise in

quantitative/qualitative analysis

Limited scope, partial

view, costly if for all sectors


D&S data with

context/ qualitative

factors

Participatory Forum

for discussion

Individuals might

dominate

Regular forum

discussion

Is there a perfect model for anticipating skill demands?

Econometric modeling

Job opportunity index Enterprise survey

SignallingUse of admin data

Special studies Sector studies

Stakeholder driven forum

• Econometric modeling to project future labor demand on a national level by industry and occupation • Annual LFS and employee surveys • Each state conducts LMIA.






Occupational Projections National

Employment Average Annual Openings

SOC Code

Occupation Est 2008 Proj 2018 Change Growth Replce Total

41-1011

First-Line Supervisors/Managers of Retail Sales Workers

1,685,500 1,773,900 5.2% 8,840 36,170 45,010

41-1012

First-Line Supervisors/Managers of Non-Retail Sales Workers

506,800 531,200 4.8% 2,440 10,510 12,950

41-2011 Cashiers 3,550,000 3,675,500 3.5% 12,550 159,440 171,990

US LMI Model

• The Skills Development Planning Unit (SDPU) conducts quarterly monitoring reports on skills supply and the outcomes of training

• Sector Education and Training Authorities (SETAs) conduct sector studies and stakeholder consultations

• The SDPU also now developing an econometric model for employment projections

The South African LMI Model






• The Human Sciences Research Council (HSRC) conducts labor market studies covering priority sectors utilising employer surveys

• HSRC conducts semi-annual LFS and enterprise-based manpower surveys

Sri Lanka LMI Model






• Occasional sector studies, eg: RMG, provide information on enterprise characteristics and distribution and an overview of government policies related to the sector

• TVEC collects and publishes statistics on training, training providers and labor market data, including job vacancies, based largely on administrative data

• Occasional tracer studies

• Job vacancies collected from newspapers as well as published through JobsNet

• Annual labor force surveys since 1992

Methodological Considerations

• Clarify exact information needs and priorities

• Balance short term responsiveness with long term planning needs

• Balance statistical accuracy with available resources and capacity

• Combine quantitative and qualitative methods

• Consider institutional arrangements

• Use standard classifications of occupations such as ISCO-08 to enable comparable evaluations across industries, regions and countries

• Use standard classifications of qualifications – one benefit of NQFs.

Key Regional Trends

• Each country approach reflects institutional arrangements and data ‘histories’

• Strengthening institutional arrangements responsible for overseeing the collection and analysis of TVET and skills data and disseminating findings

• Developing sectoral approaches in priority industries as a mechanism for obtaining information

• using labour market outcomes of TVET and skills graduates as a fundamental measure of the extent to which TVET programmes are meeting labour market needs – tracer studies

Conclusion

• Labour Market Information & Analysis (LMIA) is complex

• There are a smorgasbord of approaches, each with their own strengths and weaknesses

• Looking at institutional arrangements equally important

• Capacity and data develop longitudinally but has to start somewhere

THANKS

LMA & HR demand forecasting

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