Kenexa Case

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907C04Kenexa-Datadelcasoenexcel.xls

case

1. Conduct survey
2. Find issues in surveys
Kenexa found in 1987
First 8 years, provide talent management solutions
Later include employee and customer satisfaction research, performance management technology and consultation, and employee process outsourcing
June 24, 2005, Kenexa announced its initial public offering
Kenexa aimed at helping corporate clients to maximize their performance by improving their human capital management
2,400 clients (— financial services, life sciences, retail, health care, call centers, education and hospitality)
Kenexa reported total revenues of $65.6 million,2 an increase of 42 per cent compared to the prior year
Kenexa employed approximately 1,000 people
The personnel comprising these teams had strong analytical, cross-functional and multi-industry expertise.
Numerous Kenexa employees had PhDs in Industrial/Organizational Psychology
JACK W. WILEY
had developed WorkTrendsT, a unique database of employee opinions
PhD in Organizational Psychology from the University of Tennessee,
SCOTT M. BROOKS
B.A. from Cornell University and a PhD in Industrial and Organizational Psychology from the Ohio State University
developed customized employee and survey research products for Kenexa’s projects.
he worked closely with Wiley to prepare feedback for Kenexa’s clients based on the analysis of employee/customer survey data.
effective workforce management -> better performance
It entails seeing the workforce as a source of competitive advantage,
organizational practices -> better workforce management
-> predictors of organizational success
perceptions of an organization’s customer orientation and the extent of emphasis on service quality. -> Customer loyalty -> business performance
• Specific leadership practices -> better able to deliver quality service to customers -> better organizational performance
more visible and present certain organizational values and leadership practices -> the more energized and productive the workforce. -> greater the satisfaction and loyalty of customers -> the long-term business performance
The High Performance Model illuminated the interrelationships among organizational practices, employee perceptions of their work environment, customer satisfaction and business performance.
Organizational success was contingent on the ability to build “longterm and mutually beneficial relationships among the company, employees and customers.
High Performance Model were affected by elements of the work characteristics and contextual factors
High Performance Model involved integration and correlation of data from employees, customers and business performance metrics.
A typical employee survey focused on employee descriptions of the aspects of their business-unit’s work environment
the customer survey collected data on customer perceptions of service quality, customer satisfaction and customer loyalty
Kenexa research team developed a customized project plan for serving the needs of the client
This was followed by the survey development phase
translating the linkage research results into actions for improving workplace performance.
(1) provide an understanding of employee/customer opinions and their relation to performance of NCB’s branches in order to differentiate better-performing branches from the poorer ones
(2) identify priorities for organizational development activities;
(3) serve as a benchmark to track the progress of organizational development activities.
NCB
128 branches located in six mid-western states
Based on 2005 financial data, NCB had approximately $7.5 billion in assets, $5.1 billion in deposits and a net income of $104 million.
headquarters was responsible for setting the overall strategic direction
Branches, on the other hand, were responsible for execution of the products.
A typical branch was comprised of about 20 employees, including a branch manager, assistant branch managers, personal bankers, banking assistants and tellers.
The branch manager was responsible for coordinating with the headquarters and managing the day-to-day functioning of the branch
The assistant branch managers were responsible for working closely with the manager to create a high-energy, highperformance culture within the branch
As “champions” of customer service and sales practices, they were expected to focus on meeting and exceeding branch targets. They were specifically required to identify opportunities for training of the branch personnel if branch performance was falling behind
The personal banker(s) were responsible for the portfolio of personal services offered to existing and new consumers: personal loans, credit card applications, and day-to-day banking
Sales Banking assistants worked in the banking hall of the branch and were usually one of the first employees who came in contact with the customers
The tellers were responsible for cashing checks, accepting deposits and loan payments, processing withdrawals, accepting payments for customers' utility bills and charge cards
Employee Survey
These elements were organized along nine themes in the survey: customer orientation, quality emphasis, employee training, involvement/empowerment, communication, teamwork, engagement, intention to leave, and satisfaction with compensation and benefits
This confidential survey was administered, during October to November 2005, on company time to the employees in 128 branches; 2,230 employees returned usable surveys.
The Customer Satisfaction Survey
The resulting survey had 40 questions aimed at measuring customer opinions on specific service issues (these issues were organized along four themes: satisfaction with service quality, satisfaction with teller, satisfaction with branch in general and facilities at the branch, and satisfaction with personal banker)
300 per branch The survey did not ask for customer names but identified customers on the basis of branch affiliation; 14,114 customers returned usable surveys
BUSINESS PERFORMANCE AND BRANCH LOCATION DATA
Graham mentioned that the NCB management speculated about the possibility of different business dynamics in branches located in metropolitan areas versus those in non-metropolitan areas.
DATA AGGREGATION TEAM FOR THE NCB PROJECT GETS TO WORK
Once the initial screening was complete, the research assistants calculated scores for the employee/customer opinion themes by computing the averages for the set of questions intended to measure a particular theme
Objectives
determining the relationship between these three data categories.
Priorizar las variables más importantes
Determinar si las muestras son representativas

data

bnum badd bloc bsize ecuso equal einvol etra ecomm eteam eeng eitl eben cserq cbrtel cbr cbrpb cloy ccon teltr prod
1 Anoka (E) 1 38 3.52 3.47 3.21 3.24 3.18 3.37 3.12 2.57 3.58 3.26 4.29 4.15 4.13 3.76 1 3946 412
2 Anoka (W) 1 15 3.75 3.58 3.39 3.02 3.11 3.44 3.36 2.93 3.79 3.43 4.48 4.54 4.34 3.84 1 4041 317
3 Apple Valley 1 19 3.63 3.63 3.44 3.28 3.23 3.49 3.29 2.42 3.42 3.45 3.91 4.18 3.93 3.81 1 3510 232
4 Blaine 1 12 3.83 3.58 3.32 3.26 3.61 3.25 3.48 2.58 3.92 3.29 4.13 3.96 4.06 3.73 0 4184 323
5 Bloomington 1 27 3.22 3.16 3.19 3.08 2.85 2.91 2.68 3.3 3.52 3.67 4.13 4.15 4.09 3.98 1 3484 242
6 Brooklyn 1 28 3.7 3.6 3.36 3.09 3.24 3.68 3.03 2.07 4.04 3.59 4.06 4 3.92 4.05 0 4406 351
7 Burnsville 1 31 3.88 3.72 3.42 3.42 3.39 3.66 3.39 2.32 3.77 3.15 4.14 4.33 4.11 3.61 0 4642 324
8 Columbia hts. 1 36 3.47 3.45 3.28 3.26 3.29 3.31 3.13 2.61 3.86 3.28 4.21 4.2 4.06 3.72 0 4344 391
9 Cottage groove 1 51 3.8 3.54 3.39 3.13 3.08 3.46 3.16 2.51 3.8 3.4 4.1 3.98 3.96 3.76 0 4060 342
10 Hopkins 1 23 3.95 3.7 3.38 3.22 3.14 3.59 3.27 2.17 4 3.18 4.18 4.24 4.09 3.61 0 4399 314
11 Minneapolis 1 34 4.29 4.04 3.94 3.48 3.66 3.87 3.89 2.15 3.61 3.46 4.3 4.33 4.09 3.77 1 4056 309
12 Minneapolis (NE) 1 12 3.39 3.42 3.53 3.17 3.36 3.72 3.21 1.75 3.67 3.29 4.3 4.08 4.05 3.84 0 4186 305
13 Minnetonka 1 24 3.84 3.81 3.8 3.35 3.47 3.51 3.45 2.13 4.08 3.26 4.11 3.87 3.87 3.63 0 4051 311
14 Little Canada 1 19 3.43 3.38 2.98 3.01 3.16 3.39 2.78 2.58 3.68 3.19 4.05 4.23 4.06 3.6 0 4413 287
15 Oakdale 1 16 3.75 3.63 3.68 3.22 3.73 3.82 3.37 2.25 3.88 3.36 4.38 4.22 4.27 3.78 0 4502 294
16 Plymouth 1 9 4.19 3.56 3.65 3.34 3.26 3.63 3.58 1.44 3.56 3.18 4.2 4.24 4.15 3.78 0 3839 346
17 Robbinsdale 1 10 3.33 3.55 3.41 3.53 3.9 3.93 2.95 1.9 3 3.07 4.06 3.9 4.01 3.54 0 4588 363
18 St. Louis Park 1 12 3.31 3.38 3.25 3.17 3.33 3.4 3.33 2.08 3.83 3.26 4.07 4.16 4.03 3.7 0 4506 296
19 St. Paul (E) 1 16 4.28 3.84 3.76 3.19 3.19 3.77 3.59 2.31 3.73 3.37 4.47 4.17 4.24 3.85 0 3611 313
20 St. Cloud 1 13 3.4 3.33 3.1 3.03 3.31 3.18 3 2.23 3.46 3.24 4.12 3.8 3.95 3.63 0 4286 372
21 Willmar 1 10 4.25 4.15 3.93 3.65 3.47 3.97 4 1.9 3.8 3.63 4.27 4.21 4.18 3.92 1 4288 346
22 Eagan 0 29 3.41 3.34 3.2 2.88 2.62 3.16 3.16 2.97 3.97 3.42 4.3 3.99 4.11 3.72 0 3150 247
23 Cloquet 1 11 3.98 4.27 3.84 3.77 3.76 3.67 3.58 2.73 4.27 3.51 4.14 3.9 4.02 3.97 1 3633 246
24 Rochester (E) 1 22 3.76 3.73 3.49 3.24 3.21 3.31 3.44 3.05 3.33 3.47 4.33 3.95 4.09 3.9 1 4021 317
25 Eden Prairie 0 8 4.09 4.03 3.52 3.25 3.33 3.92 3.5 2.13 3.86 3.67 4.4 4 4.3 4.07 1 3777 271
26 Edina 0 9 4.06 4 3.98 3.44 3.67 3.67 3.58 2.22 3.67 3.21 4.14 4.26 4.12 3.65 0 4897 254
27 Brookfield 1 20 3.33 3.61 3.5 3.12 3.15 3.38 3.44 2.2 3.63 3.29 4.25 4.11 4.19 3.71 0 3961 226
28 Wayzata 1 12 3.85 3.94 3.54 3.71 3.81 3.75 3.27 2.58 3.45 3.35 4.18 4.3 3.97 3.85 1 4434 271
29 Arvada (N) 1 55 3.72 3.67 3.44 3.38 3.39 3.59 3.25 2.44 3.46 3.27 4.15 4.07 4.02 3.77 0 3621 352
30 Aurora 1 25 3.8 3.71 3.81 3.59 3.45 3.63 3.69 2.32 3.76 3.26 4.18 4.22 4.09 3.63 0 4830 343
31 Colarado Springs 1 20 3.96 4.06 3.72 3.5 3.67 3.94 3.44 2.1 4.25 3.39 4.35 4.21 4.13 3.75 0 4327 338
32 Denver (S) 1 17 3.82 3.57 3.29 3.51 3.41 3.69 3.1 2.24 3.71 3.31 4.13 4.28 4.23 3.79 0 4193 404
33 Englewood 1 23 3.03 2.71 2.85 2.51 2.18 2.76 2.5 3.65 3.52 3.17 4.1 3.91 4.05 3.51 0 4072 224
34 Fort Collins 1 26 3.52 3.36 3.12 3.21 2.96 3.22 3.21 2.73 3.42 3.73 4.2 3.91 4.1 3.98 1 4452 320
35 Broomfield 0 20 3.78 3.63 3.5 3.11 3.22 3.4 3.19 2.45 4.15 3.35 4.47 4.5 4.41 3.79 1 4369 291
36 Grand Junction 1 21 3.49 3.37 3.16 2.95 2.94 3.14 3.06 2.81 3.76 3.22 4.17 3.99 4.03 3.75 1 4702 364
37 Littleton 1 25 3.71 3.41 3.42 3.28 3.06 3.57 3.14 2.33 3.87 3.23 4.11 4.04 4.02 3.67 0 3822 262
38 Lakewood 0 31 3.81 3.65 3.42 2.91 3.05 3.48 3.05 2.74 3.16 3.36 4.24 4.06 4.1 3.86 0 2726 249
39 Longmont 1 16 3.73 3.69 3.3 3.24 3 3.58 3.27 3.06 3.33 3.66 4.43 4.04 4.15 4.04 1 3480 282
40 Northglenn 1 18 3.88 4 3.76 3.44 3.86 3.82 3.65 2 3.88 3.16 4.33 4.35 4.19 3.6 0 4256 283
41 Pueblo (NE) 1 20 3.61 3.54 3.4 3.18 3.35 3.75 3.1 2.85 3.8 3.27 4.1 4.08 4.03 3.82 1 3764 277
42 Westminister 1 10 4.48 4.05 3.83 3.62 3.44 4.02 3.99 2.1 3.9 3.35 4.53 4.34 4.32 3.81 1 5637 327
43 Altoona 0 10 3.65 3.57 3.54 3.48 3.21 3.44 2.85 3.1 4 3.22 4.33 4.25 4.28 3.66 0 3720 253
44 Des Moines 1 15 3.48 3.37 3.28 2.98 2.89 3.76 2.95 2.47 3.07 3.16 4.2 3.95 4.04 3.59 0 4307 296
45 Red Oak 0 32 3.79 3.8 3.43 3.14 3.33 3.61 3.13 2.5 3.88 3.27 4.38 4.32 4.24 3.79 0 5110 335
46 Iowa Falls 1 8 4.25 3.91 3.64 3.67 3.63 3.66 3.25 2.25 3.38 3.19 4.49 4.18 4.26 3.58 1 3830 296
47 Bellevue 1 8 3.84 3.81 3.61 3.21 3.21 3.42 3.34 2.57 4 3.3 4.34 4.33 4.19 3.84 1 4486 279
48 Columbus 1 19 4.43 4.08 3.98 3.34 3.38 3.91 3.64 2.21 4.12 3.46 4.4 4.26 4.27 3.85 1 4253 300
49 Hastings 1 9 4.31 3.94 3.9 3.54 3.7 4 3.81 2.11 3.75 3.24 4.23 4.18 4.12 3.84 0 5081 251
50 Lincoln (E) 1 12 3.69 3.38 3.26 3.04 3.08 3.5 2.94 3 3.58 3.01 4.11 4.07 3.88 3.54 1 4373 341
51 Beatrice 0 19 3.62 3.75 3.35 3.31 3.09 3.67 3.26 2.42 3.58 3.26 4.2 4.26 4.12 3.68 1 4292 254
52 North Platte 0 10 3.16 3.39 2.86 3.1 2.87 2.6 2.93 3.3 3.9 3.17 4.22 4.03 4 3.64 1 4380 202
53 Lincoln (SE) 1 12 3.98 3.67 3.49 3.44 2.83 3.69 3.21 2.58 3.91 3.24 3.99 3.74 3.94 3.69 0 5202 324
54 Omaha 1 17 3.52 3.48 3.33 3.1 3 3.39 3 1.71 3.31 3.52 4.05 3.94 4.02 4.1 0 4821 337
55 Kearney 0 7 4 3.86 3.78 3.64 3.33 4.05 3.68 1.71 3.86 3.54 4.34 4.11 3.92 4.05 1 3755 254
56 Omaha (SW) 1 22 3.89 3.69 3.61 3.26 3.08 3.59 3.46 2.14 3.88 3.17 4.03 3.84 3.92 3.66 0 3656 298
57 Gardner 0 11 3.73 3.34 3.31 3.05 2.85 3.58 2.91 3.09 3.55 3.49 4.16 3.95 3.95 3.89 1 4352 339
58 Holton 0 20 4.09 3.84 3.81 3.33 3.4 3.9 3.81 2 3.75 3.2 4.37 4.31 4.24 3.52 0 5001 387
59 Des Plaines 1 8 3.75 3.69 3.45 2.83 3.21 3.33 2.97 2.25 3.57 3.38 4.19 4.03 4.07 3.9 1 4449 325
60 Chicago (W) 1 9 3.56 3.39 3.41 3.19 2.93 3.07 3.14 2.67 3.89 3.18 4.33 4.22 4.23 3.73 0 4418 272
61 Lawrence 0 24 3.41 3.34 3.13 3.31 2.88 3.38 2.9 2.71 3 3.45 4.21 3.71 3.92 3.89 1 3415 218
62 Chicago (E) 1 8 4.16 3.91 4.05 3.63 3.29 3.71 3.63 2.63 3.71 3.44 4.27 4.1 4.09 3.82 1 4352 277
63 Topeka 1 12 3.79 3.77 3.75 3.63 3.42 3.39 3.38 3 3.91 3.4 4.32 4.01 4.13 3.87 0 4615 265
64 Wichita (N) 1 8 4.25 3.69 3.79 3.13 2.96 3.5 3.28 2.75 4.13 3.2 4.41 4.25 4.29 3.64 0 3293 166
65 Maple Grove 0 5 4.7 4.3 3.94 4.03 3.8 3.8 4.4 1.4 4.2 3.52 4.44 4.3 4.16 3.97 1 3357 255
66 Wichita - Tallgrass 1 9 4.28 4.06 4.11 3.27 3.22 3.89 4.03 2 4.22 3.49 4.24 4.05 4.07 3.94 1 4680 320
67 St. Cloud 1 8 3.66 3.25 3.36 3.24 2.74 3.17 3.22 2.38 4 3.62 4.26 3.93 4.06 4.1 1 5519 298
68 Billings 1 8 4.38 3.97 3.86 3.5 3.08 3.88 3.97 2.5 3.63 3.28 4.49 4.49 4.53 3.71 1 4306 248
69 Great Falls 1 8 3.97 3.75 3.5 2.92 2.96 3.71 3.34 2.5 3 3.16 4.29 4.26 4.16 3.51 1 4471 345
70 Helena 1 43 3.74 3.7 3.54 3.52 3.63 3.67 3.37 2.14 3.77 3.19 4.22 4.03 4.16 3.69 0 4173 334
71 Missoula (S) 1 19 3.55 3.19 2.94 3.41 3.37 3.09 2.67 2.26 3.89 3.42 4.29 4.42 4.23 3.79 1 5029 337
72 Missoula (Main) 1 11 3.39 3.18 2.88 3.14 2.94 3.52 2.73 3.27 3.64 3.43 4.38 4.36 4.19 3.9 1 4835 250
73 Overland Park 0 10 3.15 2.61 2.96 3.22 2.91 3.02 2.59 3.2 3.4 3.33 4.08 3.99 4 3.88 1 3988 381
74 Bismarck (N) 1 7 4 3.57 3.65 2.8 2.9 3.81 3.71 2.43 4.14 3.44 4.18 4.01 4.09 3.95 0 4101 249
75 Bismark (E) 1 23 3.76 3.81 3.75 3.42 3.48 3.57 3.42 2.26 3.83 3.54 4.15 4.2 4.11 3.92 0 4325 316
76 Prairie Village 0 19 3.25 3.04 2.87 2.97 2.91 3.42 2.67 2.53 3.72 3.04 4.21 4.03 4.11 3.53 1 3844 233
77 Fargo 1 13 3.69 3.35 3.36 3.49 3.69 3.74 2.79 2.46 3.92 3.42 4.38 4.36 4.3 3.81 0 4658 295
78 Devils Lake 0 9 3.39 3.14 3.1 3.26 3.26 3.27 3.06 2.25 3.89 3.35 4.36 4.37 4.28 3.86 0 3975 369
79 Grafton 0 18 3.74 3.79 3.6 3.39 3.7 3.41 3.29 2.5 4.28 3.44 4.36 4.26 4.33 3.8 1 3994 259
80 Mandan 0 19 4.2 3.74 3.5 3.24 3.25 3.63 3.37 2 3.53 3.54 4.33 4.16 4.18 3.88 1 4010 320
81 Bozeman 0 24 3.41 3.23 3.03 3.08 3.18 3.58 2.56 2.22 3.79 3.19 4.39 4.47 4.29 3.49 1 3769 294
82 Jamestown 0 16 3.72 3.56 3.33 3.2 3.31 3.38 3.3 2.31 3.63 3.2 4.55 4.65 4.44 3.68 1 3876 293
83 Colton 0 15 4.03 3.42 3.38 3.32 3.31 3.62 2.8 2.2 3.13 3.52 4.6 4.55 4.46 3.86 1 3631 257
84 Wahpeton 0 10 4.03 3.75 3.37 3.67 3.5 3.73 3.23 1.8 4.4 3.15 4.33 4.33 4.29 3.43 0 3018 280
85 Grand Forks 1 18 4.03 4.03 3.75 3.75 3.63 3.74 3.59 2.22 2.83 3.54 4.24 4.33 4.25 4.03 1 4823 289
86 Onalaska 0 15 3.73 3.5 3.36 3.48 3.04 3.58 3.37 2.73 3.73 3.48 4.21 3.95 4.14 3.86 1 4307 304
87 Langdon 1 13 3.27 3.04 3.43 3.33 3 3.36 3.02 2.31 3.77 3.34 4.28 3.92 4.12 3.74 1 4799 279
88 Evanston 0 16 3.7 3.34 3.24 3.36 3.17 3.67 3.41 2.94 4 3.19 4.32 4.21 4.21 3.63 0 3511 295
89 Cody 0 18 4.06 3.5 3.68 3.03 3.28 3.72 3.33 1.78 4 3.42 4.22 4.04 4.15 3.69 1 3666 266
90 Green River 0 18 3.67 3.47 3.47 3.27 3.13 3.93 3.26 2.22 3.67 3.15 4.28 4.26 4.26 3.44 0 3835 269
91 Lander 0 16 3.5 3.16 3.01 2.95 3.05 3.42 3.28 3 3.69 3.35 4.12 4.12 4.04 3.78 0 2965 305
92 Milwaukee (E) 1 11 3.77 3.48 3.31 2.82 3 3.3 3.27 3.18 3.4 3.36 4.12 3.95 3.94 3.75 1 3039 388
93 Laramie 0 14 3.81 3.22 3.3 2.75 2.93 3.38 3.64 3.29 3.43 3.02 4.44 4.4 4.3 3.35 1 4388 318
94 Casper 0 10 3.38 3.73 3.81 3.58 3.6 3.53 3.73 2.2 3.9 3.32 4.37 4.12 4.18 3.65 1 4319 325
95 Cody 0 15 3.58 3.47 3.04 3.29 3.38 3.6 3.17 2.53 3.93 3.17 4.32 4.25 4.2 3.59 1 3004 250
96 Gillette 0 13 3.87 3.63 3.65 3.14 3.26 3.44 3.54 2.15 3.77 3.59 4.5 4.4 4.4 4.18 1 3431 221
97 Golden 0 32 4.21 3.99 3.78 3.42 3.63 3.83 3.54 2.06 3.94 3.4 4.23 4.28 4.12 3.81 1 3409 272
98 Shoreview 0 18 3.68 3.57 3.33 3.27 3.22 3.54 3.31 2.44 3.44 3.21 4.27 3.99 4.09 3.73 0 3279 362
99 Albert Lea 0 18 3.39 3.07 2.96 3.15 3.11 3.4 3.31 2 3.39 2.95 4.38 4.54 4.27 3.41 1 3876 204
100 Cloquet 0 16 3.48 3.36 3.14 3.15 3.23 3.04 3.09 1.88 3.88 3.17 4.3 4.31 4.2 3.39 1 2858 203
101 Elk River 0 20 3.79 3.44 3.47 3.12 3.43 3.55 3.24 3 4.11 3.62 4.38 4.33 4.17 3.96 0 2924 229
102 Milwaukee (Main) 1 19 3.95 3.52 3.21 3.1 3.45 3.85 3.03 2.16 3.74 3.2 4.23 4.17 4.14 3.68 0 4227 260
103 Cheyenne (Main) 1 27 4.01 3.69 3.5 3.26 3.13 3.7 3.56 3 3.96 3.75 4.19 4.24 4.17 4.12 0 3079 213
104 Minot 1 18 3.47 3.28 3.51 3.29 3.06 3.17 3.29 3.33 4.22 3.02 3.94 3.72 3.77 3.31 1 4104 242
105 Rapid City Center 1 15 3.12 3.02 2.74 3.06 3.04 3.02 2.81 2.93 3.8 2.85 3.91 4.01 3.96 3.05 1 2861 191
106 Rapid City - St. Joseph St. 1 24 4.06 3.85 3.73 3.15 3.11 3.58 3.43 2.75 4 3.91 4.28 4.16 4.07 4.22 1 3233 441
107 Sioux Falls (E) 1 19 3.91 3.77 3.58 3.13 2.9 3.58 3.43 2.68 3.53 3.88 4.17 4.1 4.14 4.08 1 4235 200
108 Hibbing 0 22 4 3.65 3.47 3.31 3.32 3.8 3.22 2.32 3.45 3.13 4.51 4.46 4.39 3.49 0 2950 215
109 Sioux Falls (W) 1 10 3.1 2.93 2.9 2.82 2.8 2.83 3.14 2.2 3.3 3.29 4.56 4.48 4.35 3.76 0 1660 242
110 Boulder (S) 1 23 3.08 3.44 3 2.76 2.92 3 3.09 3.17 3.39 3.39 4.3 4.15 4.24 3.88 0 2917 232
111 Ankeny 0 24 3.76 3.91 3.59 3.26 3.13 3.6 3.39 2.65 4.08 3.26 4.47 4.48 4.33 3.74 0 3013 192
112 Brown Deer 1 14 3.64 3.41 3.31 3.18 3.07 3.21 2.89 2.43 3.92 3.22 4.16 4.21 4.05 3.64 1 3994 307
113 Denver - Monaco Square 1 33 3.51 3.48 3.02 3 3.21 3.48 2.9 2.33 3.82 3.46 4.16 4.06 3.98 3.79 1 4202 260
114 Colorado Springs 1 14 3.88 3.87 4.01 3.89 3.45 4 3.88 2 3.93 3.09 4.1 4.15 4.05 3.5 0 4299 295
115 Greeley 0 8 4.21 3.8 3.92 3.55 3.37 3.71 3.71 1.92 3.99 3.44 4.19 4.15 3.96 3.84 1 4135 274
116 La Junta 0 17 3.48 3.34 3.2 3.12 3.04 3.51 3.02 1.97 3.95 3.52 4.22 4.25 4.13 3.96 1 3880 335
117 Wheat Ridge 0 12 3.62 3.42 3.03 3.45 3.19 3.67 3.12 2.83 3.53 3.24 4.13 4.04 4.05 3.7 0 3491 267
118 Lakewood - Wadsworth 1 15 3.74 3.69 3.49 3.26 3.3 3.68 3.24 2.3 4.15 3.38 4.4 4.44 4.3 3.81 0 3524 392
119 Pratt 0 11 3.96 3.71 3.39 3.04 3.3 3.92 3.28 2 3.55 3.38 4.6 4.66 4.32 3.77 1 4214 303
120 Cheyenne (Frontier Mall) 1 13 4.02 3.76 3.8 3.46 3.66 3.74 3.55 1.77 3.98 3.18 4.57 4.55 4.42 3.68 1 3147 346
121 Denver - Tech Center 1 25 3.61 3.44 3.35 3.04 2.95 3.31 3.09 1.98 3.44 3.3 4.39 4.29 4.25 3.82 0 3740 251
122 Knoxville 1 14 3.64 3.63 3.26 3.28 3.28 3.84 3.18 2.09 3.79 3.37 4.36 4.2 4.05 3.8 0 3058 263
123 Mason City - N. Washington 1 23 3.59 3.45 3.08 3.08 3.13 3.56 2.93 2.39 3.35 3.19 4.5 4.48 4.32 3.68 0 3288 246
124 Mason City - Regency Peak 1 5 3.95 3.8 3.54 3.27 3.2 3.47 3.05 2 3.8 3.55 4.5 4.54 4.46 3.98 1 3689 274
125 El Dorado 1 17 3.86 3.49 3.45 3.41 3.38 3.39 3.31 2.76 4.33 3.31 4.26 4.22 4.15 3.78 0 3722 241
126 Emporia - West Plaza 1 12 3.86 3.89 3.67 3.38 3.48 3.69 3.42 1.8 3.91 3.26 4.25 4.07 4.11 3.62 0 3456 296
127 Minneapolis - University 1 15 3.99 3.69 3.22 2.83 2.98 3.68 3.16 2.53 3.7 3.33 4.49 4.54 4.39 3.75 0 3098 272
128 Minneapolis - IDS Center 1 13 3.7 3.53 3.46 3.42 3.27 3.63 3.29 2.14 3.92 3.44 4.15 3.98 3.98 3.86 0 3281 219

Sheet3