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
CCE Analysis. CCE Interviews.
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
AVERAGE SURPLUS: 6,026 FTE’S
AVERAGE SURPLUS: 1,792 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
AVERAGE SHORTAGE: 4,158 FTE’S
SHORTAGE
AVERAGE SHORTAGE: 1,065 FTE’S
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
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
Ironworkers, boilermakers, pipefitters, operating engineers, painters, and carpenters are all likely to experience labor shortages, though data is mixed in some cases
SCOPE AND FINDINGS
27
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
Ironworkers, boilermakers, pipefitters, operating engineers, painters, and carpenters are all likely to experience labor shortages, though data is mixed in some cases
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
CCE Analysis. CCE Interviews.
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
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
Ironworkers, boilermakers, pipefitters, operating engineers, painters, and carpenters are all likely to experience labor shortages, though data is mixed in some cases
The complexity and opacity of the pipelines may delay the generation of new journeyworkers and discourage newcomers – especially minorities and women
SCOPE AND FINDINGS
40
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
Ironworkers, boilermakers, pipefitters, operating engineers, painters, and carpenters are all likely to experience labor shortages, though data is mixed in some cases
The complexity and opacity of the pipelines may delay the generation of new journeyworkers and discourage newcomers – especially minorities and women
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
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
Ironworkers, boilermakers, pipefitters, operating engineers, painters, and carpenters are all likely to experience labor shortages, though data is mixed in some cases
The complexity and opacity of the pipelines may delay the generation of new journeyworkers and discourage newcomers – especially minorities and women
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.
Does not meet requirements at all
Exceeds requirements
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.
Does not meet requirements at all
Exceeds requirements
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
ASSESSMENT OF EXISTING FORECASTS AND DATA SOURCES
“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
ASSESSMENT OF EXISTING FORECASTS AND DATA SOURCES
“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
rates used for projections
Results Sensitized Variables
No Shortage
Shortage
Scenario Rates
Last Year Historical Post Crash
12.0% 7.2% 14.0%
Demand (% of supply)
SUPPLY AND DEMAND FORECAST (FTE’S)
Carpenters
68
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
rates used for projections
Results Sensitized Variables
No Shortage
Shortage
Scenario Rates
Last Year Historical Post Crash
15.2% 9.2% 17.8%
Demand (% of supply)
SUPPLY AND DEMAND FORECAST (FTE’S)
Concrete Finishers
69
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
rates used for projections
Results Sensitized Variables
No Shortage
Shortage
Scenario Rates
Last Year Historical Post Crash
19.4% 11.7% 22.7%
Demand (% of supply)
SUPPLY AND DEMAND FORECAST (FTE’S)
Electricians
70
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
rates used for projections
Results Sensitized Variables
No Shortage
Shortage
Scenario Rates
Last Year Historical Post Crash
11.2% 6.7% 13.1%
Demand (% of supply)
SUPPLY AND DEMAND FORECAST (FTE’S)
Ironworkers
71
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
rates used for projections
Results Sensitized Variables
No Shortage
Shortage
Scenario Rates
Last Year Historical Post Crash
- - -
Demand (% of supply)
SUPPLY AND DEMAND FORECAST (FTE’S)
Laborers
72
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
rates used for projections
Results Sensitized Variables
No Shortage
Shortage
Scenario Rates
Last Year Historical Post Crash
19.9% 12.0% 23.3%
Demand (% of supply)
SUPPLY AND DEMAND FORECAST (FTE’S)
Operating Engineers
73
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
rates used for projections
Results Sensitized Variables
No Shortage
Shortage
Scenario Rates
Last Year Historical Post Crash
- - -
Demand (% of supply)
SUPPLY AND DEMAND FORECAST (FTE’S)
Painters
74
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
rates used for projections
Results Sensitized Variables
No Shortage
Shortage
Scenario Rates
Last Year Historical Post Crash
14.6% 8.8% 17.1%
Demand (% of supply)
SUPPLY AND DEMAND FORECAST (FTE’S)
Pipefitters
75
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
rates used for projections
Results Sensitized Variables
No Shortage
Shortage
Scenario Rates
Last Year Historical Post Crash
10.2% 6.1% 11.9%
Demand (% of supply)
APPENDIX: SOURCES CONSULTED
Sources consulted
“2030 Transportation Policy Plan.” Metropolitan Council, 2013. Report.
“Affirmative Action Statistics Data Packet: Minneapolis-St. Paul Metropolitan Statistical Area.” Minnesota.gov. Minnesota Department of Employment and Economic Development. 12 Mar. 2014. Web.
“American Community Survey.” Census.gov. U.S. Census Bureau, 2014. Web. 25 April 2014.
“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.