minneapolis-st. paul construction workforce...

Minneapolis-St. Paul Construction Workforce Forecasting

Final Presentation

May 1, 2014

AGENDA

1

Introduce discussion participants

Review CCE project goals and approach

Examine forecast results

Explore constraints on supply

Discuss next steps for forecasting and stakeholder engagement

CCE TEAM

2

ERIC SMITH, ESQ. | TEAM MEMBER

2nd year MBA, emphasis in Health Care Consulting

Past experience in health policy and health law at Children’s Hospitals and Clinics of Minnesota, interned at Health Care Futures consulting firm

After graduation, joining Medtronic Marketing Leadership Development Rotational Program

JAKE TITUS | TEAM LEAD

2nd year MBA, emphases in Strategy and Sustainability

Past experience consulting to federal agencies and utilities on energy efficiency programs

After graduation, will return to Deloitte Consulting

MIKE SCHMIT | TEAM MEMBER

3rd year Undergraduate, studying Finance and Operations

Past experience interning at a small merchant bank and at Boston Scientific

After graduation, plans to pursue a career in management consulting

DAN ROBINSON | TEAM MEMBER

2nd year MBA, emphasis in Consulting

Past experience in management consulting and bridge engineering

After graduation, will return to McKinsey & Company

AITZAZ AHSAN | TEAM MEMBER

2nd year MBA, emphases in Finance and Strategy

Past experience as a telecommunications consultant

After graduation, will return to Cummins Power Generation

SCOPE

MSPWIN asked CCE to develop a forecasting methodology and identify next steps to support construction workforce development activities

3

Develop a methodology to forecast construction workforce shortages

Identify acute workforce shortages

Identify next steps for forecasting and

stakeholder engagement

Understand the flow of the talent

pipelines

PRIMARY SOURCE RESEARCH

CCE has interviewed contacts in labor unions, training organizations, construction firms, government, and academia

4

INTERVIEWS COMPLETED 41 ORGANIZATION CONTACT

Associated General Contractors Tim Worke

Baltimore Job Opportunities Task Force

Jason Perkins-Cohen, Matt Stubbs

Boilermakers Local 647 Luke Voigt, Carey Kowalski

Building MN Vicki Sandberg

Carlson School - Supply Chain and Operations Department Dr. Kevin Linderman

Center for Integrative Leadership Jay Kiedrowski

CLMA Brian Stamper

DEED Rachel Vilsack, Jackie Buck, Tim O’Neill, Dave Senf

Department of Human Rights Kevin Lindsey

Department of Labor & Industry Johnnie Burns

Dunwoody Richard Wagner

Electricians Local 110 Brian Winkelaar

FMI John Hughes

Hennepin County Debra Brisk

IIR Scott Kirkeby

Itasca Project Jamie Simonsen

Laborers Users & Contractors Associations

Paul Berg

Iron Workers Larry Gilbertson

ORGANIZATION CONTACT

McKnight Foundation Eric Muschler

Metropolitan Council Wanda Kirkpatrick, Aaron Koski

Michigan State University Dale Belman

Minneapolis Building and Construction Trades Council

Dan McConnell

Minneapolis Electrical Joint Apprenticeship Training Program

Jim Nimlos

Minneapolis Pipefitters Roger Garner

MNDOT Kim Collins

MnSCU Jamie Simonsen

Mortenson Bob Solfelt, Jennifer Mukhtiar, Lynn Littlejohn

MSFA Alex Tittle

North Central States Regional Council of Carpenters

Kyle Makarios

Ryan Companies Elizabeth Campbell

Saint Paul Building and Construction Trades Council

Harry Melander

St. Paul Port Authority Louis Jambois

Summit Academy OIC George Garnett, Anne-Marie Kuiper, Louis King

Thor Construction, Inc. Ravi Norman

Workforce Solutions John O’Phelan

*CCE spoke with some interviewees twice

SECONDARY SOURCE RESEARCH

CCE has reviewed research and data from trade associations, government agencies, and academia

5

Recovery: Job Growth and Education Requirements through 2020 Construction Industry Workforce Shortages: Role of Certification, Training and Green Jobs in Filling the Gaps Forecasting Demand in the Construction Industry of Hong Kong

Stock-Flow Model for Forecasting Labor Supply

Forecasting Manpower Demand in the Construction Industry of Hong Kong A Critical Review of Forecasting Models to Predict Manpower Demand

Delphi Forecasting

TC3: Twin Cities Construction Consortium

Worker Shortage Survey

Seventy-Four Percent of Construction Firms Report Having Trouble Finding Qualified Workers

Downtown Atlanta Workforce Consortium

Where the Jobs Are

Associated Builders and Contactors Merit Shop Training Data

Best Construction Jobs

New Stadium Q&A

The MetLife Survey of the American Teacher: preparing Students for College and Careers

The Construction Exchange

Construction Workforce: Building Comprehensive labor Market Information

Labor Supply/Demand Analyses Methodology

ACADEMIC PAPERS 7 TRADE INDUSTRY REPORTS 13

EMSI

Wanted Analytics

CLMA (Construction Labor Market Analyzer)

FMI

IIR (Industrial Labor Market Forecast)

REED

Dodge Market Research

PRODUCT WEBSITES 7

SECONDARY SOURCE RESEARCH

CCE has reviewed research and data from trade associations, government agencies, and academia

6

ORGANIZATION

Anoka Technical College

Better Futures Minnesota

Dakota County Technical College

Dunwoody College of Technology

Hennepin Technical College

Minneapolis Community and Technical College

Minneapolis Urban League

Saint Paul College

Summit Academy

ORGANIZATION WEBSITES 9 TITLE AGENCY

2030 Transportation Policy Plan Metropolitan Council

Future Jobs in Construction DEED

Gauging the Labor Force Effects of Retiring Baby Boomers

Bureau of Labor Statistics

Construction Projects Monitored by the Department

MN Department of Human Rights

Labor Force Projections, 2010-2045 MN Demographic Center

MN Population Projections by Race and Ethnicity, 2005 to 2035

MN Demographic Center

Employment Outlook DEED

Building Minnesota’s Workforce Through Apprenticeship

MN Department of Labor and Industry

Minnesota’s Construction Industry Conference

MN Department of Labor and Industry

Minnesota Workforce Inventory DEED

Employment Outlook DEED

Minnesota Index DEED

Another Strong Month for Minnesota Jobs DEED

Affirmative Action Statistics Data Packet: Minneapolis-St. Paul Statistical Area.

DEED

GOVERNMENT SOURCES 14

EXECUTIVE SUMMARY

7

Ironworkers, boilermakers, pipefitters, operating engineers, painters, and carpenters are all likely to experience labor shortages, though data is mixed in some cases

There is a surplus of electricians Participation by women and minorities will grow very slowly

absent intervention

There are several candidates that MSPWIN should further assess as potential forecast owners

MSPWIN will need to address several obstacles to successfully engage stakeholders in using or enhancing forecasts

There are many possible ways to address the complexity and opacity of the talent pipelines

Workforce forecasts range from acute shortages to significant surpluses

Talent development pipelines for the trades are complex and opaque

CCE’s analysis has clarified problems and identified next steps toward solutions

No one actor has a complete understanding of the talent pipeline for any particular trade

There are multiple ways to become a journeyworker, with very different requirements and time requirements

The complexity and opacity of the pipelines may delay the generation of new journeyworkers and discourage newcomers – especially minorities and women

PART I: PROJECT BACKGROUND

EXPECTED LABOR SHORTAGES

Contractors and policymakers are concerned about imminent workforce shortages in the construction industry

“Worker Shortage Survey.” Agc.org. Associated General Contractors, 4 Sept. 2013. Web. Bernstein, Harvey. “Construction Industry Workforce Shortages: Role of Certification, Training, and Green Jobs in Filling the Gap.” McGraw Hill Construction, 2012. Report.

9

69

31

13 13

74

Expecting Shortages

Not Expecting Shortages

Will your firm experience skilled worker shortages

by 2014? Not

Expecting Shortages

Expecting Shortages

Unsure

Do you expect craft worker shortages over the next 12

months?

WORKFORCE DEMOGRAPHICS IN THE SEVEN-COUNTY REGION

…and employment equity advocates see those shortages as opportunities to increase participation from minorities and women

United States Census Bureau. “Summary File.” 2006 – 2010 American Community Survey. U.S. Census Bureau’s American Community Survey Office, 2014. Web. 25 April 2014. <http://stats.metc.state.mn.us/data_download/DD_start.aspx?source=main>.

10

23

TOTAL WORKFORCE BY GENDER (%) CONSTRUCTION WORKFORCE BY GENDER (%)

CONSTRUCTION WORKFORCE BY RACE (%) TOTAL WORKFORCE BY RACE (%)

84

16 MINORITY

WHITE

MINORITY % OF POPULATION

88

12 MINORITY

WHITE

97

3 FEMALE

MALE

52

48

FEMALE

MALE

CONSTRUCTION TRADES UNATTRACTIVENESS

The construction trades are perceived as unattractive to new workforce entrants

“The MetLife Survey of the American Teacher: preparing Students for College and Careers.” Harris Interactive, May 2011. Contractor representative. Personal interview. 13 Feb. 2014.

11

1988 1997 2011

Middle and High School Students Expecting to Go to College (%)

57

67

75 “The entertainment industry is eating our lunch. They have figured out outreach, branding, and marketing in a way that [the construction industry] has not. We have to do something different.”

-Contractor

Stakeholders observed that the construction industry was perceived by students as less glamorous than other industries.

0.6

0.8

1.0

1.2

2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014

Up 14% since bottom

US CONSTRUCTION SPENDING (IN TRILLIONS OF DOLLARS)

Construction spending has risen from the low, but is still below pre-recession levels

“Construction Spending.” Census.gov. United States Census Bureau, Web. 4 Apr. 2014.

12

Still down 23% since peak

AVAILABLE DATA ON CRAFT LABOR SHORTAGES*

CCE identified nine trades that might be subject to labor shortages based on existing research…

“Worker Shortage Survey.” Agc.org. Associated General Contractors, 4 Sept. 2013. Web. Bernstein, Harvey M. “Construction Industry Workforce Shortages: Role of Certification, Training, and Green Jobs in Filling the Gaps.” McGraw-Hill Construction, 2012. Web. “Employment Outlook.” Minnesota.gov. Department of Employment and Economic Development, 2012. Web.

13

*CCE evaluated the usefulness of 14 data sources and forecasts - See Appendix for details

McGraw Hill Construction

1. Carpenters

2. Electricians

3. HVAC/Boilermakers

4. Concrete Finishers/ Cement Masons

5. Ironworkers

DEED

1. Carpenters

2. Electricians

3. Pipefitters

4. Painters

5. Operating Engineers

6. Laborers

AGC Minnesota

1. Laborers

2. Operating Engineers

3. Carpenters

4. Concrete Finishers/ Cement Masons

5. Pipefitters Tota

l Op

en

ings

20

10

-20

20

Firm

s Ex

pe

ctin

g Sh

ort

age

s

Firm

s Ex

pe

ctin

g Sh

ort

age

s

Trades with Potential Shortages

1. Carpenters 2. Electricians 3. Operating Engineers 4. Laborers 5. Pipefitters 6. Concrete Finishers 7. Boilermakers 8. Painters 9. Iron Workers

Data doesn’t answer:

How large will gaps be?

Will the gaps occur in MSP?

When will they occur?

PERCENT UNEMPLOYMENT BY TRADE IN THE U.S.

…but other data suggest that there are actually surpluses for these nine trades

“Best Construction Jobs.” Usnews.com. U.S. News Money: Careers. 20 Apr. 2014. Web. “Construction Labor Market Analyzer.” Construction Users Roundtable. 3 Mar. 2014. Web.

14

18

15

12

19

10

20

12

11

15

11

9

7

12

6

12

7

7

9

Iron Workers

Painters

Boilermakers

Concrete Finishers

Pipefitters

Laborers

Operating Engineers

Electricians

CarpentersHistoric Average (2002-2013)

2013

AGE DISTRIBUTION BY TRADE IN SEVEN-COUNTY METRO (% OF WORKFORCE)

There is much discussion of a coming wave of retirements, but workforce data does not support this

Institute of Education Sciences. Nces.ed.gov. U.S. Department of Education, Web. 9 Apr. 2014. “Analyst.” Economic Modeling Specialists Intl. Web. 25 Mar. 2014.

15

Age 65-99

Age 55-64

Age 14-54

92 92 92 91 91 90 89 87 82

8 8 7 8 8 9 10 11 15

0 0 1 1 1 1 1 1 3

CCE FORECASTING MODEL OVERVIEW – **DETAIL IN ANALYSIS TOOLKIT, SEPARATE

To address these challenges, CCE built a quantitative model that predicts labor supply and demand based on the best available data

CCE Interviews.

16

CCE adjusts CLMA forecast data by: Benchmarking against Dept. of

Commerce data Aligning geographic area with

supply forecast Aligning trade definitions with

Standard Occupational Codes used in supply forecast

CCE then disaggregates the results to find demand for minorities and women by trade

CCE CALCULATION ENGINES OUTPUTS EXTERNAL DATA

Adjustments from DEED modeling experts

Unemployment data from BLS

DEED employment growth forecasts

Project details from project owners

Forecasts from McGraw-Hill

CLMA DEMAND MODEL

CLMA translates project data into labor demand

Project values from Dept. of Commerce

County population from U.S. Census

Occupations by Standard Occupational Codes

CCE’s model combines the most current data on: Employment and

unemployment by trade Employment growth forecasts Workers who hold multiple jobs CCE then disaggregates the results to find the supply of minorities and women by trade

MONTHLY DEMAND

2015

Trade Segment Jan Feb Mar

Carpenters

Total

Minority

Female

ANNUAL SUPPLY

Trade Segment ’14 ’15 ‘16

Carpenters

Total

Minority

Female

OES employment data from BLS

CC

E SU

PP

LY M

OD

EL

CC

E D

EMA

ND

MO

DEL

PART II: WORKFORCE SUPPLY AND DEMAND FORECASTS

May

-14

Jul-

14

Sep

-14

No

v-1

4

Jan

-15

Mar

-15

May

-15

Jul-

15

Sep

-15

No

v-1

5

Jan

-16

Mar

-16

May

-16

Jul-

16

Sep

-16

No

v-1

6

Jan

-17

Mar

-17

May

-17

Jul-

17

Sep

-17

No

v-1

7

Jan

-18

Mar

-18

May

-18

Jul-

18

Sep

-18

FORECAST LABOR DEMAND FOR NINE SELECT TRADES

Labor demand will grow by over 14% annually to almost 50,000 craft workers, mostly in the private sector

CCE Analysis.

18

PUBLIC

PRIVATE

START 26,403

May 2014

TROUGH 37,628

March 2016

DEMAND BY SECTOR

(%)

PU

BLI

C

PEAK 45,443

June 2015

PEAK 48,893

October 2018

46

40

60

54

DEMAND BY SECTOR

(%)

PR

IVA

TE

PU

BLI

C

PR

IVA

TE

FORECAST LABOR SUPPLY AND DEMAND FOR NINE SELECT TRADES

Supply will only grow at 2% annually until nearly all workers will be in demand by late 2018

CCE Analysis.

19

May

-14

Jul-

14

Sep

-14

No

v-1

4

Jan

-15

Mar

-15

May

-15

Jul-

15

Sep

-15

No

v-1

5

Jan

-16

Mar

-16

May

-16

Jul-

16

Sep

-16

No

v-1

6

Jan

-17

Mar

-17

May

-17

Jul-

17

Sep

-17

No

v-1

7

Jan

-18

Mar

-18

May

-18

Jul-

18

Sep

-18

DEMAND

SUPPLY

DEMAND (% SUPPLY)

SUR

PLU

S

58

42

EMP

LOY

ED

DEMAND (% SUPPLY)

SUR

PLU

S

99

1

EMP

LOY

ED

QUANTITATIVE ANALYSIS OVERVIEW

CCE combined forecasting model results with stakeholder feedback to determine which trades will experience acute shortages

20

VALIDATED CONFLICTING UNVALIDATED

DESCRIPTION Stakeholders agree with forecasting model results

Forecasting model results conflict with stakeholder feedback

No stakeholder feedback on forecasting model results

GAP ANALYSIS RESULTS

LABOR SHORTAGES

Ironworkers

Boilermakers

LABOR SURPLUS

Electricians

LABOR SHORTAGES

Pipefitters

Painters

Operating Engineers

Carpenters

LABOR SHORTAGES

Concrete Finishers

Laborers

CCE heard conflicting feedback on labor alignment for electricians:

- vs. -

VALIDATED RESULTS (DEMAND AS A PERCENTAGE OF SUPPLY)

CCE Analysis. CCE Interviews.

21

Iro

nw

ork

ers

The model predicts shortages of ironworkers and boilermakers and surpluses of electricians, and stakeholders validated these forecasts

“3 years ago, the ironworkers said that their average worker was 52 years old….they will have a mass exodus.”

- State Agency

“We expect to need 1500 people by 2018 and are trying to find as many warm bodies as possible.”

- Union

According to a training organization, the electricians have dramatically increased their training capacity in the last 3 years. This person expected training capacity to increase.

0%

200%

400%

600%

0%

200%

400%

600%

0%

20%

40%

60%

80%

100%

120%

Bo

ilerm

ake

rs

Ele

ctri

cian

s

SHORTAGE

SURPLUS

AVERAGE SHORTAGE: 2,662 FTE’S

AVERAGE SHORTAGE : 183 FTE’S

AVERAGE SURPLUS: 2,740 FTE’S

“There is a huge surplus of electricians.”

- Union

CONFLICTING RESULTS (DEMAND AS A PERCENTAGE OF SUPPLY)

The model predicts surpluses for pipefitters, painters, operating engineers, and carpenters, but stakeholders report that there are or will be shortages


22

“Pipefitters will likely experience shortages.”

- Labor Expert

“There is a shortage of painters.” - Union

“Operators likely have shortages.” - State Agency

According to a union representative, there will be shortages and lots of

recruiting this year and for the next couple of years.

0%20%40%60%80%

100%120%

0%20%40%60%80%

100%120%

0%20%40%60%80%

100%120%

0%20%40%60%80%

100%120%

Pip

efit

ters

SURPLUS

AVERAGE SURPLUS: 893 FTE’S

Pai

nte

rs

Op

era

tin

g En

gin

ee

rs

Car

pe

nte

rs

AVERAGE SURPLUS: 940 FTE’S



CCE recommends relying on stakeholder assessments of these trades and exploring how the model can account for labor mobility

SURPLUS

SURPLUS

SURPLUS

UNVALIDATED RESULTS (DEMAND AS A PERCENTAGE OF SUPPLY)

The model predicts shortages of laborers and concrete finishers, but CCE could not validate these results with stakeholders

CCE Analysis.

23

0%

50%

100%

150%

200%

250%

0%

50%

100%

150%

200%

Lab

ore

rs

Co

ncr

ete

Fin

ish

ers

SHORTAGE


SHORTAGE


0%

5%

10%

15%

20%

25%

30%

35%

2014 2019

0%

1%

2%

3%

4%

5%

6%

7%

8%

2014 2019

WORKFORCE SUPPLY DEMOGRAPHICS

Female and minority participation in all trades is expected to follow broad demographic trends and remain low

CCE Analysis.

24

MINORITY WORKFORCE PARTICIPATION

Minorities as a percentage of workers in MSA, by trade, 2014 & 2019

FEMALE WORKFORCE PARTICIPATION

Women as a percentage of workers in MSA, by trade, 2014 & 2019

MDHR TARGET (6%)

MDHR TARGET (32%)

PART IV: TALENT DEVELOPMENT PIPELINES

SCOPE AND FINDINGS

26






pipelines


SCOPE AND FINDINGS

27






pipelines


SCOPE OF WORK FOR PIPELINE ANALYSIS

CCE chose electricians and carpenters to analyze to understand the trade pipelines

28

Pick 2 trades for pipeline analysis meeting the following criteria:

One licensed trade One un-licensed trade Trades w/ established contacts preferred Trades with larger workforce Trades with expected shortages

Pipeline stages Duration of stage Organizations involved in each stage, including:

Capacity Entry requirements

Number of tradespeople in each stage Number of people flowing between stages Factors that constrain the pipelines

Analysis Goals

Licensed:

Unlicensed:

Electricians

Carpenters

Where can influence be exerted to increase the supply of skilled craftspeople?

Once action is taken, how long will it be until results are seen?

What do construction trade pipelines look like and how do the pipelines for licensed and unlicensed trades differ?

What factors particularly affect minorities and women?

Question this analysis will help answer

TALENT DEVELOPMENT PIPELINE FOR CARPENTERS

The carpenter pipeline is highly regulated by the employers, and entrance into the union is easy once a sponsor is obtained

29

General Population

0 months Apprentices*

48 months

• Register with state

Can’t work w/o direct supervision

Journeyworkers

• Complete apprenticeship

Work unsupervised

Entry Requirements

Flow to next union stage (uncertain volume)

Percentage of new union apprentices

12 to 24 months

18 months

SP College

Months to next stage

2.5 to 5 months

Summit

BETTER FUTURES

Mpls Urban league

Non-Union

40%

20%

CCE Analysis

100%

Flow to next non-union stage (uncertain volume)

* 25% union drop out rate in 1st year of apprenticeship

Henn. Tech

• Have been hired by union contractor

• 4 weeks training per year (1/quarter) for 4 years

Union

Carpenters 322

80%

Length = 4 to 6+ years

TALENT DEVELOPMENT PIPELINE FOR ELECTRICIANS

The electrician pipeline is more complex and differs in that prospects apply first to the unions and are required to complete a 5-year union training program

30

General Population

0 months

• Apply for apprenticeship o Include work history

• Panel interview o Demonstrate knowledge

of and commitment to trade

• Must enroll in 5-yr union apprenticeship training program (free)

IBEW Local 110 IBEW Local 292

Union

Apprentices*

48 to 60 months (48 by law, 2+ yr programs credit 12)

• Register with state

Can’t work w/o direct supervision

Journeyworkers*

12 to 60 months (12 by law)

• Pass state exam o Pass rate: union 95+%, tot. 30%)

• Licensed by state

Work unsupervised according to Master’s direction

Masters

• Pass state exam • Licensed by state

Permits are only issued to Masters

Entry Requirements

Flow to next union stage (uncertain volume)

Percentage of new union apprentices

48 months

MCTC

Anoka Tech

Dakota Co

24 to 48 months

SP College

Months to next stage

2.5 to 5 months

Summit

GW EASTER SEALS

MERRICK

MN Electrical Ass.

Non-Union

Pre-Apprenticeship NECA

Building MN

• Apply to the union

40%

50%

10%

CCE Analysis

100%

Flow to next non-union stage (uncertain volume)

* Union membership ratio approx. 7 journeyworkers to 1 apprentice

Length = 5 to 8+ years

OVERVIEW OF FACTORS THAT CONSTRAIN TRADE PIPELINES

CCE has identified four pipeline constraints that delay journeyworker generation, discourage new entrants, and exacerbate the labor shortages

CCE Analysis

31

Training Constraints

8+ years to reach journey status

Training prep not matching union skillset

Experienced non-union transfers slowed

Reactive Responses

Poor contractor forecasting and reactive responses Union pressure to limit number of apprentices

Losing People

System Complexity and Misconceptions

The pipelines are complex and unique Misconceptions exist about unions

Inefficiencies significantly delay the generation of new journeyworkers

Complexities and misconceptions create a confusing and uninviting environment that may discourage candidates

Delayed response time and system losses exacerbate the labor shortages

IMPACT

1

4 3

2

DETAILS OF SYSTEM COMPLEXITY AND MISCONCEPTIONS

The daunting number of organizations and potential routes through the pipeline and a perception of closed-off unions creates an unwelcoming environment

CCE Interviews

32

The Pipelines are Complex and Unique

Difficult for someone entering pipeline to understand most optimal path

Lack of clarity about next steps, timing, costs, requirements

Training organizations’ depictions of pipeline differ from unions’ depictions

Misconceptions Exist About

Unions

Perception that unions are closed off and extremely difficult to enter

Negative experiences with one union affects all construction trades

“Everyone’s got their own special sauce, and they don’t advertise online. They don’t make it accessible to everyone.”

- Government Agency

Constraint Details

1

“Some generalize that all trades are hard to get into, but that’s not true.”

- Government Agency

After being rejected by one union, some prospects assume all will reject them.

Unique recruitment paths that aren’t publicly available hamper access to the trades.

DETAILS OF TRAINING CONSTRAINTS

Training inefficiencies exist that can slow the generation of new journeyworkers

CCE Interviews

33

Constraint Details

8+ Years to Reach Journey

Status

Can take 8+ years to reach journeyworker status in skilled trades

Entering from “off-the-street” is viable path

Individuals that could apply directly to union may instead be enrolling in 4-year pre-apprenticeship programs that delay attainment of journeyworker status by 3 years

Training Prep Not Matching Union Skillset

Trade-specific pre-apprenticeship programs may not tailor programs to match what unions and contractors desire

Experienced Non-Union Transfers Slowed

Unions consistently recruit non-union tradespeople

Knowledge-gap exists for all non-union recruits, due to union training structure it can be years before attaining journeyworker status

Non-union system is highly unorganized with lackluster training opportunities

“They have to swallow their pride a bit.”

- Union Representative

2

General programs are desirable to unions as they teach basic work ethics and stop there

“General training programs are the best.”

- Union Training Representative

Experienced non-union recruits may be in classes with brand new apprentices

DETAILS OF REACTIVE RESPONSES

The delayed response times of unions and training facilities and system losses exacerbate the labor shortages

CCE Interviews

34

Poor Contractor Forecasting and

Reactive Response

Training facilities and unions adjust recruiting based on contractor forecasts

Contractor forecasting is limited to single project planning and does not predict system-wide shortages

Unions likely prefer an undersupply situation to an oversupply one

Constraint Details

Losing People

Apprentices leaving during winter months due to financial troubles during slow winter month

Skilled tradespeople leaving for attractive alternatives: Dakotas, other industries, other trades

“Tradespeople are moving to take more reliable work in oil and gas in places like North Dakota.”

- Union Representative

3

DETAILS OF LOSING PEOPLE 4

Constraint Details

PART V: FACTORS AFFECTING MINORITY AND FEMALE PARTICIPATION

CONSTRAINTS ON MINORITY PARTICIPATION IN CONSTRUCTION

Minority participation is limited by factors that affect other newcomers – but to a much greater degree than for whites

CCE Interviews.

36

EDUCATION AWARENESS HIRING STAFFING

Minority youth do not think of construction careers because they see so few minority construction workers

Educational disparities – like the lower literacy and graduation rates documented in Mind the Gap – make minorities less prepared for craft work

Unique hiring processes for each craft that often are not publicly documented can be confusing and can discourage minorities from exploring construction

There is a perception that decisions are sometimes made based on social connections, and that minorities may have less extensive social networks in largely white trades

“We have kids who can’t read a ruler.”

- Union

“Children in communities of color don’t have construction workers to look up to.”

- Training Organization

“Everyone’s got their own special sauce, and they don’t advertise online.”

- Government Agency

According to a contractor, the fact that hiring and staffing criteria could be made more transparent, but that contractors and unions have not on the whole done so, suggests that there is an exclusionary intent behind this opacity

STAKEHOLDER PERCEPTIONS OF WOMEN’S INVOLVEMENT

Some stakeholders see little hope for increasing participation by women, but there are others who are more optimistic


37

Culture For established male construction workers, working along side women may be new and uncomfortable

Attitude Women who make it into skilled trades can perform very well

Frustration There is a perception that getting more women into the construction industry is extremely challenging. In some cases, stakeholders even seemed to feel the problem was intractable and beyond their ability to influence

Limitations Bright Spots

“Women are more patient, and they work harder, too.”

-Contractor

“There is a big cultural shock – women and minorities in the construction workforce is something very new.”

-Training Organization

“The hardest group to target is women.”

-Union

Engagement There are training programs that specifically target women, and according to one training program, they intend to start another

MDHR EEO Benchmark

6% Success Women’s participation in the painters already exceeds the project-level MDHR EEO target of 6%

7.3%

PART VI: RECOMMENDED NEXT STEPS

SCOPE AND FINDINGS

39






pipelines



SCOPE AND FINDINGS

40






pipelines



OVERVIEW OF NEXT STEPS

41

Find a forecast owner

Apply and enhance the model

Improve talent pipeline flow

Consider stakeholder feedback on where to house the forecast

Evaluate potential forecast owners

Align decisionmaking capacity

Attract more candidates

Help candidates navigate the pipeline

Better align training with needs

Reduce apprenticeship attrition

Engage stakeholders through forecasts

Enhance the forecasting model

STAKEHOLDER FEEDBACK ON FORECAST OWNERSHIP

While stakeholders saw government agencies as a natural home for future forecasts, they also shared concerns about housing them in the public sector

CCE Interviews.

42

Everyone wants objective, trustworthy information

Some stakeholders thought a state agency is already forecasting

Unions and contractors saw connections to existing state work

State agencies had concerns about performing the forecasting

Stakeholders were concerned that a state-run forecast could be cut

MOST CRITICAL TO CONSIDER LEAST CRITICAL TO CONSIDER

Some agencies are still using paper forms to collect and analyze data:

“We’re in the Stone Age.” - Government Agency

In particular, concerns that data might be manipulated for political purposes

Government agencies concerned about staff capacity and technical capabilities

Concern that the forecasts could be started within state agency, but later stopped for political reasons (e.g., forecasts seen as tool to bolster unions)

Misunderstanding of DEED, MDHR, and DOLI work, but reflects stakeholder expectations that state provide data that will benefit everyone

Unions and contractor already provide workforce data to DOLI, MDHR

Forecasting that involves race and gender triggers concern over additional requirements

POTENTIAL FORECAST OWNERS

There are several organizations that might be effective forecast hosts

43

Organization Advantages Outstanding Questions

Already the trusted source of economic data in MN

CCE’s approach is quite different from DEED’s – would DEED be willing to do this?

Not inherently a multiparty forum – how to build in stakeholder oversight / engagement

Labor-Users-Contractors Council

Includes representatives from unions, contractors, and labor users

How involved are stakeholders? Resourcing? Willingness?

Highly networked through Board connections

Potential synergies with other workforce development activities

Resourcing?

Has relationships with unions and community organizations

Willingness? Resourcing? Not inherently a multiparty forum – how to

build in stakeholder oversight / engagement

Willing to take on forecasting now Has relationships with unions and

community organizations

Not inherently a multiparty forum – how to build in stakeholder oversight / engagement?

A New Organization Can be purpose-built from the ground up Resourcing?

MSPWIN can consider identifying a short-term forecast owner while working on a longer-term solution

STAKEHOLDER ENGAGEMENT OBSTACLES

MSPWIN will need to address several challenges to engage stakeholders effectively on future forecasts and workforce development activities

CCE Interviews.

44

Issue Caution with unproven stakeholders

Conflation of MSPWIN work with MDHR work

Need to employ current supply

Scope Unions Contractors Unions

Unions

Impact Delays or prevents stakeholder engagement

Causes misunderstandings and puts stakeholders on defensive

Limits stakeholder ability and willingness to act

Most unions have so far not been responsive to requests to discuss labor supply issues, with notable exceptions

Unions and contractors intuitively link making forecasts related to demographics with imposing new EEO requirements, which may trigger reluctance to engage or even opposition

Union leaders are under pressure to protect the members they represent. Leadership may be reluctant to engage in new recruiting and training activities when members are currently on the bench

34 Union organizations contacted

12 Union organizations participated

Some unions were skeptical about the intent and impact of labor forecasting until they heard clear explanations:

“How are you going to use this against us?”

- Union

FORECASTING MODEL RECOMMENDATIONS

MSPWIN can maximize the value of the forecasting model by first maintaining and expanding it, and then by enhancing it for even more accurate trade-level analyses

45

Activity Effort Complexity

Generate forecasts using the model

LOW ~1 hour

LOW Follow CCE instructions to use CLMA and model

Ensure model accuracy by adding the most current data as it becomes available

LOW ~10 hours per year

LOW Follow CCE instructions to find and insert updated data

Analyze more of the labor market by Including additional trades

LOW ~20 hours per trade

MODERATE Collect and analyze data from identified sources Copy and extend CCE calculations

Generate very precise trade-level forecasts by refining assumptions about labor mobility and participation in residential segments by trade

MODERATE ~20 hours to start ~10 hours per trade ~20 hours per new

factor

HIGH Get stakeholder buy-in, conduct interviews, analyze results, and refine existing assumptions or develop brand new factors to add to the model

Improve current-state supply estimate by encouraging stakeholders to enter workforce data into CLMA

HIGH ~20 hours to start ~10 hours per trade

HIGH Collaborate with CLMA to develop a stakeholder engagement plan, then follow up to ensure data completeness and integrity

ENHANCE

EXPAND

MAINTAIN

USE

OPTIONS TO ADDRESS PIPELINE CONSTRAINTS

CCE has identified a number of options to address pipeline constraints

46

Training Constraints System Complexity

and Misconceptions Reactive Responses Losing People

Better align training with needs

Perform curriculum reviews to align goals with union skillsets

Explore “fast-track” union training for experienced non-union recruits

Help candidates navigate the pipeline

Complete pipeline descriptions for trades

Create assessments to help individuals chart most efficient path through pipelines

Educate career advisors on pipelines and requirements

Align capacity decisionmaking

Encourage and support use of forecast results

Develop shared definition of “shortage” with all stakeholders

Reduce apprenticeship attrition

Form partnerships with countercyclical industries, temp agencies

Offer levelized paychecks, budget planning, and alternative employment

Attract more candidates Understand what motivates people to choose the non-union path

Co-market construction trades to youth. Particularly to youth of color and women

CONSTRAINTS

OPTIONS

1 2 3 4

FINDINGS

47






pipelines



Work with CLMA, unions, contractors, training organizations, and labor users to apply and enhance the forecast model and pipeline descriptions

CCE would like to thank the following people for their exceptional contributions to this project

48

Alex Tittle Brian Stamper

Dave Senf Harry Melander

Johnnie Burns Sarah Gisser

George Garnett

Anne-Marie Kuiper, Ph.D.

Bryan Lindsley

And a special thanks to

APPENDIX: POTENTIAL NEXT STEPS FOR RESEARCH

POTENTIAL NEXT STEPS FOR FUTURE ANALYSIS

CCE has identified additional research that could enhance MSPWIN’s ability to coordinate informed action, but it requires significant preparation

50

Question Impact Prerequisites

How far in advance of shortages must interventions occur?

Persuade stakeholders to act before shortages are apparent

Prioritize and sequence MSPWIN and partner activities

Identify specific trades to research Secure formal support and involvement from at

least one pre-apprenticeship program and union for each trade

At what points are workers falling out of the talent pipeline? How many workers exit at these points?

Identify system-level opportunities and challenges

Align stakeholders around a shared understanding of the pipeline

Prioritize interventions according to their anticipated scale of impact

Identify specific trades to research Define the most appropriate geography based

on trade characteristics Identify all relevant training organizations and

unions – and at least some nonunion employers Secure formal support and involvement from

all pre-apprenticeship programs and unions for each trade and from some nonunion employers

APPENDIX: CCE FORECASTING APPROACH

CCE FORECAST MODEL DATA SOURCES

CCE evaluated several public data sources and decided to use a combination of OES and DEED projection statistics in the supply forecasting model

52

Data Source What is it? Is it used for forecasting?

Can CCE use it? (Why)

BLS/DEED Employment Projections

Biannual forecasts of industry and occupational employment for the next 10 years (latest data 2012-2022)

Employment is defined as the total number of jobs in a specific occupation

Projected employment numbers are a combination of expected growth in the occupation and the replacement needs due to attrition

MnSCU does demand planning based on these numbers Labor market consulting firms (EMSI, CLMA) use projection numbers as a base for their detailed models

YES (Employment

projections are broken down by

occupation type to allow the needed specificity for the

model)

Occupational Employment Statistics (OES)

Yearly employment numbers of specific occupations (latest year – 2013)

Employment is defined as the total number of jobs in an occupation (excludes self employed personnel)

Labor market consulting firms (EMSI, CLMA) use OES numbers in combination with BLS projections in their models

YES (Employment numbers by

occupation type)

Quarterly Census of Employment and Wages (QCEW)

Quarterly employment numbers and wage rates in specific industries

Labor market consulting firms (EMSI, CLMA) use QCEW numbers to estimate fluctuation in industrial wages

NO (Employment not disaggregated by

occupation)

CCE combined BLS projections with latest OES numbers to build the supply forecasting model

CCE SOLUTIONS TO DATA LIMITATIONS

CCE validated the sources with various experts and devised workarounds for data shortcomings

53

What did we hear? Source Importance CCE Solution

BLS employment projections forecast labor demand rather than supply

Todd Olin MET Council

HIGH The model will augment the employment projection numbers by factoring in unemployment for specific trades The projected numbers will depict employed + unemployed to give an estimate of the total labor supply

BLS employment projections should not be used to forecast trade shortages

BLS/DEED HIGH Implicitly assumes that employment projections will be combined with some other data to get shortages However the model will not estimate shortages by calculating the difference between projected employment and census workforce data as these are two statistically different data sets Instead CCE will factor in frictional unemployment rates to get the total labor supply from the employment projections data only

Employment projections overestimate the number of employed people as some hold multiple jobs

BLS/DEED LOW The model will use an estimated multiple job holding rate to trim projections

BLS projection numbers are dated (current forecast 2012-2022)

MSPWIN LOW The model extrapolates latest OES data (2013) by using the CAGR for the employment projections

“The BLS numbers represent labor demand but they can be used for figuring out rough labor

supply by making these assumptions” Todd Graham (Forecaster, MET Council)

What did the experts say about CCE solutions?

“The BLS projections can be used for labor supply forecasting with your modifications.”

Prof. Aaron Sojourner (Labor Economist)

TRADE MOBILITY

Some trades are more mobile than others, so the labor market they participate in covers a larger geographic area

54

Trade How far will workers

travel to a job?

Boilermakers 150

Carpenters 150

Concrete Finishers 150

Electricians 50

Ironworkers 150

Laborers 150

Operating Engineers 150

Painters 50

Pipefitters 100

OCCUPATION MAPPING

CCE aligned CLMA occupations with SOCs to compare demand and supply estimates

55

Include? CCE Target CLMA Definition SOC Codes

Yes Boilermakers

Boilermaker 47-2011 Boilermakers

Yes Boilermaker Welder None

Yes

Carpenters

Carpenter (Finishing) None

Yes Carpenter (Floor Covering Installer)

47-2042 Floor Layers, Except Carpet, Wood, and Hard Tiles

Yes 47-2041 Carpet Installers

Yes Carpenter (Interior Systems) 47-2081 Drywall and Ceiling Tile Installers

Yes Carpenter (Lather) None

Yes Carpenter (Pile Driver / Operator) 47-2072 Pile-Driver Operators

Yes Carpenter (Scaffold Builder) None

Yes Carpenters (All Unspecified) 47-2031 Carpenters

Yes Concrete Finishers Concrete Finisher / Cement Mason 47-2051 Cement Masons and Concrete Finishers

Yes Electricians Electrician 472111 Electricians

Yes Ironworkers

Ironworker - Reinforcing 47-2171 Reinforcing Iron and Rebar Workers

Yes Ironworker / Welder - Structural 47-2221 Structural Iron and Steel Workers

Yes Laborers Laborer 47-2061 Construction Laborers

Yes

Operating Engineers

Operator (Driller and Blaster) 47-5021 Earth Drillers, Except Oil and Gas

Yes Operator (Heavy Crane) 53-7021 Crane and Tower Operators

Yes Operator (Heavy Equipment Mechanic)

49-3042 Mobile Heavy Equipment Mechanics, Except Engines

Yes 49-3031 Bus and Truck Mechanics and Diesel Engine Specialists

Yes Operator (Heavy Equipment) 47-2073 Operating Engineers and Other Construction Equipment Operators

No Operator (Material Handlers) IGNORE

No Operator (Rotary Driller Oil & Gas) IGNORE

No Operator (Truck Driver) IGNORE

Yes Painters Painter 47-2141 Painters, Construction and Maintenance

Yes

Pipefitters

Pipefitter

47-2152 Plumbers, Pipefitters, and Steamfitters Yes Plumber

Yes Pipefitter (Sprinkler Systems)

Yes Pipefitter / Combo Welder None

PUBLICLY-FUNDED INDUSTRY TYPES

CCE identified 20 industry types likely to be publicly-funded

56

Airport Runways & Taxiways Bridge (Multi-Span) Bridge (Single Span) Capitols / Court Houses / City Halls Dormitories (1-4 Floors) Lighting - Roadways & Airports Parks & Playgrounds Roadways (DOT Resurfacing) Roadways (DOT Widening) Roadways (DOT with Bridges) Roadways (Municipal) Roadways (Signs & Guardrails) Schools Sewage Treatment Facility (City) Sewage Treatment Facility (Municipal) Sewer Line Replacement / Upgrade Stadiums & Sport Arenas Transit Terminals Water Line Replacement / Upgrade Water Treatment Facility

PRIVATE INDUSTRY TYPES

The remaining CLMA industry types are not likely to be publicly funded

57

Manufacturing - Apparel / Clothing Electric Power Generation (Fossil)

(Environmental) Manufacturing - Beverage Products, Electric Power Generation (Fossil) (New

Generation) Refinery (Outage / Non-Major Turnaround) Chemical Manufacturing - Computer and Electronic

Products Electric Power Generation (General) Electric Power Generation (Fossil) Electric Power Generation (Hydro) Electric Power Generation (Nuclear) Electric Power Generation (Solar) Electric Power Generation (Wind) Manufacturing - Petroleum and Coal

Products Manufacturing - Plastics and Rubber

Products Electric Power Transmission, Control, and

Distribution Water, Sewage and Other Systems Process (Other) Refinery Manufacturing – Paper Manufacturing – Miscellaneous Manufacturing - Tobacco Products Manufacturing - Primary Metals Manufacturing – Food Manufacturing - Fabricated Metal Products Manufacturing - Leather and Allied Products

Manufacturing - Medical Devices Manufacturing - Furniture and Related

Products Maritime / Shipping Manufacturing - Machinery and Equipment Manufacturing - Nonmetallic Mineral

Products Natural Gas (Mid-Stream) Transmission &

Distribution Steam and Air-Conditioning Supply Textile Mills Printing and Related Support Activities Manufacturing - Pharmaceutical Products Shipbuilding Refinery (Major Turnaround) Natural Gas (Mid-Stream) Compressor

Stations/Pads Manufacturing - Wood Products Other / Misc Natural Gas (Down-Stream) Refinery,

Terminal Textile Product Mills Natural Gas (Up-Stream) Wellpads, Water

Impoundment, Roads Natural Gas (Mid-Stream) Drilling, Fracking Manufacturing - Transportation Equipment

Manufacturing - Electrical Equipment, Appliances, and Components

Auto Sales & Service Facilities Funeral Homes Hospital (5+ Floors) Hotels/Motels (1-4 Floors)

Landscaping Lighting - Athletic Fields Lodges & Clubs Medical Office Building (1-4 Floors with TI) Medical Office Building (1-4 Floors without

TI) Medical Office Building (TI only) Mobile Home Parks

Nursing Homes Office Building HR (5+ Floors, TI only) Office Building HR (5+ Floors, with 80% Pre-

Lease TI) Office Building HR (5+ Floors, without TI) Office Building LR (1-4 Floors, TI only) Office Building LR (1-4 Floors, with TI) Office Building LR (1-4 Floors, without TI) Parking Lots (Surface) Parking Structure Railroads Retail (TI only) Retail (without TI) Shopping Centers (without TI) Swimming Pools Tanks (Oil / Other) Towers (Radio/TV) Transmission Lines (Communications) Transmission Lines (Power) Warehouse Distribution Facility (TI only) Warehouse Distribution Facility (without TI) Worship Facilities

APPENDIX: ASSESSMENT OF THIRD-PARTY DATA SOURCES AND FORECASTS

THIRD PARTY FORECASTS AND DATA SOURCES

CCE reviewed three off-the-shelf forecasting models and eleven sources of construction industry data

59

Forecasting Models Substitutes for CCE Model

Construction Labor Market Analyzer FMI Craft Labor Assessment EMSI Assessment

Data Sources Sources to which CCE was referred

Industrial Labor Market Forecast Dodge ― Metropolitan Construction

Insight Dodge ― MarketLook Dodge ― Construction Market Forecast

Service REED ― Construction Forecast REED ― Expansion Index REED ― Building Starts BLS ― JOLT Survey Wanted Analytics

CONSTRUCTION LABOR MARKET ANALYZER ASSESSMENT

The Construction Labor Market Analyzer is the existing forecasting tool that comes closest to meeting MSPWIN’s needs

“Construction Labor Market Analyzer.” Construction Users Roundtable. 3 Mar. 2014. Web.

60

OVERALL

ZIP Code, MSA*, County, State, Nation

Forecasts 5 years out and some data up to 8 years out

SUPPLY

No supply forecast

DEMAND

Forecasts project level demand (*At highest subscription level)

Does not meet requirements at all

Exceeds requirements

METHODOLOGY

DEMAND Industrial project data from project owners Non-industrial project data from McGraw-Hill

Construction forecasts Project data converted to craft labor demands by Project

Labor Forecaster Benchmarked against the Bureau of Labor Statistics

database for accuracy SUPPLY No supply-side forecasting currently CLMA plans to integrate market-based supply

information based on project payrolls and union rosters

FMI CRAFT LABOR STUDY ASSESSMENT

FMI can conduct a craft labor study that would forecast the next 3-5 years for ~$75,000-$125,000 and would take 3-6 months

“Craft Labor Studies.” FMI. Web. 14 Mar. 2014.

61

OVERALL

Specific to 7-county metro area

Forecast is yearly (e.g., 2015, 2016, 2017 – not quarterly)

SUPPLY

Disaggregates supply by trade

Disaggregates supply by minority status and gender – and also looks at availability of MBEs, WBEs, etc.

DEMAND

Identifies publicly-funded projects

Can forecast specific projects, but as part of the larger analysis, not a la carte

METHODOLOGY

DEMAND Estimates volume of work currently in process and

conduct an extensive analysis of work pending through public and private sources.

Uses labor multiplier approach (with consideration for project type, degree of mechanical complexity, etc.) to translate spend to labor demand.

SUPPLY Uses BLS estimates and interviews with unions about

their apprenticeship programs.



EMSI ASSESSMENT

EMSI forecasts employment to 2023 and aggregates historical employment and educational pipeline data for $12,500 / year

“Analyst.” Economic Modeling Specialists Intl. Web. 25 Mar. 2014.

62

OVERALL

Not seven-county metro; metropolitan statistical area

Forecast is monthly

SUPPLY

Disaggregates supply by trade, including historical output for credit-granting training programs

Disaggregates supply by gender, but not by minority status

DEMAND

Does not forecast aggregate demand

Cannot estimate demand for specific projects

METHODOLOGY

DEMAND Does not forecast demand. SUPPLY Creates forecasts by combining data from 90+ federal,

state, and private sources.



PRODUCT LIMITATIONS

Industrial Labor Market Forecast Forecasts monthly demand and supply for 11 trades in the heavy industry and process sector. ~$10,000-$15,000

Doesn’t include public or commercial sector forecasts – only heavy industry

Doesn’t include trades expected to experience shortages outside heavy industry

Would need to discuss nondisclosure agreement that might limit how MSPWIN shares findings based on IIR data

Scope is too narrow to be useful

Dodge ― Metropolitan Construction Insight Five-year forecasts of construction spending in an MSA by segment (e.g., retail, office, education, other nonresidential, multifamily). $500

Is not a comprehensive forecast of all construction activity Demand is forecast in dollars, not labor needs No supply forecast

Does not forecast the complete universe of relevant construction, and must be translated into labor demand

Dodge ― MarketLook Provides one-year forecasts of construction spending within specific MSAs. $400

Only 1 year of forecast Forecast is construction spending ― must be translated to labor

demand No supply forecast Not 7-county metro area

Not suitable for MSPWIN purposes

Dodge ― Construction Market Forecast Service Five-year forecasts of construction spending in each of 9 U.S. regions by structure type (e.g., commercial warehouses, highways and bridges). $1900 per structure type

Describing total market requires purchasing all structure types ($32,300)

Forecast is construction spending – must be translated to labor demand

No supply forecast Forecast is made at regional level (e.g., New England, Pacific NW)

Not suitable for MSPWIN purposes

ASSESSMENT OF EXISTING FORECASTS AND DATA SOURCES

"Industrial Labor Market Forecast." IIR Analytic Products. Web. 12 Mar. 2014. Kirkeby, Scott. Industrial Info Resources. Personal Interview. 27 Mar. 2014. "Metropolitan Construction Insights." Dodge Market Research - Industry Forecasts. Web. 12 Mar. 2014. Simonsen, Jamie. MnSCU. Personal Interview. 4 Apr. 2014.

63


“Market Intelligence.” REED Construction Data. Web. 22 Mar. 2014.

64

PRODUCT LIMITATIONS

REED ― Construction Forecast MSA-level historical and forecast data of Construction starts adjusted using local market drivers. Cost Unknown

Only shows 3 years of historical data and forecasts 3 years out (by quarter).

Outputs are aggregate dollar values and square footages.

Does not provide information about labor demand for construction projects

REED ― Expansion Index 12 to 18 month estimates of construction industry growth/shrinkage by MSA, updated monthly. $199

Data only reflects commercial non-residential construction projects (vertical); horizontal data is left out.

Provides a single ratio measure of growth; no labor estimates.

Only describes relative changes in construction activity, not absolute levels

REED ― Building Starts Current and historical data monthly construction activity statistics measured in square footage and $ value. $499

Provides only historical data from the past three years. Provides only US data. Demand is measured in dollar values and square footage ― no

mention of labor needs.

Only provides historical demand data for the US; no labor data

PRODUCT LIMITATIONS

JOLT Survey Bureau of Labor Statistics Survey that produces data on job openings, hires, and separations by industry. $0

• Only provides national data. • Does not break down data by trade. • Does not break down data by gender or race.

Only provides industry level employment openings, hires, and separations

Wanted Analytics Aggregation and analysis of online job postings, including skills and certifications needed. $12,000

Is not a forecast – only provides historical data

Does not forecast supply, cannot be integrated into supply forecast


“Construction Analytics.” Wanted Analytics. Web. 12 Mar. 2014. “Job Openings and Labor Turnover Survey.” Bureau of Labor Statistics. Web.16 Mar. 2014.

65

APPENDIX: DETAILED WORKFORCE FORECASTS BY TRADE

SUPPLY AND DEMAND FORECAST (FTE’S)

Boilermakers

67

SENSITIVITY TESTING

Scenarios Description

Last Year 2013 unemployment rate used for future

projections

Post Crash Average of 2008 – 2013 unemployment

rates used for projections

Historical Average of 2003 -2013 unemployment


Results Sensitized Variables

No Shortage

Shortage

Scenario Rates

Last Year Historical Post Crash

12.0% 7.2% 14.0%

Demand (% of supply)


Carpenters

68

SENSITIVITY TESTING



projections






No Shortage

Shortage

Scenario Rates


15.2% 9.2% 17.8%



Concrete Finishers

69

SENSITIVITY TESTING



projections






No Shortage

Shortage

Scenario Rates


19.4% 11.7% 22.7%



Electricians

70

SENSITIVITY TESTING



projections






No Shortage

Shortage

Scenario Rates


11.2% 6.7% 13.1%



Ironworkers

71

SENSITIVITY TESTING



projections






No Shortage

Shortage

Scenario Rates


- - -



Laborers

72

SENSITIVITY TESTING



projections






No Shortage

Shortage

Scenario Rates


19.9% 12.0% 23.3%



Operating Engineers

73

SENSITIVITY TESTING



projections






No Shortage

Shortage

Scenario Rates


- - -



Painters

74

SENSITIVITY TESTING



projections






No Shortage

Shortage

Scenario Rates


14.6% 8.8% 17.1%



Pipefitters

75

SENSITIVITY TESTING



projections






No Shortage

Shortage

Scenario Rates


10.2% 6.1% 11.9%


APPENDIX: SOURCES CONSULTED

Sources consulted

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“Affirmative Action Statistics Data Packet: Minneapolis-St. Paul Metropolitan Statistical Area.” Minnesota.gov. Minnesota Department of Employment and Economic Development. 12 Mar. 2014. Web.

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“Analyst.” Economic Modeling Specialists Intl. Web. 25 Mar. 2014.

Anoka Technical College. Anokatech.edu. Web. 14 Mar. 2014.

“Another Strong Month for Minnesota Jobs.” Minnesota.gov. Department of Employment and Economic Development, 23 Jan. 2014. Web.

Bernstein, Harvey M. “Construction Industry Workforce Shortages: Role of Certification, Training, and Green Jobs in Filling the Gaps.” McGraw-Hill Construction, 2012.

“Best Construction Jobs.” Usnews.com. U.S. News Money: Careers. 20 Apr. 2014. Web.

“Better Futures Minnesota.” Betterfutureenterprises.com. Better Future Enterprises, 2012. Web. 20 Apr. 2014.

“Building Minnesota’s Workforce Through Apprenticeship.” Minnesota.gov. Department of Labor and Industry. 20 Apr 2014. Web.

“Construction Analytics.” Wanted Analytics. Web. 12 Mar. 2014.

“Construction Labor Market Analyzer.” Construction Users Roundtable. 3 Mar. 2014. Web.

“Construction Projects Monitored by the Department.” Minnesota.gov. Minnesota Department of Human Rights. 10 Mar. 2014. Web.

“Construction Spending.” Census.gov. United States Census Bureau, Web. 4 Apr. 2014.

"Construction Workforce: Building Comprehensive labor Market Information.“ Curt.org. Construction Workforce Development Center, November, 2009. Web.

“Craft Labor Studies.” FMI. Web. 14 Mar. 2014.

Dakota County Technical College. Dctc.edu. Web. 21 Mar. 2014.

Dohm, Arlene. “Gauging the Labor Force Effects of Retiring Baby Boomers.” Bls.gov. Monthly Labor Review, Bureau of Labor Statistics, July 2000. Report.

“Downtown Atlanta Construction Workforce Consortium.” Cefga.org. CEFGA, 11 Dec. 2013.

7

7

Sources consulted

Dunwoody College of Technology. Dunwoody.edu. 9 Mar. 2014. Web.

“Employment Outlook.” Minnesota.gov. Department of Employment and Economic Development, 2012. Web.

"Future Jobs in Construction." Minnesota.gov. Department of Employment and Economic Development, 6 Feb. 2014. Web. 14 Feb. 2014.

Hennepin Technical College. Hennepintech.edu. 24 Apr. 2014. Web.

Hill, Arthur V. “Delphi forecasting.” The Encyclopedia of Operations Management: A Field Manual and Glossary of Operations Management Terms and Concepts. Upper Saddle River, NJ: FT, 2010. Print.

"Industrial Labor Market Forecast." IIR Analytic Products. Web. 12 Mar. 2014.

“Job Openings and Labor Turnover Survey.” Bureau of Labor Statistics. Web.16 Mar. 2014.

Kuiper, Anne-Marie. “TC3: Twin Cities Construction Consortium .” Summit Academy, OIC, 2013. Report.

“Labor Force Projections, 2010-2045.” State.mn.us. Minnesota Demographic Center, 2013. Web.

"Labor Supply/Demand Analyses Methodology." Hatrak.com. Hatrak Associates, 2012. Web.

“Market Intelligence.” REED Construction Data. Web. 22 Mar. 2014.

“Merit Shop Training Data.” Workforceunderconstruction.com. Associated Builders and Contractors, July 2010. Web.

“The MetLife Survey of the American Teacher: preparing Students for College and Careers.” Harris Interactive, May 2011.

"Metropolitan Construction Insights." Dodge Market Research - Industry Forecasts. Web. 12 Mar. 2014.

Minneapolis Community and Technical College. Minneapolis.edu. 16 Apr. 2014. Web.

Minneapolis Urban League. Mul.org. 7 Apr. 2014. Web.

“Minnesota’s 2014 Construction Industry Conference.” Minnesota.gov. Department of Labor and Industry, 6 Feb. 2014. Web.

“Minnesota Index.” Minnesota.gov. Department of Employment and Economic Development, May 2010. Web.

“Minnesota Population Projections by Race and Ethnicity, 2005 to 2035.” State.mn.us. Minnesota Demographic Center, 2009. Web.

“Minnesota Population Projections by Race and Hispanic Origin, 2005 to 2035: Region 11: Twin Cities Area.” State.mn.us. Minnesota Demographic Center. 20 Apr. 2014. Web.

7

8

Sources consulted

79

“Minnesota Workforce Industry.” Minnesota.gov. Department of Employment and Economic Development, 2012. Web.

"New Stadium Q&A." Minnesota Vikings. 27 Jan. 2014. Web. 8 Mar. 2014.

Norman, Ravi. “The Construction Exchange.” 2013. Print.

“Recovery: Job Growth and Education Requirements through 2020.” Georgetown Public Policy Institute, June 2013.

Saint Paul College. Saintpaul.edu. 16 Apr. 2014

“Seventy-Four Percent of Construction Firms Report Having Trouble Finding Qualified Workers.” Agc.org. Associated General Contractors, 4 Sept. 2013. Web.

”Stock-Flow Model for Forecasting Labor Supply.” J. Constr. Eng. Manage., 138(6), 707–715.Technical Papers Twin Cities construction industry ramps up hiring efforts, Minneapolis Star Tribune, April 4, 2013.

Summit Academy OIC. Saoic.org. 16 Feb. 2014.

“Where the Jobs Are.” Usatoday.com. Moody’s Analytics, 2013. Web.

Wong, Ming-wah James. “Forecasting Manpower Demand in the Construction Industry of Hong Kong.” The Hong Kong Polytechnic University, 2006.

“Worker Shortage Survey.” Agc.org. Associated General Contractors, 4 Sept. 2013. Web.

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