regional business profiling and innovation networking project final report

Regional Business Profiling and Innovation Networking Project

Prepared for

North Central Regional Planning Commission

Prepared by

Advanced Manufacturing Institute

510 McCall Rd. Manhattan, Kansas 66502-5034

785.532.7044

2013

Assets Mapping Report 2013 Northcentral Kansas

2

Contents

CONTENTS ......................................................................................................................................... 2

PROJECT INTRODUCTION ................................................................................................................... 5

OBJECTIVES .......................................................................................................................................... 5

GEOGRAPHIC AREA ................................................................................................................................. 5

DATA USED ........................................................................................................................................... 6

PART I: REGIONAL OVERVIEW ............................................................................................................ 7

EDUCATIONAL ATTAINMENT (2012) .................................................................................................................... 8

AGE (2012) ..................................................................................................................................................... 9

RACE (2012) .................................................................................................................................................. 11

COMMUTE ..................................................................................................................................................... 11

INFRASTRUCTURE ............................................................................................................................................ 15

GROSS REGIONAL PRODUCT (GRP) .................................................................................................................... 16

REGION IMPORTS ............................................................................................................................................ 17

REGION EXPORTS ............................................................................................................................................ 18

JOBS .............................................................................................................................................................. 19

TOP EMPLOYERS.............................................................................................................................................. 21

GROWING/DECLINING OCCUPATIONS ................................................................................................................. 21

GROWING/DECLINING INDUSTRIES ..................................................................................................................... 23

AVERAGE EARNINGS BY INDUSTRY ...................................................................................................................... 24

REGIONAL KNOWLEDGE LOCATION QUOTIENT ..................................................................................................... 24

REGIONAL SKILLS LOCATION QUOTIENT ............................................................................................................... 25

REGIONAL PATENTS ......................................................................................................................................... 25

PART II: INDUSTRY OVERVIEW .......................................................................................................... 27

INDUSTRY JOBS .................................................................................................................................... 29

TOTAL JOBS .................................................................................................................................................... 29

STATE & NATIONAL JOBS .................................................................................................................................. 32

JOB CHANGE AND ESTABLISHMENTS .................................................................................................................... 33

SHIFT SHARE ................................................................................................................................................... 34

UNEMPLOYMENT............................................................................................................................................. 36

REGIONAL BUSINESSES ..................................................................................................................................... 37

LOCATION QUOTIENT BY INDUSTRY AND COUNTY ................................................................................................. 39

INDUSTRY WAGES ................................................................................................................................ 40

REGION, STATE, & NATIONAL EARNINGS ............................................................................................................. 40

INDUSTRY CLUSTERS ............................................................................................................................. 41

JOBS, EARNINGS, GROWTH AND ESTABLISHMENTS ................................................................................................ 41

REGIONAL COMPETITIVENESS (SHIFT SHARE) ....................................................................................................... 42

LOCATION QUOTIENT ....................................................................................................................................... 44


3

PART III: OCCUPATION OVERVIEW .................................................................................................... 46

TOTAL JOBS .................................................................................................................................................... 46

JOBS BY OCCUPATION ...................................................................................................................................... 47

OPENINGS ...................................................................................................................................................... 48

SHIFT SHARE ................................................................................................................................................... 49


STATE & NATIONAL JOBS .................................................................................................................................. 53

WAGES BY OCCUPATION ........................................................................................................................ 55

HOURLY WAGE ............................................................................................................................................... 55

PART IV: EDUCATION COMPLETIONS ................................................................................................ 57

INSTITUTION COMPLETIONS .............................................................................................................................. 57

REGIONAL COMPLETIONS .................................................................................................................................. 57

REGIONAL PROGRAMS .......................................................................................................................... 60

TOP TEN REGIONAL COMPLETIONS BY PROGRAM ................................................................................................. 60

TOP TEN REGIONAL OPENINGS BY PROGRAM ....................................................................................................... 61

TOP TEN MEDIAN HOURLY WAGES BY PROGRAM ................................................................................................. 61

TOP TEN REGIONAL JOBS BY PROGRAM ............................................................................................................... 62

REGIONAL JOB GROWTH ................................................................................................................................... 62

REGIONAL HISTORIC COMPLETIONS .......................................................................................................... 63

CAREER CLUSTER DATA REPORT .............................................................................................................. 66

JOBS AND JOBS CHANGE ................................................................................................................................... 66

HOURLY EARNINGS .......................................................................................................................................... 67


OPENINGS ...................................................................................................................................................... 68

RANK CAREER CLUSTERS REPORT ............................................................................................................. 70

CAREER CLUSTERS RANKED BY GROWTH ............................................................................................................. 70

CAREER CLUSTERS RANKED BY LOCATION QUOTIENT ............................................................................................. 71

EDUCATIONAL ATTAINMENT ................................................................................................................... 72

PART V - INNOVATION ASSESSMENT SURVEY ................................................................................... 74

INTRODUCTION .................................................................................................................................... 74

DEMOGRAPHICS .............................................................................................................................. 74

COUNTY OF RESIDENCE..................................................................................................................................... 74

WORKPLACE COUNTY ....................................................................................................................................... 75

ORGANIZATION TYPE........................................................................................................................................ 75

GEOGRAPHIC LIMITS OF ORGANIZATION’S COMMUNITY ........................................................................................ 76

REGION AS DESCRIBED BY THE COMMUNITY ..................................................................................... 77

REGIONAL ENVIRONMENT ................................................................................................................................. 77

DEFINITION OF THE REGION .............................................................................................................................. 77

LOCAL DECISION MAKING ................................................................................................................................. 78

REGIONAL PERFORMANCE ................................................................................................................................. 79

GOVERNMENT PROGRAM AND POLICY ISSUES ...................................................................................................... 88


4

REGIONAL ISSUES AND BUSINESS SUCCESS ........................................................................................................... 89

HOUSING ........................................................................................................................................... 90

HOUSING NEED ............................................................................................................................................... 90

SINGLE/MULTI-FAMILY HOUSING ESTIMATES ...................................................................................................... 90

AVAILABILITY OF QUALITY HOUSING ................................................................................................................... 91

QUALITY OF REGION FOR BUSINESS SUCCESS .............................................................................................. 92

REGIONAL QUALITY PROJECTION ........................................................................................................................ 93

INSTITUTION EVALUATION ................................................................................................................................. 94

MOST SUPPORTIVE INSTITUTIONS TO INNOVATION ............................................................................................... 95

UNIVERSITY AND TECHNICAL SCHOOL CHALLENGES ............................................................................................... 96

REGIONAL NORMS AND ATTITUDES .................................................................................................................... 97

SOCIAL NETWORKS ............................................................................................................................... 98

GROUP FORMALITY .......................................................................................................................................... 98

FORMAL GROUP MEETING PLACES ..................................................................................................................... 99

INFORMAL GROUP MEETING PLACES ................................................................................................................ 100

GROUP MEETING FREQUENCY ......................................................................................................................... 100

GROUPS AND REGIONAL DEVELOPMENT ............................................................................................................ 101

GROUPS AND BUSINESS DEVELOPMENT ............................................................................................................ 101

SOCIAL NETWORK MAPPING .......................................................................................................... 102

RESPONDENTS ANALYSIS ...................................................................................................................... 103

NETWORK MAPS ............................................................................................................................... 109

MEASURE: DEGREE............................................................................................................................. 109

DEGREE CASE 1: ............................................................................................................................................ 110

DEGREE CASE 2: ............................................................................................................................................ 111

DEGREE CASE 3: ............................................................................................................................................ 112

DEGREE CASE 4: ............................................................................................................................................ 113

DEGREE CASE 5: ............................................................................................................................................ 114

DEGREE CASE 6: ............................................................................................................................................ 115

DATA SOURCES AND CALCULATIONS .............................................................................................. 116

STATE DATA SOURCES .................................................................................................................................... 116

GLOSSARY .................................................................................................................................................... 116

CONTACT ....................................................................................................................................... 118

KOIN TEAM ................................................................................................................................................. 118


5

Project Introduction

Innovation is key to sustainable regional growth and development and requires strong participation in

open and collaborative networks. Successful innovation networks often consist of a critical mass of

spontaneously-forming collaborative teams potentially located in different places, but working together

and interacting frequently. Rural regions that may lack this spontaneous critical mass need to

proactively weave inter-linked networks of entrepreneurs, universities, government agencies, banks and

other support institutions.

The North Central Regional Planning Commission (NCRPC) intends to identify, strengthen and utilize

existing/underlying formal and informal networks to foster innovation in the region. This project was

undertaken to help the NCRPC strengthen the region by assisting businesses as they connect and build

regional networks that enhance competitiveness and capabilities. The goal of the project was to

increase the number of globally competitive innovative products and services produced in North Central

Kansas.

Objectives

The project has the following objectives:

1. To develop and pilot a process to profile businesses in the North Central Kansas based on their

needs, capabilities, capacity and innovation readiness as opposed to their industry and

product/service.

2. To create a database of regional assets, businesses profiled and regional resources in an open

system accessible to stakeholders in the region.

3. To create a networking process that can help search for opportunities for collaboration among

companies, regional educational institutions and regional organizations.

4. To leverage lessons learned and insights gained in previous AMI/NCRPC regional pilot projects

and continue to develop and build a regional technology-based economic development strategy.

Geographic area

The geographic area for this project included the following nineteen counties in the region of

Northcentral Kansas.


6

County Areas

Chase, Kansas (20017), Clay, Kansas (20027) Cloud, Kansas (20029) Dickinson, Kansas (20041) Ellsworth, Kansas (20053) Geary, Kansas (20061) Jewell, Kansas (20089) Lincoln, Kansas (20105)

Lyon, Kansas (20111) Marshall, Kansas (20117) Mitchell, Kansas (20123) Morris, Kansas (20127) Ottawa, Kansas (20143) Pottawatomie, Kansas (20149) Republic, Kansas (20157)

Riley, Kansas (20161) Saline, Kansas (20169) Wabaunsee, Kansas (20197) Washington, Kansas (20201)

Data used

This report was prepared using data from the

Economic Modeling Specialists, Inc. (EMSI) and

utilizing their Analyst tool. EMSI uses data from

U.S. Department of Commerce (Bureau of

Economic Analysis, U.S.Census Bureau), U.S.

Department of Labor (Bureau of Labor

Statistics) and U.S. Department of Education,

National Center for Education Statistics and US

Patent data repository at the University of

Nebraska.

This report consists of six parts. Part I of the

report provides an overview of the region. Part

II describes in more detail the region’s industry,

including major industrial clusters, shift share,

jobs and wages. Part III describes the regional

occupations in more details including data

about jobs, education and wages. Part IV of the

report describes in detail the educational

programs in the region including regional

completions, openings, jobs and median wage.

The fifth part of the reports summarizes the

findigns from the regional innovation survey

underatken in the region. The last part of the

report summarizes the findings from the social

network survey undertaken in the region and

the social netwrok maps thus generated.


Prepared by AMI using EMSI data 7

Part I: Regional Overview

This section provides an overview of the region

including information on demographic

characteristics, GRP structure, export and

import balance in the region, job development

and breakdown, top regional employers,

growing and declining occupations and

industries, earnings breakdown as well as

regional knowledge and skills overview.

The Northcentral Kansas region includes 19 of

the 105 counties in the state. The counties in

this region are: Chase, Clay, Cloud, Dickinson,

Ellsworth, Geary, Jewell, Lincoln, Lyon,

Marshall, Mitchell, Morris, Ottawa,

Pottawatomie, Republic, Riley, Saline,

Wabaunsee and Washington. In 2012 the

population of this region was 322,278.

According to 2012 data, the 14,170 square

miles in the region have a population density of

22.7 people per square mile.



Educational Attainment (2012)

The following figure shows the highest level of

education attained by the labor force for the

region.

Figure 1: Educational Attainment (2012)

More than 90% of the labor force participants

have a high school diploma or better and more

than 59% of the labor force have at least some

college experience.

The following map shows spatial distribution of

median earnings per hour over the region.

College degree represents the population with

some college, an Associate’s degree or

Bachelor’s degree. Graduate degree represents

the population with a Graduate degree or

higher. There is a relation between median

earnings and obtained education. The higher

the percentage of college or graduate degree

holders the higher earnings are. Riley, Saline

and Pottawatomie counties have highest

median earnings and highest percentage of

graduate degree over the population, their

percentage of population with college degree is

also significantly higher than average. Also the

rest of the counties with high median earnings

have higher percentage of population with

some degree than regional average.



Age (2012)

The following figure shows the age distribution

of the region.

Figure 2: Age structure (2012)

About 55% of the region is younger than 40

years old.

The following population pyramid graphics

show the spatial variations in the ages of the

population over the counties. Counties Republic

and Jewell have significantly high portions of

population with ages over 70. For men it’s over

8%, for women it’s over 11%, it means that

every fifth person in this region is older than 70

years. This stationary (or sometimes called

regressive) pyramis, reflects increasing

percentage of the old population and

decreasing percentage of the younger

population. On the other hand counties Riley

and Geary represent progressive type of

population pyramid. These counties have higher

portion of the young population and low

portion of the older, which will result in

increase of population in future. In Geary

County every fifth person is younger than 10.

Riley County is unique in that almost one third

of its population is between 21 and 30 years of

age. This is caused by the presence of Kansas

State University in this county.

Other trends visible in the map are relations

between the county population and the type of

population pyramid. Counties with high

population tend to have a progressive type of

pyramid with wider base and triangle shape and

counties with lower

population tend to have

more stationary or

degressive types with a

narrower base.

A third finding is the

distribution of the age by

gender. Men have bigger

representation in the middle

age from 40 to 60 years and

women have bigger

representation in the higher

age groups which is most

likely caused by higher life

expectancy for women.



The following map shows spatial variations in

average family size and median age over the

region. It’s interesting to compare this map to

previous one. Counties with the highest family

size are also more populated counties. Counties

with the highest portion of young population

are also counties with bigger average family

size. These counties also have the lowest

median age.



Race (2012)

The following figure shows the population proportion by race. The region is over 80% White, Non-Hispanic.

Figure 3: Race structure (2012)

Commute

Counties with the most incoming workers are Riley and Geary. These counties also have the most

outcoming workers but this number is significantly lower. This means that these counties have largest

gain of workers over the region. On the other hand Dickinson, Pottawatomie and Wabaunsee have the

highest absolute loss of workers.



The following map shows commuting patterns

in better detail. The chart shows particular

flows of migration between counties as well as

commuter range and number of incoming

commuters. Also, the ratio of inter and outer

county commute is visible in the graph. In all

counties inter-county dominates over outer-

county. It means that most of people work in

the same county as they live. But in some

counties percentage of outer-county commute

reaches 30% (Geary and Pottawatomie

counties). Counties Riley and Saline have the

most commuters. This result corresponds with

previous map.



The following map displays the spatial

distribution of commuters over the region. In

Mitchell county more than 50% of the

population is commuting to work. On the other

hand in Geary county it’s around 40%. Two

thirds of people (67% - almost 100,000) travel

to work less than 20 minutes with the two

maximums between 5-9 and 10-14 minutes

(44% - 65,000). These numbers indicate that it’s

mostly in-city commute. Another small peak is

at 30-34 minutes, this peak probably represents

out-city commute. You can also see spatial

variations in commute length over the counties.

For example in Saline county more than one

third of people commute between 10 and 14

minutes. This contrasts to Wabaunsee and

Ottawa counties, where commute is spreaded

equally with maximum between 30-34 minutes.

This probably means that people are

commuting to work out of city they live.



The following map represents spatial

distribution of commuters over the region with

emphasis on time leaving home to go to work.

33% of workers (48,000) are traveling to work

between 7 and 8. Higher numbers at the earlier

time from midnight to 5 am is probably caused

by the wider definition of time interval. Similar

reasoning can be used for the peaks after noon.



Infrastructure

The next map shows spatial distribution of rails

over the region and the railroad company. Rail

network is pretty dense and covering all region

equally. All county seats beside Washington,

Council Grove and Westmoreland are on the rail

line. Interestingly, Clay Center (Clay County) has

only one connection to the northwest, which

makes transportation to all other directions

more complicated.



Gross Regional Product (GRP)

The GRP is the market value of all final goods

and services produced over a given period of

time. The following table and figure summarize

the region and break it down by industry during

2012.

GRP in $Millions

Earnings 7,799 Property Income 3,706 Taxes on Production 661.8 Total 12,168

Figure 4: Northcentral Kansas GRP (2012)

Government is the largest industry with over $4 billion. Manufacturing is over the $1.25 billion mark.

438.45

172.57

347.99

421.45

1,278.74

445.87

738.33

321.59

238.13

517.93

388.31

280.73

78.53

223.62

67.17

735.73

31.01

262.15

228.82

4,148.98

0 1,000 2,000 3,000 4,000 5,000

Agriculture, Forestry, Fishing and Hunting

Mining, Quarrying, and Oil and Gas Extraction

Utilities

Construction

Manufacturing

Wholesale Trade

Retail Trade

Transportation and Warehousing

Information

Finance and Insurance

Real Estate and Rental and Leasing

Professional, Scientific, and Technical Services

Management of Companies and Enterprises

Administrative and Support and Waste…

Educational Services (Private)

Health Care and Social Assistance

Arts, Entertainment, and Recreation

Accommodation and Food Services

Other Services (except Public Administration)

Government

Northcentral Kansas GRP $Millions (2012)

GRP $Millions



Region Imports

The following table and figure summarize and

breakdown regional imports by industry in

2012.

Imports in $Millions

Imports - 22,640 (77% of Demand) Locally Produced and Consumed - 6,616 (23% of Demand)

Figure 5: Northcentral Kansas Import (2012)

745.51

248.04

258.11

613.76

5,447.88

1,079.67

558.68

705.28

1,044.14

1,279.16

772.78

2,022.89

265.72

442.05

226.45

1,027.16

154.83

371.89

229.72

5,146.57

0 1,000 2,000 3,000 4,000 5,000 6,000


Mining, Quarrying, and Oil and Gas…

Utilities

Construction

Manufacturing

Wholesale Trade

Retail Trade


Information



Professional, Scientific, and Technical…

Management of Companies and…






Other Services (except Public…

Government

Northcentral Kansas Imports (2012)

Imports $millions



The region imports over 75% of its demand,

over $5 billion in both Manufacturing and

Government. Professional, Scientific, and

Technical Services are over $2 billion each. Four

other industries are over $1 billion: Finance and

Insurance, Wholesale Trade, Information, and

Health Care and Social Assistance. On the other

hand Locally Produced & Consumed goods

represent 23% of its demand in Region and 43%

in State.

Region Exports

The following table and figure summarize and

breakdown of regional exports by industry in

2012.

Exports $Millions

Exports 24,682 79% of Supply

Figure 6: Northcentral Kansas Exports (2012)

The region exports 79% of its supply.

Government is the largest export at almost $14

billion. Manufacturing exports about $4.5 billion

and Agriculture, Forestry, Fishing, and Hunting

exports $1.3 billion. This region's export

1,319.95

297.16

354.68

375.70

4,449.54

543.98

512.35

577.78

237.02

497.95

242.69

121.23

106.77

132.89

41.10

594.81

17.25

178.64

204.61

13,876.37

0 5,000 10,000 15,000



Utilities

Construction

Manufacturing

Wholesale Trade

Retail Trade


Information











Government

Northcentral Kansas Exports (2012)

Exports $Millions



represents 79% of supply which is higher than the State's (60%).

Jobs

The following table and figure show the total

number of full and part-time jobs in the region.

Total Jobs in 2012

Total 202,247 Male 53.4% (National Average 52.2%) Female 46.6% (National Average 47.8%)

Figure 7: Northcentral Kansas Total jobs (2002-2012)

The figure shows solid job growth in the region.

The region weathered the financial collapse of

2008 storm well, only experiencing a slight loss

of jobs in 2009. Job growth continued, though

at a slower pace and in 2012, and was at the

highest point in the 10-year period. The region

has added about 19,000 jobs during the 2002-

2012 time frame.

175,000

180,000

185,000

190,000

195,000

200,000

205,000

2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012

Northcentral Kansas Total Jobs (2002-2012)

Total jobs



Figure 8: Northcentral Kansas Jobs 2012

Government supplies over 28% of jobs in the

region. Retail Trade supplies 10% of jobs in the

region and Manufacturing and Health Care and

Social Assistance supply about 8% of jobs.

11,278

1,456

868

9,707

16,850

5,372

20,083

4,800

2,120

7,497

5,629

6,217

995

6,965

2,421

17,964

2,017

12,373

10,153

57,481

0 10,000 20,000 30,000 40,000 50,000 60,000 70,000



Utilities

Construction

Manufacturing

Wholesale Trade

Retail Trade


Information





Administrative and Support and Waste Management…






Government

Northcentral Kansas Jobs 2012

Jobs



Top Employers

The following figure shows the top five businesses with the most employees.

Figure 9: Local Employers (2012)

Two of the top employers are in the food

processing industry (Tony’s Pizza and Tyson

Fresh Meats). The second largest employer is

the university, and the remaining two

employers are hospitals (Mercy Health Center

and Salina Regional Reference Laboratory).

Growing/Declining Occupations

The following graphic shows occupations with

the largest job growth/decline in the time

period from 2002-2012.

Military (9,446), Education, Training, and Library

(1,737), and Business and Financial Operations

(1,523) were the largest growing occupations

while Production (-1,000), Transportation and

Material Moving (-849), and Office and

Administrative Support (-211) lost the most

jobs.

1,750

1,060 961 945 909

0

200

400

600

800

1,000

1,200

1,400

1,600

1,800

2,000

Tony's Pizza Svc. Kansas StateUniversity

Mercy Health Ctr Tyson Fresh Meats Salina RegionalReference

Laboratory, Inc

Local Employers

Local Employees



Figure 10: Growing/Declining Occupations (2002-2012)

2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012

Military 11,158 11,615 11,788 11,015 13,032 16,019 17,032 17,870 19,903 20,375 20,604

Education, Training, and Library 11,063 11,532 11,648 11,685 11,973 12,309 12,352 12,506 12,271 12,156 12,800

Business and Financial Operations 5,647 5,587 5,709 5,886 5,959 6,333 6,720 6,845 6,907 6,944 7,170

Office and Administrative Support 24,119 24,154 24,432 24,563 24,945 25,160 25,618 24,905 24,540 23,805 23,908

Transportation and Material Moving 11,322 11,078 11,223 11,218 10,970 11,100 11,118 10,541 10,384 10,393 10,473

Production 12,729 12,547 12,932 13,262 13,169 13,296 12,891 11,619 11,317 11,628 11,729

0

5,000

10,000

15,000

20,000

25,000

30,000

Job

s

Growing/Declining Occupations (2002-2012)



Growing/Declining Industries

The following graphic shows industries with the

largest job growth/decline in the time period

from 2002-2012. Government (13,345), Real

Estate and Rental and Leasing (21,050), and

Health Care and Social Assistance (1,722) added

the most jobs. Retail Trade (-1,572),

Manufacturing (-1,332), and Transportation and

Warehousing (-929) lost the most jobs.

Figure 11: Growing/Declining Industries (2002-2012)

2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012

Government 44,136 44,771 45,249 44,647 47,452 50,699 51,964 53,457 55,489 55,521 57,481

Real Estate and Rental and Leasing 3,479 3,757 3,780 4,075 4,439 4,532 4,721 4,850 5,167 5,494 5,629

Health Care and Social Assistance 16,242 16,153 16,323 16,161 16,763 17,071 17,314 17,420 17,268 17,545 17,964

Transportation and Warehousing 5,729 5,508 5,631 5,667 5,078 5,214 5,330 4,921 4,768 4,754 4,800

Manufacturing 18,182 18,107 18,582 19,291 19,121 19,034 18,365 16,597 16,020 16,787 16,850

Retail Trade 21,655 21,634 21,858 21,385 21,552 21,060 20,556 20,593 20,344 20,314 20,083

0

10,000

20,000

30,000

40,000

50,000

60,000

70,000

Axi

s Ti

tle

Growing/Declining Industries (2002-2012)



Average Earnings by Industry

The following table and figure break down

earnings by gender and industry.

Utilities and Management of Companies were

the industries with the highest average earnings

in 2012.

Average Earnings in $Thousands

Average Earnings 38.2 Percent of National Average 75% Male 44.8 Percent of National Average 73% Female 30.8 Percent of National Average 77%

Figure 12: Northcentral Kansas Avg. Earnings (2012)

Regional Knowledge Location Quotient

25.03

44.38

103.55

39.57

51.45

45.40

23.06

48.05

43.74

36.66

20.44

35.64

66.21

26.14

24.68

37.57

10.65

13.80

19.94

52.65

0 20 40 60 80 100 120



Utilities

Construction

Manufacturing

Wholesale Trade

Retail Trade


Information











Government

Northcentral Kansas Average Earnings (2012)

Avg. Earnings $Thousands



The following graphic shows the knowledge

base in relation to the national average. A

location quotient (LQ) of 1.0 is equal to the

nation. Greater than 1.0 shows knowledge

greater than the national average. The region

shows proficiency in Science and

Manufacturing.

Figure 13: Regional Knowledge Overview LQ (2012)

Regional Skills Location Quotient

The follow figure shows the skills base of the

labor force in relation to the national average. A

location quotient (LQ) of 1.0 is equal to the

nation. An LQ greater than 1.0 shows

proficiency in a skill greater than the national

average. The region shows proficiency in

Technical and Resource Management skills.

Figure 14: Regional Skills Overview LQ (2012)

Regional Patents

This map shows the spatial distribution of

inventors by industry. Colors are defined by

industry cluster and size is allocated by the

number of inventions by a single inventor.

1.07

1.06

0.99

0.98

0.98

0.97

0.8 0.9 1.0 1.1 1.2

Manufacturing

Science

Liberal Arts

Health

Technical

Business

Regional Knowledge Overview LQ (2012)

LQ (2012)

1.05

1.01

0.99

0.99

0.99

0.98

0.8 0.9 1.0 1.1 1.2

Technical

Resource Management

Basic

Social

Complex Problem Solving

System

Regional Skills Overview LQ (2012)

LQ (2012)



Patents are spread over the whole region with

most belonging to Agriculture, Machinery and

Transportation clusters.



Part II: Industry Overview

Part II of the report describes in detail the

region’s Industry, including major industrial

clusters, shift share analysis, jobs and wages.

The following graphic shows the average

earnings, size, and growth of each industry for

the time period 2002-2012. The vertical axis

shows the average annual earnings. The

horizontal axis shows overall growth/decline of

the industry, with the midpoint being zero. The

relative size of the bubble represents 2002 jobs

in each industry. The growth rate is over the

entire ten year period.

$0

$20,000

$40,000

$60,000

$80,000

$100,000

$120,000

(50%) (30%) (10%) 10% 30% 50% 70% 90% 110% 130% 150%

Avg

. Ea

rnin

gs P

er

Wo

rke

r

2002-2012 Growth %

Agriculture, Forestry, Fishing and Hunting Mining, Quarrying, and Oil and Gas Extraction

Utilities Construction

Manufacturing Wholesale Trade

Wholesale Trade Retail Trade

Transportation and Warehousing Information

Finance and Insurance Real Estate and Rental and Leasing

Professional, Scientific, and Technical Services Management of Companies and Enterprises

Administrative and Support and Waste Management Educational Services (Private)

Health Care and Social Assistance Arts, Entertainment, and Recreation

Accommodation and Food Services Other Services (except Public Administration)

Figure 15: Industry Overview (2012)



Description 2002 Jobs 2012 Jobs Change 2002-2012

% Change 2012 Earnings

Government 44,136 57,481 13,345 30% $52,648

Retail Trade 21,655 20,083 (1,572) (7%) $23,064

Manufacturing 18,182 16,850 (1,332) (7%) $51,450

Health Care and Social Assistance 16,242 17,964 1,722 11% $37,572

Agriculture, Forestry, Fishing and Hunting 12,110 11,278 (832) (7%) $25,033

Accommodation and Food Services 11,446 12,373 927 8% $13,800

Other Services (except Public Administration) 10,484 10,153 (331) (3%) $19,943

Construction 8,765 9,707 942 11% $39,574

Finance and Insurance 6,620 7,497 877 13% $36,662

Administrative and Support and Waste Management and Remediation Services

5,757 6,965 1,208 21% $26,141

Transportation and Warehousing 5,729 4,800 (929) (16%) $48,053

Wholesale Trade 5,348 5,372 24 0% $45,397

Professional, Scientific, and Technical Services 5,218 6,217 999 19% $35,639

Real Estate and Rental and Leasing 3,479 5,629 2,150 62% $20,441

Information 2,983 2,120 (863) (29%) $43,737

Arts, Entertainment, and Recreation 2,016 2,017 1 0% $10,645

Educational Services (Private) 1,823 2,421 598 33% $24,680

Management of Companies and Enterprises 846 995 149 18% $66,213

Utilities 638 868 230 36% $103,550

Mining, Quarrying, and Oil and Gas Extraction 610 1,456 846 139% $44,384

Total 184,088 202,247 18,159 10% $38,238

Source: EMSI 2013.1

Table 1: Industry Overview

The above graphic and table show the decline in

jobs for Information, Transportation and

Warehousing, Manufacturing, and Agriculture,

Forestry, Fishing, and Hunting over the previous

ten years. Mining, Quarrying, and Oil and Gas

Extraction, Real Estate and Rental and Leasing,

Utilities, and Education all had greater than 30%

growth over the previous years.



Industry Jobs

Total Jobs

The following table shows the number of full

and part-time employment in 2012 for the

region by 2-digit NAICS Code. The North

American Industry Classification System (NAICS)

is the standard used by Federal statistical

agencies in classifying business establishments

for the purpose of collecting, analyzing, and

publishing statistical data related to the U.S.

business economy. Government is the region’s

largest industry by employment with 57.481

employees. Retail Trade is the second largest

industry with 20,083 employees.

NAICS Code

Description 2012 Jobs

11 Agriculture, Forestry, Fishing and Hunting 11,278

21 Mining, Quarrying, and Oil and Gas Extraction 1,456

22 Utilities 868

23 Construction 9,707

31-33 Manufacturing 16,850

42 Wholesale Trade 5,372

44-45 Retail Trade 20,083

48-49 Transportation and Warehousing 4,800

51 Information 2,120

52 Finance and Insurance 7,497

53 Real Estate and Rental and Leasing 5,629

54 Professional, Scientific, and Technical Services 6,217

55 Management of Companies and Enterprises 995

56 Administrative and Support and Waste Management and Remediation Services 6,965

61 Educational Services (Private) 2,421

62 Health Care and Social Assistance 17,964

71 Arts, Entertainment, and Recreation 2,017

72 Accommodation and Food Services 12,373

81 Other Services (except Public Administration) 10,153

90 Government 57,481

99 Unclassified Industry 0

Total 202,247

Source: EMSI 2013.1 Table 2: Industry Jobs (2012)




financial institutions over the region. Most of

them are situated in bigger cities like

Manhattan, Salina, Junction City and Emporia. It

also corresponds with distribution of jobs in

NAICS 52 Industry – Finance and Insurance

Industry. The lighter color indicates a fewer

number of jobs and vice versa. Also, counties

that are right next to these big cities tend to

have more jobs and financial institutions. The

more peripheral a county is the fewer jobs are

located there.




airports and highways over the region. There

are just three counties without airports: Lincoln,

Morris and Wabaunsee. Also you can see that

the bigger the city and corresponding airport,

the more jobs in NAICS 48-49 Transportation

and Warehousing are located there.



State & National Jobs

The following table shows the number of jobs

by NAICS code for the region, state, and nation.

Also shown is the ratio of industry jobs to total

jobs in the overall area (expressed in

percentage). The regional industries that have a

higher percentage of total jobs than either state

or nation are Government and Agriculture,

Forestry, Fishing, and Hunting.

NAICS Code

Description Northcentral 2012 Jobs

Northcentral 2012 %

State 2012 Jobs

State 2012 %

National 2012 Jobs

National 2012 %

11 Agriculture, Forestry, Fishing and Hunting

11,278 5.58% 72,766 3.99% 3,514,563 1.96%

21 Mining, Quarrying, and Oil and Gas Extraction

1,456 0.72% 40,171 2.20% 1,445,241 0.81%

22 Utilities 868 0.43% 8,495 0.47% 587,607 0.33%

23 Construction 9,707 4.80% 85,176 4.67% 8,806,849 4.92%

31-33 Manufacturing 16,850 8.33% 171,475 9.40% 12,502,832 6.98%

42 Wholesale Trade 5,372 2.66% 65,955 3.62% 6,195,614 3.46%

44-45 Retail Trade 20,083 9.93% 174,530 9.57% 17,818,881 9.95%

48-49 Transportation and Warehousing 4,800 2.37% 55,916 3.07% 5,765,739 3.22%

51 Information 2,120 1.05% 29,636 1.63% 3,223,422 1.80%

52 Finance and Insurance 7,497 3.71% 98,716 5.41% 9,894,473 5.52%

53 Real Estate and Rental and Leasing 5,629 2.78% 61,937 3.40% 8,063,250 4.50%

54 Professional, Scientific, and Technical Services

6,217 3.07% 96,900 5.31% 12,413,942 6.93%

55 Management of Companies and Enterprises

995 0.49% 15,448 0.85% 2,128,789 1.19%

56 Administrative and Support and Waste Management and Remediation Services

6,965 3.44% 102,535 5.62% 11,076,286 6.18%

61 Educational Services (Private) 2,421 1.20% 27,991 1.53% 4,449,888 2.48%

62 Health Care and Social Assistance 17,964 8.88% 194,795 10.68% 19,648,487 10.97%

71 Arts, Entertainment, and Recreation 2,017 1.00% 28,256 1.55% 3,884,113 2.17%

72 Accommodation and Food Services 12,373 6.12% 106,100 5.82% 12,504,071 6.98%

81 Other Services (except Public Administration)

10,153 5.02% 93,390 5.12% 10,875,226 6.07%

90 Government 57,481 28.42% 293,522 16.09% 24,163,374 13.49%

Total 202,247 1,823,714 179,159,830

Source: EMSI 2013.1

Table 3: State & National Jobs



Job change and Establishments

The following table shows the percentage

change of jobs by industry over the ten year

period and number of new establishments.

Government had the largest growth in overall

jobs added (13,345), and Mining, Quarrying,

and Oil and Gas Extraction added the most jobs

by percentage (139%). Retail trade lost the

most jobs (-1,572) while Information lost the

largest percentage of jobs (29%). Retail trade

has the most establishments (1,229).

NAICS Code

Description 2002 Jobs

2012 Jobs

Change 2002-2012

% Change 2012 Establishments

11 Agriculture, Forestry, Fishing and Hunting 12,110 11,278 (832) (7%) 189


610 1,456 846 139% 31

22 Utilities 638 868 230 36% 29

23 Construction 8,765 9,707 942 11% 919

31-33 Manufacturing 18,182 16,850 (1,332) (7%) 327

42 Wholesale Trade 5,348 5,372 24 0% 485

44-45 Retail Trade 21,655 20,083 (1,572) (7%) 1,229

48-49 Transportation and Warehousing 5,729 4,800 (929) (16%) 325

51 Information 2,983 2,120 (863) (29%) 145

52 Finance and Insurance 6,620 7,497 877 13% 574

53 Real Estate and Rental and Leasing 3,479 5,629 2,150 62% 311


5,218 6,217 999 19% 681

55 Management of Companies and Enterprises

846 995 149 18% 37


5,757 6,965 1,208 21% 455

61 Educational Services (Private) 1,823 2,421 598 33% 67

62 Health Care and Social Assistance 16,242 17,964 1,722 11% 798

71 Arts, Entertainment, and Recreation 2,016 2,017 1 0% 108

72 Accommodation and Food Services 11,446 12,373 927 8% 699


10,484 10,153 (331) (3%) 783

90 Government 44,136 57,481 13,345 30% 905

Total 184,088 202,247 18,159 10% 9,095

Source: EMSI 2013.1 Source: EMSI

2013.1 Table 4: Job Change and Establishments (2002-2012)



Shift Share

Shift share is a standard method of regional

economic analysis that attempts to separate

regional job growth into its component causes.

The three main causes identified are the

"national growth effect," which is regional

growth that can be attributed to the overall

growth of the entire U.S. economy; the

"independent mix effect," which is regional

growth that can be attributed to positive trends

in the specific industry at a national level; and

the "regional competitive effect," which is

growth that cannot be explained by either

overall or industry-specific trends. Shift share

can be applied to job decline as well as job

growth. This graph shows three occupations

with biggest positive and negative competitive

effect.

The following graphic and table show the shift

share of the region by industry. The shift share

shows the competitive effect of the industry.

The sum of the Industry Mix Effect and the

National Growth Effect yield the expected

change. The difference between actual job

change and expected job change is the

competitive effect.

Figure 16: Industry Shift Share (2002-2012), greatest change in competitive effect

Government Manufacturing ConstructionTransportation

andWarehousing

Other Services(except Public

Administration)

Health Care andSocial

Assistance

90 31-33 23 48-49 81 62

Independent Mix Effect (2,798) (5,343) (1,567) (4) 839 2,781

National Growth Effect 3,901 1,607 775 506 927 1,435

Expected Change 1,103 (3,736) (792) 502 1,766 4,216

Competitive Effect 12,242 2,404 1,734 (1,430) (2,096) (2,495)

(8,000)

(6,000)

(4,000)

(2,000)

0

2,000

4,000

6,000

8,000

10,000

12,000

14,000

Industry Shift Share 2002-2012



NAICS Code

Description Independent Mix Effect

National Growth Effect

Expected Change

Competitive Effect

11 Agriculture, Forestry, Fishing and Hunting (1,421) 1,070 (351) (481)


519 54 573 273

22 Utilities (75) 56 (19) 248

23 Construction (1,567) 775 (792) 1,734

31-33 Manufacturing (5,343) 1,607 (3,736) 2,404

42 Wholesale Trade (359) 473 114 (90)

44-45 Retail Trade (2,136) 1,914 (222) (1,351)

48-49 Transportation and Warehousing (4) 506 502 (1,430)

51 Information (687) 264 (423) (440)

52 Finance and Insurance 1,154 585 1,739 (862)

53 Real Estate and Rental and Leasing 1,155 308 1,463 687


707 461 1,168 (170)

55 Management of Companies and Enterprises 78 75 153 (4)


338 509 847 360

61 Educational Services (Private) 493 161 654 (56)

62 Health Care and Social Assistance 2,781 1,435 4,216 (2,495)

71 Arts, Entertainment, and Recreation 230 178 408 (407)

72 Accommodation and Food Services 807 1,012 1,819 (891)


839 927 1,766 (2,096)

90 Government (2,798) 3,901 1,103 12,242

Total (5,287) 16,269 10,982 7,176

Source: EMSI 2013.1 Table 5: Shift Share (2002-2012)

Government, Manufacturing, and Construction

are the industries with the largest positive

competitive effect. Health Care and Social

Assistance, Other Services (except Public

Administration), and Transportation and

Warehousing has the largest negative

competitive effect.



Unemployment

The following tables show the unemployment rate for the region, state, and nation in 2012.

Manufacturing and Government make up equal parts of the unemployment in the region at 13.2%. Also

Retail Trade and Government are industries with unemployment rate over 10% (12.7% and 13.2%).

Average Unemployment rate November 2012

Northcentral Kansas 5.25%

State 5.93%

Nation 8.12% Table 6: Average Unemployment Rate (2012)

NAICS Code Description

November 2012 Unemployment

% of Unemployed State % National %

11 Agriculture, Forestry, Fishing and Hunting 25 0.30% 0.30% 2.60%

21 Mining, Quarrying, and Oil and Gas Extraction 26 0.30% 0.70% 0.60%

22 Utilities 39 0.50% 0.50% 0.40%

23 Construction 748 9.50% 8.70% 8.00%

31-33 Manufacturing 1,035 13.20% 13.50% 10.00%

42 Wholesale Trade 154 2.00% 2.20% 2.00%

44-45 Retail Trade 1,002 12.70% 11.40% 11.30%

48-49 Transportation and Warehousing 179 2.30% 2.90% 2.80%

51 Information 120 1.50% 2.00% 1.50%

52 Finance and Insurance 166 2.10% 2.80% 2.80%

53 Real Estate and Rental and Leasing 97 1.20% 1.30% 1.50%

54 Professional, Scientific, and Technical Services 172 2.20% 3.50% 3.90%

55 Management of Companies and Enterprises <10 0.10% 0.10% 0.10%


356 4.50% 6.90% 7.10%

61 Educational Services (Private) 93 1.20% 1.50% 2.00%

62 Health Care and Social Assistance 590 7.50% 8.50% 7.10%

71 Arts, Entertainment, and Recreation 50 0.60% 0.90% 2.30%

72 Accommodation and Food Services 552 7.00% 6.30% 8.50%

81 Other Services (except Public Administration) 346 4.40% 3.90% 4.10%



90 Government 1,037 13.20% 8.50% 6.80%

99 No Previous Work Experience/Unspecified 1,066 13.60% 13.40% 14.60%

Source: EMSI 2013.1

Table 7: State & National Unemployment Rates (2012)

Regional Businesses

The following table shows the industry of the businesses with the most employees.

Description Business Name Local Employees

Full-Service Restaurants Tony's Pizza Svc. 1,750

Colleges, Universities, and Professional Schools (Private)

Kansas State University 1,060

Offices of Physicians (except Mental Health Specialists)

Mercy Health Ctr 961

Meat Processed from Carcasses Tyson Fresh Meats 945

General Medical and Surgical Hospitals (Private) Salina Regional Reference Laboratory, Inc 909

All Other Miscellaneous Waste Management Services

Steris Foodlabs, Inc. 800

All Other Professional, Scientific, and Technical Services

Salina Regional Health Center 753

General Medical and Surgical Hospitals (Private) Irwin Army Community Hospital 723

Shoe Stores Foot Locker Retail Inc 700

Ornamental and Architectural Metal Work Manufacturing

Land Pride 700

General Freight Trucking, Long-Distance, Truckload Great Plains Manufacturing, Inc. - Grain Drills

700

Hotels (except Casino Hotels) and Motels B & L Motels, Inc 690

n/a City Of Emporia Administrative Offices Weekdays

690

Warehouse Clubs and Supercenters Walmart 690

Nursing Care Facilities Manhattan Retirement Foundation, Inc 690

Electrical Apparatus and Equipment, Wiring Supplies, and Related Equipment Merchant Wholesalers

Exide Technologies 682

n/a Geary County Schools 600

Commercial Banking Sunflower Banks Na 500

All Other Miscellaneous Fabricated Metal Product Manufacturing

Florence Corporation 450

Warehouse Clubs and Supercenters Walmart Supercenter 450

Iron and Steel Pipe and Tube Manufacturing from Purchased Steel

Steel & Pipe Supply Company, Inc. 425



n/a Cooperative State Research Ed 400

Warehouse Clubs and Supercenters Walmart Supercenter 370

Construction Machinery Manufacturing Caterpillar Work Tools, Inc. 356

Engineering Services Alfred Benesch & Company 352

n/a Didde Corp 350

General Medical and Surgical Hospitals (Private) Newman Regional Health 346

Warehouse Clubs and Supercenters Walmart 345

General Medical and Surgical Hospitals (Private) Geary Community Hospital 345

Other Social Advocacy Organizations City Of Manhattan Other Lcl Agencies Riley Cnty P

345

Supermarkets and Other Grocery (except Convenience) Stores

Dillon Food Stores 345

Discount Department Stores Target 345

Commercial Bakeries Dolly Madison Bakery 342

Commercial Bakeries Butternut Bread #10 342

n/a Concordia School District 335

Automobile and Other Motor Vehicle Merchant Wholesalers

Eldorado National Kansas, Inc. 300

n/a Emporia Police Department 293

All Other Miscellaneous Store Retailers (except Tobacco Stores)

Sunflower Manufacturing Company Inc 290

Discount Department Stores Kmart 265

n/a Administrative Resource Center 265

Wholesale Trade Agents and Brokers Leiszler Oil Co., Inc. 250

Research and Development in Biotechnology Dpra Incorporated 250

Lessors of Residential Buildings and Dwellings Mc Cullough Development Inc 230

Discount Department Stores Kmart 230

Metal Service Centers and Other Metal Merchant Wholesalers

Alstom Power Inc - Air Preheater Company

220

Offices of Certified Public Accountants Kennedy And Coe, Llc 220

Commercial Banking Sunflower Bank National Association Inc. 210

Ambulance Services Salina Administrative Calls 207

Offices of Bank Holding Companies Landmark Bancorp, Inc. 207

Commercial Banking Pinnacle Bank 200

Source: EMSI 2013.1

Table 8: Regional businesses


Prepared by AMI using EMSI Analyst and data

Economic Modeling Specialists, Inc. | www.economicmodeling.com 39

Location Quotient by Industry and County

Description Chase Clay Cloud Dickinson Ellsworth Geary Jewell Lincoln Lyon Marshall Mitchell Morris Ottawa Pottawatomie Republic Riley Saline Wabaunsee Washington

Agriculture, Forestry, Fishing and Hunting 5.26 5.03 4.27 5.20 3.89 0.39 11.80 10.32 2.33 5.76 4.61 9.65 9.81 3.10 8.92 0.87 1.01 9.59 12.39


14.91 -- -- 0.30 5.99 0.04 -- -- 0.62 -- -- 0.89 -- -- -- 0.56 1.02 -- --

Utilities -- -- -- 2.14 -- 0.10 13.46 -- 1.21 1.35 -- 4.11 -- 7.19 0.00 0.81 0.41 0.00 --

Construction 2.09 1.87 1.73 1.64 1.41 1.30 1.09 1.08 1.06 1.01 0.95 0.95 0.94 0.92 0.91 0.88 0.77 0.65 0.44

Manufacturing 0.54 1.15 0.96 2.04 1.25 0.25 -- 0.31 2.18 2.33 1.48 0.89 0.90 1.98 0.82 0.24 2.08 0.79 0.68

Wholesale Trade 0.12 1.12 1.44 1.02 0.54 0.14 1.21 1.27 0.94 1.36 1.65 0.15 0.92 0.91 1.22 0.66 0.86 0.48 1.55

Retail trade 0.12 1.12 1.44 1.02 0.54 0.14 1.21 1.27 0.94 1.36 1.65 0.15 0.92 0.91 1.22 0.66 0.86 0.48 1.55

Transportation and Warehousing 1.69 1.13 0.63 1.17 0.44 0.29 1.17 0.63 0.76 1.78 0.74 1.07 1.38 0.70 0.43 0.18 1.17 0.87 1.35

Information -- 0.49 0.91 0.38 0.63 0.40 -- -- 0.62 0.88 0.71 1.58 -- 0.87 0.17 0.69 0.62 -- --

Finance and Insurance 1.05 0.95 0.82 0.51 0.95 0.22 1.22 1.46 0.44 0.98 1.07 0.66 1.28 0.94 0.99 0.70 0.74 0.80 0.58

Real Estate and Rental and Leasing 1.13 1.32 0.54 0.41 0.41 0.48 0.37 0.53 0.48 0.54 0.46 0.33 0.45 1.21 0.21 0.72 0.57 0.67 0.27


0.59 0.51 0.35 0.30 0.36 0.20 0.39 0.40 0.28 0.45 0.33 0.51 0.38 0.55 0.32 0.60 0.68 0.39 0.26

Management of Companies and Enterprises 0.00 0.23 0.00 2.90 0.07 -- -- 0.06 -- 0.00 0.00 0.00 -- 0.00 0.30 1.07 0.00 --

Administrative and Support and Waste Management and Remediation Services

0.68 0.54 0.37 0.34 0.50 0.73 0.25 0.70 0.65 0.46 0.22 0.34 0.39 0.58 0.26 0.45 0.59 1.55 0.22

Educational Services (Private) 0.68 0.54 0.37 0.34 0.50 0.73 0.25 0.70 0.65 0.46 0.22 0.34 0.39 0.58 0.26 0.45 0.59 1.55 0.22

Health Care and Social Assistance 0.44 0.85 1.40 0.53 1.70 0.21 0.17 0.55 0.97 0.80 0.66 0.66 1.11 0.94 1.07 0.98 1.11 0.47 0.55

Arts, Entertainment, and Recreation 0.61 0.34 0.44 0.49 0.47 0.19 0.39 0.40 0.41 0.39 0.70 0.58 0.39 0.92 0.63 0.57 0.47 0.25 --

Accommodation and Food Services 0.91 0.42 0.94 0.67 0.50 0.50 0.62 0.58 1.06 0.60 0.63 0.79 0.41 0.48 0.63 1.66 1.04 0.35 0.55


1.01 0.82 1.22 1.07 0.80 0.36 0.94 0.78 0.75 0.69 0.95 0.71 0.95 0.80 0.86 1.01 1.05 0.88 0.89

Government 0.68 1.20 1.31 1.49 1.55 5.21 1.41 1.60 1.80 0.89 1.76 1.56 1.42 0.78 1.73 2.02 0.93 1.46 1.75

The location quotient for the following industry is given by county. The highest overall LQ was the Mining, Quarrying, and Oil and Gas Extraction in Chase

County. Agriculture, Forestry, Fishing and Hunting have an LQ higher than 1.0 in every county except for Geary and Riley county.

Table 9: Location Quotient by Industry and County (2012)


Prepared by AMI using EMSI Analyst and data 40

Industry Wages

Region, State, & National Earnings

The following table shows the annual wage of

each industry by the region, state, and nation.

Also found in the table is what percentage the

regions wage is to the state and nation. The

annual wage in the region for Government was

larger than the state average. No industry had

earnings higher than its national counterpart.

NAICS Code

Description 2012 Northcentral Earnings

% of State

% of National

2012 State Earnings

2012 National Earnings

11 Agriculture, Forestry, Fishing and Hunting $25,033 86.33% 92.18% $28,998 $27,159

21 Mining, Quarrying, and Oil and Gas Extraction $44,384 83.93% 54.03% $52,882 $82,140

22 Utilities $103,550 86.46% 82.92% $119,764 $124,878

23 Construction $39,574 86.69% 80.84% $45,652 $48,952

31-33 Manufacturing $51,450 77.84% 68.56% $66,095 $75,044

42 Wholesale Trade $45,397 67.67% 60.70% $67,089 $74,782

44-45 Retail Trade $23,064 86.12% 75.26% $26,781 $30,645

48-49 Transportation and Warehousing $48,053 96.87% 93.83% $49,604 $51,212

51 Information $43,737 60.29% 51.34% $72,545 $85,191

52 Finance and Insurance $36,662 65.96% 46.25% $55,582 $79,268

53 Real Estate and Rental and Leasing $20,441 83.25% 68.01% $24,553 $30,056


$35,639 61.99% 48.96% $57,492 $72,785

55 Management of Companies and Enterprises $66,214 68.24% 57.14% $97,038 $115,884


$26,140 73.32% 77.14% $35,651 $33,885

61 Educational Services (Private) $24,679 96.96% 67.83% $25,453 $36,382

62 Health Care and Social Assistance $37,572 81.60% 71.66% $46,045 $52,428

71 Arts, Entertainment, and Recreation $10,645 77.04% 38.81% $13,817 $27,425

72 Accommodation and Food Services $13,800 85.06% 66.70% $16,223 $20,691

81 Other Services (except Public Administration) $19,942 94.45% 83.45% $21,114 $23,897

90 Government $52,648 102.17% 82.14% $51,529 $64,092

Total $38,238 $44,481 $51,164

Source: EMSI 2013.1

Table 10: Region, State & National Earnings (2012)



Industry Clusters

Clusters are based on compilations of NAICS

codes based on methodology from Purdue

University. It is important to note that some

industries are found in multiple clusters, and

some industries are not found in any cluster.

Jobs, Earnings, Growth and Establishments

The following table shows the number of jobs, earnings and job growth from 2002-2012 for each industry cluster in the regionand the number of establishments for each.

Agribusiness, Food Processing & Technology,

Biomedical/Biotechnical (Life Sciences), and

Business & Financial Services are the clusters

with the most employees.

The cluster with the highest average earning in

2012 is Electrical Equipment, Appliance &

Component Manufacturing with over $70,000.

The Business and Financial Services cluster

added the most jobs (3,077) while Apparel and

Textiles grew by the largest percentage (129%).

Agribusiness, Food Processing, & Technology

lost the most jobs (-2,408), and Computer &

Electronic Product Manufacturing declined by

the largest percentage (-78%).

Business and financial Services cluster had most

new establishments with 1,154. Second largest

is Energy cluster with 433.

Cluster Name 2012 EPW

2002 Jobs

2012 Jobs

Change 2002-2012

% Change 2012 Establishments

Advanced Materials $56,237 2,658 2,488 -170 -6% 95

Agribusiness, Food Processing & Technology

$41,821 11,339 8,931 -2,408 -21% 249

Apparel & Textiles $32,386 481 1,102 621 129% 46

Arts, Entertainment, Recreation & Visitor Industries

$14,800 3,935 3,825 -110 -3% 242

Biomedical/Biotechnical (Life Sciences) $36,158 10,536 11,211 675 6% 340

Business & Financial Services $32,245 9,386 12,463 3,077 33% 1154

Chemicals & Chemical Based Products $58,268 1,467 1,977 510 35% 81

Computer & Electronic Product Manufacturing

$65,454 144 32 -112 -78% 2

Defense & Security $43,757 1,711 2,134 423 25% 175

Education & Knowledge Creation $25,428 2,070 2,236 166 8% 98

Electrical Equipment, Appliance & Component Manufacturing

$71,881 2,060 1,620 -440 -21% 7

Energy (Fossil & Renewable) $53,983 7,054 7,846 792 11% 433



Fabricated Metal Product Manufacturing

$48,441 1,079 1,862 783 73% 47

Forest & Wood Products $43,818 1,033 674 -359 -35% 29

Glass & Ceramics $44,852 326 301 -25 -8% 11

Information Technology & Telecommunications

$65,856 3,562 2,996 -566 -16% 198

Machinery Manufacturing $56,947 2,100 2,944 844 40% 63

Manufacturing Supercluster $57,676 7,370 8,319 949 13% 157

Mining $66,340 1,109 1,334 225 20% 38

Primary Metal Manufacturing $57,257 122 169 47 39% 16

Printing & Publishing $31,244 2,148 1,830 -318 -15% 146

Transportation & Logistics $49,867 5,510 4,580 -930 -17% 320

Transportation Equipment Manufacturing

$55,405 1,864 1,691 -173 -9% 23

Source: EMSI 2013.1

Table 11: Industry Clusters Jobs, Earnings, Growth and Establishments (2002-2012)

Regional Competitiveness (Shift Share)








"independent mix effect," which is regional


in the specific industry at a national level; and

the "regional competitive effect," which is

growth that cannot be explained by either

overall or industry-specific trends. Shift share

can be applied to job decline as well as job

growth. This graph shows three occupations

with biggest positive and negative competitive

effect.

The following graphic and table show the shift

share of the region by industry. The shift share

shows the competitive effect of the industry.

The sum of the Industry Mix Effect and the

National Growth Effect yield the expected

change. The difference between actual job

change and expected job change is the

competitive effect.



Figure 17: Industry cluster Shift Share (2002-2012), greatest change in competitive effect

Cluster Name Job Change

Independent Mix Effect


Expected Change

Competitive Effect

Manufacturing Supercluster 949 -1,956 651 -1,305 2,253

Machinery Manufacturing 844 -401 186 -215 1,060

Fabricated Metal Product Manufacturing 783 -199 95 -104 887

Chemicals & Chemical Based Products 510 -427 130 -297 808

Apparel & Textiles 620 -175 43 -132 752

Transportation Equipment Manufacturing -173 -532 165 -367 194

Advanced Materials -170 -559 235 -324 155

Defense & Security 422 137 151 288 134

Business & Financial Services 3,076 2,120 830 2,950 127

Mining 225 32 98 130 95

ManufacturingSupercluster

MachineryManufacturing

FabricatedMetal ProductManufacturing

Transportation& Logistics

Biomedical/Biotechnical (Life

Sciences)

Agribusiness,Food Processing

& Technology

Job Change 949 844 783 -930 675 -2,409

Independent Mix Effect -1,956 -401 -199 -70 1,331 -857

National Growth Effect 651 186 95 487 931 1,002

Expected Change -1,305 -215 -104 417 2,262 145

Competitive Effect 2,253 1,060 887 -1,347 -1,587 -2,554

-3000

-2000

-1000

0

1000

2000

3000

Industry Cluster Shift Share 2002-2012



Electrical Equipment, Appliance & Component Manufacturing

-441 -694 182 -512 72

Primary Metal Manufacturing 46 -35 11 -24 71

Glass & Ceramics -25 -108 29 -79 54

Forest & Wood Products -360 -427 91 -336 -24

Computer & Electronic Product Manufacturing

-112 -51 13 -38 -74

Printing & Publishing -317 -249 190 -59 -258

Education & Knowledge Creation 166 403 183 586 -420

Information Technology & Telecommunications

-567 -412 315 -97 -469

Arts, Entertainment, Recreation & Visitor Industries

-109 22 348 370 -479

Energy (Fossil & Renewable) 792 775 623 1,398 -607

Transportation & Logistics -930 -70 487 417 -1,347

Biomedical/Biotechnical (Life Sciences) 675 1,331 931 2,262 -1,587

Agribusiness, Food Processing & Technology

-2,409 -857 1,002 145 -2,554

Source: EMSI 2013.1

Table 12: Shift Share (2002-2012)

Manufacturing Supercluster, Machinery

Manufacturing, and Fabricated Metal Product

Manufacturing have the largest positive

competitive effect in the region. Transportation

and Logistics, Biomedical/Biotechnical (Life

Sciences), and Agribusiness, Food Processing &

Technology had the lowest regional competitive

effect.

Location Quotient

The following table shows the change in

location quotient (LQ) by cluster over the period

2002-2012. Apparel & Textiles had the largest

LQ increase, though it is still well below the

national level. Fabricated metal Product

Manufacturing went from below the national

level to well above it with a 90% change in LQ.

Cluster Name 2002 LQ 2012 LQ Percent Change LQ

Agribusiness, Food Processing & Technology 3.88 2.99 -23%

Electrical Equipment, Appliance & Component Manufacturing 3.62 3.75 4%

Mining 2.2 2.35 7%

Machinery Manufacturing 1.49 2.31 55%

Energy (Fossil & Renewable) 1.02 0.93 -9%

Transportation & Logistics 0.99 0.76 -23%



Manufacturing Supercluster 0.92 1.25 36%

Transportation Equipment Manufacturing 0.91 1.01 11%

Biomedical/Biotechnical (Life Sciences) 0.83 0.72 -13%

Glass & Ceramics 0.77 0.93 21%

Fabricated Metal Product Manufacturing 0.62 1.18 90%

Printing & Publishing 0.61 0.53 -13%

Education & Knowledge Creation 0.58 0.48 -17%

Arts, Entertainment, Recreation & Visitor Industries 0.55 0.48 -13%

Chemicals & Chemical Based Products 0.5 0.84 68%

Business & Financial Services 0.5 0.5 0%

Information Technology & Telecommunications 0.5 0.42 -16%

Advanced Materials 0.41 0.43 5%

Forest & Wood Products 0.41 0.39 -5%

Defense & Security 0.33 0.35 6%

Apparel & Textiles 0.24 0.74 208%

Primary Metal Manufacturing 0.22 0.38 73%

Computer & Electronic Product Manufacturing 0.09 0.03 -67%

Source: EMSI 2013.1

Table 13: Location Quotient (2002-2012)



Part III: Occupation Overview

Part III describes the regional occupations in

more detail, including data about jobs,

education and wages by major occupations.

This figure represents distribution of jobs by

occupation in 2012.

Figure 18: Occupation Overview (2012)

Total Jobs

North Central | Jobs by Industry

202,247 53.4% 46.6%

Total Jobs (2012) Male Female

(National: 52.2%) (National: 47.8%)

The highest representation from all occupation

had Office and Administrative support

occupations, Sales and Related occupations and

Military occupations. These three occupation

areas exceeded level of 20,000 jobs.

0

5,000

10,000

15,000

20,000

25,000

30,000

23

,90

8

22

,38

6

20

,60

4

17

,11

3

12

,80

0

12

,69

5

11

,72

9

10

,47

3

9,1

64

8,5

98

2012 Jobs

Office and Administrative Support Occupations

Sales and Related Occupations

Military occupations

Management Occupations

Education, Training, and Library Occupations

Food Preparation and Serving Related Occupations

Production Occupations

Transportation and Material Moving Occupations

Construction and Extraction Occupations

Personal Care and Service Occupations



Jobs by Occupation

SOC (Standard Occupational Classification) is

federal system of classifying occupations using

six-digit codes. Column Growth % represents

overall change between years. The most

significant negative change in number of jobs

during observed time was presented by

Production Occupations and Transportation and

Material Moving Occupations, close to the value

of 1,000 jobs, which means overall loss of 7% of

jobs. On the opposite site, the most jobs

appeared in Military Occupations (9,446 jobs),

Education, Training and Library Occupations

(1,737) and Personal Care and Service

Occupations. These changes represent overall

growth of 85, 16 and 17%.

SOC Description 2002 Jobs 2012 Jobs Change 2002-2012

Growth %

11-0000 Management Occupations 17,266 17,113 (153) -1%

13-0000 Business and Financial Operations Occupations 5,647 7,170 1,523 27%

15-0000 Computer and Mathematical Occupations 1,587 1,738 151 10%

17-0000 Architecture and Engineering Occupations 1,551 1,724 173 11%

19-0000 Life, Physical, and Social Science Occupations 1,284 1,485 201 16%

21-0000 Community and Social Service Occupations 2,361 2,544 183 8%

23-0000 Legal Occupations 729 782 53 7%

25-0000 Education, Training, and Library Occupations 11,063 12,800 1,737 16%

27-0000 Arts, Design, Entertainment, Sports, and Media Occupations

3,650 4,110 460 13%

29-0000 Healthcare Practitioners and Technical Occupations

7,065 7,799 734 10%

31-0000 Healthcare Support Occupations 4,407 4,726 319 7%

33-0000 Protective Service Occupations 2,756 3,092 336 12%

35-0000 Food Preparation and Serving Related Occupations

11,943 12,695 752 6%

37-0000 Building and Grounds Cleaning and Maintenance Occupations

7,126 7,850 724 10%

39-0000 Personal Care and Service Occupations 7,371 8,598 1,227 17%

41-0000 Sales and Related Occupations 21,381 22,386 1,005 5%

43-0000 Office and Administrative Support Occupations 24,119 23,908 (211) -1%

45-0000 Farming, Fishing, and Forestry Occupations 1,608 1,676 68 4%

47-0000 Construction and Extraction Occupations 8,087 9,164 1,077 13%

49-0000 Installation, Maintenance, and Repair Occupations

7,301 7,454 153 2%

51-0000 Production Occupations 12,729 11,729 (1,000) -8%

53-0000 Transportation and Material Moving Occupations

11,322 10,473 (849) -7%



55-0000 Military occupations 11,158 20,604 9,446 85%

99-0000 Unclassified Occupation 578 625 47 8%

Total 184,088 202,247 18,159 10%

Source: EMSI 2013.1

Table 14: Jobs by Occupations (2002-2012)

Openings

Openings represent sum of new and

replacement jobs in the occupation over the

entire timeframe (in this case 10 years). This

number includes full time positions as well as

part time. Annual Openings represents sum of

new and replacement jobs in the occupation

over the entire timeframe, divided by the

number of years in the timeframe. The most

openings were in Sales and Related Occupations

(15,049), followed by Office and Administrative

Support Occupations (10,806) and Military

occupations (10,560). The least positions

appeared in Legal Occupations (439) Computer

and Mathematical Occupations (1,045) and Life,

Physical, and Social Science Occupations

(1,172).

SOC Description Openings Annual Openings

11-0000 Management Occupations 7,222 722

13-0000 Business and Financial Operations Occupations 4,470 447

15-0000 Computer and Mathematical Occupations 1,045 104

17-0000 Architecture and Engineering Occupations 1,283 128

19-0000 Life, Physical, and Social Science Occupations 1,172 117

21-0000 Community and Social Service Occupations 1,634 163

23-0000 Legal Occupations 439 44

25-0000 Education, Training, and Library Occupations 7,170 717

27-0000 Arts, Design, Entertainment, Sports, and Media Occupations 3,060 306

29-0000 Healthcare Practitioners and Technical Occupations 4,531 453

31-0000 Healthcare Support Occupations 2,611 261

33-0000 Protective Service Occupations 1,858 186

35-0000 Food Preparation and Serving Related Occupations 8,607 861

37-0000 Building and Grounds Cleaning and Maintenance Occupations 3,932 393

39-0000 Personal Care and Service Occupations 5,892 589

41-0000 Sales and Related Occupations 15,049 1,505

43-0000 Office and Administrative Support Occupations 10,806 1,081

45-0000 Farming, Fishing, and Forestry Occupations 1,343 134

47-0000 Construction and Extraction Occupations 6,196 620

49-0000 Installation, Maintenance, and Repair Occupations 4,992 499



51-0000 Production Occupations 8,325 833

53-0000 Transportation and Material Moving Occupations 5,907 591

55-0000 Military occupations 10,560 1,056

99-0000 Unclassified Occupation 490 49

Total 118,593 11,859

Source: EMSI 2013.1

Table 15: Openings (2002-2012)

Shift Share








"occupational mix effect," which is regional


in the specific occupation at a national level;

and the "regional competitiveness effect,"

which is growth that cannot be explained by

either overall or occupation-specific trends.

Shift share can be applied to job decline as well

as job growth. This graph shows three

occupations with biggest positive and negative

competitive effect.

1,505

1,081 1,056

861 833

0

200

400

600

800

1,000

1,200

1,400

1,600

Sales andRelated

Occupations

Office andAdministrative

SupportOccupations

Militaryoccupations

FoodPreparation andServing Related

Occupations

ProductionOccupations

Top 5 Occupations by Annual Openings



Figure 19: Occupation Shift Share (2002-2012), greatest change in competitive effect

SOC Description Occupational Mix Effect


Expected Change

Competitive Effect

11-0000 Management Occupations 56 1,526 1,582 (1,734)

13-0000 Business and Financial Operations Occupations 1,076 499 1,575 (52)

15-0000 Computer and Mathematical Occupations 56 140 196 (45)

17-0000 Architecture and Engineering Occupations (199) 137 (62) 235

19-0000 Life, Physical, and Social Science Occupations 121 113 234 (33)

21-0000 Community and Social Service Occupations 95 209 304 (121)

Militaryoccupations

Constructionand ExtractionOccupations

ProductionOccupations

Personal Careand ServiceOccupations

ManagementOccupations

Sales andRelated

Occupations

55-0000 47-0000 51-0000 39-0000 11-0000 41-0000

Occupational Mix Effect (1,177) (1,057) (3,025) 2,112 56 854

National Growth Effect 986 715 1,125 651 1,526 1,890

Expected Change (191) (342) (1,900) 2,763 1,582 2,744

Competitive Effect 9,637 1,419 899 (1,537) (1,734) (1,739)

(4,000)

(2,000)

0

2,000

4,000

6,000

8,000

10,000

12,000

Occupation Shift Share 2002-2012



23-0000 Legal Occupations 18 64 82 (29)

25-0000 Education, Training, and Library Occupations 390 978 1,368 370


348 323 671 (211)

29-0000 Healthcare Practitioners and Technical Occupations 674 624 1,298 (565)

31-0000 Healthcare Support Occupations 1,013 389 1,402 (1,083)

33-0000 Protective Service Occupations (84) 244 160 178

35-0000 Food Preparation and Serving Related Occupations 688 1,056 1,744 (991)


979 630 1,609 (885)

39-0000 Personal Care and Service Occupations 2,112 651 2,763 (1,537)

41-0000 Sales and Related Occupations 854 1,890 2,744 (1,739)

43-0000 Office and Administrative Support Occupations (2,332) 2,132 (200) (10)

45-0000 Farming, Fishing, and Forestry Occupations (129) 142 13 55

47-0000 Construction and Extraction Occupations (1,057) 715 (342) 1,419

49-0000 Installation, Maintenance, and Repair Occupations (647) 645 (2) 154

51-0000 Production Occupations (3,025) 1,125 (1,900) 899

53-0000 Transportation and Material Moving Occupations (948) 1,001 53 (901)

55-0000 Military occupations (1,177) 986 (191) 9,637

99-0000 Unclassified Occupation 99 51 150 (103)

Total (1,019) 16,269 15,250 2,908

Source: EMSI 2013.1

Table 16: Shift Share (2002-2012)

Biggest positive change in Competitive effect

was reached by Military occupations (9,637),

Construction and Extraction Occupations

(1,419) and Production Occupations (899). On

the other side biggest negative change was

reached by Sales and Related Occupations (-

1,739), Management Occupations (-1,734), and

Personal Care and Service Occupations (-1,537).

The Biggest positive change in Occupational Mix

Effect was reached by Personal Care and Service

Occupations (2,112), while the biggest negative

change by Production occupations (-3,025).

Location Quotient

SOC Description 2012 State Location Quotient

2012 National Location Quotient

11-0000 Management Occupations 1.02 1.24

13-0000 Business and Financial Operations Occupations 0.70 0.62



15-0000 Computer and Mathematical Occupations 0.48 0.38

17-0000 Architecture and Engineering Occupations 0.56 0.58

19-0000 Life, Physical, and Social Science Occupations 1.00 0.85

21-0000 Community and Social Service Occupations 1.02 0.92

23-0000 Legal Occupations 0.63 0.46

25-0000 Education, Training, and Library Occupations 1.18 1.22

27-0000 Arts, Design, Entertainment, Sports, and Media Occupations 0.85 0.69

29-0000 Healthcare Practitioners and Technical Occupations 0.84 0.82

31-0000 Healthcare Support Occupations 0.85 0.89

33-0000 Protective Service Occupations 0.95 0.81

35-0000 Food Preparation and Serving Related Occupations 1.03 0.94

37-0000 Building and Grounds Cleaning and Maintenance Occupations 1.05 0.93

39-0000 Personal Care and Service Occupations 0.95 0.92

41-0000 Sales and Related Occupations 0.89 0.84

43-0000 Office and Administrative Support Occupations 0.89 0.87

45-0000 Farming, Fishing, and Forestry Occupations 1.17 1.20

47-0000 Construction and Extraction Occupations 0.94 1.05

49-0000 Installation, Maintenance, and Repair Occupations 0.99 1.06

51-0000 Production Occupations 0.92 1.11

53-0000 Transportation and Material Moving Occupations 0.86 0.89

55-0000 Military occupations 5.02 8.86

99-0000 Unclassified Occupation 0.73 0.72

Source: EMSI 2013.1

Table 17: State & National LQ (2012)

Highest values of Location Quotient were held

by Military occupations in both the state and

national level (5.02 and 8.86), followed by

Education, Training, and Library Occupations

(1.18 and 1.22). Third, was Farming, Fishing, and

Forestry Occupations (1.17 and 1.20).

Interesting is the difference between Location

Quotient in Production Occupations (0.99 and

1.11) compared to Management Occupations

with values 1.02 at State level and 1.24 at

National level. Lowest values were found in

Computer and Mathematical Occupations (0.48

and 0.38), Architecture and Engineering

Occupations (0.56 and 0.58) and Business and

Financial Operations Occupations (0.70 and

0.62).



State & National Jobs

Column Growth % represents overall change

between years. Biggest positive change in

absolute number of jobs was recorded in

Business and Financial Operations Occupations

(17,685 jobs, representing 24% growth)

followed by Personal Care and Service

Occupations (15,182 jobs, representing 23%

growth) and Education, Training, and Library

Occupations (9,869 jobs, representing 11%

growth). Biggest positive change in % was

recorded in Military occupations (8,547 jobs,

representing 30% growth). Biggest negative

change in absolute number of jobs was

recorded in Production Occupations (-5,276

jobs, representing 4% decrease), Office and

Administrative Support Occupations (-3,983

jobs, representing 2% decrease) and

Installation, Maintenance, and Repair

Occupations (-2,445 jobs, representing 3%

decrease). Biggest negative change in % of jobs

was recorded in Architecture and Engineering

Occupations (-1,533 jobs representing 5%

decrease).

SOC Description State 2002 Jobs

State 2012 Jobs

State Change 2002-2012

State % Growth

11-0000 Management Occupations 144,380 151,425 7,045 5%

13-0000 Business and Financial Operations Occupations 74,264 91,949 17,685 24%

15-0000 Computer and Mathematical Occupations 32,615 32,619 4 0%

17-0000 Architecture and Engineering Occupations 29,197 27,664 (1,533) (5%)

19-0000 Life, Physical, and Social Science Occupations 11,113 13,459 2,346 21%

21-0000 Community and Social Service Occupations 21,028 22,533 1,505 7%

23-0000 Legal Occupations 9,963 11,210 1,247 13%

25-0000 Education, Training, and Library Occupations 88,037 97,906 9,869 11%


40,413 43,746 3,333 8%


74,013 83,341 9,328 13%

31-0000 Healthcare Support Occupations 42,562 50,098 7,536 18%

33-0000 Protective Service Occupations 27,879 29,498 1,619 6%


107,420 111,470 4,050 4%


59,602 67,273 7,671 13%

39-0000 Personal Care and Service Occupations 66,832 82,014 15,182 23%

41-0000 Sales and Related Occupations 218,442 226,307 7,865 4%

43-0000 Office and Administrative Support Occupations

247,302 243,319 (3,983) (2%)

45-0000 Farming, Fishing, and Forestry Occupations 11,494 12,879 1,385 12%



47-0000 Construction and Extraction Occupations 84,601 87,782 3,181 4%


70,218 67,763 (2,455) (3%)

51-0000 Production Occupations 119,650 114,374 (5,276) (4%)


109,705 110,352 647 1%

55-0000 Military occupations 28,489 37,036 8,547 30%

99-0000 Unclassified Occupation 6,893 7,697 804 12%

Total 1,726,110 1,823,714 97,604 6%

Source: EMSI 2013.1

Table 18: State Jobs (2002-2012)

SOC Description National 2002 Jobs

National 2012 Jobs

National Change 2002-2012

National % Growth

11-0000 Management Occupations 11,159,272 12,181,596 1,022,324 9%

13-0000 Business and Financial Operations Occupations

7,970,897 10,193,737 2,222,840 28%

15-0000 Computer and Mathematical Occupations 3,599,591 4,045,068 445,477 12%

17-0000 Architecture and Engineering Occupations 2,759,891 2,650,521 (109,370) (4%)

19-0000 Life, Physical, and Social Science Occupations

1,312,808 1,552,412 239,604 18%

21-0000 Community and Social Service Occupations 2,172,629 2,452,390 279,761 13%

23-0000 Legal Occupations 1,338,991 1,490,569 151,578 11%

25-0000 Education, Training, and Library Occupations 8,273,764 9,296,638 1,022,874 12%


4,464,355 5,285,103 820,748 18%


7,132,483 8,443,434 1,310,951 18%

31-0000 Healthcare Support Occupations 3,577,985 4,716,599 1,138,614 32%

33-0000 Protective Service Occupations 3,194,006 3,378,670 184,664 6%


10,419,164 11,939,897 1,520,733 15%


6,105,534 7,483,630 1,378,096 23%

39-0000 Personal Care and Service Occupations 6,029,136 8,289,569 2,260,433 37%

41-0000 Sales and Related Occupations 20,848,671 23,523,574 2,674,903 13%

43-0000 Office and Administrative Support Occupations

24,672,093 24,466,758 (205,335) (1%)

45-0000 Farming, Fishing, and Forestry Occupations 1,230,885 1,241,241 10,356 1%



47-0000 Construction and Extraction Occupations 8,075,392 7,733,725 (341,667) (4%)


6,205,687 6,204,207 (1,480) 0%

51-0000 Production Occupations 11,037,136 9,389,406 (1,647,730) (15%)


10,327,923 10,375,613 47,690 0%

55-0000 Military occupations 2,097,000 2,061,143 (35,857) (2%)

99-0000 Unclassified Occupation 606,382 764,330 157,948 26%

Total 164,611,676 179,159,83 14,548,154 9%

Source: EMSI 2013.1

Table 19: National Jobs (2002-2012)

The biggest positive change in absolute number

of jobs was recorded in Sales and Related

Occupations (2,674,903 jobs, representing 13%

growth), Personal Care and Service Occupations

(2,260,433 jobs, representing 37% growth) and

Business and Financial Operations Occupations

(2,222,840 jobs, representing 28% growth).

Biggest positive change in % was recorded in

Personal Care and Service Occupations

(2,260,433 jobs, representing 37% growth).

Biggest negative change in absolute number of

jobs was recorded in Production Occupations (-

1,647,730 jobs, representing 15% decrease)

followed by Construction and Extraction

Occupations (-341,667 jobs, representing 4%

decrease) and Office and Administrative

Support Occupations (-205,335 jobs,

representing 1% decrease). Biggest negative

change in % of jobs was recorded in Production

Occupations (-1,647,730 jobs representing 15%

decrease).

Wages by Occupation

Hourly Wage

SOC Description Median Hourly Wage

State Median Hourly Wage

National Median Hourly Wage

11-0000 Management Occupations $19.01 $24.38 $31.40

13-0000 Business and Financial Operations Occupations $23.14 $26.07 $28.79

15-0000 Computer and Mathematical Occupations $24.65 $30.95 $35.10

17-0000 Architecture and Engineering Occupations $26.41 $32.79 $34.71

19-0000 Life, Physical, and Social Science Occupations $25.91 $28.92 $30.75

21-0000 Community and Social Service Occupations $17.93 $17.55 $19.62

23-0000 Legal Occupations $29.53 $30.95 $39.23

25-0000 Education, Training, and Library Occupations $19.06 $18.38 $21.59


$13.37 $14.95 $17.85

29-0000 Healthcare Practitioners and Technical Occupations $28.25 $31.63 $34.80



31-0000 Healthcare Support Occupations $11.40 $11.69 $12.45

33-0000 Protective Service Occupations $14.80 $16.72 $18.93

35-0000 Food Preparation and Serving Related Occupations $9.05 $9.12 $9.59


$9.76 $10.49 $10.73

39-0000 Personal Care and Service Occupations $9.16 $9.45 $10.16

41-0000 Sales and Related Occupations $12.46 $14.82 $15.60

43-0000 Office and Administrative Support Occupations $12.94 $14.30 $15.73

45-0000 Farming, Fishing, and Forestry Occupations $10.60 $11.52 $10.74

47-0000 Construction and Extraction Occupations $15.36 $17.07 $17.69

49-0000 Installation, Maintenance, and Repair Occupations $17.09 $18.70 $18.96

51-0000 Production Occupations $14.02 $15.77 $15.47

53-0000 Transportation and Material Moving Occupations $13.96 $14.76 $14.83

55-0000 Military occupations $12.57 $12.61 $13.24

99-0000 Unclassified Occupation $14.42 $13.21 $14.91

Total $14.98 $17.30 $19.05

Source: EMSI 2013.1

Table 20: Regional, State & National Median Hourly Wages (2012)

The occupations with highest Median Hourly

Wages are Legal Occupations ($29.53),

Healthcare Practitioners and Technical

Occupations ($28.25) and Architecture and

Engineering Occupations (26.41). The lowest

wages in the region are for the Food

Preparation and Serving Related Occupations

($9.16), Building and Grounds Cleaning and

Maintenance Occupations ($9.76) and Farming,

Fishing, and Forestry Occupations ($10.6).

Highest Median Hourly Wages in State scale

were in Architecture and Engineering

Occupations ($32.79), Healthcare Practitioners

and Technical Occupations ($31.63), Computer

and Mathematical Occupations and Legal

Occupations (both $30.95). While on the

National scale were Legal Occupations ($39.23)

followed by Computer and Mathematical

Occupations ($35.10) and Healthcare

Practitioners and Technical Occupations

($34.80). Lowest Median Hourly Wages in State

scale were in Food Preparation and Serving

Related Occupations ($9.12), Personal Care and

Service Occupations ($9.45) and Building and

Grounds Cleaning and Maintenance

Occupations ($10.49). On the National scale

were Food Preparation and Serving Related

Occupations ($9.59), Personal Care and Service

Occupations ($10.16) and Building and Grounds

Cleaning and Maintenance Occupations

($10.73). Community and Social Service

Occupations and Education, Training, and

Library Occupations Median Hourly Wages in

the region were higher than State Median

Hourly Wages.



Part IV: Education Completions

Part IV of the report describes in detail the

educational programs in the region including

regional completions, openings, jobs, median

wages and also career clusters and Educational

Attainment.

Institution Completions

The table below shows the top ten programs by

completion. Institutions included are Cloud

County Community College, Flint Hills Technical

College, North Central Kansas Technical College,

Salina Area Technical College, and Manhattan

Area Technical College. Program Code

represents CIP (Classification of Instructional

Programs) which is a standard numerical code

for a post-secondary course of study, developed

and defined by the U.S. Department of

Education's National Center for Education

Statistics. Column Growth % represents overall

change between years.

Program Code

Program Institution Completions

Regional Jobs (2012)

Growth (2002-2012)

51.3902 Nursing Assistant/Aide and Patient Care Assistant/Aide 431 61515 18%

51.3901 Licensed Practical/Vocational Nurse Training 166 29452 8%

24.0101 Liberal Arts and Sciences/Liberal Studies 147 13849 26%

51.2603 Medication Aide 112 7304 -12%

51.3801 Registered Nursing/Registered Nurse 93 88098 42%

51.9999 Health Professions and Related Clinical Sciences, Other 63 0 0%

47.0604 Automobile/Automotive Mechanics Technology/Technician

60 31516 -68%

52.0401 Administrative Assistant and Secretarial Science, General 56 163864 0%

48.0508 Welding Technology/Welder 53 17574 15%

47.0201 Heating, Air Conditioning, Ventilation and Refrigeration Maintenance Technology/Technician

47 9432 54%

Source: EMSI 2013.1 Table 21: Institutional Completions (2011)

Regional Completions

Column Growth represents overall change between years.

CIP Program Regional Completions (2011)

Regional Openings (2002)



Growth in Jobs (2002-2012)

51.3902 Nursing Assistant/Aide and Patient Care Assistant/Aide

431 85 2,252 2,210 (2%)

13.1202 Elementary Education and Teaching 323 114 1,460 1,631 12%

52.0201 Business Administration and Management, General

264 286 5,761 6,136 6%

51.3901 Licensed Practical/Vocational Nurse Training

251 48 933 979 5%



51.3801 Registered Nursing/Registered Nurse 215 167 2,414 2,595 7%

52.0301 Accounting 197 45 1,131 1,350 19%

19.0701 Human Development and Family Studies, General

190 6 108 128 19%

01.0901 Animal Sciences, General 180 219 9,758 8,632 (12%)

24.0101 Liberal Arts and Sciences/Liberal Studies 178 386 1,939 2,566 32%

45.0101 Social Sciences, General 173 4 59 59 0%

52.1401 Marketing/Marketing Management, General

157 32 531 611 15%

45.1101 Sociology 137 0 3 2 (37%)

25.0101 Library and Information Science 134 14 224 239 7%

09.0401 Journalism 134 37 429 428 0%

42.0101 Psychology, General 124 21 264 339 28%

14.1901 Mechanical Engineering 123 36 436 511 17%

52.0801 Finance, General 121 84 1,746 2,382 36%

13.0301 Curriculum and Instruction 119 7 109 142 29%

13.1314 Physical Education Teaching and Coaching

118 203 2,783 3,035 9%

51.2603 Medication Aide 112 11 156 166 6%

Source: EMSI 2013.1

Table 22: Regional Completions (2011)

The following map illustrates the division of

high school graduate students over the region.

The most graduates were concentrated in Riley

and Salina counties. You can also see change in

ACT scores between years 2010 and 2011. If the

blue section of pie chart is bigger than the red

one, the ACT score was improved. This is not

case of many schools. Most of them remain

stable.



The following map shows graduation the ratio

over all regions. The larger the blue section of

the pie chart the higher the graduation rate of

students at certain high schools.



Regional Programs

Top Ten Regional Completions by Program

CIP Program Regional Completions (2011)

51.3902 Nursing Assistant/Aide and Patient Care Assistant/Aide 431

13.1202 Elementary Education and Teaching 323

52.0201 Business Administration and Management, General 264

51.3901 Licensed Practical/Vocational Nurse Training 251

51.3801 Registered Nursing/Registered Nurse 215

52.0301 Accounting 197

19.0701 Human Development and Family Studies, General 190

01.0901 Animal Sciences, General 180

24.0101 Liberal Arts and Sciences/Liberal Studies 178

45.0101 Social Sciences, General 173

Source: EMSI 2013.1



Table 23: Top Ten Regional Completions (2011)

Highest number of Completions was recorded in

Nursing Assistant/Aide and Patient Care

Assistant/Aide (431) followed by Elementary

Education and Teaching (323) and in Business

Administration and Management, General

(264).

Top Ten Regional Openings by Program

CIP Program Regional Openings (2011)

12.0505 Food Preparation/Professional Cooking/Kitchen Assistant 270

52.0201 Business Administration and Management, General 248

01.1102 Agronomy and Crop Science 232

13.1314 Physical Education Teaching and Coaching 231

01.0901 Animal Sciences, General 229

01.1103 Horticultural Science 228

09.0100 Communication, General 226

01.0307 Horse Husbandry/Equine Science and Management 226

01.0101 Agricultural Business and Management, General 225

52.0101 Business/Commerce, General 225

Source: EMSI 2013.1

Table 24: Top Ten Regional Openings (2011)

Top three Programs by number of Openings

were Food Preparation/Professional

Cooking/Kitchen Assistant (270), Business

Administration and Management (248), and

General and Agronomy and Crop Science (232).

Top Ten Median Hourly Wages by Program

CIP Program Median Hourly Wage

40.0801 Physics, General $49.68

14.0701 Chemical Engineering $49.20

14.0301 Agricultural Engineering $48.69

14.2301 Nuclear Engineering $48.63

40.0101 Physical Sciences $47.90

04.0601 Landscape Architecture $45.89

45.1001 Political Science and Government, General $44.73

04.0301 City/Urban, Community and Regional Planning $43.24

42.9999 Psychology, Other $42.36



40.0601 Geology/Earth Science, General $41.89

Source: EMSI 2013.1

Table 25: Top Ten Median Hourly Wages (2012)

Top three Programs by Median Hourly Wage

were Physics, General ($49.68), Chemical

Engineering ($49.20) and Agricultural

Engineering ($48.69).

Top Ten Regional Jobs by Program

CIP Program Regional Jobs (2002)


01.1102 Agronomy and Crop Science 9,804 8,687

01.0901 Animal Sciences, General 9,758 8,632

01.1103 Horticultural Science 9,698 8,586

01.0307 Horse Husbandry/Equine Science and Management 9,656 8,533

01.0101 Agricultural Business and Management, General 9,647 8,524

52.0201 Business Administration and Management, General 5,761 6,136

12.0505 Food Preparation/Professional Cooking/Kitchen Assistant 5,646 5,752

52.0101 Business/Commerce, General 5,038 5,463

52.0401 Administrative Assistant and Secretarial Science, General 4,473 4,554

44.0401 Public Administration 3,727 4,011

Source: EMSI 2013.1

Table 26: Top Ten Regional Jobs (2012)

Top three programs by number of jobs in 2012

were Agronomy and Crop Science (8,687)

followed by Animal Sciences (8,632), General

and Horticultural Science (8,586).

Regional Job Growth

Column Growth represents overall change

between years. Highest growth in number of

jobs was recorded in Veterinary Medicine,

Veterinary Sciences/Veterinary Clinical

Sciences, General Pre-Veterinary Studies (130%)

followed by Home Health Aide/Home Attendant

(73%) and Psychology, Other (65%). Highest

decrease was recorded in Sociology (37%, but it

was decrease just from 3 to 2 jobs), Animal

Sciences, General (34%) and Nursing

Assistant/Aide and Patient Care Assistant/Aide

(33%, but just from 4 to 3 jobs).

CIP Program Regional Jobs (2002)


Growth in Jobs (2002-2012)

51.2401 Veterinary Medicine 72 165 130%

51.2501 Veterinary Sciences/Veterinary Clinical Sciences, General 72 165 130%



51.1104 Pre-Veterinary Studies 72 165 130%

51.2602 Home Health Aide/Home Attendant 1,385 2,396 73%

42.9999 Psychology, Other 27 45 65%

25.0103 Archives/Archival Administration 905 1,332 47%

51.2301 Art Therapy/Therapist 41 60 45%

31.0505 Kinesiology and Exercise Science 41 60 45%

45.0701 Geography 2 3 45%

15.1401 Nuclear Engineering Technology/Technician 5 8 44%

47.0105 Industrial Electronics Technology/Technician 420 350 (17%)

52.0407 Business/Office Automation/Technology/Data Entry 243 201 (18%)

01.0201 Agricultural Mechanization, General 207 166 (19%)

01.0204 Agricultural Power Machinery Operation 207 166 (19%)

47.0604 Automobile/Automotive Mechanics Technology/Technician

1,307 1,028 (21%)

01.0401 Agricultural and Food Products Processing 621 477 (23%)

51.2310 Vocational Rehabilitation Counseling/Counselor 156 113 (28%)

45.0201 Anthropology 4 3 (33%)

47.0603 Autobody/Collision and Repair Technology/Technician 480 315 (34%)

45.1101 Sociology 3 2 (37%)

Source: EMSI 2013.1

Table 27: Regional Job Growth (2002-2012)

Regional Historic Completions

CIP Code Code

Description 2003 Completions

2011 Completions

01 AGRICULTURE, AGRICULTURE OPERATIONS, AND RELATED SCIENCES 510 547

03 NATURAL RESOURCES AND CONSERVATION 0 0

04 ARCHITECTURE AND RELATED SERVICES 161 146

05 AREA, ETHNIC, CULTURAL, GENDER, AND GROUP STUDIES 0 15

09 COMMUNICATION, JOURNALISM, AND RELATED PROGRAMS 214 198

10 COMMUNICATIONS TECHNOLOGIES/TECHNICIANS AND SUPPORT SERVICES

24 8

11 COMPUTER AND INFORMATION SCIENCES AND SUPPORT SERVICES 375 165



12 PERSONAL AND CULINARY SERVICES 246 137

13 EDUCATION 1,059 1,169

14 ENGINEERING 390 472

15 ENGINEERING TECHNOLOGIES AND ENGINEERING-RELATED FIELDS 217 257

16 FOREIGN LANGUAGES, LITERATURES, AND LINGUISTICS 36 56

19 FAMILY AND CONSUMER SCIENCES/HUMAN SCIENCES 309 392

22 LEGAL PROFESSIONS AND STUDIES 6 6

23 ENGLISH LANGUAGE AND LITERATURE/LETTERS 80 107

24 LIBERAL ARTS AND SCIENCES, GENERAL STUDIES AND HUMANITIES 204 184

25 LIBRARY SCIENCE 127 141

26 BIOLOGICAL AND BIOMEDICAL SCIENCES 285 181

27 MATHEMATICS AND STATISTICS 40 76

28 MILITARY SCIENCE, LEADERSHIP AND OPERATIONAL ART 0 0

29 MILITARY TECHNOLOGIES AND APPLIED SCIENCES 0 0

30 MULTI/INTERDISCIPLINARY STUDIES 6 62

31 PARKS, RECREATION, LEISURE, AND FITNESS STUDIES 134 181

32 BASIC SKILLS AND DEVELOPMENTAL/REMEDIAL EDUCATION 0 0

33 CITIZENSHIP ACTIVITIES 0 0

34 HEALTH-RELATED KNOWLEDGE AND SKILLS 0 0

35 INTERPERSONAL AND SOCIAL SKILLS 0 0

36 LEISURE AND RECREATIONAL ACTIVITIES 0 0

37 PERSONAL AWARENESS AND SELF-IMPROVEMENT 0 0

38 PHILOSOPHY AND RELIGIOUS STUDIES 11 9

39 THEOLOGY AND RELIGIOUS VOCATIONS 52 46

40 PHYSICAL SCIENCES 67 77

41 SCIENCE TECHNOLOGIES/TECHNICIANS 0 0

42 PSYCHOLOGY 183 145

43 HOMELAND SECURITY, LAW ENFORCEMENT, FIREFIGHTING AND RELATED PROTECTIVE SERVICES

41 37

44 PUBLIC ADMINISTRATION AND SOCIAL SERVICE PROFESSIONS 37 34

45 SOCIAL SCIENCES 413 501

46 CONSTRUCTION TRADES 139 108



47 MECHANIC AND REPAIR TECHNOLOGIES/TECHNICIANS 271 206

48 PRECISION PRODUCTION 35 60

49 TRANSPORTATION AND MATERIALS MOVING 49 59

50 VISUAL AND PERFORMING ARTS 193 195

51 HEALTH PROFESSIONS AND RELATED PROGRAMS 709 1,600

52 BUSINESS, MANAGEMENT, MARKETING, AND RELATED SUPPORT SERVICES

1,095 1,022

53 HIGH SCHOOL/SECONDARY DIPLOMAS AND CERTIFICATES 0 0

54 HISTORY 72 82

60 RESIDENCY PROGRAMS 0 0

Total 7,790 8,681

Source: EMSI 2013.1

Table 28: Regional Historic Completions (2003-2011)

Highest number of Regional Historic

Completions in 2011 was recorded in Health

professions and related programs (1,600),

Education (1,169) and Business, Management,

Marketing and related Support services (1,022).

The lowest number of completions (0) was

recorded in twelve programs.



Career Cluster Data Report

A career cluster is a group of related

occupations that require similar interests,

training, and skills. Career clusters include

"pathways" that define related entry-level,

intermediate, and advanced occupations. The

career clusters used here are used by the States

Career Clusters Initiative

(www.careerclusters.org) and are based on

standard SOC occupations. It is important to

note that some occupations are found in

multiple clusters, and some occupations are not

found in any cluster.

Jobs and Jobs Change

Column Growth % represents overall change

between years. The highest number of jobs was

recorded in Business, Management &

Administration cluster (36,946), Marketing,

Sales & Service cluster (28,876) and Hospitality

& Tourism cluster (27,507). The least jobs were

recorded in Information Technology cluster

(978) followed by Science, Technology,

Engineering & Mathematics (6,666) and in

Manufacturing cluster (6,910). Biggest positive

absolute change were recorded in Government

& Public Administration cluster (10,627),

Human Service cluster (3,903) and Business,

Management & Administration cluster (2,431),

negative change was recorded just in one

cluster, Transportation, Distribution, & Logistics

cluster (-139). With regard to Growth, highest

change was presented by Government & Public

Administration cluster (66.16%), Human

Services cluster (20.18%) and Law, Public Safety,

Corrections & Security cluster (18.64%),

decrease was recorded just in one cluster,

Transportation, Distribution, & Logistics (-

0.64%).

Cluster Name 2002 Jobs 2012 Jobs Change % Growth

Government & Public Administration 16,063 26,690 10,627 66.16%

Human Services 19,337 23,240 3,903 20.18%

Business, Management & Administration 34,515 36,946 2,431 7.04%

Health Science 15,854 17,683 1,829 11.54%

Education & Training 13,323 14,997 1,674 12.56%

Hospitality & Tourism 25,861 27,507 1,646 6.36%

Architecture & Construction 10,945 12,271 1,326 12.12%

Finance 8,691 9,889 1,198 13.78%

Law, Public Safety, Corrections & Security 6,093 7,229 1,136 18.64%

Agriculture, Food & Natural Resources 17,480 18,485 1,005 5.75%

Marketing, Sales & Service 27,929 28,876 947 3.39%

Manufacturing 6,002 6,910 908 15.13%

Arts, A/V Technology & Communications 6,452 7,248 796 12.34%

Science, Technology, Engineering & Mathematics 5,938 6,666 728 12.26%

Information Technology 922 978 56 6.07%



Transportation, Distribution, & Logistics 21,880 21,741 -139 -0.64%

Source: EMSI 2013.1

Table 29: Jobs and Job Change (2002-2012)

Hourly Earnings

Cluster Name 2012 Hourly Earnings

Government & Public Administration $15.13

Human Services $14.90

Business, Management & Administration $16.31

Health Science $19.88

Education & Training $18.01

Hospitality & Tourism $14.12

Architecture & Construction $18.53

Finance $19.09

Law, Public Safety, Corrections & Security $23.89

Agriculture, Food & Natural Resources $20.39

Marketing, Sales & Service $12.54

Manufacturing $19.03

Arts, A/V Technology & Communications $24.41

Science, Technology, Engineering & Mathematics $29.81

Information Technology $20.73

Transportation, Distribution, & Logistics $16.78

Source: EMSI 2013.1

Table 30: Hourly Earnings (2012)

The highest Hourly Earnings from all career

clusters had Science, Technology, Engineering &

Mathematics cluster ($29.81), Arts, A/V

Technology & Communications cluster ($24.41),

Law, Public Safety, Corrections & Security

cluster ($23.89). Lowest Hourly Earnings were

presented by Marketing, Sales & Service cluster

($12.54), Hospitality & Tourism ($14.12) and

Human Services cluster ($14.90).

Location Quotient

Cluster Name LQ

Government & Public Administration 2.31

Education & Training 1.17

Agriculture, Food & Natural Resources 0.98

Human Services 0.84

Hospitality & Tourism 0.83

Manufacturing 0.98

Health Science 0.77

Marketing, Sales & Service 0.8



Law, Public Safety, Corrections & Security 0.9

Transportation, Distribution, & Logistics 0.81

Arts, A/V Technology & Communications 0.82

Business, Management & Administration 0.74

Architecture & Construction 0.85

Finance 0.7

Science, Technology, Engineering & Mathematics 0.8

Information Technology 0.5

Source: EMSI 2013.1

Table 31: Location Quotient (2012)

Highest value of Location Quotient had the

Government & Public Administration cluster

(2.31), Education & Training cluster (1.17) and

Agriculture, Food & Natural Resources cluster

(0.98). Lowest value of Location Quotient was

presented by Information Technology cluster

(0.5) followed by Science, Technology,

Engineering & Mathematics cluster (0.8) and

Finance cluster (0.7).

Openings

Openings represents sum of new and

replacement jobs in the occupation over the

entire timeframe. Annual Openings represents

the sum of new and replacement jobs in the

occupation over the entire timeframe, divided

by the number of years in the timeframe. The

most openings could be found in Business,

Management & Administration (21,185),

Marketing, Sales & Service (16,913) and

Hospitality & Tourism clusters (15,754). The

least positions appeared in Information

Technology (676), Science, Technology,

Engineering & Mathematics (4,069) and Law,

Public Safety, Corrections & Security clusters

(4,454).

Cluster Name Openings Annual Openings

Government & Public Administration 14,114 1,411

Human Services 15,739 1,574

Business, Management & Administration 21,185 2,118

Health Science 10,785 1,079

Education & Training 8,867 887

Hospitality & Tourism 15,754 1,575

Architecture & Construction 7,896 790

Finance 7,069 707

Law, Public Safety, Corrections & Security 4,454 445

Agriculture, Food & Natural Resources 11,707 1,171

Marketing, Sales & Service 16,913 1,691



Manufacturing 4,814 481

Arts, A/V Technology & Communications 4,659 466

Science, Technology, Engineering & Mathematics 4,069 407

Information Technology 676 68

Transportation, Distribution, & Logistics 12,938 1,294

Source: EMSI 2013.1

Table 32: Openings (2002-2012)



Rank Career Clusters Report

Career Clusters Ranked by Growth

Figure 20: Career Cluster Job Growth (2002-2012)

-139

56

728

796

908

947

1,005

1,136

1,198

1,326

1,646

1,674

1,829

2,431

3,903

10,627

-1000 2000 5000 8000 11000

Human Services

Health Science

Education & Training

Finance

Agriculture, Food & Natural Resources

Government & Public Administration

Law, Public Safety, Corrections & Security

Business, Management & Administration

Hospitality & Tourism

Marketing, Sales & Service

Architecture & Construction

Manufacturing

Transportation, Distribution, & Logistics

Arts, A/V Technology & Communications

Information Technology

Science, Technology, Engineering & Mathematics

Career Cluster Job Growth (2002-2012)



Career Clusters Ranked by Location Quotient

Figure 21: Career Clusters ranked by LQ (2012)

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Career Clusters ranked by LQ

Government & PublicAdministration

Education & Training

Agriculture, Food & NaturalResources

Manufacturing

Law, Public Safety, Corrections& Security

Architecture & Construction

Human Services

Hospitality & Tourism

Arts, A/V Technology &Communications

Transportation, Distribution, &Logistics

Marketing, Sales & Service

Science, Technology,Engineering & Mathematics

Health Science

Business, Management &Administration



Educational Attainment

Race/Ethnicity 2012 Population

Less Than High School

High School Diploma College Degree

White, Non-Hispanic 169,967 14,331 98,729 56,907

White, Hispanic 10,597 3,255 5,291 2,051

Black, Non-Hispanic 7,646 765 4,388 2,493

Asian, Non-Hispanic 3,906 407 1,457 2,042

Two or More Races, Non-Hispanic 2,406 316 1,454 636

American Indian or Alaskan Native, Non-Hispanic

983 152 613 218

Black, Hispanic 529 97 303 130

American Indian or Alaskan Native, Hispanic 411 131 202 79

Two or More Races, Hispanic 349 84 186 78

Native Hawaiian or Pacific Islander, Non-Hispanic

250 11 171 68

Asian, Hispanic 145 36 75 34

Native Hawaiian or Pacific Islander, Hispanic 37 10 20 8

Total 197,226 19,595 112,889 64,742

Source: EMSI 2013.1

Table 33: Educational Attainment (2012)

With regards to ethnicity the majority of people

in the region were found to be White, Non-

Hispanic (169,967), followed by White, Hispanic

(10,597)and Black, Non/Hispanic (7,646). The

least number of people were Native Hawaiian

or Pacific Islander, Hispanic (37), Asian, Hispanic

(145) and Native Hawaiian or Pacific Islander,

Non-Hispanic (250). This distribution

corresponds with the distribution of education.

The most people with College Degree, High

School Diploma and Less Than High School were

also White, Non/Hispanic, followed by White,

Hispanic and Black Non-Hispanic. The other end

also looked similar to the population

distribution.



Race/Ethnicity Demographics

Figure 22: Race/Ethnicity Demographics (2012)



PART V - Innovation Assessment Survey

Introduction

This section describes the results of the regional innovation assessments survey conducted in the region. The

survey covered the following topics: demographics, regional environment, region definition, local decision

making, regional performance, government programs/policies, regional issues, housing, quality of region for

business, and social networks. The survey was open during spring of 2013 for the regional population to take.

Online survey platform (surveymonkey) was used to deploy the survey in the region.

DEMOGRAPHICS

The respondents were initially inquired about their county of residence, county of work, type of organization,

and the geographic limits of their organization.

County of Residence

Clay (14.5%) and Ellsworth (13.3%) Counties had the highest representations of respondents living within

them. Geary had 10.8% and Dickinson was tied with Mitchell at 9.6%. None of the respondents were from

Chase or Morris County. One separate option was listed as living in Shawnee County.

Clay (14.5%)

Ellsworth (13.3%)

Geary (10.8%)

Dickinson (9.6%)

Mitchell (9.6%)

Saline (6.0%)

Cloud (4.8%)

Republic (4.8%)

Washington (4.8%)

Jewell (3.6%)

Lincoln (3.6%)

Ottawa (3.6%)

Riley (3.6%)

Marshall (2.4%)

Pottawatomie (2.4%)

Lyon (1.2%)

Wabaunsee (1.2%)



Workplace County

The chart belwo shows the place of work of the repsondents. Majority of respondents worked in these

counties: Clay (18.8%), Ellsworth (18.8%), Geary (15.3%), Dickinson (12.9%), Mitchell (12.9%), and Cloud

(10.6%). The lowest four were Morris, Wabaunsee, Lyon, and Chase Counties. 3.5% worked in Morris and 4.7%

worked in Chase, Lyon, and Wabaunsee.

Organization Type

The three majority organizations are local governments (33.87%), economic development offices (22.58%),

and regional businesses (20.97%). Together, they account for 77.42% of the respondents. The lowest reporting

organizations were state departments supporting regional businesses and social services, each at 1.61%.

0%

2%

4%

6%

8%

10%

12%

14%

16%

18%

20%

Regional Businesses (20.97%)

Economic Development Officees (22.58%)

Banks (9.68%)

Educational Institutions (4.84%)

Business Support Institutes (4.84%)

State Department Supporting Businesses (1.61%)

Local Governments (33.87%)

Social Services (1.61%)



Geographic Limits of Organization’s Community

In this region there is a wide variety in the reach of organizations. Over 30% of organizations reported having a

geographical limit of multiple counties. County limits, city limits, and national limits were each found in over

10% of the respondents. The “others” category includes educational institutions, business support institutes,

state departments supporting regional businesses, and social services.

0.0%

10.0%

20.0%

30.0%

40.0%

50.0%

60.0%

70.0%

80.0%

City Limits County Limits MultipleCounties

Multi-CityWithin the

Same County

Multi-CityAcross

Counties

MultipleStates

Nation

Banks Economic Development Offices Local Governments Others Regional Businesses



REGION AS DESCRIBED BY THE COMMUNITY

Regional Environment

This section describes the region as defined by the respondents.

Definition of the Region

The respondents were asked to define the region’s characteristics as chosen from a list and more than one

could be selected. This list contained eight different characteristics with which to describe a region: having a

hub or center, a similar culture, similar needs, similar economies, similar issues/concerns, political/identified

boundaries, and all of the above. About 60% of all respondents picked the “all of the above” option. The next

two highest were “similar issues/concerns” and “similar needs.” The responses were broken down in the chart

below by organization type.

0.0% 10.0% 20.0% 30.0% 40.0% 50.0%

All of the Above

Political or Identified Boundaries

Similar Issues/Concerns

A Similar Economy

Similar Needs

A Similar Culture

A Hub or Center

Regional Businesses Others Local Governments Economic Development Offices Banks



Local Decision Making

Respondents were asked how a healthy region should make local decisions. The majority chose that local

decisions should be made to maximize the benefit for the local area while causing the least harm to the

region. This answer received a 53.2% response. Receiving 25.3% was the option that local decisions should be

made to benefit the whole region while less than 2% said that they should be made to help local areas stand

out in the region. Below, this data is broken down by organization type.

0% 10% 20% 30% 40% 50% 60% 70%

Benefit the Whole Region

Help Most Criticial Regional Issues

Cause No Harm in Other Parts of the Region

Help a Local Area Stand Out in the Region

Maximize Local Area Benefit, Minimize RegionalHarm




Regional Performance

This section shows how the respondents rated the region based on multiple factors. Each factor was rated

very harmful, harmful, neutral, beneficial, or very beneficial. The following graph represents the average of

the values given by all of the respondents. Overall, the quality of higher education, quality of life, and quality

of tech assistance offered by universities were the highest rated of the 16 factors. The only factors to fall

below neutral into harmful territory are the availability of skilled workers, availability of workers, availability of

labs for testing/development, regulations affecting business, and taxation relative to other regions. On the

following pages this will be broken down by factor and organization type.

Very Harmful Harmful Neutral Beneficial Very Beneficial

Cost of Doing Business

Cost of Living for Employees

Quality of Life

Quality of Higher Education

Quality of University Tech Assistance

Availability of Skilled Workers

Availability of Workers

Intellectual Protection Counsel

Availability of Capital

Availability of Labs for Testing

Quality of Specialized Suppliers

Availability of Demanding Customers

Regulations Affecting Business

Taxation Relative to Other Regions

Government Growth Incentives

Promotional Campaigns for the Region

Regional Performance Factors Regional Businesses Others Local Government Economic Development Offices Banks




The most supportive group of the region’s cost of

doing business is the economic development

offices. Over 80% of them reported this cost as

being beneficial, and none reported it as being

harmful. Both regional businesses and local

governments had members that voted this factor

as very beneficial to the region. Businesses had a

variety of opinions but the majority of them were

positive.


Banks in the region considered cost of living for

employees the most beneficial and none found

them harmful. Over 60% of economic development

offices found it to be positive, but nearly 20%

considered it harmful. For businesses, the majority

view it as either beneficial (38%) or very beneficial

(25%). However, 38% called it harmful. Local

government and “others” had roughly the same

percentages viewing cost of living as beneficial, but

the “others” category was the only one to view it

as very harmful (13%).

0%10%20%30%40%50%60%70%80%


Banks

EconomicDevelopment Offices

Local Governments

Others

Regional Businesses

0%

10%

20%

30%

40%

50%

60%

70%

80%


Banks


Local Governments

Others

Regional Businesses



Quality of Life

Overall, the quality of life in the region registers as

a positive aspect of the region. A very few number

of respondents list it as harmful, while the vast

majority consider it beneficial or very beneficial.

Banks and economic development offices are the

most consistent in considering the quality of life

beneficial with 80% and 82% responses in that

category, though they are the only two to view it as

harmful. The other three categories are spread

between neutral, beneficial, and very beneficial.

Most notably, 38% of the businesses consider

quality of life to be very beneficial, compared to

the next highest (“Others” category) being at 14%

very beneficial. Quality of life appears to be one of

the region’s strengths.


The region’s quality of higher education is the

highest rated of the factors presented to the

respondents. 100% of banks view it has beneficial

or higher, 40% of them choosing the very beneficial

option. 91% of economic development offices think

of it as beneficial or greater. “Others” and regional

business both hold a 75% view that it’s beneficial

or better. Local government had the lowest rate of

voting beneficial or better (65%) with the

remainder considering it neither beneficial nor

harmful. Only the “others” category had

respondents that viewed quality of life as harmful.

0%10%20%30%40%50%60%70%80%

Quality of Life

Banks


Local Governments

Others

Regional Businesses

0%

10%

20%

30%

40%

50%

60%


Banks


Local Governments

Others

Regional Businesses




Compared to quality of higher education, the

respondents are not as enthusiastic about the

quality of university tech assistance but they are

still very positive. The organizations that view this

factor most often as beneficial or better are the

“others” category (85%), banks (80%), and regional

businesses (76%). Of these, banks are the highest

in reporting it as very beneficial (40%). Local

government and economic development offices

are more likely than the others to view this as a

neutral factor. 13% of regional businesses and 6%

of local governments think the quality of university

tech assistance is a harmful factor for the region.


The availability of skilled workers, according to the

respondents, is something the region needs to

work on. Only regional businesses have at least

50% viewing this factor as beneficial or better.

Banks are the only group to not have any negative

viewers of this factor but 60% take a neutral view.

50% of local government agencies hold this as

either harmful or very harmful. 38% of “others”,

38% of businesses, and 27% of economic

development offices consider the availability of

skilled workers as harmful or worse to the region.

Local governments and businesses had the most

diverse set of opinions, ranging from very harmful,

to very beneficial, and every category between.

0%

10%

20%

30%

40%

50%

60%

70%


Banks


Local Governments

Others

Regional Businesses

0%

10%

20%

30%

40%

50%

60%


Banks


Local Governments

Others

Regional Businesses




The respondents also viewed the availability of

workers negatively. None of the organizations held

a dominantly positive view. Banks were by far the

most positive with 40% viewing it as beneficial and

being the only organization to not have any

harmful or very harmful votes against this factor.

The availability of workers was considered harmful

or worse by 55% of economic development offices,

50% of businesses, 38% of “others”, and 37% of

local governments. Although businesses were the

second highest in reporting this factor as harmful,

they had the highest view of it being very beneficial

(25%). Local governments and businesses had the

widest range of views.


The majority of organization types had over 50%

reporting this as neither helpful nor harmful:

businesses (63%), economic development offices

(55%), and local governments (50%). Banks led the

way on the positive side with 60% of them viewing

it as beneficial and none considering it harmful.

50% of “others” considered it beneficial as well.

Only economic development offices, local

governments, and “others” considered this harmful

at 18%, 22%, and 25% respectfully. None of the

organization types had respondents who

considered this as a very harmful regional factor.

0%

10%

20%

30%

40%

50%

60%


Banks


Local Governments

Others

Regional Businesses

0%

10%

20%

30%

40%

50%

60%


Banks


Local Governments

Others

Regional Businesses




The availability of capital is considered most

beneficial by banks (60%), “others” (57%), and

economic development offices (54%). Economic

development offices were also the highest in

viewing this factor as harmful, at a 36% rate.

Regional businesses were the only other notable

group to view capital availability as harmful or

worse at 26%. Businesses were the only ones with

a very harmful vote. Local governments had the

highest rate of neutrality (63%) followed by

“others” (43%), banks (40%), and businesses (38%).

Availability of Labs for Testing

No groups find this to be very beneficial to the

region and a majority considers it neutral or

harmful. No banks found this to be beneficial; 60%

are neutral and 40% say that it is harmful to the

region. The groups with the highest rates of calling

this harmful or worse are the “others” category

(63%), local governments (45%), and banks (40%).

Only two organization types report over a 25%

favorable rate. These two are regional businesses

with 38% reporting beneficial and economic

development offices with 27% reporting it

beneficial. This is the lowest rated factor overall.

0%

10%

20%

30%

40%

50%

60%


Banks


Local Governments

Others

Regional Businesses

0%

10%

20%

30%

40%

50%

60%Availability of Labs for Testing

Banks


Local Governments

Others

Regional Businesses




Overall the quality of specialized suppliers is seen

as only slightly beneficial. The organizations who

most feel this factor as beneficial or better for the

region are economic development offices (51%)

and businesses (38%). A large portion of banks

economic development offices and local

governments are neutral on this issue at 60%, 45%,

and 44% respectively. The three with the most

votes for harmful or very harmful are banks (40%),

the “others” category (38%), and local

governments (34%).


Availability of demanding customers is mostly seen

as neither harmful nor beneficial to the region by

the respondents. All five of the organization types

had over a 50% neutral voting rate. 82% of

economic development offices were neutral, 63%

of businesses, 63% of the “others” category, 60% of

banks, and 59% of local governments felt this was a

neutral factor. 26% of businesses considered it

beneficial or very beneficial, and 24% of local

governments considered it beneficial. 25% of the

“others” category thought of this as a harmful

factor. There were no votes for this being a very

harmful factor for the region.

0%

10%

20%

30%

40%

50%

60%


Banks


Local Governments

Others

Regional Businesses

0%10%20%30%40%50%60%70%80%


Banks


Local Governments

Others

Regional Businesses




Regulations affecting business is found to be

slightly harmful overall. 63% of businesses, 40% of

banks, and 25% of “others” find it to be either

harmful or very harmful. None of the banks found

this to be a beneficial aspect of the region. Higher

percentages of local governments and economic

development offices feel this is a beneficial factor

of the region. 50% of local governments and 45%

percent of economic development offices thought

the regulations to be a beneficial factor. By far the

group with the highest percentage of people

neutral on this issue is banks with 60%.


Taxation relative to other regions is one of the

weakest factors according to the respondents.

While 55% of economic development offices and

41% of local governments think its beneficial, 80%

of banks, 76% of businesses, and 36% of local

governments call it either harmful or very harmful.

75% of the “others” category, and 36% of

economic development offices feel that this factor

is neither helpful nor harmful to the region. None

of the five organization types view this as a very

beneficial factor.


While overall this factor is seen as beneficial, not all

of the organization types feel that way. The banks

singlehandedly throw off the bell curve that has

been seen, to one degree or another, in all of these

factors. 60% of banks find the government growth

incentives to be harmful compared to the 25% of

the closest group to feel it is harmful. 45% of

economic development offices, 41% of local

governments, 38% of businesses, and 38% of

0%

10%

20%

30%

40%

50%

60%

70%


Banks


Local Governments

Others

Regional Businesses

0%

10%

20%

30%

40%

50%

60%

70%


Banks


Local Governments

Others

Regional Businesses

0%

10%

20%

30%

40%

50%

60%


Banks


Local Government

Others

Regional Businesses



“others” view this factor as either beneficial or very beneficial.


Most of the respondents held the opinion that

promotional campaigns are neither beneficial nor

harmful to the region, and the next largest group

supports this factor to be beneficial. Over 50% of

every group takes the neutral position: 82% of

economic development offices, 65% of local

governments, 63% of regional businesses, 60% of

banks, and 50% of “others”. 40% of banks, 38% of

businesses, 35% of local governments, and 25% of

“others” view promotional campaigns for the

region to be either beneficial or very beneficial.

0%

10%

20%

30%

40%

50%

60%

70%

80%


Banks


Local Government

Others

Regional Businesses



Government Program and Policy Issues

Most of the responses stated that taxes and more specifically property taxes need to be lower. High property

taxes are preventing new businesses from coming to the area and are in turn hurting the entire local

economy. Many others expressed the need for more housing and more affordable housing. There seems to be

a need for small business incentives and more support for education in the region. Needs for increased

education from K-12, job training, technical schools, and universities were mentioned. The survey-takers

report a need for an improved and increased workforce. One person wrote that there should be expanded

work opportunities for 14-18 year olds. Several infrastructure and quality of life issues were mentioned such

as water, electricity, transportation, high speed internet, childcare, and recreation. Other issues mentioned

were short-term borrowing complications, long term commitments from businesses and incentives to

facilitate these commitments, not enough cooperation between county and city governments, and finding

ways to market the region to attract people and businesses.



Regional Issues and Business Success

The respondents were given the opportunity to list what they considered to be the most important regional

issues that should be addressed to improve any business’s prospects for success. Just as with the program and

policy problems listed, housing was once again a prominent issue. Many people voiced the need for affordable

housing for the workforce. Many also mentioned a need for more skilled workers and higher wages. Several

people listed schools and business education as well as incentives for new businesses. People want to see

better transportation, affordable health insurance and other quality of life enhancements such as outdoor

recreation. Other issues noted were a need for investment groups to research and support community

businesses, a higher percentage of equity capital compared to borrowed capital, keeping sales and property

taxes at a competitive level to attract more people and businesses, and more regional businesses to list jobs

on the internet so people from outside of the region will know about them.



Housing

This section shows the results of questions regarding the need for housing, annual requirements for single

versus multi-family units, and an open ended response as to how to improve the availability of quality

housing.

Housing Need

The survey showed that the vast majority of

respondents think there is an unfulfilled quality

housing need. 100% of banks and economic

development offices agreed to this point. Also, 83%

of businesses and 77% of local governments held

the same opinion.

Single/Multi-Family Housing Estimates

Next respondents were asked to give an estimate

of the annual requirement for new housing in the

region. They were asked about both single and

multi-family housing. The graph to the right shows

the average values given by each organization type.

The overall average was about 44 single family

units, and 24 multi-family units. Banks and

economic development offices were the only ones

to have a major difference between their single

and multi-house estimates. They both had a

significantly lower estimate for multi-family houses

compared to the other organization types. Banks

had the highest estimate for single family housing

by over 14 units.

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Yes No

Unfulfilled Housing Need Banks

EconomicDevelopmentOfficesLocalGovernments

Others

RegionalBusinesses

0.0

10.0

20.0

30.0

40.0

50.0

60.0

Single FamilyHousing

Units

Multi-FamilyHousing

Units

Banks

EconomicDevelopmentOffices

LocalGovernments

Others

RegionalBusinesses



Availability of Quality Housing

When given the chance to offer solutions to the housing shortage, the most reported answer was to make

more affordable housing. There is more available lower-income and higher-income housing, but a massive

shortage of housing in the price range of working class citizens. Respondents noted the need for development

to be done to match the income range of the area’s housing demand. Rehabilitation of deteriorating units was

another common answer. This would not only provide more housing at a cheaper cost, but it would improve

the aesthetics of the community. More appropriate financing should be available to both potential home

owners and builders. They want more incentives (and less government regulations) for builders to build mid-

income housing and they want wages to increase so people can afford the housing that is available.



Quality of Region for Business Success

After considering all of the factors the participants were asked to rate the overall quality of the region as a

place for a business to succeed. Banks and economic development offices rated the region the highest, with

80% of banks and 85% of economic development offices rating it as a good location or better. Regional

businesses rated it the lowest, with only 50% grading it between good and excellent while the other half put it

as either fair or poor.

0%

0%

0%

0%

15%

46%

31%

8%

35%

41%

24%

38%

50%

13%

13%

38%

38%

13%

0% 10% 20% 30% 40% 50%

Poor Location

Fair Location

Good Location

Very Good Location

Excellent Location

Regional Business Other Local Government Economic Development Office Banks



Regional Quality Projection

When asked about the quality of the region for business success in the next five years, the reaction was

optimistic. All organization types except for regional businesses think that the region will become a more

hospitable environment for businesses to succeed. This feeling is held by 75% of economic development

offices, 67% of banks, 57% of “others”, 54% of local government, and 43% of regional businesses. Only the

regional businesses had any who predict that the state of the region will decline. The rest believe that the

status quo will be maintained.

33%

67%

25%

75%

46%

54%

43%

57%

14%

43%

43%

0% 10% 20% 30% 40% 50% 60% 70% 80%

Decline

Stay the Same

Improve

Region for Business Success: 5-Year Projection




Institution Evaluation

The respondents were asked to value the interaction between these groups/institutions and business capacity

to innovate. Overall, the top three rated were banks, regional customers, and educational institutions. The

lowest rated were non-professional associations, angel investors, and venture capital firms. The chart below

shows the averages of how each organization type valued each group.

Not At AllValuable

SomewhatValuable

Valuable Quite Valuable ExtremelyValuable

Educational Institutions

Professional Service Firms

Regional Customers

Regional Suppliers

Other Regional Businesses

Banks

Venture Capital Firms

Angel Investors

Government Agencies

Industry/Cluster Associations

Non-Professional Associations

Entrepreneurial Networks

Business Assistance Centers

Value of Interaction to Innovation




Most Supportive Institutions to Innovation

Given the chance to name specific institutions that are important to regional innovation, by far

the top three were the North Central Regional Planning Commission (NCRPC), Kansas State

University (KSU), and North Central Kansas Small Business Development Centers (NCKSBDC).

Many people mentioned local banks and several mentioned North Central Kansas Technical

College (NCK Tech). Chambers of Commerce and Network Kansas both received considerable

mentions as well as several colleges such as Manhattan Area Technical College, Salina Area

Technical College, Cloud County Community College, and Washburn University. Other listings

include economic development agencies such as Smoky Hill, the SBA, accounting firms, local

governments, and various businesses.



University and Technical School Challenges

Many people stressed the need for connections between local businesses and schools. They

want proper training in the region that will provide students with the skills necessary to start

working in the region. It is important that graduates from the region stay in the region and that

more people come in to the region. They want incentives to help keep people in the region.

Survey-takers mentioned the need for more funding of post-high school institutions and

reducing the cost of education. A few people mentioned the need for outreach and online

education programs from universities and tech colleges. Some want to promote technical and

trade jobs as more attractive and successful careers in the area. Several listed different areas

that they want to see programs in the area. These include welding, design, fabrication,

machinists, health care workers, advertising, graphic arts, landscaping, technical writing,

business, accounting, electricians, plumbing, heating, carpentry, teaching, CNC, and other

technical training programs. Welding was the highest stressed program need.



Regional Norms and Attitudes

The respondents gave their feedback regarding specific statements about the region. These

statements revolved around regional attitudes towards diversity, collaboration, investment,

integration, and other aspects. The statements least agreed upon involved artist-business

interaction and the idea that business cultures learn from failure. Most agreed upon was

business celebration of growth, interaction between different sectors, and positive

environment for diversity.

StronglyDisagree

Disagree Neutral Agree StronglyAgree

Easy Integration of New Residents

Attractive For People of Diverse Backgrounds

Leaders Responsive Residents Irrespective of Ethnicity,Cultural Heritage, Gender, and Lifestyle

Business Culture Understands Failure as part of theLearning and Innovation Process

Frequent Interaction Between DifferentIndustry/Economic Sectors

Region Celebrates Growth, Not Just Absolute Size, ofCompanies

Artists and Business-People Frequently Interact

Local Governments Eagerly Partner With PrivateSector to Promote New Business Development

Business Leaders Treat New Companies as FullPartners in All Aspects of Industry Cooperation

Business Leaders Proactively Share Information andResources When Possible

Residents Actively Participate in CommunityDevelopment Organizations and Projects

Successful Business People Actively Invest in EconomicDevelopment Projects and Start-up Ventures




Social Networks

The various organizations were all asked if they regularly meet to discuss important issues in

the region. In total, it was found 60% meet regularly and 40% did not. The majority of these

were regional businesses and economic development offices with 83% and 67% reporting

respectively. Only 40% of banks, 46% of local governments, and half of the “others” claimed to

be regularly discussing these issues.

Group Formality

When asked whether or not their meetings were formally organized, the results were about

60% formal and 40% not formal. All of the banks, most of local governments, and “others” met

in formal groups. However, none of the regional businesses had formal groups, and neither did

half of the economic development offices.

40%

67%

46%

50%

83%

-60%

-33%

-54%

-50%

-17%

-90% -60% -30% 0% 30% 60% 90%

No - Yes


100%

50%

67%

75%

-50%

-33%

-25%

-100%

-100% -80% -60% -40% -20% 0% 20% 40% 60% 80% 100%

No - Yes




Formal Group Meeting Places

Formal group members were asked where their meetings took place. Government/organization

offices and formal conventions/conferences were the specific locations used most often by

formal groups, especially for economic development offices, local governments, and “others”.

EDG offices and college campuses were among some of the alternative locations reported by

organizations.

0%

10%

20%

30%

40%

50%

60%

70%

80%

Member Offices Government orOrganization Office

Formal Conventionsor Conferences

Other Location




Informal Group Meeting Places

The three most often used locations for informal groups are coffee shops, churches, and clubs.

Regional businesses, banks, economic development offices, and “others” primarily used coffee

shops as their meeting place. Local governments were the only ones to have a different main

meeting place. Their top choices were churches and clubs. Alternative locations listed by the

organizations were homes and offices.

Group Meeting Frequency

When asked about the frequency of their meetings, 85% of all groups reported that they held

regularly scheduled meetings, and 15% only had them under some special circumstances or

events. None of them chose the third option of meeting only rarely in an organized fashion.

0%

10%

20%

30%

40%

50%

Coffee Shops Clubs Churches Games Other Location


85%

15%

Regular Meetings

Only Special Occasions



Groups and Regional Development

The survey asked how well these formal/informal groups helped to develop the region. 30% of

respondents felt that they were very helpful to regional development, 26% said they were

somewhat helpful, 35% called them only a little bit helpful, and 9% claimed they weren’t at all

helpful.

Groups and Business Development

Respondents were also asked if these groups helped individual business owners in some way.

22% thought that groups were very helpful, 26% somewhat helpful, 43% a little bit helpful, and

9% not at all helpful to individual business owners.

9%

35%

26% 30%

0%

5%

10%

15%

20%

25%

30%

35%

40%

45%

50%

Not at All A Little Bit Somewhat Very Much

9%

43%

26% 22%

0%

5%

10%

15%

20%

25%

30%

35%

40%

45%

50%

Not at All A Little Bit Somewhat Very Much



Social Network Mapping

One of the objectives of the project was to map the social networks that exist in the North

Central region within the economic development community. A brief social network data

collection form was given to complete and return. The template had a list of key names in the

region. Every respondent was required to pick out their frequency of interaction with the

individual or bank institution and reason of connection.

The objective of this project element is to understand who is connected to whom and how. A

social network map provides an image of the connections at a point in time, but since these

networks are dynamic, they change over time. Moreover, a social network map is not just a

picture to look at but, when combined with the social network analysis metrics, provides an

insight into how those networks are formed, how dense the networks are, and where two

nodes (individuals) need to be tied (linked). It is also able to identify the shortest path to

facilitate the connection as well as who is the bridge between those two nodes.

The goal of developing these maps is to improve density of connectedness within the region’s

banks and economic development community. A name in the center of the graph probably has

the most ties and that’s because they provided their network information to generate the map.

These maps are based on preliminary information collected and are representative of the

collected information. This will not be a complete map of the region, since such information is

highly dynamic, but a segment of the current network that can be made visible. The more

effectively the network members can leverage their connections and the connections of others

the better they can cultivate new economic development opportunities within their

communities and the broader region.

The maps should be used to look at the ties between the organizations rather than individuals.

So these maps will represent a professional network rather than a personal or informal network

(e.g. more like LinkedIn rather than a Facebook network). These maps can be used to

strengthen the network by providing the possible connections to the community. Everyone

cannot be directly connected to everyone else, but using this map they can find a way to reach

someone using the available connections and their company connections.

Individual respondents have been sent links to maps with keys to their name, from this online

map individuals can see their position in this social network. The public may view the map, with

all names replaced with numbers to ensure privacy, at

http://public.tableausoftware.com/views/NCRPC_SNA/Finaldash?:embed=y

http://public.tableausoftware.com/views/NCRPC_SNA/Finaldash?:embed=y



Respondents Analysis

The survey was sent out to four different groups - the economic development offices, state

departments supporting regional businesses, educational institutes, regional businesses and

bankers.

The survey consists of two parts. First is filling connections with people from economic

development community and second is filling connections with banks.

A total of 33 responses were received with a total of 513 connections. In total the survey

includes 171 organizations. From 171 nodes are 92 banks (54%), 33 (19%) economic

development offices and 14 (8%) other organizations. Complete listings can be found in the

following chart.

33

14

92

11 11 10

0

10

20

30

40

50

60

70

80

90

100

EconomicDevelopment

Office

Other Bank StateDepartmentsSupporting

Business

EducationInstitute

RegionalBusiness

Organization Count



From 513 connections, 236 belong to economic development offices, 143 to others, 57 to

education institutions, 68 to state departments supporting regional businesses and 9 to banks.

106 connections were filled in both ways, which means that 53 are mutual. These connections

are made by 30 people.

Comparing the number of connections per person shows how active people from different

organizations are. Most active are those from state departments supporting regional businesses

with 34 connections per person. Second are economic development offices with 16.86

connections per person and third are other organizations with 14.3 connections per person.



The highest overall degree has Economic Development Offices, followed by Other institutions

and Banks. Also State departments supporting regional businesses and Education Institutions

have over 100.

The following charts represent the ratio of incoming connections and outcoming connections.

The horizontal axis represents incoming connections, vertical axis represents number of

outcoming connections. Bubble size represents the total number of connections.



The line in the graph represents equal number of incoming and outcoming connections.

Bubbles under this line have higher number of incoming connections and smaller outcoming.

Banks, Regional businesses and Bankers have higher number of incoming connections. Banks

and Regional businesses didn’t fill the survey, so they have 0 outcoming connections.

In the second graph you can see contribution of incoming and outcoming connections to total

number of connections among the organizations.

0

50

100

150

200

250

300

0 50 100 150 200 250

In/Out Ratio

EconomicDevelopment Office

Other

Bank

State DepartmentsSupporting Business

Education Institute

0

100

200

300

400

500

600

700

800

900

EconomicDevelopment

Office

Other Bank StateDepartmentsSupporting

Business

EducationInstitute

RegionalBusiness

Total VS Out VS In Degrees

In-Degree Out-Degree Total



The following map shows the number of connections between organization types. Color

represents organization type. Most connections are between people in Econ Development

Offices and Banks. Edge thickness represents number of connections. Exact numbers are

presented in following table.

The following map shows the spatial distribution of vertexes across the region. As you can see

most of them are located in bigger cities like Manhattan, Salina, Emporia or Junction City.



Network Maps

Social network maps for the North Central Regional Planning Commission Economic

Development Community are shown in the following sections. The social network maps can be

analyzed using a number of metrics including centrality. Centrality of a social network gives a

rough indication of the social power of a node based on how well they “connect” the network.

“Betweenness”, “Closeness”, and “Degree” are all measures of centrality. Graph layouts are

based on frequency of interaction.

Overall, 5% of the connections are in daily interaction, 12% in weekly and 27% monthly.

Measure: Degree

Degree is the count of the number of ties to other players in the network i.e. the number of

direct connections a node has. Higher degrees for a node might show that the node is an active

player in the network or is often a connector or hub in network. Most connected does not

mean most powerful position in network as power is depicted by connections of connections,

may be in an advantaged position in the network, may be less dependent on other individuals.

Size of the node increases with increasing degree and nodes with higher degree are towards

the center of the map.

Arrows show the direction of the connection. Thicker lines represent mutual connection. Total:

513 connections.

9%

17%

28%

27%

12%

5%

2%

Frequency of Interaction

N/A

Occasionally, whenneededA few times a year

At least once a month

At least once a week

At least once daily

Not filled



Degree Case 1:

All respondents of the survey



Degree Case 2:

Frequency =1 (i.e. interaction occasionally, when needed) Total 456 connections.



Degree Case 3:

Frequency =2 (i.e. interaction few times a year) Total 370 connections.



Degree Case 4:

Frequency =3 (i.e. at least once a month) Total 224 connections.



Degree Case 5:

Frequency =4 (i.e. interaction at least once a week) Total 86 connections.



Degree Case 6:

Frequency =5 (i.e. interaction at least once daily). Total 25 connections.


Data Sources and Calculations

State Data Sources

This report uses state data from the following agencies: Kansas Department of Labor, Labor Market

Information Services, and Kansas Wage Survey.

Glossary

Industry A group of businesses that produce similar goods and services and share similar production processes for creating the goods and services they sell. Industries are classified using NAICS codes. Note that in the NAICS system, what a business produces is given less importance than the process used to create it. Jobs This column in our data represents full and part-time jobs, which can explain some situations in which the number of jobs in a region seems unusually high compared to the total regional population. Unlike individual government sources, our data include jobs held by nearly all types of workers: payroll workers (who have unemployment insurance), farm workers, railroad workers, military workers, and sole proprietors. Location Quotient (LQ) Location quotient is a way of comparing a region to a larger reference region according to some characteristic or asset. Suppose X is the amount of some asset in a region (e.g., manufacturing jobs), and Y is the total amount of assets of comparable types in the region (e.g., all jobs). X/Y is then the regional concentration of that asset in the region. If X' and Y' are similar data points for some larger reference region (like a state or nation), then the LQ or relative concentration of that that asset in the region compared to the nation is (X/Y) / (X'/Y'). Occupation A worker's job description contains a defined set of tasks and responsibilities. Occupations are classified using SOC codes (and O*NET extensions to SOC). Race and Ethnicity The federal government tracks several racial categories (White, Black or African American, Asian, etc.) but only two ethnic categories, Hispanic and Non-Hispanic. There may be some overlap between race and ethnicity unless the two characteristics are clearly separated, e.g., "White non-Hispanic," "White Hispanic," and "Non-white Hispanic." See www.whitehouse.gov/omb/fedreg/race-ethnicity.html.


Contact

KOIN Team

The KOIN effort is led by Jeff Tucker, associate director at the Advanced Manufacturing Institute, under

the supervision and guidance of Brad Kramer, director at AMI. Manveen Saini, economic development

project manager at AMI, oversees all economic development projects at the institute, and Dale

Wunderlich, industrial designer at AMI, works with the team to apply design thinking to economic

development approaches.

You can reach us at

Brad Kramer

Director

[email protected]

Jeff Tucker

Associate Director

[email protected]

Manveen Saini

Economic Development Project Manager

[email protected]

Dale Wunderlich

Design and Open Innovation Specialist

[email protected]

KOIN Team

Advanced Manufacturing Institute

510 McCall Road

Manhattan, KS 66502-5034

T 785-532-7044

F 785-532-7031

www.amisuccess.com

regional business profiling and innovation networking project final report

Documents