Table of - Bureau of Engineeringeng.lacity.org/sites/g/files/wph726/f/CABM_Update_2009.pdf · Table...

Table ofContentsTOC

Page TOC-1

CHAPTER 1 EXECUTIVE SUMMARY A. Introduction ...................................................................................................... 1B. Performance Benchmarking ....................................................................2C. Best Management Practices ................................................................. 10D. Online Discussion Forum ........................................................................ 13E. Conclusions ................................................................................................... 13

CHAPTER 2 INTRODUCTION A. Background .................................................................................................... 18B.BenefitsofParticipation ......................................................................... 19C. Study Focus .....................................................................................................22D. Study Goals .....................................................................................................22

CHAPTER 3 PERFORMANCE BENCHMARKING A. Study Criteria .................................................................................................25B.DataCollectionandConfirmation ...................................................... 27C. Performance Database ............................................................................30D. Performance Model Selection .............................................................33E. Modeling Methodology ............................................................................34F. Characteristics of Data Analyzed........................................................35G. Regression Analysis Results ................................................................38

CHAPTER 4 BEST MANAGEMENT PRACTICES A. New Best Management Practices .......................................................45B.DescriptionofBestManagementPractices .................................45C.ProgressonBestManagementPracticeImplementation ...53

Page TOC-2

Annual Report Update 2009 California Multi-Agency CIP Benchmarking Study

CHAPTER 5 ONLINE DISCUSSION FORUM A. InfrastructureandFixedAssetCapitalizationPolicies ......... 69B. Permeable and Pervious Pavements ................................................ 70C.SeparateSectionforEstimatingandScheduling .......................71D. Resource Level Scheduling ................................................................... 72E. QualificationBasedConsultantSelection(QBCS)

Policy/Procedure .........................................................................................74F. Materials Testing Laboratory Services ............................................74G. Project Labor Agreement..........................................................................77H. Covered Pedestrian Walkways ............................................................ 79I. Job Order Contracting ............................................................................... 81

CHAPTER 6 CONCLUSIONS A. Performance Benchmarking .................................................................83B. Best Management Practices .................................................................84C. Online Discussion Forum ........................................................................84D.PlanningforUpdate2010 ........................................................................84E. Acknowledgements ...................................................................................85

APPENDIX A PERFORMANCE QUESTIONNAIRE A-1

APPENDIX B PERFORMANCE CURVE B-1

APPENDIX C INDIRECT RATES C-1

Page TOC-3

TOC Table of Contents

TABLESTable 1-1 Growth of Database ............................................................................................ 3Table1-2 ProjectCountandProjectDeliverybyCompletionYear ................ 5Table1-3 ProjectDeliveryCostsbyProjectType(%ofTCC)

(FullRangeofTCC) .............................................................................................. 6Table1-4 ProjectDeliveryCostsbyProjectType(%ofTCC)

(SmallerProjectSubsetofTCC) ...................................................................7 Table 1-5 Project Delivery Performance and Consultant

Usage by Agency .................................................................................................. 9 Table1-6 SummaryofPerformanceModels(FullRangeofTCC) .................. 11 Table 1-7 Summary of Performance Models

(SmallerProjectSubsetofTCC) ................................................................ 12 Table 2-1 Agencies’ Overall Information .................................................................... 19Table3-1 ProjectTypesandClassifications ........................................................... 27Table 3-2 Project Cost Categories .................................................................................28 Table 3-3 Growth of Database .......................................................................................... 31Table 3-4 Projects Distribution Matrix ........................................................................32Table3-5 ProjectCountandProjectDeliverybyCompletionYear ............. 35Table3-6 ProjectDeliveryCostsbyProjectType(%ofTCC)

(FullRangeofTCC) ........................................................................................... 36Table3-7 ProjectDeliveryCostsbyProjectType(%ofTCC)

(SmallerProjectSubsetofTCC) ................................................................ 37Table 3-8 Project Delivery Performance and Consultant

Usage by Agency ............................................................................................... 39 Table3-9 SummaryofPerformanceModels(FullRangeofTCC) ..................41Table 3-10 Summary of Performance Models

(SmallerProjectSubsetofTCC) ................................................................42Table4-1 DescriptionofBestManagementPractices .......................................46 Table4-2 ImplementationofBMPs .............................................................................. 58Table 5-1 City of San Jose Survey ................................................................................... 75Table 5-2 City of Oakland Survey .....................................................................................77Table 5-3 City of San Diego Survey ................................................................................ 79Table 5-4 City of San Francisco Survey ....................................................................... 81

chapter ExecutiveSummary1

Page 1

A. IntroductIonDuring these highly challenging economic times, the California Multi-Agency CIP Benchmarking Study (Study) has continued its unparalleled effort to share the collective Capital Improvement Project implementation experiences of seven out of the eight largest cities in California for the eighth consecutive year. Since the participating Cities of Long Beach, Los Angeles, Oakland, Sacramento, San Diego, San Jose and the City and County of San Francisco first initiated these efforts, they have obtained a better understanding of the changing capital project delivery process.

This year, the participating agencies spent a substantial amount of effort sharing approaches to continue to provide high value implementation of their capital programs in the most efficient manner possible in the face of unprecedented fiscal hardships. The Study provides a forum for the Agencies to share information amongst themselves via: quarterly meetings with a focus on current issues, an online portal where topics for discussion can be posed and challenges addressed, and a database that serves as both, a repository of the Agencies’ projects and a tool for data analysis. Through these acts of collaboration, often times an optimum solution is found that can be translated into a Best Management Practice (BMP) for the group.

The sharing of best ideas amongst the Study participants has benefitted the agencies and owners who can turn to one another to gather insight on how to address challenges that might be new to them, but which others have already faced.

In this eighth year of the Study, the Update 2009 participants have continued to pursue on-going endeavors, as well as taken on new ones:

Addition of the “Special Topic” • roundtable discussion forums at Quarterly Meetings to explore areas of potential positive impact in relation to the current fiscal challenges;

Improved online discussion • forum for efficient information sharing;

Continued improvement to the • modeling methodology of the performance models;

Continue to improve the quality • of the performance data and the functionality of the database;

Track the adoption of BMPs; and•

Create new BMPs targeted to • common issues.


B. PerformAnce BenchmArkIngPerformance benchmarking involves collecting documented project costs and creating data models of the component costs of project delivery versus the total construction cost. Project delivery costs are defined as the sum of all agency and consultant costs associated with project planning, design, bid, award, construction management, and closeout activities. The Update 2009 performance curves have been developed from data on projects completed on or after January 1, 2004.

Performance modelTable 1-1 summarizes the number of projects included in the database and in the analyses. The 5-year database used for the current analysis contains 729 projects. This total excludes project data older than five years or projects identified as outliers. Projects identified as outliers are not included in the performance data analysis but are retained in the performance database. Outlier analysis was performed using statistical techniques to ensure consistency in the selection of outlier data points. This methodology was first implemented during Update 2008 and the agencies recognize the merits of a scientific approach for outlier elimination. Some of the projects classified as outliers in previous Study years have been included in the performance data analysis, and vice-versa.

This is an improved practice when compared to prior Study years where project data points were classified as outliers based on a combination of statistical parameters and subjective judgments by the Project Team. Previously, projects identified as outliers during one Study phase were kept as outliers in subsequent Study phases.

Table 1-1 shows that as the rules for project selection were refined, non-representative and projects with total construction cost (TCC) less than $100K have decreased in number. In addition, only 14 projects have been excluded as outliers in the Update 2009 Study as compared to the elimination of 147 projects in Update 2007 and 113 projects in Update 2006.

Chapter 1 Executive Summary

Tabl

e 1-

1 G

row

th o

f Dat

abas

e

Stud

yPh

ase1

Subm

itted

Del

eted

Cou

nt A

fter

Del

etio

nsEx

clud

edN

et

(a) T

otal

(b

) TC

C

<$10

0K

(c) N

on-

Rep

re-

sent

ativ

e2(d

)=(a

)-(b)

-(c)

(e) P

roje

ct

Com

plet

ion

Dat

e <

2004

(f)

Out

liers

3 Pr

ojec

ts in

A

naly

ses

(g)=

(d

)-(e)

-(f)

I 23

725

4416

816

80

0II

285

035

250

250

00

III

262

029

233

230

03

IV

170

1721

132

364

92V

18

20

317

919

315

7

VI

189

00

189

32

184

VII

158

10

157

73

147

VIII

151

20

149

12

146

Tota

l 1,

634

4513

21,

457

714

1472

9

Not

es:

1 Stu

dy P

hase

indi

cate

s act

ion

take

n on

the

coun

t of p

roje

cts c

orre

spon

ding

to S

tudy

Yea

rs I

= 20

02, I

I = 2

003,

III =

200

4, IV

= 2

005,

V =

200

6, V

I = 2

007,

VII

=

2

008,

and

VIII

= 2

009.

2 Pr

ojec

ts th

at d

o no

t fit S

tudy

crit

eria

for p

roje

ct c

lass

ifica

tions

and

min

imum

TC

C o

f $10

0K w

ere

rem

oved

from

the

data

base

.3 O

utlie

rs a

re id

entifi

ed b

ased

on

statis

tical

ana

lysi

s.


Performance model SelectionDuring Update 2008, a significant amount of time and effort was expended on improving the accuracy of the performance model. A linear trendline was selected to replace the logarithmic relation between the project delivery costs and the TCC. These efforts yielded positive results by eliminating auto-correlation in the modeling methodology and by producing significant improvements in the performance model results yielding R2 values of significantly higher magnitudes.

Although the participating agencies acknowledged the merits of a refined performance model using a l inear trend line, it does not completely reflect the agencies’ observations that on a percentage basis, projects with lower TCCs are more expensive to deliver than projects with higher TCCs. At the request of the participating agencies, during Update 2009 the Study Team evaluated five types of curves (logarithmic, exponential, polynomial, power, and linear) to determine the best-fit curve for the regression model.

Logarithmic and exponential curves resulted in poor R2 values and generally fit poorly to the data points. Although polynomial curves exhibited good R2

values, they did not model real world results. Power curves generated good R2 values and represented a good fit for the project data. In all the cases, the resulting power curves were almost linear in nature.

However, the associated expression used to calculate the project delivery percentage was mathematically complex. Linear trendlines generated good R2 values and represented a good fit for the project data. In addition, the associated expression used to calculate the project delivery percentage was a simple mathematical relationship.

The findings of the best-fit analysis were reviewed by a statistics expert before being presented to the participating agencies during a quarterly meeting. The participating agencies agreed with the results of the analysis and approved the use of the linear trendline as the best-fit curve for the project data points, particularly with the enhancements made to the modeling methodology.

modeling methodologyTo explore the agencies’ observations that on a percentage basis, projects with lower TCCs are more expensive to deliver than projects with higher TCCs, the Study Team conducted additional investigations. The objective was to identify a subset of project size (in terms of TCC) that represented what was generally considered as the smaller projects. A statistical analysis of the distribution of the projects in the database revealed that generally 80 percent of the projects lay between a TCC ranging from $100,000 to $2 Million. Regressions were then undertaken to determine if delivery costs for this subset behaved in a different fashion than for the full range of projects. The statistical tests generally produced favorable results and it was concluded that this subset of projects were representative of the characteristics of smaller projects.


Therefore, it was decided to analyze the projects data in the following two ranges:

Full range of TCC 1.

Smaller project subset of TCC 2. (first 80 percent of the project distribution)

Preliminary results of such an evaluation using the Update 2008 projects database were presented to the agencies during a quarterly meeting. The results conformed to the agencies’ practical experiences. After reviewing the results, the agencies directed the Study Team to analyze the Update 2009 projects data in the two ranges discussed above. The characteristics of the data in the performance model database are presented in the following paragraphs.

Project Completion Date

Design Cost (% of TCC)

Construction Management

Cost (% of TCC)

Total Project Delivery Cost

(% of TCC) Median TCC ($M)

2004 27% 18% 46% $0.57 2005 23% 17% 40% $0.66 2006 20% 17% 37% $0.86 2007 23% 17% 40% $0.70 2008 23% 17% 40% $0.72

Average 23% 17% 40% $0.65

Notes: 1 Project Delivery percentages represent arithmetic averages of the individual projects and do not represent the results from the regression analyses.2 Project Delivery percentages vary from year to year based on the selection and the composition of the projects in the database.

Table 1-2Project Delivery Costs by Project Completion Year

(As % of Total Construction Cost)

characteristics of data AnalyzedProject performance data were analyzed using the custom database application at both the Project Type level and the Project Classification level.

Project Count and Project Delivery by Completion Year

Table 1-2 summarizes characteristics of the projects included in the analyses by project completion year and shows trends in the average TCC values, median TCC values, design costs, construction management costs, and overall project delivery costs. The median value is the value at which 50% of the values are above and 50% of the values are below.


As indicated in Table 1-2, project size (measured as median TCC), increased significantly between 2004 and 2006 with an increase of approximately 51 percent. Project size declined approximately 16 percent between 2006 and 2008. The average TCC also declined steadily between 2006 and 2008. Similarly, project delivery costs measured as a percentage of the TCC declined significantly between 2004 and 2006. The project delivery percentages have remained stable during 2007 and 2008 having increased slightly from 2006.

Project Delivery Costs by Project Type

Table 1-3 shows project delivery costs by each of the four project types in the Study for the full range of TCC. The project delivery percentage for a category is the arithmetic average of the project delivery percentages of the individual projects grouped under that category.

Type

Design

Construction

Managem

ent

Project Delivery

(Total)

Median Total

Construction C

ost ($M)

Num

ber of Projects (N

)

Municipal Facilities 21% 16% 36% 3.08 116Parks 23% 16% 39% 0.34 83

Pipe Systems 20% 17% 36% 0.71 267Streets 27% 19% 46% 0.54 263Average 23% 17% 40% 0.65 729


Table 1-3 Project Delivery Costs by Project Type (% of TCC) (Full Range of TCC )


Projects belonging to the Pipes and the Municipal categories have the lowest average project delivery cost. The Pipes category has the maximum number of projects (n = 267) in the Update 2009 database. The Streets category also has a similar number of projects in the database (n = 263). The Streets category also exhibits the highest average project delivery cost. The influence of low project delivery cost from Pipes projects is balanced by the influence of high project delivery cost from Streets projects. The average project delivery percentage for the overall dataset is approximately 40 percent.

Over the course of the Study, the Agencies have observed that the relatively high average project delivery cost of Streets projects is probably due to increasing cost

influences of right-of-way acquisition, community outreach requirements, environmental mitigation requirements, and the smaller median total construction cost of these projects.

Table 1-4 shows project delivery costs by each of the four project types in the Study for the smaller project subset of TCC. The trends in the project delivery costs for the projects in the smaller project subset of TCC follow that of the projects in the full range of TCC. As expected based upon the Agencies’ practical experience, project delivery costs are higher for projects that fall in the smaller project subset of TCC.

Type

Design

Construction

Managem

ent

Project Delivery

(Total)

Median Total

Construction C

ost ($M)

Num

ber of Projects (N

)




Table 1-4 Project Delivery Costs by Project Type (% of TCC)

(Smaller Project Subset of TCC)


Consultant Usage Analysis

Project del ivery performance and consultant usage by agency are presented in Table 1-5. The table indicates that approximately 56 percent of the design work and approximately 82 percent of the construction management efforts are completed in-house by the participating agencies. Consultants account for approximately 32 percent of the total project delivery costs while in-house efforts by the participating agencies accounts for the remaining 68 percent of the project delivery costs. For the available data, a clear relationship between the level of in-house effort and project delivery costs cannot be established.

regression Analysis resultsDuring Update 2008, several changes were made to improve the modeling methodology. These included developing a statistically-sound method for outlier analysis, using a linear trendline for modeling project costs relationships, and using the upper and lower bounds of a 90 percent confidence interval to estimate the range of the project delivery percentages. As a result of these improvements, the model relationships could be predicted with a higher degree of certainty as compared to previous Study years. During Update 2009, the modeling methodology was further refined by analyzing the data in two ranges of TCC.

Given all these improvements to the analysis of the data, the reader is advised that direct comparison of data between Update 2009 and previous years may be more difficult due to these improvements.


AG

ENC

Y

D E

S I

G N

CO

NST

RU

CTI

ON

MA

NA

GEM

ENT

PRO

JEC

T D

ELIV

ERY

TCC

In-H

ouse

Con

sulta

nts

In-H

ouse

Con

sulta

nts

In-H

ouse

Con

sulta

nts

Average

Median

($M)

% of Design1

($M)

% of Design

Total % of TCC2,3

($M)

% of CM

($M)

% of CM

Total % of TCC

($M)

% of PD

($M)

% of PD

Total % of TCC

Age

ncy

A31

.547

%35

.953

%27

%32

.968

%15

.232

%15

%64

.456

%51

.144

%42

%2.

50.

7A

genc

y B

12.2

47%

13.5

53%

18%

11.6

61%

7.6

39%

12%

23.8

53%

21.1

47%

30%

1.4

0.4

Age

ncy

C25

.393

%2.

07%

17%

24.7

97%

0.8

3%17

%50

.095

%2.

85%

34%

1.6

1.1

Age

ncy

D62

.253

%55

.047

%22

%10

0.1

85%

17.6

15%

21%

162.

369

%72

.531

%43

%5.

01.

3A

genc

y E

3.4

30%

8.0

70%

19%

6.8

72%

2.6

28%

14%

10.3

49%

10.6

51%

33%

2.3

1.1

Age

ncy

F38

.561

%24

.739

%25

%44

.488

%5.

912

%22

%82

.973

%30

.627

%47

%1.

40.

4A

genc

y G

13.3

60%

8.8

40%

25%

9.4

100%

0.0

0%13

%22

.772

%8.

828

%38

%0.

80.

4O

VER

ALL

186.

556

%14

7.9

44%

23%

230.

082

%49

.718

%17

%41

6.5

68%

197.

632

%40

%2.

20.

6

Tabl

e 1-

5 Pr

ojec

t Del

iver

y Pe

rfor

man

ce a

nd C

onsu

ltant

Usa

ge b

y A

genc

y

Not

es:

1 In-

Hou

se a

nd C

onsu

ltant

cos

ts ar

e ex

pres

sed

as p

erce

ntag

es o

f tot

al a

genc

y D

esig

n, C

M (C

onstr

uctio

n M

anag

emen

t), a

nd P

D (P

roje

ct D

eliv

ery)

cos

ts.

2 Tot

al C

onstr

uctio

n C

ost (

TCC

) is t

he su

m o

f con

struc

tion

cont

ract

aw

ard,

cha

nge

orde

rs, u

tility

relo

catio

n co

st, a

nd c

ity fo

rces

con

struc

tion

cost.

3 Des

ign,

CM

, and

PD

cos

ts ar

e ex

pres

sed

as p

erce

ntag

es o

f TC

C a

nd a

re u

nwei

ghte

d, a

rithm

etic

ave

rage

s of p

roje

cts b

y ag

ency

.


The results of the regression analyses are discussed in the remainder of this section. The results of the regression analyses are summarized in Table 1-6 and Table 1-7. Table 1-6 summarizes the performance model results for the full range of TCC while Table 1-7 summarizes the results for the smaller project subset of TCC. These tables also summarize the design, construction management, and project delivery costs expressed as a percentage of the TCC and the R2 and the p-values for the different project types.

The plots depicting the regression relationships are shown in Appendix B. It should also be noted that while majority of projects are clustered near the origin of the graph, the slope of the trendline is predominantly governed by the data points scattered at relatively high TCC values. Since the slope of the trendline provides the design, construction management, or the project delivery costs as a percentage of the TCC for a group of projects, the results better reflect the properties of a program of projects rather than that of an individual project. Therefore, the reader must avoid budgeting individual projects based on these analyses.

In most cases, the results reflect the agencies’ experience with the delivery of capital projects that on a percentage basis projects with lower TCCs are more expensive to deliver than projects with higher TCCs.

It is important to note that while the slopes of the linear regression models are an expression of the project delivery cost as a percentage of construction, the slopes are not equal to the average and median project delivery percentages. The project delivery percentages in Table 1-2 represent arithmetic averages of the individual projects and do not represent the results for the regression analysis.

In addition, it should be noted that although the R2 and p-values are higher than in previous Study phases, the reader is cautioned that this table only be used as a reference and not for future prediction of future performance. Readers are urged to review the curves in Appendix B in conjunction with using this table.

c. BeSt mAnAgement PrActIceSAt the start of the Study, the agencies examined over 100 practices used in project delivery. Included in the Study are those practices that the study participants did not already commonly use, but believed should be implemented as BMPs. New BMPs are also added annually, and in some cases existing BMPs are reworked by the agencies to address specific challenges they encounter. BMPs are also added or modified to reflect new learnings by the participants. Agency implementation of these selected practices has been and will continue to be tracked during the Study.


Tabl

e 1-

6 Su

mm

ary

of P

erfo

rman

ce M

odel

s (F

ull R

ange

of T

CC

)

Not

es:

1 TC

C =

Tot

al C

onstr

uctio

n C

ost;

Des

. = D

esig

n C

ost;

CM

= C

onstr

uctio

n M

anag

emen

t Cos

t, an

d PD

= P

roje

ct D

eliv

ery

Cos

t. C

I = C

onfid

ence

Inte

rval

. The

pro

ject

de

liver

y pe

rcen

tage

s ind

icat

ed ar

e the

rang

es co

rresp

ondi

ng to

the 9

5 pe

rcen

t con

fiden

ce in

terv

als o

n th

e slo

pe o

f the

line

ar re

gres

sion

trend

line.

Cau

tion

and

revi

ew o

f th

e rep

ort t

ext a

re u

rged

in u

sing

this

info

rmat

ion.

Ref

er to

App

endi

x B

for t

he co

rresp

ondi

ng re

gres

sion

curv

es, R

2 va

lues

, and

N v

alue

s for

mor

e det

ails

. Hig

hlig

hted

va

lues

indi

cate

thos

e fo

r whi

ch R

2 va

lues

wer

e lo

w (b

elow

0.5

0).

2 Oth

er P

ipes

Pro

ject

s are

not

incl

uded

in th

is ta

ble

due

to a

smal

l num

ber o

f pro

ject

s (le

ss th

an 5

).

Proj

ect T

ype

or

Classificatio

nN

umbe

r of

Proj

ects

(N)

Des

ign

Cos

tC

onst

ruct

ion

Man

agem

ent C

ost

Proj

ect D

eliv

ery

Cos

t

(% o

f TC

C)

95%

CI (

%

of T

CC

)R

2p-

valu

e(%

of

TCC

)95

% C

I (%

of

TC

C)

R2

p-va

lue

(% o

f TC

C)

95%

CI (

%

of T

CC

)R

2p-

valu

e

Mun

icip

al P

roje

cts

116

17%

16%

-19%

0.90

8.28

E-59

18%

17%

-19%

0.92

1.06

E-65

35%

34%

-38%

0.94

3.06

E-71

Libr

arie

s23

16%

9%-1

6%0.

633.

11E-

712

%7%

-15%

0.59

1.22

E-5

28%

19%

-28%

0.77

1.41

E-9

Polic

e/Fi

re S

tatio

ns31

17%

14%

-22%

0.78

6.05

E-11

16%

13%

-21%

0.75

2.5E

-10

33%

29%

-41%

0.81

3.14

E-12

Com

m./R

ec.C

ente

r/C

hild

Car

e/G

yms

5017

%13

%-1

8%0.

772.

2E-1

711

%7%

-11%

0.64

1.28

E-13

28%

21%

-28%

0.80

4.91

E-20

Oth

er M

unic

ipal

1218

%15

%-2

1%0.

941.

5E-7

19%

18%

-21%

0.99

1.82

E-11

37%

34%

-42%

0.98

6.48

E-10

Stre

ets

Proj

ects

263

16%

14%

-17%

0.63

1.26

E-59

18%

17%

-19%

0.94

5.7E

-165

34%

32%

-35%

0.91

8.4E

-137

Wid

enin

g/N

ew/

3313

%10

%-1

4%0.

746.

17E-

1319

%18

%-2

0%0.

977.

07E-

2632

%29

%-3

3%0.

971.

04E-

27G

rade

Sep

arat

ions

Brid

ges

1035

%18

%-5

2%0.

731.

62E-

312

%10

%-1

3%0.

983.

18E-

847

%31

%-6

3%0.

851.

58E-

4

Rec

onst

ruct

ions

6924

%23

%-3

1%0.

691.

31E-

917

%17

%-2

1%0.

831.

11E-

2841

%40

%-5

1%0.

791.

19E-

25

Bike

/Ped

estri

an/

Stre

etsc

apes

7820

%15

%-2

2%0.

531.

91E-

1414

%10

%-1

5%0.

626.

52E-

1834

%25

%-3

6%0.

629.

52E-

18

Sign

als

7316

%10

%-1

6%0.

433.

29E-

1217

%13

%-1

8%0.

616.

69E-

1734

%25

%-3

2%0.

752.

22E-

27

Pipe

s Pr

ojec

ts26

79%

9%-1

0%0.

885.

0E-1

2510

%9%

-10%

0.99

1.3E

-307

19%

18%

-19%

0.96

6.6E

-193

Gra

vity

Mai

ns22

79%

9%-1

0%0.

885.

7E-1

0710

%9%

-10%

1.00

5.9E

-277

19%

18%

-19%

0.96

1.5E

-164

Pres

sure

Sys

tem

s22

7%0%

-7%

0.00

7.28

E-2

10%

4%-1

0%0.

467.

52E-

517

%5%

-17%

0.23

1.35

E-3

Pum

p St

atio

ns13

14%

11%

-17%

0.89

9.95

E-07

10%

6%-1

2%0.

801.

75E-

0524

%20

%-2

5%0.

972.

21E-

10

Park

s Pr

ojec

ts83

25%

24%

-29%

0.83

5.5E

-33

10%

7%-1

1%0.

499.

04E-

1535

%33

%-3

8%0.

911.

28E-

43

Play

grou

nds

6521

%19

%-2

2%0.

891.

07E-

3215

%14

%-1

7%0.

872.

8E-2

936

%33

%-3

8%0.

927.

15E-

37

Spor

tfiel

ds12

30%

31%

-46%

0.84

7.78

E-07

4%0%

-3%

0.00

3.27

E-1

34%

31%

-47%

0.90

1.46

E-6

Res

troom

s6

38%

5%-1

11%

0.58

3.89

E-2

18%

0%-3

1%0.

421.

13E-

155

%32

%-1

10%

0.80

7.27

E-3


Tabl

e 1-

7Su

mm

ary

of P

erfo

rman

ce M

odel

s (S

mal

ler P

roje

ct S

ubse

t of T

CC

)

Not

es:

1 TC

C =

Tot

al C

onstr

uctio

n C

ost;

Des

. = D

esig

n C

ost;

CM

= C

onst

ruct

ion

Man

agem

ent C

ost,

and

PD =

Pro

ject

Del

iver

y C

ost.

CI =

Con

fiden

ce In

terv

al. T

he p

roje

ct

deliv

ery

perc

enta

ges i

ndic

ated

are t

he ra

nges

corre

spon

ding

to th

e 95

perc

ent c

onfid

ence

inte

rval

s on

the s

lope

of t

he li

near

regr

essio

n tre

ndlin

e. C

autio

n an

d re

view

of

the

repo

rt te

xt a

re u

rged

in u

sing

this

info

rmat

ion.

Ref

er to

App

endi

x B

for t

he c

orre

spon

ding

regr

essi

on c

urve

s, R

2 va

lues

, and

N v

alue

s for

mor

e de

tails

. Hig

hlig

hted

va

lues

indi

cate

thos

e fo

r whi

ch R

2 va

lues

wer

e lo

w (b

elow

0.5

0).

2 Oth

er P

ipes

Pro

ject

s are

not

incl

uded

in th

is ta

ble

due

to a

smal

l num

ber o

f pro

ject

s (le

ss th

an 5

).

Proj

ect T

ype

or

Classificatio

nN

umbe

r of

Proj

ects

(N)

Des

ign

Cos

tC

onst

ruct

ion

Man

agem

ent C

ost

Proj

ect D

eliv

ery

Cos

t

(% o

f TC

C)

95%

CI (

%

of T

CC

)R

2p-

valu

e(%

of

TCC

)95

% C

I (%

of

TC

C)

R2

p-va

lue

(% o

f TC

C)

95%

CI (

%

of T

CC

)R

2p-

valu

e

Mun

icip

al P

roje

cts

9317

%13

%-1

7%0.

648.

17E-

2314

%12

%-1

5%0.

734.

58E-

2831

%25

%-3

2%0.

788.

89E-

33Li

brar

ies

1818

%6%

-23%

0.41

2.29

E-3

12%

0%-9

%0.

005.

63E-

130

%6%

-27%

0.07

3.65

E-3

Polic

e/Fi

re S

tatio

ns25

14%

7%-1

3%0.

544.

22E-

714

%10

%-1

5%0.

791.

28E-

928

%18

%-2

8%0.

751.

87E-

09C

omm

./Rec

.Cen

ter/

Chi

ld C

are/

Gym

s40

19%

11%

-22%

0.45

8.11

E-7

14%

10%

-16%

0.69

1.3E

-11

34%

23%

-35%

0.66

3.14

E-11

Oth

er M

unic

ipal

1017

%14

%-2

2%0.

933.

25E-

610

%3%

-12%

0.52

7.04

E-3

26%

20%

-31%

0.93

5.7E

-6St

reet

s Pr

ojec

ts20

827

%22

%-3

0%0.

447.

85E-

2819

%15

%-2

0%0.

506.

97E-

3346

%39

%-4

9%0.

611.

05E-

44W

iden

ing/

New

/ 26

26%

9%-2

9%0.

314.

72E-

417

%11

%-2

1%0.

663.

48E-

743

%23

%-4

7%0.

534.

4E-6

Gra

de S

epar

atio

nsBr

idge

s8

37%

7%-3

9%0.

261.

29E-

216

%5%

-21%

0.65

6.43

E-3

53%

19%

-53%

0.50

2.18

E-3

Rec

onst

ruct

ions

5523

%15

%-2

8%0.

452.

43E-

814

%9%

-14%

0.51

1.31

E-10

37%

26%

-40%

0.62

5.4E

-13

Bike

/Ped

estri

an/

Stre

etsc

apes

6128

%15

%-3

2%0.

343.

36E-

719

%14

%-2

6%0.

445.

56E-

947

%32

%-5

6%0.

489.

46E-

10

Sign

als

5825

%15

%-3

0%0.

391.

31E-

721

%7%

-25%

0.17

6.25

E-4

46%

29%

-50%

0.50

1.99

E-10

Pipe

s Pr

ojec

ts21

417

%11

%-1

6%0.

313.

36E-

2117

%14

%-1

8%0.

601.

75E-

4435

%26

%-3

4%0.

542.

61E-

39

Gra

vity

Mai

ns18

217

%11

%-1

6%0.

326.

47E-

1918

%15

%-1

9%0.

597.

38E-

3735

%27

%-3

4%0.

553.

87E-

34

Pres

sure

Sys

tem

s18

11%

4%-1

5%0.

481.

07E-

314

%11

%-1

7%0.

855.

52E-

825

%17

%-3

0%0.

797.

35E-

7

Pum

p St

atio

ns10

21%

8%-2

6%0.

622.

05E-

322

%16

%-2

9%0.

894.

34E-

543

%27

%-5

1%0.

866.

61E-

5

Park

s Pr

ojec

ts66

21%

11%

-23%

0.30

5.54

E-7

14%

6%-1

4%0.

232.

68E-

635

%19

%-3

4%0.

403.

8E-1

0

Play

grou

nds

5223

%13

%-2

4%0.

442.

01E-

814

%4%

-13%

0.09

1.09

E-3

36%

19%

-35%

0.42

4.96

E-9

Spor

tfiel

ds10

12%

0% -

24%

0.26

1.5E

-110

%0%

-12%

0.00

2.31

E-1

21%

0%-3

1%0.

002.

17E-

1

Res

troom

s5

11%

0% -

23%

0.00

5.77

E-1

25%

10%

-49%

0.86

1.68

E-2

36%

2%-6

5%0.

784.

38E-

2


In Update 2009, the Project Team added one new BMP under a new category called Sustainable Development to the BMP Implementation tracking list. This BMP was developed to address the growing need to incorporate environmental sustainability in engineering design and construction practices. The agencies felt that this new category should be added to Best Management Practices. The BMP was worded as:

7.a.2009 - To quantify the envi-• ronmental benefits of the project at the time of award.

This BMP is believed to influence the cost of either design or construction management and, ultimately, project delivery efficiency. This BMP also has an intangible benefit through its positive long range effect on our environment.

d. onlIne dIScuSSIon forumThe following discussion topics are summarized in the Chapter 5 Online Discussion Forum.

Infrastructure and Fixed Assest • Capitalization Policies

Permeable and • Pervious Pavements

Separate Section for Estimating • and Scheduling

Resource Level Scheduling•

Qualification Based Con-• sultant Selection (QBCS) Policy/Procedure

Materials Testing Laboratory • Services

Project Labor Agreement•

Covered Pedestrian Walkways•

Job Order Contracting•

An archive of the full discussion forum is posted confidentially on the Study website for access by the participants.

e. concluSIonS

I. Performance BenchmarkingThis year’s Study focused on refining the modeling methodology used to develop relationships between the different components that constitute project delivery costs and the TCC. Statistical studies to determine the best-fit curve for the projects in the database revealed that the linear trendline was the best-fit curve amongst the five types of curves (logarithmic, exponential, polynomial, power, and linear) selected for evaluation. Improvements to the model also resulted in good R2 and p-values indicating good relationships between the project delivery components and the TCC.


In order to incorporate the agencies’ observations that on a percentage basis, projects with lower TCCs are more expensive to deliver than projects with higher TCCs, the Study Team conducted investigations with an objective to identify a subset of project size (in terms of TCC) that represented what was generally considered as the smaller projects. Regressions and statistical tests for the smaller projects revealed that the delivery costs for the smaller projects were higher than for the full range of projects. Therefore, in Update 2009, project data was analyzed in two ranges of TCC. The results of this analysis conformed to the agencies’ practical experiences.

Although the results of the performance analyses are based on historical data provided by the participating agencies, there are several factors that affect project delivery and are not captured in the performance model. These external factors include personnel turnover in the agencies, competitive bids etc which impact project delivery. The reader is cautioned that the improved results of the regression analyses only be used as a reference and not for prediction of future performance.

Due to the current economic conditions, agencies are receiving bids that are significantly lower than the engineer’s estimates. Therefore, it should be noted that project data collected over the next few Study cycles may exhibit higher project delivery costs as a percentage of the TCC as a result of the low construction bids due to the current economic crisis. It is recommended that the reader use best judgment while using the Study results for planning and budgeting.

Project delivery percentages (arithmetic averages) for the Update 2009 Study varied between the following values for the full range and the smaller project subset of TCC respectively:

Municipal Projects: 36% - 39%

Parks Projects: 39% - 41%

Pipes Projects: 36% - 39%

Streets Projects: 46% - 49%


II. Best management PracticesThe agencies have continued to fully implement selected BMPs. Given the current state of the economy and due to staff reductions, furloughs, and the management’s increased involvement in resolving budgetary issues, progress on fully implementing BMPs has been impacted. The agencies have focused their efforts on tracking BMPs that have been implemented and which continue to provide efficiencies in project delivery processes for participating departments. As of Update 2009, the agencies have fully implemented about 72 percent of all BMPs. Many more have been partially implemented with the goal of complete implementation over the next two years. In Update 2009, the Project Team added one new BMP under a new category called Sustainable Development to the BMP Implementation tracking list. This BMP was developed to address the growing need to incorporate environmental sustainability in engineering design and construction practices. This BMP also has an intangible benefit through its positive long range effect on our environment. BMPs in the other areas will be discussed and developed during future Study phases.

As the BMPs are implemented, participating agencies should begin to realize project delivery efficiencies including but not limited to reduction in delivery times, reduced change orders, and overall project cost reductions.

III. online discussion forumIn Update 2009, the Agencies transitioned from using emails to an online portal for collaboration on project delivery issues. There are several benefits of this transition one of which is the ability to archive all topics of discussion in a single location which is easily accessible. The use of the online portal also ensures that communication is not lost when a member leaves the Project Team.

The Online Discussion Forum continues to be an increasingly important feature for Study participants, with active exchanges occurring frequently and important issues addressed with changes to policy, approach, or BMP implementation. Participants will continue sharing information through the Online Discussion Forum and during the quarterly meetings, and presenting the more interesting results to the public through the Study reports. The continued sharing of challenges and solutions through the Online Discussion Forum remains a remarkable advantage to all participants.

chapter

Introduction2

Page 17

During these highly challenging economic times, the California Mult i-Agency CIP Benchmarking Study (Study) has continued its unparalleled effort to share the collective Capital Improvement Project implementation experiences of seven out of the eight largest cities in California for the eighth consecutive year. Since the participating Cities of Long Beach, Los Angeles, Oakland, Sacramento, San Diego, San Jose and the City and County of San Francisco first initiated these efforts, they have obtained a better understanding of the changing capital project delivery process.

This year, the participating agencies spent a substantial amount of effort sharing approaches to continue to provide high value implementation of their capital programs in the most efficient manner possible in the face of unprecedented fiscal hardships. The Study provides a forum for the Agencies to share information amongst themselves via: quarterly meetings with a focus on current issues, an online portal where topics for discussion can be posed and challenges addressed, and a database that serves as both, a repository of the Agencies’ projects and a tool for data analysis. Through these acts of collaboration, often times an optimum solution is found that can be translated into a Best Management Practice (BMP) for the group.

The sharing of best ideas amongst the Study participants have benefitted the agencies and owners can turn to one another to gather insight on how to address challenges that might be new to them, but which others have already faced.

In this eighth year of the Study, the Update 2009 participants have continued to pursue on-going endeavors, as well as taken on new ones:

Addition of the “Special Topic” • roundtable discussion forums at Quarterly Meetings to explore areas of potential positive impact in relation to the current fiscal challenges;

Improved online discussion • forum for efficient information sharing;

Continued improvement to the • modeling methodology of the performance models;

Continue to improve the quality • of the performance data and the functionality of the database;

Track the adoption of BMPs; • and

Create new BMPs targeted to • common issues.


A. BAckgroundIn October 2001, the City of Los Angeles, Department of Public Works, Bureau of Engineering initiated the Study with several of the largest cities in California. These cities joined together to form the Project Team for the Study. After working together for eight years, this team agrees that they benefit from collaborating and pooling their project delivery knowledge and experience. The Study initially involved six agencies, with a seventh joining the team in 2003. The participating agencies currently include:

City of Long Beach, Department • of Public Works

City of Los Angeles, Depart-• ment of Public Works, Bureau of Engineering

City of Oakland, Department of • Engineering and Construction

City of Sacramento, Department • of General Services, Depart-ment of Transportation, and Department of Utilities

Ci ty of San Diego, Engi -• neering and Capital Projects Department

City and County of San Francis-• co, Department of Public Works, Bureau of Engineering, Bureau of Architecture, and Bureau of Construction Management

City of San Jose, Depart-• ment of Public Works and City Manager’s Office

Table 2-1 summarizes some of general characteristics of the participating agencies and/or of specific departments.

Upon initiation of the Study, it was agreed that published data provided by Study participants should remain anonymous in order to create a positive, non-competitive team environment, conducive to meeting the Study’s goals.

Chapter 2 Introduction

Page 19

B. Benefits of PArticiPAtionThe participating agencies have been very supportive of the Study efforts over the years. The Study is possible only because the agencies believe they are benefiting from their continued participation.

The agencies have expressed the benefits they experience in a variety of ways:

The City of San Jose continues to • benefit by having ready access to the performance data and BMPs of the largest cities in California. This has assisted their decision-making process regarding policy and procedural improvements, especially with regard to newer topics that impact capital project delivery such as LEED [Leader-ship in Energy and Environmental Design] and ”green building” initia-tives and alternative contracting

Information Population2Area (sq. mi.)

Website Government Form

Long Beach 492,682 50 http://www.longbeach.govCouncil-

Manager- Charter1

Los Angeles 4,065,585 469 http://eng.lacity.org Mayor-Council

Oakland 425,068 66 www.oaklandnet.com Mayor-Council-Administrator

Sacramento

481,097 99 http://www.cityofsacramento.org

Council- Manager

Dept. of General ServicesDept. of TransportationDept. of Utilities

San Diego 1,353,993 342 http://www.sandiego.gov Mayor-Council

San Francisco 845,559 47 http://www.sfdpw.com

Mayor-Board of

Supervisors (11 members)

San Jose 1,006,892 178 http://www.sanjoseca.gov Mayor-Council-Manager

Table 2-1 Agencies’ Overall Information

Notes: 1 Mayor has veto power.2 Source: California Department of Finance Population Estimates for Cities, Counties, and the State.


methods (e.g., design-build). San Jose also offers: “What is great is that we learn new things at every meeting that lead to ways we can challenge ourselves to improve our processes and procedures. The online forum has also proved to be a very valuable tool between meetings and has generated some very informative discussions on a broad range of topics.”

“The City and County of San • Francisco uses the Benchmarking Study in working with other City agencies using our services. De-sign costs initially quoted by out-side consultants may not reflect the final design costs associated with occupied facilities, seismic retrofits, and rehabilitation (espe-cially involving corrosion, dry rot and hazardous material abate-ment). Presenting seven cities’ data is far more persuasive than presenting our estimates and past data alone. International prices for steel, cement, and petroleum-based products have been vola-tile over the past 5 years. Since the mortgage lending and auto company economic crisis, the bid-ding environment has been even more unpredictable. Having the larger sample size of information afforded by the Benchmarking Study is essential to forecasting pricing trends with any degree of certainty. The online forum has helped us provide elected officials accurate information quickly re-garding other cities’ practices on accepting streets and structures for maintenance, and how main-tenance work is funded.”

The City of Los Angeles has • stated that “in addition to the general benefits that we have described in past years and con-tinue to receive from participation in the benchmarking group, there was one very notable additional benefit this study year in that it was very helpful in dealing with the challenges resulting from the sharp downturn in the economy. We found that many of the agen-cies were experiencing some-what similar challenges, but were dealing with them in slightly dif-ferent ways. For instance, many agencies had either implement-ed furloughs, or were planning to in the near future. It was very helpful to hear how the agencies were handling tasks such as construction management and inspection within their furlough programs. Responses ranged from declaring the furlough days non-working days to staggering staff furlough days so that con-struction projects would stay on the original schedule.”

The City of Long Beach offers • this comment: “In an unprec-edented period of budget reduc-tions, cost reallocations, chang-ing bid environment, increasing public awareness and scrutiny, and the ever growing green movement, having the abil-ity to compare notes on project delivery with other agencies in California has moved from being a luxury to a necessity. When every dollar spent on delivering a project needs to be justified and


Page 21

accounted for, it becomes ex-tremely important for cities to be able share project delivery suc-cesses and failures in a coopera-tive unthreatening environment. By doing so, the successes can be rapidly duplicated statewide, and hopefully, future failures avoided, thus saving time and money if each agency were to have to discover these project delivery methods on their own. Participation in the statewide benchmarking process has al-lowed the City of Long Beach to share and acquire such knowl-edge allowing the City to meet head on the current challenges of project delivery.”

According to the City of Sacramen-• to, “the benefits of our continued participation in the Study have increased geometrically each year we have participated. Our data col-lection and tracking have evolved to mirror the Study format, making it much easier for us to directly cor-relate the results of our work and effort with that of our industry peers. As we continue to implement new BMPs each year, our project man-agement and delivery standards have improved greatly over where we were just a few years ago. We have also found that the online discussion forum is an invaluable resource when we are research-ing a new policy or practice, as all of the participating agencies are very generous in sharing their own knowledge, standards, and practices.”

The City of San Diego “finds • the Study extremely useful in validating our Engineering De-partment’s performance and in setting benchmarks and goals, especially after our implemen-tation of our Business Process Reengineering. Participation in the quarterly meetings allows us to share information on new pro-cesses that we or the other agen-cies are implementing, and we always get new or better ideas to improve our project delivery. The discussion forum is a great way to keep the momentum between meetings and to share detail in-formation on processes.”

According to the City of Oakland • “the Study has been an invalu-able resource to help the City of Oakland deliver its CIP. It has provided hard data from seven out of the eight largest California cities on the costs of planning, designing and constructing proj-ects ranging from small restroom remodels to multimillion dollar street, sewer and building proj-ects. It also has allowed compari-son of BMPs used by each City to deliver projects; and provided a mechanism to obtain instant responses from each City to questions about how to improve their processes. The Study has greatly improved Oakland’s ability to deliver projects better, cheaper and faster.”


c. study focusImproving the accuracy and the functionality of the performance models has been a continuous goal of the Study. During Update 2008, the regression models were refined and the resultant R2 values (a measure of goodness-of-fit of the trendline) typically increased tenfold. Although these activities resulted in an improved performance model and laid the foundations for this year’s Study, the model did not fully capture the Agencies’ practical experiences in the delivery of capital projects where it was generally observed that smaller projects normally cost more to deliver when the project delivery costs are expressed as a percentage of the TCC.

Therefore, this year special attention was given to refine the modeling methodology to incorporate the Agencies’ experiences. As part of the model refinements, statistical evidence was used to reconfirm the selection of a linear regression as the best-fit curve for the project data points. Using the linear model, it was possible to determine the benefits of evaluating the performance data considering two ranges of construction costs. This analysis revealed that an economy of scale exists in the delivery of capital projects reflecting the experiences of the Agencies. Details regarding the changes to the regression model are presented in Chapter 3 Performance Benchmarking.

In addition, the focus of the Quarterly Meetings was adjusted to include a “Special Topic” roundtable discussion forum. This forum explored areas of potential positive impact in relation to current events and fiscal challenges. Topics were identified prior to each meeting allowing time for each agency to prepare and participate meaningfully in the discussions.

d. study goAlsThe Study method is described in detail in the first Study report (published in 2002) and modifications to it have been documented in subsequent Study reports. In Update 2009 the agencies made progress on several goals:

Improve the modeling meth-1. odology to incorporate prac-tical project delivery consid-erations. Improving the perfor-mance models has been a con-tinuous goal of the Study. This year special attention was given to refine the modeling method-ology to reflect an economy of scale in the delivery of capital projects. The modeling meth-odology was refined to evaluate projects under two ranges of construction costs. The results from this evaluation provided support to the Agencies’ experi-ence that an economy of scale exists in the delivery of capital projects.

Conduct roundtable discus-2. sions on Special Topics. This year during each quarterly meet-ing roundtable discussions were held on current events. These sessions included discussions on innovative project delivery issues, the preparedness of the agencies to receive economic stimulus funding and the chal-lenges posed by the current economic crisis towards efficient project delivery, and quality as-surance and quality control of design and construction projects in the current fiscal crisis.


Page 23

Track the adoption of BMPs.3. The Study Team continued to track the implementation of BMPs in order to link these practices to project delivery performance improvement over time in order to encourage their implementation.

Create new BMPs targeted to 4. address commonly held prob-lem areas. The Project Team continued to discuss common challenges and share ideas for addressing those challenges during the quarterly meetings as well as in the online discus-sion forum. One new BMP was adopted by the Project Team for implementation and added to the BMP implementation list. This BMP involved the estimation of environmental benefits in concert with the project award process.

Continue efficient informa-5. tion sharing with one another through the online discussion forum. In Update 2009, the Project Team utilized an online portal for discussing issues and challenges. The use of the online portal allows for efficient archiving of discussion topics and ease of access. The Project Team uses the discussion forum to share information; survey cur-rent processes and policies; and collaborate on implementing new processes and policies.

chapter performanceBenchmarking3

page 25

Performance benchmarking involves collecting documented project costs and plotting the component costs of project delivery against the total construction cost (TCC). The objective of this exercise is to develop relationships between these variables. As explained later in this Chapter (see Section D and Section E), the adoption of statistical techniques for model selection and vast improvements in the modeling methodology have significantly improved the model results in Update 2009 as compared to the results obtained in previous Study years.

The project costs data are collected from the agencies using a Performance Questionnaire created in Microsoft Excel®. Data are then compiled from the questionnaires in Excel® using a Visual Basic for Applications (VBA) code and transferred into the database, where the data is reviewed and vetted. A copy of the current Performance Questionnaire can be found in Appendix A.

A. Study CriteriAThe following criteria applied to Update 2009 performance benchmarking analyses:

Total Construction Cost• – TCC is the sum of the awarded con-struction contract, net change orders, utility relocation, and construction by agency forces. TCC does not include land ac-quisition, environmental moni-toring and mitigation, design, or construction management costs. All projects included in the analyses have a TCC ex-ceeding $100,000. The partici-pating agencies use fully-loaded (direct and indirect) costs for project delivery tasks. They have also agreed that land acquisition costs and environ-mental impact mitigation costs should be excluded from the TCC calculation.

Completion Date• – Projects included in the Study analyses were completed on or after Janu-ary 1, 2004. Projects with earlier completion dates were kept in the database, but excluded from the analyses.


Outlier Elimination• – Statistical elimination was used to iden-tify outliers in the performance model. The total project delivery percentage of each project in the database was evaluated against all other projects in the same classification. An outlier was identified as a project whose total project delivery percentage was outside the range expressed by the following equation:

y=m + 3σ, where;

m represents the mean of the project delivery percentages and σ represents the standard deviation of the project delivery percentages for all projects in the same classification.

It should be noted that this ap-proach, which was first adopted in Update 2008, allows for the in-clusion of more data than in pre-vious years where other methods including visual inspection were used for the elimination of outlier data points. This change was in part allowed by the improved modeling techniques that will be described in more detail in sub-sequent subsections.

Projects confirmed as outliers by this statistical technique were kept in the database, but ex-cluded from the analyses.

Project Delivery Method• – All projects in this Study were de-livered through the traditional de-sign-bid-build method. Projects delivered using other project de-livery methods are not included in this Study at this time.

Change Order Classification• – To support meaningful change order analyses, the Project Team report-ed change orders in accordance with the following classifications:

Changed/Unforeseen 1. Conditions

Changes to Bid Documents2.

Client-Initiated Changes3.

Project Classifications – Sixteen • project classifications grouped into four project types are used in this Study. In Update 2008, two new project classifications, “Other Municipal Facilities” and “Other Pipes” were added to the Municipal and the Pipes proj-ects categories respectively. No projects were submitted by the agencies for the “Other Pipes” category in Update 2008. In Update 2009, five projects were submitted for the “Other Pipes” category. These two classifica-tions will include projects that do not fall under the existing Mu-nicipal and Pipes classifications but are representative of the Municipal and the Pipes catego-ries. The agencies will continue to collect data for these classifi-cations for future analyses. The project types and classifications are shown in Table 3-1.

Chapter 3 Performance Benchmarking

Table 3-1 Project Types and Classifications

Project Types Classifications

Municipal Facilities

Libraries• Police and Fire Stations• Community Centers, Recreation Centers, • Child Care Facilities, GymnasiumsOther Municipal Facilities• 1

Streets

Widening, New, and Grade Separation• Bridges• Reconstruction• Bike Ways, Pedestrian Ways, and Streetscapes• Signals•

Pipe Systems

Gravity Systems• Pressure Systems• Pump Stations• Other Pipes•

ParksPlaygrounds• Sportfields• Restrooms•

B. dAtA ColleCtion And ConfirmAtion

To obtain meaningful results from the performance model, it is essential that the data collected from the agencies are accurate and conform to the Study criteria. The agencies recognize the importance of quality input data and are committed to providing accurate, complete project delivery cost data to support the development of performance models. Project delivery costs are defined as the sum of all agency and consultant costs associated with project planning, design, bid, award, construction management, and closeout activities. Examples of specific activities included in each phase of project delivery are presented in Table 3-2.

For the Update 2009 Study, the agencies completed the questionnaires with comparable, complete, and accurate values. The agencies also review and compare their data collection and confirmation techniques on a regular basis. For example, in a quarterly meeting during Update 2008, each agency delivered a presentation describing how it compiles the project delivery data for the Performance Questionnaire. The presentations and the subsequent discussions helped clarify any inconsistencies in the data collection methodologies of the agencies. Such discussions ensure that inconsistencies in the data collection and confirmation process are identified and addressed. This also ensures that input data is vetted before projects are submitted for analysis.

Notes: 1 Projects include design and/or construction activities for parking structures, yards, soil anchors, docks, animal shelters, reservoirs, water treatment plants, piers, and animal services centers.


Category and Phase Description

1) Design Costs:

The design phase (and associated costs) begins with the initial concept development, includes planning as well as design, and ends with the issuance of a construction Notice to Proceed. Design costs consist of direct labor costs, other direct agency costs such as art fees and permits, and consultant services cost associated with planning and design. Design may include the following:

Planning

Complete schematic design documents• Review and develop scope • Evaluate schedule and budget• Review alternative approaches to design and construction• Obtain owner approval to proceed• Attend hearings and proceedings in connection with the project• Prepare feasibility studies• Prepare comparative studies of sites, buildings, or locations• Provide submissions for governmental approvals• Provide services related to future facilities, systems, or equipment • Provide services as related to the investigation of existing • conditions of site or buildings or to prepare as-built drawings Develop life cycle costs• Complete environmental documentation and clearances• Manage right-of-way procurement process• Monitor and control project costs•

Design

Complete design development documents • including outline specifications Evaluate budget and schedule against • updated construction cost estimate Complete design and specifications• Develop bid documents and forms including contracts• Complete permit applications• Coordinate agency reviews of documents• Review substitutions of materials and equipment• Prepare additive or deductive alternate documentation• Coordinate geotechnical, hazardous material, • acoustic or other specialty design requirements Provide interior design services• Monitor and control project costs•

Table 3-2 Project Cost Categories



Bid and Award

Prepare advertisement for bids• Qualify bidders• Manage the pre-bid conference• Evaluate bids• Prepare the recommendation for award• Obtain approval of contract award from Board/Council• Prepare the Notice to Proceed• Monitor and control project costs•

2) Construction Management Costs:

All costs associated with construction management, including closeout costs, are included in this category. Construction management costs consist of direct labor, other agency costs, and consultant usage. Construction management may include the following:

Construction

Hold pre-construction conference• Review and approve schedule and schedule updates• Perform on-site management• Review shop drawings, samples, and submittals• Perform testing and inspection• Process payment requests • Review and negotiate Change Orders • Prepare monthly reports to owner and agencies• Respond to Requests for Information• Develop and implement a project communications plan• Perform document control• Manage claims • Perform final inspections and develop and track punch list •

Closeout Phase

Commission facilities and equipment• Train maintenance and operation personnel• Document and track warranty and guarantee information • Plan move-in• File notices (occupancy, completion, etc.)• Check and file as-built documents• Monitor and control project costs•

3) Total Project Delivery Costs:

This is the total cost of delivering a capital improvement project, equal to the sum of the design cost and construction management costs indicated above.

Table 3-2 Project Cost Categories (cont’d)



4) Change Order Cost:

Please see the update 2005 Report for descriptions of the following types of change orders:

Changed/unforeseen conditions - This type of change • is necessitated by discovery of actual job site conditions that differ from those shown on the contract plans or described in the specifications. These are conditions a designer could not have reasonably been expected to know about during the design of the project. Changes to Bid Documents - This type of change is necessitated • by a mistake or oversight in the original contract documents and is required to correct the plans and specifications. Client-Initiated Changes - This type of change results from • additions, deletions or revisions to the physical work.

5)Total Construction Cost (TCC):

This is the direct construction cost, including all change orders during the construction phase (from the issuance of Notice to Proceed to Notice of Completion). The following costs are associated with construction and are included in the TCC:

Direct actual construction• Total amount of positive change orders throughout construction• Fixtures, furnishing, and equipment (FFE)• Utilities relocation• Work performed by the agency’s staff and other agencies’ staff•

C. PerformAnCe dAtABASeThe projects data submitted by the agencies are complied in a customized Microsoft Access® database. This database not only serves as a repository for the data collected since the inception of the Study, but also allows for data analysis using built-in functions. The database also provides customized reports and tables for easy data interpretation. Each year, the projects database is updated with the inclusion of projects data submitted for that Study year. The analysis and the reporting features of the database are also updated.

Table 3-3 summarizes the number of projects included in the database and in the analyses. The 5-year database used

for the current analysis contains 729 projects. This total excludes project data older than five years or projects identified as outliers. Projects identified as outliers are not included in the performance data analysis but are retained in the performance database. As explained under subsection A Study Criteria of this chapter, outlier analysis was performed using statistical techniques to ensure consistency in the selection of outlier data points. This methodology was first implemented during Update 2008 and the agencies recognize the merits of a scientific approach for outlier elimination. Some of the projects classified as outliers in previous Study years have been included in the performance data analysis, and vice-versa.

Table 3-2 Project Cost Categories (cont’d)


This is an improved practice when compared to prior Study years where project data points were classified as outliers based on a combination of statistical parameters and subjective judgments by the Project Team. Previously, projects identified as outliers during one Study phase were kept as outliers in subsequent Study phases.

Study Phase1

Submitted Deleted Increase Excluded Net

(a) Total (b) TCC <$100K

(c) Non-Repre-

sentative2

(d)=(a)-(b)-(c)

(e) Project Completion Date <2002

(f) Outliers3

Projects in

Analyses (h)= (d)-(e)-(f)-(g)

I 237 25 44 168 168 0 0II 285 0 35 250 250 0 0III 262 0 29 233 230 0 3IV 170 17 21 132 36 4 92V 182 0 3 179 19 3 157VI 189 0 0 189 3 2 184VII 158 1 0 157 7 3 147VIII 151 2 0 149 1 2 146

Total 1,634 45 132 1,457 714 14 729Notes: 1 Study Phase indicates action taken on the count of projects corresponding to Study Years I = 2002, II = 2003, III = 2004, IV = 2005, V = 2006, VI = 2007, and VII = 2008.2Projects that do not fit Study criteria for project classifications and minimum TCC of $100K were removed from the database.3Outliers are identified based on statistical analysis and visual elimination.

Table 3-3 Growth of Database

Table 3-3 shows that as the rules for project selection got refined, non-representative projects and projects with TCC less than $100K have gone down. In addition, only 14 projects have been excluded as outliers in the Update 2009 Study as compared to the elimination of 147 projects in Update 2007 and 113 projects in Update 2006.

As previously indicated, there are 4 project types (Municipal Facilities, Streets, Pipe Systems, and Parks) and 16 project classifications included in this Study. Table 3-4 summarizes the distribution of projects included in the Update 2009 analyses.

In the Study 2002 report, it was recommended that at least 10 projects per classification and a minimum data set of 2,000 projects distributed evenly among classifications, ranges of TCC, and agencies are necessary to achieve statistically-significant results.

Although the requirement for the minimum number of projects per classification has been met for most project categories, more data needs to be collected to ensure an even distribution of projects amongst all classifications.

The agencies acknowledged that it is vital to the success of the Study to continue increasing the size of the data set, thereby increasing the confidence, consistency, and reliability of results.


Age

ncy

Long

B

each

Los

Ang

eles

Oak

land

Sacr

amen

toSa

n D

iego

San

Fran

cisc

oSa

n Jo

seTo

tal

Mun

icip

al F

acili

ties

536

1211

108

3411

6Li

brar

ies

010

00

31

923

Polic

e/Fi

re S

tatio

ns1

91

64

28

31C

omm

./Rec

. Cen

ter/

Chi

ld C

are/

Gym

s1

1510

41

415

50

Oth

er M

unic

ipal

Fac

ilitie

s23

21

12

12

12St

reet

s9

1642

5544

3958

263

Wid

enin

g/N

ew/

Gra

de S

epar

atio

ns0

60

115

29

33

Brid

ges

(New

/Ret

rofit

)0

40

21

03

10

Rec

onst

ruct

ions

74

184

422

1069

Bike

/Ped

estri

an/

12

1827

115

1478

Stre

etsc

apes

10

611

2310

2273

Sign

als

287

3436

3632

4026

7Pi

pe S

yste

ms

282

3427

2126

3522

7G

ravi

ty S

yste

ms

(Sto

rm

Dra

ins/

Sew

ers)

00

06

86

222

Pres

sure

Sys

tem

s0

10

27

03

13Pu

mp

Stat

ions

04

01

00

05

Park

s2

826

21

935

83Pl

aygr

ound

s2

320

11

929

65Sp

ortfi

elds

05

41

00

212

Res

troom

s0

02

00

04

6To

tal1

1814

711

410

491

8816

772

9N

otes

: 1 T

otal

refe

rs to

the

proj

ects

incl

uded

in th

e U

pdat

e 20

09 a

naly

ses o

nly.

2 Pro

ject

s inc

lude

des

ign

and/

or c

onstr

uctio

n ac

tiviti

es fo

r par

king

stru

ctur

es, y

ards

, soi

l anc

hors

, doc

ks, a

nim

al sh

elte

rs, r

eser

voirs

, wat

er tr

eatm

ent p

lant

s, pi

ers,

and

anim

al se

rvic

es c

ente

rs.

Tabl

e 3-

4 Pr

ojec

ts D

istr

ibut

ion

Mat

rix


d. PerformAnCe model SeleCtionPrior to discussing the model selection methodology for Update 2009, a brief overview of the relevant statistical terminology and their definitions is provided.

Regression DefinitionsPerformance curves produced for this Study are regressions of data, demonstrating how close of a relationship exists between the dependent variable (on the y-axis) and the independent variable (on the x-axis). For instance, a regression curve of design cost versus TCC would be prepared to evaluate how much of the variability in design cost is due to the TCC value.

The regression trendline can be used as a starting point for evaluating the budget for a suite of projects. Caution and use of professional judgment is required if using the regression trendline to budget an individual project.

Confidence Interval

The upper and lower bounds of the confidence interval indicates the level of certainty in a data set and how likely it is that a random sample from the data set will fall within the interval. The wider the distance between the upper and lower bounds of a confidence interval, the less certainty in the model and greater the need to collect more data before drawing conclusions from the data set.

Coefficient of Determination

A best-fit logarithmic curve is calculated using the least-squares method in Excel®, and a R2 value is displayed. The R2 value, also called the coefficient of determination, is a value between 1 and 0, with a value

approaching 0 indicating a poor model and a value approaching 1 indicating a high dependence of the y-value statistic on the x-value statistic.

Statistical Significance

To evaluate the statistical significance of the result obtained, the regression analyses included a calculation of p-values. Whereas the R2 value is a descriptive statistic (i.e., describes the current set of data), the p-value is a predictive statistic. It indicates whether there are enough data points to arrive at statistically-significant results and whether the data set could be used to forecast new values. The selection of a desirable p-value is subjective, though 0.10 or 0.05 is usually used as the maximum desirable value.

For the purposes of this Study, a critical p-value of 0.10 was selected. Thus, any result where p ≤ 0.10 is considered statistically significant. There is no difference between a p-value slightly below 0.10 as one that is far below 0.10. Both results are considered to have equal statistical significance.

For regressions resulting in a p-value above 0.10, additional projects should be added to the database to improve the result. Please see the Study 2002 report for additional detail on the connection between the number of projects and p-values.

For each of the regressions, the R2 value and p-value should be considered separately. A high R2 value does not mean the result is statistically-significant, and vice-versa.


Model Selection During Update 2008, a significant amount of time and effort was expended on improving the accuracy of the performance model. A linear trendline was selected to replace the logarithmic relation between the project delivery costs and the TCC. These efforts yielded positive results by eliminating auto-correlation in the modeling methodology and by producing significant improvements in the performance model results that yielded R2 values of significantly higher magnitudes.

Although the participating agencies acknowledge the merits of a refined performance model using a l inear trend line, it does not completely reflect the agencies’ observations that on a percentage basis, projects with lower TCCs are more expensive to deliver than projects with higher TCCs. At the request of the participating agencies, during Update 2009 the Study Team evaluated five types of curves (logarithmic, exponential, polynomial, power, and linear) to determine the best-fit curve for the regression model.

Logarithmic and exponential curves resulted in poor R2 values and generally fit poorly to the data points. Although polynomial curves exhibited good R2 values, they did not model real world results. Power curves generated good R2 values and represented a good fit for the project data. In all the cases, the resulting power curves were almost linear in nature. However, the associated expression used to calculate the project delivery percentage was mathematically complex. Linear

trendlines generated good R2 values and represented a good fit for the project data. In addition, the associated expression used to calculate the project delivery percentage was a simple mathematical relationship.

The findings of the best-fit analysis were reviewed by a statistics expert before being presented to the participating agencies during a quarterly meeting. The participating agencies agreed with the results of the analysis and approved the use of the linear trendline as the best-fit curve for the project data points, particularly with the enhancements made to the modeling methodology discussed in the next subsection.

e. modeling methodologyTo explore the agencies’ observations that on a percentage basis, projects with lower TCCs are more expensive to deliver than projects with higher TCCs, the Study Team conducted additional investigations. The objective was to identify a subset of project size (in terms of TCC) that represented what was generally considered as the smaller projects. A statistical analysis of the distribution of the projects in the database revealed that generally 80 percent of the projects lay between a TCC ranging from $100,000 to $2 Million. Regressions were then undertaken to determine if delivery costs for this subset behaved in a different fashion than for the full range of projects. The statistical tests generally produced favorable results and it was concluded that this subset of projects were representative of the characteristics of smaller projects.


Therefore, it was decided to analyze the projects data in the following two ranges:

Full range of TCC 1.

Smal ler project subset of 2. TCC (first 80 percent of the project distribution)

Preliminary results of such an evaluation using the Update 2008 projects database were presented to the agencies during a quarterly meeting. The results conformed to the agencies’ practical experiences. After reviewing the results, the agencies directed the Study Team to analyze the Update 2009 projects data in the two ranges discussed above. The characteristics of the project data in the performance database are presented in the following subsection.

f. ChArACteriStiCS of dAtA AnAlyzed

Project performance data were analyzed using the custom database application at both the Project Type level and the Project Classification level (see Table 3-1).

Project Count and Project Delivery by Completion Year

Table 3-5 summarizes characteristics of the projects included in the analyses by project completion year and shows trends in the average TCC values, median TCC values, design costs, construction management costs, and overall project delivery costs. The median value is the value at which 50% of the values are above and 50% of the values are below.

Project Completion

Date

Count by Project Type Project Delivery DataM

unicipal Facilities

Streets

Pipes

Parks

Total

Average TC

C ($M

)

Median

TCC

($M)

Design C

ost (%

of TCC

)

Construction

Managem

ent C

ost (%

of TCC

)

Project D

elivery Cost

(% of TC

C)

2004 24 56 37 27 144 $2.99 $0.57 27% 18% 46%2005 27 70 80 18 195 $1.74 $0.66 23% 17% 40%2006 35 53 63 9 160 $2.68 $0.86 20% 17% 37%2007 16 50 45 14 125 $2.58 $0.70 23% 17% 40%2008 14 34 42 15 105 $2.36 $0.72 23% 17% 40%Total 116 263 267 83 729 $2.21 $0.65 23% 17% 40%


Table 3-5 Project Count and Project Delivery by Completion Year


As indicated in Table 3-5, project size (measured as median TCC), increased significantly between 2004 and 2006 with an increase of approximately 51 percent. Project size declined approximately 16 percent between 2006 and 2008. The average TCC also declined steadily between 2006 and 2008. Similarly, project delivery costs measured as a percentage of the TCC declined significantly between 2004 and 2006. The project delivery percentages have remained stable during 2007 and 2008 having increased slightly from 2006.

Project Delivery Costs by Project Type

Table 3-6 shows project delivery costs by each of the four project types in the Study for the full range of TCC. The project

delivery percentage for a category is the arithmetic average of the project delivery percentages of the individual projects grouped under that category.

Although it is desirable for project delivery costs to decrease as agency efficiencies increase and BMPs are implemented, this can be confounded by other factors that change annually such as project size and market competition. For example, presently actual bid amounts have been depressed by competitive forces associated with the current recession. This will result in the rise of delivery cost as a percentage of TCC as TCC is depressed. The result may be noticed in the coming years as these projects are completed and reported into the database.

Type

Design

Construction

Managem

ent

Project Delivery

(Total)

Median Total

Construction C

ost ($M)

Num

ber of Projects (N

)




Table 3-6 Project Delivery Costs by Project Type (% of TCC) (Full Range of TCC )


Projects belonging to the Pipes and the Municipal categories have the lowest average project delivery cost. The Pipes category has the maximum number of projects (n = 267) in the Update 2009 database. The Streets category also has a similar number of projects in the database (n = 263). The Streets category also exhibits the highest average project delivery cost. The influence of low project delivery cost from Pipes projects is balanced by the influence of high project delivery cost from Streets projects. The average project delivery percentage for the overall dataset is approximately 40 percent.

Over the course of the Study, the Agencies have observed that the relatively high

Type

Design

Construction

Managem

ent

Project Delivery

(Total)

Median Total

Construction C

ost ($M)

Num

ber of Projects (N

)




Table 3-7 Project Delivery Costs by Project Type (% of TCC)

(Smaller Project Subset of TCC )

average project delivery cost of Streets projects is probably due to increasing cost influences of right-of-way acquisition, community outreach requirements, environmental mitigation requirements, and the smaller median total construction cost of these projects.

Table 3-7 shows project delivery costs by each of the four project types in the Study for the smaller projects subset of TCC. The trends in the project delivery costs for the projects in the smaller project subset of TCC follow that of the projects in the full range of TCC. As expected based upon the Agencies’ practical experience, project delivery costs are higher for projects that fall in the smaller project subset of TCC.


Consultant Usage Analysis

Project del ivery performance and consultant usage by agency are presented in Table 3-8. The table indicates that approximately 56 percent of the design work and approximately 82 percent of the construction management efforts are completed in-house by the participating agencies. Consultants account for approximately 32 percent of the total project delivery costs while in-house efforts by the participating agencies accounts for the remaining 68 percent of the project delivery costs. For the available data, a clear relationship between the level of in-house effort and project delivery costs cannot be established.

g. regreSSion AnAlySiS reSultS

During Update 2008, several changes were made to improve the modeling methodology. These included developing a statistically-sound method for outlier analysis, using a linear trendline for modeling project costs relationships, and using the upper and lower bounds of a 90 percent confidence interval to estimate the range of the project delivery percentages. As a result of these improvements, the model relationships could be predicted with a high degree of certainty as compared to previous Study years. During Update 2009, the modeling methodology was further refined by analyzing the data in two ranges of TCC.


AG

ENC

Y

D E

S I

G N

CO

NST

RU

CTI

ON

MA

NA

GEM

ENT

PRO

JEC

T D

ELIV

ERY

TCC

In-H

ouse

Con

sulta

nts

In-H

ouse

Con

sulta

nts

In-H

ouse

Con

sulta

nts

Average

Median

($M)

% of Design1

($M)

% of Design

Total % of TCC2,3

($M)

% of CM

($M)

% of CM

Total % of TCC

($M)

% of PD

($M)

% of PD

Total % of TCC

Age

ncy

A31

.547

%35

.953

%27

%32

.968

%15

.232

%15

%64

.456

%51

.144

%42

%2.

50.

7A

genc

y B

12.2

47%

13.5

53%

18%

11.6

61%

7.6

39%

12%

23.8

53%

21.1

47%

30%

1.4

0.4

Age

ncy

C25

.393

%2.

07%

17%

24.7

97%

0.8

3%17

%50

.095

%2.

85%

34%

1.6

1.1

Age

ncy

D62

.253

%55

.047

%22

%10

0.1

85%

17.6

15%

21%

162.

369

%72

.531

%43

%5.

01.

3A

genc

y E

3.4

30%

8.0

70%

19%

6.8

72%

2.6

28%

14%

10.3

49%

10.6

51%

33%

2.3

1.1

Age

ncy

F38

.561

%24

.739

%25

%44

.488

%5.

912

%22

%82

.973

%30

.627

%47

%1.

40.

4A

genc

y G

13.3

60%

8.8

40%

25%

9.4

100%

0.0

0%13

%22

.772

%8.

828

%38

%0.

80.

4O

VER

ALL

186.

556

%14

7.9

44%

23%

230.

082

%49

.718

%17

%41

6.5

68%

197.

632

%40

%2.

20.

6

Tabl

e 3-

8 Pr

ojec

t Del

iver

y Pe

rfor

man

ce a

nd C

onsu

ltant

Usa

ge b

y A

genc

y

Not

es:

1 In-

Hou

se a

nd C

onsu

ltant

cos

ts ar

e ex

pres

sed

as p

erce

ntag

es o

f tot

al a

genc

y D

esig

n, C

M (C

onstr

uctio

n M

anag

emen

t), a

nd P

D (P

roje

ct D

eliv

ery)

cos

ts.

2 Tot

al C

onstr

uctio

n C

ost (

TCC

) is t

he su

m o

f con

stru

ctio

n co

ntra

ct a

war

d, c

hang

e or

ders

, util

ity re

loca

tion

cost,

and

city

forc

es c

onstr

uctio

n co

st.3 D

esig

n, C

M, a

nd P

D c

osts

are

expr

esse

d as

per

cent

ages

of T

CC

and

are

unw

eigh

ted,

arit

hmet

ic a

vera

ges o

f pro

ject

s by

agen

cy.


Given all these improvements to the analysis of the data, the reader is advised that direct comparison of data between Update 2009 and previous years may be more difficult due to these improvements.

The results of the regression analyses are discussed in the remainder of this section. The results of the regression analyses are summarized in Table 3-9 and Table 3-10. Table 3-9 summarizes the performance model results for the full range of TCC while Table 3-10 summarizes the results for the smaller project subset of TCC. These tables also summarize the design, construction management, and project delivery costs expressed as a percentage of the TCC and the R2 and the p-values for the different project types.

The plots depicting the regression relationships are shown in Appendix B. It should also be noted that while majority of projects are clustered near the origin of the graph, the slope of the trendline is predominantly governed by the data points scattered at relatively high TCC values. Since the slope of the trendline provides the design, construction management, or the project delivery costs as a percentage of the TCC for a group of projects, the results better reflect the properties of a program of projects rather than that of an individual project. Therefore, the reader must avoid budgeting individual projects based on these analyses.

In most cases, the results reflect the agencies’ experience with the delivery of capital projects that on a percentage basis projects with lower TCCs are more expensive to deliver than projects with higher TCCs. For projects belonging to the Pipes category, there is a significant increase (approximately 16 percent) in the project delivery percentages for projects evaluated in the smaller project subset of TCC. Similarly, project delivery percentages for projects belonging to the Streets category exhibit a 12 percent increase. Projects under the Municipal category exhibit a minor increase while projects under the Parks category show no change in their project delivery percentages for projects evaluated in the smaller project subset of TCC. Comparing the results summarized in Table 3-9 and Table 3-10 shows that an economy of scale exists in delivering projects with a higher TCC versus those with a lower TCC.

It is important to note that while the slopes of the linear regression models are an expression of the project delivery cost as a percentage of construction, the slopes are not equal to the average and median project delivery percentages shown in Table 3-5, Table 3-6 and Table 3-7. The project delivery percentages in the tables represent arithmetic averages of the individual projects and do not represent the results for the regression analysis. In addition, it should be noted that although the R2 and p-values are higher than in previous Study phases, the reader is cautioned that this table only be used as a reference and not for prediction of performance. Readers are urged to review the curves in Appendix B in conjunction with using this table.


Proj

ect T

ype

or

Cla

ssifi

catio

nN

umbe

r of

Proj

ects

(N)

Des

ign

Cos

tC

onst

ruct

ion

Man

agem

ent C

ost

Proj

ect D

eliv

ery

Cos

t

(% o

f TC

C)

95%

CI (

%

of T

CC

)R

2p-

valu

e(%

of

TCC

)95

% C

I (%

of

TC

C)

R2

p-va

lue

(% o

f TC

C)

95%

CI (

%

of T

CC

)R

2p-

valu

e

Mun

icip

al P

roje

cts

116

17%

16%

-19%

0.90

8.28

E-59

18%

17%

-19%

0.92

1.06

E-65

35%

34%

-38%

0.94

3.06

E-71

Libr

arie

s23

16%

9%-1

6%0.

633.

11E-

712

%7%

-15%

0.59

1.22

E-5

28%

19%

-28%

0.77

1.41

E-9

Polic

e/Fi

re S

tatio

ns31

17%

14%

-22%

0.78

6.05

E-11

16%

13%

-21%

0.75

2.5E

-10

33%

29%

-41%

0.81

3.14

E-12

Com

m./R

ec.C

ente

r/C

hild

Car

e/G

yms

5017

%13

%-1

8%0.

772.

2E-1

711

%7%

-11%

0.64

1.28

E-13

28%

21%

-28%

0.80

4.91

E-20

Oth

er M

unic

ipal

1218

%15

%-2

1%0.

941.

5E-7

19%

18%

-21%

0.99

1.82

E-11

37%

34%

-42%

0.98

6.48

E-10

Stre

ets

Proj

ects

263

16%

14%

-17%

0.63

1.26

E-59

18%

17%

-19%

0.94

5.7E

-165

34%

32%

-35%

0.91

8.4E

-137

Wid

enin

g/N

ew/

3313

%10

%-1

4%0.

746.

17E-

1319

%18

%-2

0%0.

977.

07E-

2632

%29

%-3

3%0.

971.

04E-

27G

rade

Sep

arat

ions

Brid

ges

1035

%18

%-5

2%0.

731.

62E-

312

%10

%-1

3%0.

983.

18E-

847

%31

%-6

3%0.

851.

58E-

4

Rec

onst

ruct

ions

6924

%23

%-3

1%0.

691.

31E-

917

%17

%-2

1%0.

831.

11E-

2841

%40

%-5

1%0.

791.

19E-

25

Bike

/Ped

estri

an/

Stre

etsc

apes

7820

%15

%-2

2%0.

531.

91E-

1414

%10

%-1

5%0.

626.

52E-

1834

%25

%-3

6%0.

629.

52E-

18

Sign

als

7316

%10

%-1

6%0.

433.

29E-

1217

%13

%-1

8%0.

616.

69E-

1734

%25

%-3

2%0.

752.

22E-

27

Pipe

s Pr

ojec

ts26

79%

9%-1

0%0.

885.

0E-1

2510

%9%

-10%

0.99

1.3E

-307

19%

18%

-19%

0.96

6.6E

-193

Gra

vity

Mai

ns22

79%

9%-1

0%0.

885.

7E-1

0710

%9%

-10%

1.00

5.9E

-277

19%

18%

-19%

0.96

1.5E

-164

Pres

sure

Sys

tem

s22

7%0%

-7%

0.00

7.28

E-2

10%

4%-1

0%0.

467.

52E-

517

%5%

-17%

0.23

1.35

E-3

Pum

p St

atio

ns13

14%

11%

-17%

0.89

9.95

E-07

10%

6%-1

2%0.

801.

75E-

0524

%20

%-2

5%0.

972.

21E-

10

Park

s Pr

ojec

ts83

25%

24%

-29%

0.83

5.5E

-33

10%

7%-1

1%0.

499.

04E-

1535

%33

%-3

8%0.

911.

28E-

43

Play

grou

nds

6521

%19

%-2

2%0.

891.

07E-

3215

%14

%-1

7%0.

872.

8E-2

936

%33

%-3

8%0.

927.

15E-

37

Spor

tfiel

ds12

30%

31%

-46%

0.84

7.78

E-07

4%0%

-3%

0.00

3.27

E-1

34%

31%

-47%

0.90

1.46

E-6

Res

troom

s6

38%

5%-1

11%

0.58

3.89

E-2

18%

0%-3

1%0.

421.

13E-

155

%32

%-1

10%

0.80

7.27

E-3

Tabl

e 3-

9 Su

mm

ary

of P

erfo

rman

ce M

odel

s (F

ull R

ange

of T

CC

)

Not

es:

1 TC

C =

Tot

al C

onstr

uctio

n C

ost;

Des

. = D

esig

n C

ost;

CM

= C

onst

ruct

ion

Man

agem

ent C

ost,

and

PD =

Pro

ject

Del

iver

y C

ost.

CI =

Con

fiden

ce In

terv

al. T

he p

roje

ct

deliv

ery

perc

enta

ges i

ndic

ated

are t

he ra

nges

corre

spon

ding

to th

e 95

perc

ent c

onfid

ence

inte

rval

s on

the s

lope

of t

he li

near

regr

essio

n tre

ndlin

e. C

autio

n an

d re

view

of

the r

epor

t tex

t are

urg

ed in

usin

g th

is in

form

atio

n. R

efer

to A

ppen

dix

B fo

r the

corre

spon

ding

regr

essi

on cu

rves

, R2

valu

es, a

nd N

val

ues f

or m

ore d

etai

ls. H

ighl

ight

ed

valu

es in

dica

te th

ose

for w

hich

R2

valu

es w

ere

low

(bel

ow 0

.50)

.2 O

ther

Pip

es P

roje

cts a

re n

ot in

clud

ed in

this

tabl

e du

e to

a sm

all n

umbe

r of p

roje

cts (

less

than

5).


Proj

ect T

ype

or

Cla

ssifi

catio

nN

umbe

r of

Proj

ects

(N)

Des

ign

Cos

tC

onst

ruct

ion

Man

agem

ent C

ost

Proj

ect D

eliv

ery

Cos

t

(% o

f TC

C)

95%

CI (

%

of T

CC

)R

2p-

valu

e(%

of

TCC

)95

% C

I (%

of

TC

C)

R2

p-va

lue

(% o

f TC

C)

95%

CI (

%

of T

CC

)R

2p-

valu

e

Mun

icip

al P

roje

cts

9317

%13

%-1

7%0.

648.

17E-

2314

%12

%-1

5%0.

734.

58E-

2831

%25

%-3

2%0.

788.

89E-

33Li

brar

ies

1818

%6%

-23%

0.41

2.29

E-3

12%

0%-9

%0.

005.

63E-

130

%6%

-27%

0.07

3.65

E-3

Polic

e/Fi

re S

tatio

ns25

14%

7%-1

3%0.

544.

22E-

714

%10

%-1

5%0.

791.

28E-

928

%18

%-2

8%0.

751.

87E-

09C

omm

./Rec

.Cen

ter/

Chi

ld C

are/

Gym

s40

19%

11%

-22%

0.45

8.11

E-7

14%

10%

-16%

0.69

1.3E

-11

34%

23%

-35%

0.66

3.14

E-11

Oth

er M

unic

ipal

1017

%14

%-2

2%0.

933.

25E-

610

%3%

-12%

0.52

7.04

E-3

26%

20%

-31%

0.93

5.7E

-6St

reet

s Pr

ojec

ts20

827

%22

%-3

0%0.

447.

85E-

2819

%15

%-2

0%0.

506.

97E-

3346

%39

%-4

9%0.

611.

05E-

44W

iden

ing/

New

/ 26

26%

9%-2

9%0.

314.

72E-

417

%11

%-2

1%0.

663.

48E-

743

%23

%-4

7%0.

534.

4E-6

Gra

de S

epar

atio

nsBr

idge

s8

37%

7%-3

9%0.

261.

29E-

216

%5%

-21%

0.65

6.43

E-3

53%

19%

-53%

0.50

2.18

E-3

Rec

onst

ruct

ions

5523

%15

%-2

8%0.

452.

43E-

814

%9%

-14%

0.51

1.31

E-10

37%

26%

-40%

0.62

5.4E

-13

Bike

/Ped

estri

an/

Stre

etsc

apes

6128

%15

%-3

2%0.

343.

36E-

719

%14

%-2

6%0.

445.

56E-

947

%32

%-5

6%0.

489.

46E-

10

Sign

als

5825

%15

%-3

0%0.

391.

31E-

721

%7%

-25%

0.17

6.25

E-4

46%

29%

-50%

0.50

1.99

E-10

Pipe

s Pr

ojec

ts21

417

%11

%-1

6%0.

313.

36E-

2117

%14

%-1

8%0.

601.

75E-

4435

%26

%-3

4%0.

542.

61E-

39

Gra

vity

Mai

ns18

217

%11

%-1

6%0.

326.

47E-

1918

%15

%-1

9%0.

597.

38E-

3735

%27

%-3

4%0.

553.

87E-

34

Pres

sure

Sys

tem

s18

11%

4%-1

5%0.

481.

07E-

314

%11

%-1

7%0.

855.

52E-

825

%17

%-3

0%0.

797.

35E-

7

Pum

p St

atio

ns10

21%

8%-2

6%0.

622.

05E-

322

%16

%-2

9%0.

894.

34E-

543

%27

%-5

1%0.

866.

61E-

5

Park

s Pr

ojec

ts66

21%

11%

-23%

0.30

5.54

E-7

14%

6%-1

4%0.

232.

68E-

635

%19

%-3

4%0.

403.

8E-1

0

Play

grou

nds

5223

%13

%-2

4%0.

442.

01E-

814

%4%

-13%

0.09

1.09

E-3

36%

19%

-35%

0.42

4.96

E-9

Spor

tfiel

ds10

12%

0% -

24%

0.26

1.5E

-110

%0%

-12%

0.00

2.31

E-1

21%

0%-3

1%0.

002.

17E-

1

Res

troom

s5

11%

0% -

23%

0.00

5.77

E-1

25%

10%

-49%

0.86

1.68

E-2

36%

2%-6

5%0.

784.

38E-

2

Tabl

e 3-

10

Sum

mar

y of

Per

form

ance

Mod

els

(Sm

alle

r Pro

ject

Sub

set o

f TC

C)

Not

es:

1 TC

C =

Tot

al C

onstr

uctio

n C

ost;

Des

. = D

esig

n C

ost;

CM

= C

onst

ruct

ion

Man

agem

ent C

ost,

and

PD =

Pro

ject

Del

iver

y C

ost.

CI =

Con

fiden

ce In

terv

al. T

he p

roje

ct

deliv

ery

perc

enta

ges i

ndic

ated

are t

he ra

nges

corre

spon

ding

to th

e 95

perc

ent c

onfid

ence

inte

rval

s on

the s

lope

of t

he li

near

regr

essio

n tre

ndlin

e. C

autio

n an

d re

view

of

the r

epor

t tex

t are

urg

ed in

usin

g th

is in

form

atio

n. R

efer

to A

ppen

dix

B fo

r the

corre

spon

ding

regr

essi

on cu

rves

, R2

valu

es, a

nd N

val

ues f

or m

ore d

etai

ls. H

ighl

ight

ed

valu

es in

dica

te th

ose

for w

hich

R2

valu

es w

ere

low

(bel

ow 0

.50)

.2 O

ther

Pip

es P

roje

cts a

re n

ot in

clud

ed in

this

tabl

e du

e to

a sm

all n

umbe

r of p

roje

cts (

less

than

5).


The elimination of auto-correlation in Update 2008 and the use of the linear trendline to describe the relationship between project delivery costs and the TCC have significantly improved the R2 values as compared to the previous Study years.

For projects evaluated under the full range of TCC, Pipes and Municipal Facilities projects exhibit higher R2 values as compared to Streets and Parks projects for the project delivery versus TCC regressions. This may be attributed to better definition of Pipes and Municipal Facilities projects at the beginning of a project and thus allow for the design effort to be more focused. This would lead to more consistent performance and therefore higher R2 values.

It is observed that the R2 values are lower for projects falling in the smaller project subset of TCC than for projects falling under the full range of TCC. This is explained due to the fact that there is greater scatter amongst the project data points evaluated under a smaller range of TCC than the full range of TCC. Project classifications with very few data points typically exhibit low R2 values (less than 0.5).

The results of statistical significance tests also improved with the elimination of auto-correlation during Update 2008. Increasing the number of data points in models with p-values above 0.10 should improve (reduce) the p-values. For those models with p-values above 0.10, the model should not be used alone to forecast delivery costs for individual projects.

Increasing the size of the project database is a major challenge posed to the Study participants. This is primarily because of the 5-year rolling window criterion for project completion dates; even as new projects are added, old projects are excluded from analyses by the window of time. In addition, the agencies are also challenged to identify as many completed projects as possible that meet the rest of the Study criteria. The Project Team wil l identify and evaluate ways to address this issue as the Study continues in future phases.

chapter Best ManagementPractices4

Page 45

At the start of the Study, the agencies examined over 100 practices used in project delivery. Included in the Study are those practices that the study participants did not already commonly use, but believed should be implemented as BMPs. Each year new BMPs are added, and in some cases existing BMPs are reworked by the agencies to address specific challenges they encounter. BMPs are also added or modified to reflect relevant experiences by the participants. Agency implementation of these selected practices has been and will continue to be tracked during the Study. One new BMP was added to the list this year which started a new category, Sustainable Development. The BMPs discussed in this chapter are believed to influence the cost of either design or construction management and, ultimately, project delivery efficiency.

A. NEW BEST MANAGEMENT PRACTICES

In Update 2009, the Project Team added one new BMP and one new category to the BMP implementation tracking list. The BMP was developed to address the growing field of sustainable design and practices. The agencies felt that a new category, Sustainable Development, should be added to Best Management Practices. The new BMP is:

7.a.2009 - To quantify the envi-• ronmental benefits of the project at the time of award.

This BMPs is believed to influence the cost of either design or construction management and, ultimately, project delivery efficiency. This BMP also has an intangible benefit through its positive long range effect on our environment.

B. DESCRIPTION OF BEST MANAGEMENT PRACTICES

The Study 2002 report inc luded descriptions of the BMPs that the Project Team felt were most critical to improving project delivery performance. These descriptions, presented in Table 4-1, have been updated to reflect changes in interpretation of those BMPs, as well as additions since 2002 to the BMP list.


Cat

egor

yR

ef:*

BM

PD

escr

iptio

n

Plan

ning

1.a

Defi

ne c

apita

l pro

ject

s w

ell w

ith r

espe

ct

to s

cope

and

bud

get i

nclu

ding

com

mun

ity

and

clie

nt a

ppro

val

at t

he e

nd o

f th

e pl

anni

ng p

hase

.

Cha

nges

in p

roje

ct s

cope

or b

udge

t inc

reas

e bo

th to

tal c

onst

ruct

ion

cost

and

the

cost

of p

roje

ct d

eliv

ery.

The

late

r the

se c

hang

es o

ccur

in th

e lif

e of

the

proj

ect,

the

grea

ter t

he in

crea

se. R

each

ing

and

docu

men

ting

cons

ensu

s w

ith th

e co

mm

unity

an

d th

e cl

ient

will

redu

ce c

hang

es a

fter t

he p

roje

ct d

eliv

ery

proc

ess

begi

ns.

1.b

Com

plet

e Fe

asib

ility

Stu

dies

on

proj

ects

pr

ior t

o de

finin

g bu

dget

and

sco

pe.

Feas

ibili

ty s

tudi

es s

houl

d be

com

plet

ed e

arly

in th

e pr

oces

s so

that

issu

es a

re

iden

tified

and

eith

er re

solv

ed o

r acc

omm

odat

ed w

ithin

the

final

defi

nitio

n of

sco

pe,

budg

et, a

nd p

roje

ct d

eliv

ery

sche

dule

. Thi

s w

ill al

so re

duce

ove

rall p

roje

ct d

eliv

ery

cost

s. E

arly

feas

ibili

ty s

tudi

es a

re p

artic

ular

ly im

porta

nt o

n co

mpl

ex p

roje

cts

and

proj

ects

with

a c

onst

ruct

ion

budg

et g

reat

er th

an $

5 m

illio

n.

1.d

Util

ize

a Bo

ard/

Cou

ncil p

roje

ct p

riorit

izat

ion

syst

em.

Dep

artm

ents

resp

onsi

ble

for p

roje

ct d

eliv

ery

have

limite

d re

sour

ces.

A s

yste

m w

ill en

sure

that

reso

urce

s ar

e di

rect

ed to

mee

t the

com

mun

ity’s

mos

t crit

ical

nee

ds.

1.e

Res

ourc

e lo

ad a

ll C

IP p

roje

cts

for d

esig

n an

d co

nstru

ctio

n.

The

reso

urce

s re

quire

d to

del

iver

pro

ject

s ac

cord

ing

to th

e m

aste

r CIP

sch

edul

e m

anda

ted

by th

e B

oard

/Cou

ncil

shou

ld b

ecom

e pa

rt of

the

CIP

. Thi

s w

ill fa

cilit

ate

defin

ing

perfo

rman

ce m

easu

res

and

ensu

re th

at th

ere

is a

com

mon

und

erst

andi

ng

of th

e re

sour

ces

requ

ired

to d

eliv

er th

e C

IP.

1.f

Incl

ude

a M

aste

r S

ched

ule

in t

he C

IP

that

ide

ntifi

es s

tart

and

finis

h da

tes

for

proj

ects

.

A m

aste

r sc

hedu

le c

an b

e us

ed t

o de

fine

reso

urce

nee

ds a

nd p

erfo

rman

ce

mea

sure

s.

1.g

2007

Mak

e an

ear

ly d

eter

min

atio

n on

whi

ch

envi

ronm

enta

l doc

umen

t is

req

uire

d an

d in

corp

orat

e in

to th

e sc

hedu

le.

Com

plet

ing

the

envi

ronm

enta

l ass

essm

ent

and

perm

ittin

g pr

oces

s in

fluen

ces

proj

ect s

ched

ules

and

cos

ts. E

stab

lish

a ch

eckl

ist o

f pot

entia

l env

ironm

enta

l and

pe

rmit

requ

irem

ents

and

exa

min

e ea

ch p

roje

ct s

cope

aga

inst

the

list e

arly

in th

e pl

anni

ng p

roce

ss.

1.i

Sho

w p

roje

cts

on a

Geo

grap

hica

l In

form

atio

n S

yste

m (G

IS).

Ent

erin

g an

d tra

ckin

g pl

anne

d pr

ojec

ts in

to a

GIS

whi

ch is

ava

ilabl

e to

all

priv

ate

and

publ

ic s

ecto

r pr

ojec

t pla

nner

s w

ill r

educ

e th

e po

tent

ial f

or c

onfli

cts

and

re-

wor

k.Tabl

e 4-

1D

escr

iptio

n of

Bes

t Man

agem

ent P

ract

ices

Chapter 4 Best Management Practices

Cat

egor

yR

ef:*

BM

PD

escr

iptio

n

Des

ign

2.b

Pro

vide

a d

etai

led

clea

r, pr

ecis

e sc

ope,

sc

hedu

le,

and

budg

et t

o de

sign

ers

prio

r to

des

ign

star

t.

Ente

ring

and

track

ing

plan

ned

proj

ects

into

a G

IS w

hich

is a

vaila

ble

to a

ll priv

ate

and

publ

ic s

ecto

r pro

ject

pla

nner

s w

ill re

duce

the

pote

ntia

l for

con

flict

s an

d re

-wor

k.

2.f

Def

ine

requ

irem

ents

for

rel

iabi

lity,

m

aint

enan

ce, a

nd o

pera

tion

prio

r to

desi

gn

initi

atio

n.

Des

ign

prof

essi

onal

s w

ill w

ork

mor

e ef

ficie

ntly

if g

iven

a c

lear

sco

pe w

hen

cont

ract

ed

to p

rovi

de t

he d

esig

n se

rvic

es.

Cle

ar s

cope

and

bud

get

shou

ld b

e de

fined

in

adva

nce

and

mad

e a

part

of th

e de

sign

pro

fess

iona

l’s c

ontra

ct if

/whe

n a

cons

ulta

nt

is u

sed.

2.i

Ada

pt s

ucce

ssfu

l des

igns

to p

roje

ct s

ites,

w

hene

ver

poss

ible

(e.

g. f

ire s

tatio

ns,

gym

nasi

ums,

etc

).

Rel

iabi

lity,

mai

nten

ance

, op

erat

iona

l req

uire

men

ts,

and

stan

dard

mat

eria

ls a

nd

equi

pmen

t sho

uld

be c

lear

ly d

efine

d in

adv

ance

, app

rove

d by

the

user

/clie

nt, a

nd

incl

uded

in th

e de

sign

pro

fess

iona

l’s c

ontra

ct w

hen

a co

nsul

tant

is u

sed.

2.k

2003

Trai

n in

-hou

se s

taff

to u

se G

reen

Bui

ldin

g S

tand

ards

.

Suc

cess

ful d

esig

ns o

f fire

sta

tions

, pol

ice

faci

litie

s, m

aint

enan

ce fa

cilit

ies,

pum

p st

atio

ns, a

nd m

any

othe

r pro

ject

s sh

ould

be

re-u

sed

whe

n po

ssib

le. S

ite a

dapt

atio

ns

of s

ucce

ssfu

l des

igns

may

redu

ce d

esig

n co

sts

by h

alf.

2.l

2004

Lim

it S

cope

Cha

nges

to

early

sta

ges

of

desi

gn.

Com

mun

ities

hav

e a

stak

e in

the

envi

ronm

ent a

s w

ell a

s in

the

cost

of o

pera

ting

and

mai

ntai

ning

pub

lic fa

cilit

ies.

Util

izin

g “G

reen

Bui

ldin

g S

tand

ards

” allo

ws

faci

litie

s to

be

bui

lt an

d op

erat

ed w

ith re

new

able

reso

urce

s an

d ot

her e

nviro

nmen

tally

sou

nd

prac

tices

.

2.m

20

04

Req

uire

sco

pe c

hang

es d

urin

g de

sign

to

be a

ccom

pani

ed b

y bu

dget

and

sch

edul

e ap

prov

als.

It is

wel

l kno

wn

with

in th

e in

dust

ry th

at th

e la

ter a

cha

nge

occu

rs in

the

cons

truct

ion

proc

ess,

the

mor

e co

stly

the

chan

ge is

.

2.n

2006

Impl

emen

t a

rota

ting

Req

uest

for

Quo

te

proc

ess

for

cont

ract

ing

smal

l pr

ojec

ts

to s

trea

mlin

e th

e bi

ddin

g an

d aw

ard

proc

ess

durin

g co

nstr

uctio

n. (

Incl

ude

crite

ria fo

r exe

mpt

ions

from

form

al C

ounc

il ap

prov

al.)

Sm

alle

r pro

ject

s co

st m

ore

(as

a pe

rcen

tage

of c

onst

ruct

ion

cost

) to

deliv

er. O

ne

way

of r

educ

ing

the

cost

of p

roje

ct d

eliv

ery

on s

mal

l pro

ject

s is

to s

horte

n th

e bi

d an

d aw

ard

proc

ess

by s

ettin

g a

thre

shol

d am

ount

und

er w

hich

the

deliv

ery

team

may

so

licit

and

rece

ive

quot

es fr

om q

ualifi

ed c

ontra

ctor

s an

d aw

ard

cont

ract

s w

ithou

t ge

tting

Boa

rd/C

ounc

il pr

ior a

ppro

val.

2.o

2007

Esta

blis

h cr

iteria

for o

btai

ning

inde

pend

ent

cost

est

imat

es w

hich

take

in c

onsi

dera

tion

both

pro

ject

cha

ract

eris

tics

and

vola

tility

of

the

mar

ket.

Hav

ing

to r

e-de

sign

and

re-

bid

a pr

ojec

t on

whi

ch b

ids

com

e in

ove

r bu

dget

can

si

gnifi

cant

ly im

pact

pro

ject

del

iver

y co

st. A

ccur

ate

estim

ates

at

the

end

of e

ach

desi

gn p

hase

, per

form

ed b

y un

bias

ed, i

ndep

ende

nt, q

ualifi

ed p

rofe

ssio

nals

with

an

und

erst

andi

ng o

f loc

al m

arke

t con

ditio

ns w

ill re

duce

the

pote

ntia

l for

rece

ivin

g un

expe

cted

bid

s.

Tabl

e 4-

1D

escr

iptio

n of

Bes

t Man

agem

ent P

ract

ices

(con

t’d)


Cat

egor

yR

ef:*

BM

PD

escr

iptio

n

2.o

2007

Est

ablis

h cr

iter

ia f

or o

btai

ning

in

depe

nden

t co

st e

stim

ates

whi

ch

take

in

cons

ider

atio

n bo

th p

roje

ct

char

acte

ristic

s an

d vo

latil

ity o

f th

e m

arke

t.

Hav

ing

to re

-des

ign

and

re-b

id a

pro

ject

on

whi

ch b

ids

com

e in

ove

r bud

get c

an

sign

ifica

ntly

impa

ct p

roje

ct d

eliv

ery

cost

. Acc

urat

e es

timat

es a

t the

end

of e

ach

desi

gn p

hase

, per

form

ed b

y un

bias

ed, i

ndep

ende

nt, q

ualifi

ed p

rofe

ssio

nals

with

an

und

erst

andi

ng o

f loc

al m

arke

t con

ditio

ns w

ill re

duce

the

pote

ntia

l for

rece

ivin

g un

expe

cted

bid

s.

Des

ign

2.p

2008

Esta

blis

h cr

iteria

for r

espo

nsib

le c

harg

e de

sign

app

rova

l suc

h th

at it

occ

urs

at

the

low

est

appr

opria

te o

rgan

izat

iona

l le

vel

in o

rder

to

expe

dite

des

ign

com

plet

ion.

Man

y tim

es re

spon

sibl

e ch

arge

des

ign

appr

oval

is s

et a

t a v

ery

high

leve

l. Th

is c

an

som

etim

es re

sult

in o

nly

one

pers

on w

ith li

mite

d tim

e w

ho c

an a

ppro

ve a

ll sh

eets

in

a d

esig

n pa

ckag

e. T

his

lead

s to

a b

ottle

neck

situ

atio

n.

Qua

lity

Ass

uran

ce

/ Qua

lity

Con

trol

3.I.a

Dev

elop

and

use

a s

tand

ardi

zed

Proj

ect

Del

iver

y M

anua

l.

Sta

ndar

dize

d pr

oced

ures

stre

amlin

e pr

ojec

t de

sign

, bi

ddin

g, a

nd c

onst

ruct

ion

proc

esse

s. S

tand

ardi

zed

desi

gn m

anag

emen

t pro

cedu

res

will

redu

ce s

cope

cre

ep

and

dela

ys in

con

stru

ctio

n do

cum

ent p

repa

ratio

n. D

urin

g co

nstru

ctio

n, s

tand

ard

proc

edur

es w

ill re

duce

resp

onse

tim

es o

n R

FIs,

and

add

ove

rall c

larit

y an

d ef

ficie

ncy

to t

he c

onst

ruct

ion

man

agem

ent

proc

ess.

Hav

ing

a st

anda

rd m

anua

l will

als

o re

duce

the

time

nece

ssar

y fo

r pro

ject

doc

umen

tatio

n tra

inin

g.

3.II.

bP

erfo

rm a

for

mal

Val

ue E

ngin

eerin

g S

tudy

for

pro

ject

s la

rger

tha

n $1

m

illio

n.

Valu

e En

gine

erin

g id

entifi

es lif

e cy

cle

cost

s of

des

ign

elem

ents

incl

uded

in a

pro

ject

an

d ce

rtain

alte

rnat

ives

. Whi

le th

e co

st o

f the

val

ue e

ngin

eerin

g pr

oces

s m

ay in

itial

ly

add

cost

s to

pro

ject

del

iver

y, o

vera

ll pr

ojec

t cos

ts w

ill b

e re

duce

d.

3.III

.aU

se a

for

mal

Qua

lity

Man

agem

ent

Sys

tem

.

Qua

lity

man

agem

ent s

houl

d in

clud

e al

l act

iviti

es fr

om th

e pr

epar

atio

n of

des

ign

docu

men

ts t

hrou

gh t

he c

lose

out

of c

onst

ruct

ion.

(C

onst

ruct

abili

ty r

evie

ws,

in

depe

nden

t cos

t est

imat

es, c

lass

ifica

tion

and

audi

ting

of c

hang

e or

ders

, etc

.) Th

e im

plem

enta

tion

and

track

ing

of q

ualit

y co

ntro

l sho

uld

be fo

rmal

ized

on

a ch

eckl

ist

to e

nsur

e ap

plic

atio

n.

3.III

.bP

erfo

rm a

nd u

se p

ost-p

roje

ct re

view

s to

iden

tify

less

ons

lear

ned.

Pro

ject

Man

ager

s sh

ould

dev

elop

form

al p

ost p

roje

ct re

view

s an

d id

entif

y le

sson

s le

arne

d. T

hese

doc

umen

ts s

houl

d be

mad

e av

aila

ble

to P

M’s

on

proj

ects

of a

sim

ilar

scop

e an

d na

ture

. Thi

s B

MP

will

mak

e fu

ture

pro

ject

man

agem

ent a

nd d

eliv

ery

mor

e ef

ficie

nt a

nd c

ost e

ffect

ive.

3.III

.k

2007

Est

ablis

h a

Uti

lity

Coo

rdin

atin

g C

omm

ittee

with

mem

bers

from

pub

lic

and

priv

ate

entit

ies.

Reg

ular

mee

tings

of a

com

mitt

ee w

ill e

stab

lish

a fo

rum

for i

deas

to im

prov

e th

e ut

ility

relo

catio

n pr

oces

s an

d th

us im

prov

e pr

ojec

t pro

gres

s. M

eetin

gs w

ill a

lso

be

an o

ppor

tuni

ty fo

r pro

blem

pro

ject

s (r

eloc

atio

ns) t

o be

dis

cuss

ed.

3.III

.l 20

07

Des

igna

te a

resp

onsi

ble

pers

on o

r gro

up

and

esta

blis

h a

proc

ess

of n

otifi

catio

ns

and

mile

ston

es fo

r util

ity re

loca

tions

.

Iden

tifyi

ng a

util

ity re

loca

tion

spec

ialis

t with

in th

e pr

ojec

t del

iver

y te

am w

ho is

fam

iliar

with

the

proc

edur

es a

nd c

onta

cts

with

in th

e pu

blic

and

priv

ate

utili

ty e

ntiti

es w

ill

impr

ove

com

mun

icat

ion

and

prob

lem

sol

ving

dur

ing

desi

gn a

nd c

onst

ruct

ion.

Tabl

e 4-

1D

escr

iptio

n of

Bes

t Man

agem

ent P

ract

ices

(con

t’d)


Cat

egor

yR

ef:*

BM

PD

escr

iptio

n

2.o

2007

Est

ablis

h cr

iter

ia f

or o

btai

ning

in

depe

nden

t co

st e

stim

ates

whi

ch

take

in

cons

ider

atio

n bo

th p

roje

ct

char

acte

ristic

s an

d vo

latil

ity o

f th

e m

arke

t.

Hav

ing

to re

-des

ign

and

re-b

id a

pro

ject

on

whi

ch b

ids

com

e in

ove

r bud

get c

an

sign

ifica

ntly

impa

ct p

roje

ct d

eliv

ery

cost

. Acc

urat

e es

timat

es a

t the

end

of e

ach

desi

gn p

hase

, per

form

ed b

y un

bias

ed, i

ndep

ende

nt, q

ualifi

ed p

rofe

ssio

nals

with

an

und

erst

andi

ng o

f loc

al m

arke

t con

ditio

ns w

ill re

duce

the

pote

ntia

l for

rece

ivin

g un

expe

cted

bid

s.

Des

ign

2.p

2008

Esta

blis

h cr

iteria

for r

espo

nsib

le c

harg

e de

sign

app

rova

l suc

h th

at it

occ

urs

at

the

low

est

appr

opria

te o

rgan

izat

iona

l le

vel

in o

rder

to

expe

dite

des

ign

com

plet

ion.

Man

y tim

es re

spon

sibl

e ch

arge

des

ign

appr

oval

is s

et a

t a v

ery

high

leve

l. Th

is c

an

som

etim

es re

sult

in o

nly

one

pers

on w

ith li

mite

d tim

e w

ho c

an a

ppro

ve a

ll sh

eets

in

a d

esig

n pa

ckag

e. T

his

lead

s to

a b

ottle

neck

situ

atio

n.

Qua

lity

Ass

uran

ce

/ Qua

lity

Con

trol

3.I.a

Dev

elop

and

use

a s

tand

ardi

zed

Proj

ect

Del

iver

y M

anua

l.

Sta

ndar

dize

d pr

oced

ures

stre

amlin

e pr

ojec

t de

sign

, bi

ddin

g, a

nd c

onst

ruct

ion

proc

esse

s. S

tand

ardi

zed

desi

gn m

anag

emen

t pro

cedu

res

will

redu

ce s

cope

cre

ep

and

dela

ys in

con

stru

ctio

n do

cum

ent p

repa

ratio

n. D

urin

g co

nstru

ctio

n, s

tand

ard

proc

edur

es w

ill re

duce

resp

onse

tim

es o

n R

FIs,

and

add

ove

rall c

larit

y an

d ef

ficie

ncy

to t

he c

onst

ruct

ion

man

agem

ent

proc

ess.

Hav

ing

a st

anda

rd m

anua

l will

als

o re

duce

the

time

nece

ssar

y fo

r pro

ject

doc

umen

tatio

n tra

inin

g.

3.II.

bP

erfo

rm a

for

mal

Val

ue E

ngin

eerin

g S

tudy

for

pro

ject

s la

rger

tha

n $1

m

illio

n.

Valu

e En

gine

erin

g id

entifi

es lif

e cy

cle

cost

s of

des

ign

elem

ents

incl

uded

in a

pro

ject

an

d ce

rtain

alte

rnat

ives

. Whi

le th

e co

st o

f the

val

ue e

ngin

eerin

g pr

oces

s m

ay in

itial

ly

add

cost

s to

pro

ject

del

iver

y, o

vera

ll pr

ojec

t cos

ts w

ill b

e re

duce

d.

3.III

.aU

se a

for

mal

Qua

lity

Man

agem

ent

Sys

tem

.

Qua

lity

man

agem

ent s

houl

d in

clud

e al

l act

iviti

es fr

om th

e pr

epar

atio

n of

des

ign

docu

men

ts t

hrou

gh t

he c

lose

out

of c

onst

ruct

ion.

(C

onst

ruct

abili

ty r

evie

ws,

in

depe

nden

t cos

t est

imat

es, c

lass

ifica

tion

and

audi

ting

of c

hang

e or

ders

, etc

.) Th

e im

plem

enta

tion

and

track

ing

of q

ualit

y co

ntro

l sho

uld

be fo

rmal

ized

on

a ch

eckl

ist

to e

nsur

e ap

plic

atio

n.

3.III

.bP

erfo

rm a

nd u

se p

ost-p

roje

ct re

view

s to

iden

tify

less

ons

lear

ned.

Pro

ject

Man

ager

s sh

ould

dev

elop

form

al p

ost p

roje

ct re

view

s an

d id

entif

y le

sson

s le

arne

d. T

hese

doc

umen

ts s

houl

d be

mad

e av

aila

ble

to P

M’s

on

proj

ects

of a

sim

ilar

scop

e an

d na

ture

. Thi

s B

MP

will

mak

e fu

ture

pro

ject

man

agem

ent a

nd d

eliv

ery

mor

e ef

ficie

nt a

nd c

ost e

ffect

ive.

3.III

.k

2007

Est

ablis

h a

Uti

lity

Coo

rdin

atin

g C

omm

ittee

with

mem

bers

from

pub

lic

and

priv

ate

entit

ies.

Reg

ular

mee

tings

of a

com

mitt

ee w

ill e

stab

lish

a fo

rum

for i

deas

to im

prov

e th

e ut

ility

relo

catio

n pr

oces

s an

d th

us im

prov

e pr

ojec

t pro

gres

s. M

eetin

gs w

ill a

lso

be

an o

ppor

tuni

ty fo

r pro

blem

pro

ject

s (r

eloc

atio

ns) t

o be

dis

cuss

ed.

3.III

.l 20

07

Des

igna

te a

resp

onsi

ble

pers

on o

r gro

up

and

esta

blis

h a

proc

ess

of n

otifi

catio

ns

and

mile

ston

es fo

r util

ity re

loca

tions

.

Iden

tifyi

ng a

util

ity re

loca

tion

spec

ialis

t with

in th

e pr

ojec

t del

iver

y te

am w

ho is

fam

iliar

with

the

proc

edur

es a

nd c

onta

cts

with

in th

e pu

blic

and

priv

ate

utili

ty e

ntiti

es w

ill

impr

ove

com

mun

icat

ion

and

prob

lem

sol

ving

dur

ing

desi

gn a

nd c

onst

ruct

ion.

Cat

egor

yR

ef:*

BM

PD

escr

iptio

n

Qua

lity

Ass

uran

ce /

Qua

lity

Con

trol

3.III

.m

2008

Mai

ntai

n an

d re

gula

rly

upda

te e

lect

roni

c st

anda

rd

cont

ract

spe

cific

atio

ns a

nd

rela

ted

docu

men

ts,

as

wel

l as

tec

hnic

al/s

peci

al

prov

isio

ns.

Sta

ndar

d co

ntra

ct s

peci

ficat

ions

and

tec

hnic

al s

peci

al p

rovi

sion

s ne

ed t

o be

reg

ular

ly

mai

ntai

ned

and

upda

ted

in o

rder

to re

duce

the

amou

nt o

f tim

e re

quire

d to

cre

ate

cont

ract

bi

d do

cum

ents

. If a

City

impl

emen

ts n

ew re

quire

men

ts, t

he s

tand

ards

sho

uld

be m

odifi

ed

for e

very

pro

ject

one

tim

e in

stea

d of

eac

h m

anag

er h

avin

g to

mod

ify th

ese

docu

men

ts o

f ev

ery

proj

ect.

Con

stru

ctio

n M

anag

emen

t4.

I.a

Del

egat

e au

thor

ity t

o th

e C

ity E

ngin

eer/P

ublic

Wor

ks

Dire

ctor

or o

ther

dep

artm

ents

to

app

rove

cha

nge

orde

rs to

th

e co

ntin

genc

y am

ount

.

Cha

nge

orde

r w

ork

shou

ld b

e au

thor

ized

as

soon

as

is p

ract

ical

ly p

ossi

ble

in o

rder

to

avoi

d po

tent

ial d

elay

s to

crit

ical

wor

k. S

ched

ulin

g a

sign

ifica

nt c

hang

e or

der

for

revi

ew

and

auth

oriz

atio

n by

the

Boa

rd m

ay d

elay

pro

ject

pro

gres

s, e

ven

thou

gh it

may

be

with

in

the

cont

inge

ncy

amou

nt a

llow

ed in

the

proj

ect b

udge

t. A

utho

rizat

ion

of th

e C

ity E

ngin

eer/

Pub

lic W

orks

Dire

ctor

to a

ppro

ve c

hang

es w

ithin

the

cont

inge

ncy

budg

eted

for c

hang

es

will

ens

ure

that

crit

ical

cha

nges

are

act

ed o

n pr

ompt

ly a

nd th

at d

elay

s ar

e m

inim

ized

.

4.I.m

Cla

ssify

typ

es o

f ch

ange

or

ders

.

Cla

ssifi

catio

n of

cha

nge

orde

rs in

to c

ateg

orie

s su

ch a

s ch

ange

d co

nditi

ons,

unf

ores

een

cond

ition

s, o

wne

r re

ques

ts,

or d

esig

n ch

ange

s fo

r ow

ner

use

impr

oves

und

erst

andi

ng

of th

e pr

ojec

t and

less

ons

lear

ned

from

the

data

may

impr

ove

proj

ect d

eliv

ery

on s

imila

r pr

ojec

ts.

4.II.

aIn

clud

e a

form

al D

ispu

te

Res

olut

ion

Pro

cedu

re in

all

cont

ract

agr

eem

ents

.

Con

stru

ctio

n is

ack

now

ledg

ed a

s a

disp

ute

pron

e in

dust

ry. A

s su

ch, i

t mak

es s

ense

to

prov

ide

optio

ns in

the

con

tract

doc

umen

ts t

o av

oid

litig

atio

n an

d to

exp

edite

dis

pute

s re

solu

tion

usin

g al

tern

ativ

es to

litig

atio

n.

4.III

.aU

se a

team

bui

ldin

g pr

oces

s fo

r pr

ojec

ts g

reat

er th

an $

5 m

illio

n.

Par

tner

ing

is a

tea

m-b

uild

ing

proc

ess

that

has

a p

rove

n re

cord

of

impr

ovin

g w

orki

ng

rela

tions

hips

and

pro

duct

ion,

and

redu

cing

cla

ims

and

disp

utes

on

cons

truct

ion

proj

ects

. It

is o

ne o

f sev

eral

team

-bui

ldin

g pr

oces

ses

that

sho

uld

be u

sed

in th

e in

tere

st o

f red

ucin

g co

nflic

t and

faci

litat

ing

proj

ect d

eliv

ery.

4.IV

.aIn

volv

e th

e C

onst

ruct

ion

Man

agem

ent

Team

prio

r to

co

mpl

etio

n of

des

ign.

Exp

erie

nced

con

tract

ors

and

cons

truct

ion

man

ager

s sh

ould

be

incl

uded

in t

he d

esig

n pr

oces

s to

mak

e de

sign

s m

ore

cons

truct

ible

and

low

er c

ost.

Con

stru

ctio

n m

anag

ers

and

cont

ract

ors

are

frequ

ently

mor

e ex

perie

nced

abo

ut th

e pr

oduc

ts a

nd/o

r equ

ipm

ent a

s w

ell

as c

onst

ruct

ion

met

hods

that

are

read

ily a

vaila

ble.

The

ir co

ntrib

utio

ns to

sel

ectio

ns a

nd

deci

sion

s du

ring

the

desi

gn p

roce

ss w

ill fa

cilit

ate

cons

truct

ion

proc

urem

ent,

mea

ns a

nd

met

hods

.

Tabl

e 4-

1D

escr

iptio

n of

Bes

t Man

agem

ent P

ract

ices

(con

t’d)


Cat

egor

yR

ef:*

BM

PD

escr

iptio

n

Con

stru

ctio

n M

anag

emen

t4.

V.a

2003

Del

egat

e au

thor

ity b

elow

Cou

ncil

to m

ake

cont

ract

aw

ards

und

er $

1 m

illio

n.

The

time

and

cost

s of

sch

edul

ing

and

pres

entin

g a

Cou

ncil

or B

oard

item

can

be

sav

ed a

nd p

roje

ct s

tarts

can

be

expe

dite

d if

awar

ds o

n pr

ojec

ts w

ith b

udge

ts

unde

r $1

mill

ion

can

be a

war

ded

adm

inis

trativ

ely.

4.V.

b 20

03E

stab

lish

a pr

e-qu

alifi

catio

n pr

oces

s fo

r co

ntra

ctor

s on

larg

e, c

ompl

ex p

roje

cts.

Pre

qual

ifica

tion

help

s sc

reen

con

tract

ors

for

prio

r pe

rform

ance

on

sim

ilar

proj

ects

, saf

ety

and

finan

cial

cap

abilit

y th

us re

duci

ng ri

sk a

nd, u

ltim

atel

y, p

roje

ct

deliv

ery

cost

.

4.V.

c 20

03M

ake

bid

docu

men

ts a

vaila

ble

onlin

e.M

akin

g bi

d do

cum

ents

ava

ilabl

e on

line

will

redu

ce a

genc

y pr

intin

g co

sts.

It m

ay

also

incr

ease

bid

der

parti

cipa

tion

by m

akin

g do

cum

ents

eas

ily a

vaila

ble

to a

la

rger

poo

l of p

oten

tial b

idde

rs a

nd s

ubco

ntra

ctor

s.

Proj

ect

Man

agem

ent

5.I.f

Ass

ign

a cl

ient

rep

rese

ntat

ive

to e

very

pr

ojec

t.

Clie

nt (

end

user

) re

pres

enta

tion

durin

g th

e lif

e of

the

pro

ject

will

exp

edite

de

cisi

ons

on s

ubm

ittal

s, s

ubst

itutio

ns,

and

chan

ges.

The

ir in

volv

emen

t w

ill

also

hel

p de

term

ine

inte

nt a

nd s

tream

line

the

com

mis

sion

ing

and

occu

panc

y pr

oces

s.

5.I.j

20

03C

reat

e in

-hou

se p

roje

ct m

anag

emen

t tea

m

for s

mal

l pro

ject

s.

It ha

s be

en d

ocum

ente

d th

at th

e co

st o

f pro

ject

del

iver

y of

sm

all p

roje

cts

is a

hi

gher

per

cent

age

of th

e co

nstru

ctio

n co

st. E

stab

lishi

ng a

pro

ject

man

agem

ent

team

tha

t sp

ecia

lizes

in s

mal

ler

proj

ects

may

lead

to

econ

omie

s su

ch a

s gr

oupi

ng s

imila

r pr

ojec

ts d

urin

g pe

rmitt

ing

and

bidd

ing

thus

red

ucin

g pr

ojec

t de

liver

y co

st.

5.I.k

20

04In

stit

uti

on

ali

ze

Pro

ject

M

an

ag

er

perfo

rman

ce a

nd a

ccou

ntab

ility

.

Rec

ogni

ze th

at p

rofe

ssio

nal p

roje

ct m

anag

emen

t req

uire

s sp

ecifi

c ed

ucat

ion,

tra

inin

g, a

nd e

xper

ienc

e. P

rovi

de f

or P

MI,

CC

M,

or o

ther

for

mal

tra

inin

g an

d ce

rtific

atio

n an

d es

tabl

ish

perfo

rman

ce m

easu

res

for

proj

ect

deliv

ery

pers

onne

l.

5.II.

aPr

ovid

e fo

rmal

trai

ning

for P

roje

ct M

anag

ers

on a

regu

lar b

asis

.

Pro

ject

Man

ager

s co

me

to p

roje

cts

with

var

ying

deg

rees

of s

kill

and

fam

iliar

ity

with

age

ncy

proc

edur

es.

Orie

ntat

ion

and

train

ing

will

impr

ove

thei

r ab

ility

to

deliv

er th

e pr

ojec

t on

the

inte

nded

sch

edul

e. It

is a

lso

impo

rtant

that

upd

ated

tra

inin

g is

ava

ilabl

e at

leas

t on

an a

nnua

l bas

is.

Tabl

e 4-

1D

escr

iptio

n of

Bes

t Man

agem

ent P

ract

ices

(con

t’d)


Cat

egor

yR

ef:*

BM

PD

escr

iptio

n

Con

stru

ctio

n M

anag

emen

t4.

V.a

2003

Del

egat

e au

thor

ity b

elow

Cou

ncil

to m

ake

cont

ract

aw

ards

und

er $

1 m

illio

n.

The

time

and

cost

s of

sch

edul

ing

and

pres

entin

g a

Cou

ncil

or B

oard

item

can

be

sav

ed a

nd p

roje

ct s

tarts

can

be

expe

dite

d if

awar

ds o

n pr

ojec

ts w

ith b

udge

ts

unde

r $1

mill

ion

can

be a

war

ded

adm

inis

trativ

ely.

4.V.

b 20

03E

stab

lish

a pr

e-qu

alifi

catio

n pr

oces

s fo

r co

ntra

ctor

s on

larg

e, c

ompl

ex p

roje

cts.

Pre

qual

ifica

tion

help

s sc

reen

con

tract

ors

for

prio

r pe

rform

ance

on

sim

ilar

proj

ects

, saf

ety

and

finan

cial

cap

abilit

y th

us re

duci

ng ri

sk a

nd, u

ltim

atel

y, p

roje

ct

deliv

ery

cost

.

4.V.

c 20

03M

ake

bid

docu

men

ts a

vaila

ble

onlin

e.M

akin

g bi

d do

cum

ents

ava

ilabl

e on

line

will

redu

ce a

genc

y pr

intin

g co

sts.

It m

ay

also

incr

ease

bid

der

parti

cipa

tion

by m

akin

g do

cum

ents

eas

ily a

vaila

ble

to a

la

rger

poo

l of p

oten

tial b

idde

rs a

nd s

ubco

ntra

ctor

s.

Proj

ect

Man

agem

ent

5.I.f

Ass

ign

a cl

ient

rep

rese

ntat

ive

to e

very

pr

ojec

t.

Clie

nt (

end

user

) re

pres

enta

tion

durin

g th

e lif

e of

the

pro

ject

will

exp

edite

de

cisi

ons

on s

ubm

ittal

s, s

ubst

itutio

ns,

and

chan

ges.

The

ir in

volv

emen

t w

ill

also

hel

p de

term

ine

inte

nt a

nd s

tream

line

the

com

mis

sion

ing

and

occu

panc

y pr

oces

s.

5.I.j

20

03C

reat

e in

-hou

se p

roje

ct m

anag

emen

t tea

m

for s

mal

l pro

ject

s.

It ha

s be

en d

ocum

ente

d th

at th

e co

st o

f pro

ject

del

iver

y of

sm

all p

roje

cts

is a

hi

gher

per

cent

age

of th

e co

nstru

ctio

n co

st. E

stab

lishi

ng a

pro

ject

man

agem

ent

team

tha

t sp

ecia

lizes

in s

mal

ler

proj

ects

may

lead

to

econ

omie

s su

ch a

s gr

oupi

ng s

imila

r pr

ojec

ts d

urin

g pe

rmitt

ing

and

bidd

ing

thus

red

ucin

g pr

ojec

t de

liver

y co

st.

5.I.k

20

04In

stit

uti

on

ali

ze

Pro

ject

M

an

ag

er

perfo

rman

ce a

nd a

ccou

ntab

ility

.

Rec

ogni

ze th

at p

rofe

ssio

nal p

roje

ct m

anag

emen

t req

uire

s sp

ecifi

c ed

ucat

ion,

tra

inin

g, a

nd e

xper

ienc

e. P

rovi

de f

or P

MI,

CC

M,

or o

ther

for

mal

tra

inin

g an

d ce

rtific

atio

n an

d es

tabl

ish

perfo

rman

ce m

easu

res

for

proj

ect

deliv

ery

pers

onne

l.

5.II.

aPr

ovid

e fo

rmal

trai

ning

for P

roje

ct M

anag

ers

on a

regu

lar b

asis

.

Pro

ject

Man

ager

s co

me

to p

roje

cts

with

var

ying

deg

rees

of s

kill

and

fam

iliar

ity

with

age

ncy

proc

edur

es.

Orie

ntat

ion

and

train

ing

will

impr

ove

thei

r ab

ility

to

deliv

er th

e pr

ojec

t on

the

inte

nded

sch

edul

e. It

is a

lso

impo

rtant

that

upd

ated

tra

inin

g is

ava

ilabl

e at

leas

t on

an a

nnua

l bas

is.

Cat

egor

yR

ef:*

BM

PD

escr

iptio

n

Proj

ect

Man

agem

ent

5.II.

d 20

06

Impl

emen

t ve

rific

atio

n pr

oced

ures

to

ensu

re th

at P

M tr

aini

ng in

clud

es a

genc

y po

licie

s, p

roce

dure

s, fo

rms,

and

sta

ndar

ds

of p

ract

ice

(sch

edul

ing,

bud

getin

g, c

laim

s av

oida

nce,

risk

ana

lysi

s, e

tc).

The

succ

ess

of a

pro

ject

is in

fluen

ced

sign

ifica

ntly

by

the

educ

atio

n an

d sk

ills

of

the

proj

ect m

anag

er. A

genc

ies

shou

ld v

erify

that

PM

’s k

now

and

use

the

tool

s av

aila

ble

with

in a

n ag

ency

and

that

they

are

cur

rent

with

indu

stry

pra

ctic

es.

5.III

.aA

dopt

and

use

a P

roje

ct C

ontro

l Sys

tem

on

all

proj

ects

.

A w

eb-b

ased

pro

ject

con

trol s

yste

m w

ill im

prov

e co

llabo

ratio

n an

d do

cum

enta

tion

durin

g th

e de

sign

and

con

stru

ctio

n pr

oces

s. Q

uest

ions

, ans

wer

s, p

ropo

sals

, and

de

cisi

ons

can

be e

xped

ited

usin

g a

colla

bora

tive

syst

em.

5.III

.e

2006

Impl

emen

t a fi

nanc

ial s

yste

m th

at tr

acks

ex

pend

iture

s by

cat

egor

y to

mon

itor

proj

ect h

ard

and

soft

cost

s du

ring

proj

ect

deliv

ery.

It is

rec

omm

ende

d th

at a

sys

tem

tha

t id

entifi

es a

ctua

l exp

endi

ture

s ag

ains

t pl

anne

d bu

dget

s be

mad

e av

aila

ble

to p

roje

ct m

anag

ers

to b

e us

ed a

s a

perfo

rman

ce m

easu

rem

ent t

ool.

5.III

.f 20

06

Impl

emen

t a

Wor

k B

reak

dow

n S

truct

ure

(WB

S)

to m

easu

re p

rogr

ess

on p

roje

ct

deliv

erab

les.

Get

ting

accu

rate

dat

a on

the

cost

of p

roje

ct d

eliv

ery

depe

nds

upon

bei

ng a

ble

to c

aptu

re a

nd c

lass

ify e

xpen

ses

to th

e ph

ases

of c

onst

ruct

ion

on e

ach

proj

ect.

Idea

lly, c

osts

wou

ld b

e id

entifi

ed b

y ea

ch o

f five

pro

ject

del

iver

y ph

ases

and

co

ded

to p

artic

ular

mile

ston

es o

r del

iver

able

s.

5.III

.g

2006

Mon

itor

“ear

ned

valu

e” v

ersu

s bu

dget

ed

and

actu

al e

xpen

ditu

res

durin

g pr

ojec

t de

liver

y.

Sof

t cos

ts “b

urn

rate

” sho

uld

be p

ropo

rtion

ate

to p

erce

nt c

ompl

ete

durin

g th

e de

sign

and

con

stru

ctio

n ph

ases

. Usi

ng a

pro

gram

whi

ch m

easu

res

and

rela

tes

soft

cost

exp

ense

s to

ear

ned

valu

es p

erm

its b

ette

r tra

ckin

g an

d co

ntro

l dur

ing

proj

ect d

eliv

ery.

5.III

.h

2007

Incl

ude

a fix

ed R

OW

acq

uisi

tion

mile

ston

e sc

hedu

le a

nd o

btai

n co

mm

itmen

ts f

rom

pa

rtici

patin

g C

ity d

epar

tmen

ts.

Pro

long

ed R

OW

acq

uisi

tion

can

be a

void

ed i

f al

l st

akeh

olde

rs a

gree

on

mile

ston

es to

com

plet

e th

e ac

quis

ition

s.

Tabl

e 4-

1D

escr

iptio

n of

Bes

t Man

agem

ent P

ract

ices

(con

t’d)


Cat

egor

yR

ef:*

BM

PD

escr

iptio

nPr

ojec

t M

anag

emen

t5.

III.i

2008

Impl

emen

t an

elec

troni

c pr

ogre

ss p

aym

ent

syst

em to

impr

ove

effic

ienc

yR

educ

tion

in t

he le

ngth

of

time

and

inef

ficie

ncie

s in

pro

cess

ing

of p

rogr

ess

paym

ents

thro

ugh

the

use

of e

lect

roni

c m

eans

.5.

IV.a

20

06B

undl

e sm

all p

roje

cts

whe

neve

r pos

sibl

e.Bu

ndlin

g sm

all p

roje

cts

so th

at th

ey a

re d

esig

ned,

bid

, and

con

stru

cted

toge

ther

w

ill re

duce

pro

ject

del

iver

y co

st p

ropo

rtion

atel

y.

5.IV

.b

2007

Hav

e a

coor

dina

tor

with

exp

ertis

e in

th

e en

viro

nmen

tal

proc

ess

with

in t

he

depa

rtmen

t de

liver

ing

the

engi

neer

ing/

capi

tal p

roje

ct.

Iden

tifyi

ng a

n en

viro

nmen

tal s

peci

alis

t with

in th

e pr

ojec

t del

iver

y te

am w

ho is

fa

mili

ar w

ith p

roce

dure

s an

d co

ntac

ts w

ithin

the

appr

ovin

g en

titie

s w

ill re

duce

pe

rmit

proc

urem

ent t

ime

and

cost

s.

Con

sulta

nt

Sele

ctio

n an

d U

se6.

c.In

clud

e a

stan

dard

con

sulta

nt c

ontra

ct

in t

he R

FQ/R

FP w

ith a

n in

dem

nific

atio

n cl

ause

.

The

nego

tiatio

n of

the

des

ign

cont

ract

can

be

expe

dite

d if

the

cons

ulta

nt

unde

rsta

nds

and

agre

es to

the

cond

ition

s of

the

cont

ract

at t

he ti

me

a pr

opos

al

is s

ubm

itted

.

6.e.

Del

egat

e au

thor

ity t

o th

e P

ublic

Wor

ks

Dir

ecto

r/C

ity

Eng

inee

r to

app

rove

co

nsul

tant

con

tract

s un

der $

250,

000

whe

n a

form

al R

FP s

elec

tion

proc

ess

is u

sed.

Aut

horiz

atio

n fo

r the

Pub

lic W

orks

Dire

ctor

/City

Eng

inee

r to

awar

d co

nsul

ting

cont

ract

s en

sure

s ea

rlier

sta

rt of

des

ign

and

cons

truct

ion

man

agem

ent a

ctiv

ities

an

d w

ill re

duce

con

sulta

nt s

elec

tion

proc

ess

cost

s.

6.g.

Impl

emen

t an

d us

e a

cons

ulta

nt r

atin

g sy

stem

that

iden

tifies

qua

lity

of c

onsu

ltant

pe

rform

ance

.

The

perfo

rman

ce o

f con

sulta

nts

shou

ld b

e tra

cked

so

that

thos

e w

ho d

eliv

er

qual

ity s

ervi

ces

at r

easo

nabl

e co

sts

can

be a

dequ

atel

y co

nsid

ered

for

futu

re

awar

ds.

6.m

20

06

Impl

emen

t as-

need

ed, r

otat

ing,

or o

n-ca

ll co

ntra

cts

for

desi

gn a

nd c

onst

ruct

ion

man

agem

ent

wor

k th

at a

llow

wor

k to

be

aut

horiz

ed o

n a

task

ord

er b

asis

to

expe

dite

the

deliv

ery

of s

mal

ler p

roje

cts.

Est

ablis

hing

an

on-c

all l

ist o

f qua

lified

con

sulta

nts

with

exp

ertis

e in

a v

arie

ty o

f de

sign

dis

cipl

ines

will

exp

edite

the

star

t of t

he d

esig

n pr

oces

s.

Sus

tain

able

D

evel

opm

ent

7.a.

20

09Id

entif

y th

e en

viro

nmen

tal b

enefi

ts o

f the

pr

ojec

t at t

he ti

me

of a

war

d.P

rovi

de w

ritte

n, e

nviro

nmen

tal b

enefi

ts to

the

awar

ding

aut

horit

y on

pro

ject

s th

at u

se s

usta

inab

le p

ract

ices

or a

im to

ach

ieve

LE

ED

cer

tifica

tion.

Tabl

e 4-

1D

escr

iptio

n of

Bes

t Man

agem

ent P

ract

ices

(con

t’d)


C. PROGRESS ON BEST MANAGEMENT PRACTICE IMPLEMENTATION

In Update 2009, the agencies continued to exchange ideas regarding strategies for implementing various BMPs using both the networking opportunities at the quarterly meetings and the online discussion forum. Agencies have started to review and update those BMPs that have been fully implemented for several years. Agencies continue to pursue full implementation of BMPs although many remain only partially implemented. Given the current state of the economy and due to staff reductions, furloughs, and the management’s increased involvement in resolving budgetary issues, progress on fully implementing BMPs has been impacted. The agencies have focused

their efforts on tracking BMPs that have been implemented and which continue to provide efficiencies in project delivery processes for participating departments. As of Update 2009, the agencies have fully implemented about 72 percent of all BMPs. Many of the remaining BMPs require multiple department involvement and are more complicated to implement than other BMPs.

To support the linking of BMPs to performance improvements, BMP implementation has been tracked and project completion dates have been collected on Performance Questionnaires.

BMPs targeted for future implementation a n d p r o g r e s s o n a c t u a l B M P implementation since the Update 2008 are summarized below.

Implemented from June 2008 to May 2009:

Targeted June 2009 Onward:

4.V.c 2003 Make bid documents available • online.

5.III.f 2006 Implement a Work Breakdown • Structure (WBS) to measure progress on project deliverables.

5.III.g 2006 M o n i t o r “ e a r n e d v a l u e ” • versus budgeted and actual expenditures during project delivery.

5.III.h 2007 Include a fixed ROW acquisi-• tion milestone schedule and obtain commit-ments from participating City departments (partially implemented).

I. City of Los Angeles


II. City of Long Beach Implemented from June

2008 to May 2009:Targeted June 2009 Onward:

3.I.a. Develop and use a standardized Project De-• livery Manual (partially implemented).

3.III.a. Use a formal Quality Management System • (partially implemented).

3.III.b Perform and use post-project reviews to • identify lessons learned.

3.III.m.2008 Maintain and regularly update electron-• ic standard contract specifications and related docu-ments as well as technical/special provisions.

6.g. Implement and use a consultant rating system • that identifies quality of consultant performance (In Progress).

Implemented from June 2008 to May 2009:


1.i. Show projects on a Geographical Information • System.

2.f. Define requirements for reliability, maintenance, • and operation prior to design initiation.

3.III.a. Use a formal Quality Management System.•

III. City of Oakland


IV. City of SacramentoImplemented from June


Department of Transportation

4.V.c 2003 Make bid documents avail-• able online.

5.1.f Assign a client representative to • every project.

5.III.e.2006 Implement verification proce-• dures to ensure that PM training includes agency policies, procedures, forms, and standards of practice (scheduling, bud-geting, claims avoidance, risk analysis, etc.).

5.III.h 2007 Include a fixed ROW ac-• quisition milestone schedule and obtain commitments from participating City departments.

Department of Utilities

2.p. 2008 Establish criteria for respon-• sible charge design approval such that it occurs at the lowest appropriate organizational level in order to expedite design completion.

3.III.m.2008 Maintain and regularly • update electronic standard contract specifications and related documents as well as technical/special provisions.

4.II.a. Include a formal dispute • Resolution Procedure in all contract agreements.

5.III.e 2006 Implement a financial sys-• tem that tracks expenditures by category to monitor project hard and soft costs during project delivery.

6.c. Include a standard consultant • contract in the RFQ/RFP with an indem-nification clause.

Department of Transportation

5.I.k 2004 Institutionalize Project Manager performance and • accountability.

5.III.f 2006 Implement a Work Breakdown Structure (WBS) to • measure progress on project deliverables. (partially implemented)

5.III.g 2006 Monitor “earned value” versus budgeted and actual • expenditures during project delivery. (partially implemented)

Department of Utilities

1.d Utilize a Board/Council project prioritization system. (par-• tially implemented)

4.V.c 2003 Make bid documents available online. (partially • implemented)

5.I.k 2004 Institutionalize Project Manager performance • and accountability. (partially implemented)

5.III.h Include a fixed ROW acquisition milestone schedule • and obtain commitments from participating City departments. (partially implemented)

6.m. 2006 Implement as-needed, rotating, or on-call • contracts for design and construction management work that allow work to be authorized on a task order basis to expedite the delivery of smaller projects. (partially implemented)


V. City of San DiegoImplemented from June


1.a Define capital projects well with respect to • scope and budget including community and client approval at the end of the planning phase.

1.b Complete Feasibility Studies on projects prior • to defining budget and scope.

1.e. Resource load all CIP projects for design and • construction. (partially implemented)

1.f Include a Master Schedule in the CIP that • identifies start and finish dates for projects.

2.b Provide a detailed clear, precise scope, • schedule, and budget to designers prior to design start.

3.I.a. Develop and use a standardized Project • Delivery Manual. (partially implemented)

5.I.k 2004 Institutionalize Project Manager • performance and accountability. (partially imple-mented)

5.III.e 2006 Implement a financial system that tracks • expenditures by category to monitor project hard and soft costs during project delivery

5.III.g 2006 Monitor “earned value” versus budgeted • and actual expenditures during project delivery. (par-tially implemented)

VI. City and County of San FranciscoImplemented from June


1.d Utilize a Board/Council project prioritization • system.

2.l. 2004 Limit Scope Changes to early stages of • design.

2.m. 2004 Require scope changes during design • to be accompanied by budget and schedule ap-provals.

2.o. 2007 Establish criteria for obtaining indepen-• dent cost estimates which take in consideration both project characteristics and volatility of the market.

5.I.j 2003 Create in-house project management • team for small projects. (partially implemented)

5.I.k 2004 Institutionalize Project Manager perfor-• mance and accountability. (partially implemented)

1.e. Resource load all CIP projects for design and • construction (partially implemented)

1.f. Include a Master Schedule in the CIP that identi-• fies start and finish dates for projects.

4.V.c. 2003 Make bid documents available online.•

5.II.d. 2006 Implement verification procedures to • ensure that PM training includes agency policies, procedures, forms, and standards of practice (scheduling, budgeting, claims avoidance, risk analysis, etc).

5.III.f. 2006 Implement a Work Breakdown Structure • (WBS) to measure progress on project deliver-ables.

5.III.g 2006 Monitor “earned value” versus budgeted • and actual expenditures during project delivery.


VII. City of San JoseImplemented

from June 2008 to May 2009:


3.1.a Develop and use a standardized Project Delivery Manual•

3.III.a. Use a formal Quality Management System.•

3.III.l 2007 Designate a responsible person or group and establish a • process of notifications and milestones for utility relocations (partially imple-mented).

3.III.m.2008 Maintain and regularly update electronic standard contract speci-• fications and related documents as well as technical/special provisions.

5.I.k 2004 Institutionalize Project Manager performance and account-• ability. (partially implemented)

5.II.a Provide formal training for Project Managers on a regular basis. (par-• tially implemented)

5.II.d 2006 Implement verification procedures to ensure that PM train-• ing includes agency policies, procedures, forms, and standards of practice (scheduling, budgeting, claims avoidance, risk analysis, etc).

5.III.f 2006 Implement a Work Breakdown Structure (WBS) to measure • progress on project deliverables. (partially implemented)

6.e Delegate authority to the Public Works Director/City Engineer to approve • consultant contracts under $250,000 when a formal RFP selection process is used.

Table 4-2 summarizes the BMPs that have been implemented by the participating agencies, as well as the planned implementation priorities.


Tabl

e 4-

2Im

plem

enta

tion

of B

MPs

Cat

egor

yR

ef:*

BM

PLA

LBO

KSC

SDSF

SJN

otes

DG

SD

TD

U

Plan

ning

1.a.

Def

ine

capi

tal

proj

ects

w

ell w

ith re

spec

t to

scop

e an

d bu

dget

inc

ludi

ng

com

mun

ity

and

clie

nt

appr

oval

at t

he e

nd o

f the

pl

anni

ng p

hase

.

S

C D

U: C

omm

unity

invo

lved

afte

r pr

ojec

t is

bette

r-de

fined

, typ

ical

ly a

t 30%

des

ign.

1.b.

Co

mp

lete

F

ea

sib

ilit

y S

tudi

es o

n pr

ojec

ts p

rior

to d

efin

ing

budg

et a

nd

scop

e.

LB: W

hen

appl

icab

le

SC

DU

: O

nly

on c

ompl

ex p

roje

cts

that

req

uire

a

Feas

ibili

ty S

tudy

S

F: W

hen

appl

icab

le

SJ:

Som

e ex

cept

ions

1.d.

Util

ize

a B

oard

/Cou

ncil

pro

ject

p

rio

riti

zati

on

syst

em.

N

IP

I, TB

DP

I, 20

08

PI,

2009

Nl

LA

: C

ou

nci

l a

llo

ws

Str

ee

ts,

Bri

dg

es

an

d S

torm

wat

er p

rogr

ams

a pr

ojec

t pr

iorit

y sy

stem

. S

C D

U: G

ettin

g cl

oser

to a

ppro

ved

Ass

et M

gt s

yste

m

that

wou

ld fa

cilit

ate

this

BM

P, b

ut p

roje

ct d

river

s va

ry

(per

mit

requ

irem

ents

, pro

ject

s in

oth

er d

epar

tmen

ts,

etc)

S

D: R

esul

t of C

IP B

ench

mar

king

SF: C

apita

l pla

n de

velo

ped

City

-wid

e an

d pr

iorit

ies

set

by C

ity-w

ide

com

mitt

ee o

f maj

or d

epar

tmen

t hea

ds.

1.e.

Res

ourc

e lo

ad a

ll C

IP

proj

ects

for

des

ign

and

cons

truct

ion.

TB

D

NI

LB

: Sof

twar

e in

dev

elop

men

t. S

C D

U: E

stim

ate

draf

ting

only.

Key

: LA

: Los

Ang

eles

; LB

: Lon

g B

each

; OK

: Oak

land

; SC

: Sac

ram

ento

(DG

S: D

epar

tmen

t of G

ener

al S

ervi

ces,

DT:

Dep

artm

ent o

f Tra

nspo

rtatio

n, D

U: D

epar

tmen

t of

Util

ities

), SD

: San

Die

go, S

F: S

an F

ranc

isco

, and

SJ:

San

Jose

: I

mpl

emen

ted

PI: P

artia

lly im

plem

ente

d N

I: N

o pl

ans t

o im

plem

ent a

t thi

s tim

eTB

D: T

o be

det

erm

ined

yyyy

: Will

be

impl

emen

ted

in c

alen

dar y

ear “

yyyy

”*

See

Proc

ess Q

uest

ionn

aire

in A

ppen

dix

C o

f 200

2 R

epor

t; ye

ar n

oted

indi

cate

s thi

s BM

P w

as a

dded

late

r.


Tabl

e 4-

2Im

plem

enta

tion

of B

MPs

(con

t’d)

Cat

egor

yR

ef:*

BM

PLA

LBO

KSC

SDSF

SJN

otes

DG

SD

TD

U

Plan

ning

1.f.

Incl

ude

a M

aste

r Sch

edul

e in

the

CIP

tha

t id

entifi

es

star

t an

d fin

ish

date

s fo

r pr

ojec

ts.

TB

D

2010

LB

: Sof

twar

e in

dev

elop

men

t. S

C D

U: C

ompl

etio

n da

te o

nly

estim

ated

, not

det

erm

ined

by

sch

edul

ing

anal

ysis

.

1.g

2007

Ma

ke

a

n

ea

rly

dete

rmin

atio

n on

whi

ch

envi

ronm

enta

l do

cum

ent

is re

quire

d an

d in

corp

orat

e in

to th

e sc

hedu

le.

2008

1.i.

Sh

ow

p

roje

cts

on

a

Geo

grap

hica

l Inf

orm

atio

n S

yste

m.

LB

: Inf

rast

ruct

ure

only

Des

ign

2.b.

Pro

vide

a d

etai

led

clea

r, pr

ecis

e sc

ope,

sch

edul

e,

and

budg

et t

o de

sign

ers

prio

r to

desi

gn s

tart.

S

C D

U: G

ener

al s

cope

onl

y fo

r sim

ple

proj

ects

.

2.f.

Def

ine

requ

irem

ents

for

re

liabi

lity,

mai

nten

ance

, an

d op

erat

ion

prio

r to

de

sign

initi

atio

n.

P

I, 20

08

NI

S

D: S

ome

Div

isio

ns o

nly

Key

: LA

: Los

Ang

eles

; LB

: Lon

g B

each

; OK

: Oak

land

; SC

: Sac

ram

ento

(DG

S: D

epar

tmen

t of G

ener

al S

ervi

ces,

DT:

Dep

artm

ent o

f Tra

nspo

rtatio

n, D

U: D

epar

tmen

t of

Util

ities

), SD

: San

Die

go, S

F: S

an F

ranc

isco

, and

SJ:

San

Jose

: I

mpl

emen

ted

PI: P

artia

lly im

plem

ente

d N

I: N

o pl

ans t

o im

plem

ent a

t thi

s tim

eTB

D: T

o be

det

erm

ined

yyyy

: Will

be

impl

emen

ted

in c

alen

dar y

ear “

yyyy

”*

See

Proc

ess Q

uest

ionn

aire

in A

ppen

dix

C o

f 200

2 R

epor

t; ye

ar n

oted

indi

cate

s thi

s BM

P w

as a

dded

late

r.


Tabl

e 4-

2Im

plem

enta

tion

of B

MPs

(con

t’d)

Cat

egor

yR

ef:*

BM

PLA

LBO

KSC

SDSF

SJN

otes

DG

SD

TD

U

Des

ign

2.i.

Ada

pt s

ucce

ssfu

l des

igns

to

pro

ject

site

s, w

hene

ver

poss

ible

(e.g

. fire

sta

tions

, gy

mna

sium

s, e

tc).

NI

SC

DU

: Thi

s is

key

to lo

w d

eliv

ery

cost

s. S

td s

peci

al

prov

isio

ns a

re u

pdat

ed c

ontin

uous

ly fo

r les

sons

lear

ned,

ne

w re

quire

men

ts, c

hang

ing

tech

nolo

gy, e

tc.

2.k.

20

03

Trai

n in

-hou

se s

taff

to

use

G

ree

n

Bu

ild

ing

Sta

ndar

ds.

NI

NI

Th

is B

MP

is in

tend

ed t

o im

prov

e cl

ient

sat

isfa

ctio

n (q

ualit

y) a

nd m

ay n

ot r

educ

e pr

ojec

t de

liver

y co

st

dire

ctly.

SF:

Whe

n ap

plic

able

2.l.

2004

Lim

it S

cope

Cha

nges

to

early

sta

ges

of d

esig

n.

NI

S

C D

U: C

ontro

l and

min

imiz

e, b

ut d

ifficu

lt to

elim

inat

e,

sinc

e cl

ient

s an

d en

gine

ers

com

e up

with

new

/bet

ter

solu

tions

.

2.m

. 20

04

Req

uire

sco

pe c

hang

es

du

rin

g

de

sig

n

to

be

acco

mpa

nied

by

budg

et

and

sche

dule

app

rova

ls.

N

I

Key

: LA

: Los

Ang

eles

; LB

: Lon

g B

each

; OK

: Oak

land

; SC

: Sac

ram

ento

(DG

S: D

epar

tmen

t of G

ener

al S

ervi

ces,

DT:

Dep

artm

ent o

f Tra

nspo

rtatio

n, D

U: D

epar

tmen

t of

Util

ities

), SD

: San

Die

go, S

F: S

an F

ranc

isco

, and

SJ:

San

Jose

: I

mpl

emen

ted

PI: P

artia

lly im

plem

ente

d N

I: N

o pl

ans t

o im

plem

ent a

t thi

s tim

eTB

D: T

o be

det

erm

ined

yyyy

: Will

be

impl

emen

ted

in c

alen

dar y

ear “

yyyy

”*

See

Proc

ess Q

uest

ionn

aire

in A

ppen

dix

C o

f 200

2 R

epor

t; ye

ar n

oted

indi

cate

s thi

s BM

P w

as a

dded

late

r.


Tabl

e 4-

2Im

plem

enta

tion

of B

MPs

(con

t’d)

Cat

egor

yR

ef:*

BM

PLA

LBO

KSC

SDSF

SJN

otes

DG

SD

TD

U

Des

ign

2.n.

20

06

Impl

emen

t a

rota

ting

R

eque

st fo

r Quo

te p

roce

ss

for

cont

ract

ing

smal

l pr

ojec

ts to

stre

amlin

e th

e bi

ddin

g an

d aw

ard

proc

ess

du

rin

g

con

stru

ctio

n.

(In

clu

de

cr

ite

ria

fo

r ex

empt

ions

fro

m f

orm

al

Cou

ncil

appr

oval

.)

Nl

N

l

Nl

Nl

SC

DT:

Mai

ntai

ns o

n-ca

ll co

nsul

tant

list

for

vario

us

engi

neer

ing,

tra

ffic,

lan

dsca

pe,

arch

itect

ure,

and

ge

otec

hnic

al s

ervi

ces.

S

F: A

s-ne

eded

job

orde

r con

tract

ing

(JO

C)

2.o

2007

Est

ablis

h cr

iter

ia f

or

obta

inin

g in

depe

nden

t co

st e

stim

ates

whi

ch

take

in c

onsi

dera

tion

both

pr

ojec

t cha

ract

eris

tics

and

vola

tility

of t

he m

arke

t.

TBD

PI,

TBD

TBD

TBD

2009

TBD

TB

D

TBD

LA w

ill li

kely

impl

emen

t thi

s in

som

e fa

shio

n, b

ut is

st

ill w

orki

ng o

ut th

e de

tails

. We

are

cons

ider

ing

only

im

plem

entin

g th

is o

n pr

ojec

ts o

ver $

10M

.S

F: E

stab

lishi

ng e

stim

atin

g da

taba

se

2.p

2008

Est

ablis

h cr

iter

ia f

or

resp

onsi

ble

char

ge d

esig

n ap

prov

al su

ch th

at it

occu

rs

at t

he lo

wes

t ap

prop

riate

or

gani

zatio

nal

leve

l in

or

der

to e

xped

ite d

esig

n co

mpl

etio

n.

TB

DTB

DTB

D

TB

D

TBD

Key

: LA

: Los

Ang

eles

; LB

: Lon

g B

each

; OK

: Oak

land

; SC

: Sac

ram

ento

(DG

S: D

epar

tmen

t of G

ener

al S

ervi

ces,

DT:

Dep

artm

ent o

f Tra

nspo

rtatio

n, D

U: D

epar

tmen

t of

Util

ities

), SD

: San

Die

go, S

F: S

an F

ranc

isco

, and

SJ:

San

Jose

: I

mpl

emen

ted

PI: P

artia

lly im

plem

ente

d N

I: N

o pl

ans t

o im

plem

ent a

t thi

s tim

eTB

D: T

o be

det

erm

ined

yyyy

: Will

be

impl

emen

ted

in c

alen

dar y

ear “

yyyy

”*

See

Proc

ess Q

uest

ionn

aire

in A

ppen

dix

C o

f 200

2 R

epor

t; ye

ar n

oted

indi

cate

s thi

s BM

P w

as a

dded

late

r.


Tabl

e 4-

2Im

plem

enta

tion

of B

MPs

(con

t’d)

Cat

egor

yR

ef:*

BM

PLA

LBO

KSC

SDSF

SJN

otes

DG

SD

TD

UQ

ualit

y A

ssur

ance

/ Q

ualit

y C

ontr

ol

3.I.a

.D

eve

lop

a

nd

u

se

a st

anda

rdiz

ed P

roje

ct

Del

iver

y M

anua

l.

PI,

2011

2010

SC

DU

: Bad

ly n

eeds

upd

atin

g.

3.II.

b.

Per

form

a f

orm

al V

alue

E

ngin

eeri

ng S

tudy

for

pr

ojec

ts l

arge

r th

an $

1 m

illio

n.

NI

NI

NI

LA: F

or p

roje

cts

> $1

0M

LB: A

s ne

eded

S

C: A

s ne

eded

S

D: A

s ne

eded

S

F: A

s ne

eded

S

J: F

or p

roje

cts

> $5

mill

ion

3.III

.a.

Use

a f

orm

al Q

ualit

y M

anag

emen

t Sys

tem

.

PI,

2010

N

I

20

10S

D: S

ome

Div

isio

ns o

nly

3.III

.bP

erfo

rm a

nd u

se p

ost-

proj

ect r

evie

ws

to id

entif

y le

sson

s le

arne

d.

2009

SC D

U: F

or s

elec

ted

proj

ects

in o

ne-o

n-on

e m

eetin

gs

with

des

ign

and

cons

truct

ion

staf

f. A

lso

incl

udes

fe

edba

ck f

rom

clie

nt.

Inte

nded

to

prom

ote

cand

id

disc

ussi

on.

3.III

.k

2007

Est

ab

lish

a

U

tili

ty

Coo

rdin

atin

g C

omm

ittee

w

ith m

embe

rs fr

om p

ublic

an

d pr

ivat

e en

titie

s.

P

I

NI

3.III

.l 20

07

Des

igna

te a

res

pons

ible

pe

rson

for

and

est

ablis

h a

proc

ess

of n

otifi

catio

ns

and

mile

ston

es f

or u

tility

re

loca

tions

.

N

ITB

DN

I

P

I, 20

10

Key

: LA

: Los

Ang

eles

; LB

: Lon

g B

each

; OK

: Oak

land

; SC

: Sac

ram

ento

(DG

S: D

epar

tmen

t of G

ener

al S

ervi

ces,

DT:

Dep

artm

ent o

f Tra

nspo

rtatio

n, D

U: D

epar

tmen

t of

Util

ities

), SD

: San

Die

go, S

F: S

an F

ranc

isco

, and

SJ:

San

Jose

: I

mpl

emen

ted

PI: P

artia

lly im

plem

ente

d N

I: N

o pl

ans t

o im

plem

ent a

t thi

s tim

eTB

D: T

o be

det

erm

ined

yyyy

: Will

be

impl

emen

ted

in c

alen

dar y

ear “

yyyy

”*

See

Proc

ess Q

uest

ionn

aire

in A

ppen

dix

C o

f 200

2 R

epor

t; ye

ar n

oted

indi

cate

s thi

s BM

P w

as a

dded

late

r.


Cat

egor

yR

ef:*

BM

PLA

LBO

KSC

SDSF

SJN

otes

DG

SD

TD

UQ

ualit

y A

ssur

ance

/ Q

ualit

y C

ontr

ol

3.I.a

.D

eve

lop

a

nd

u

se

a st

anda

rdiz

ed P

roje

ct

Del

iver

y M

anua

l.

PI,

2011

2010

SC

DU

: Bad

ly n

eeds

upd

atin

g.

3.II.

b.

Per

form

a f

orm

al V

alue

E

ngin

eeri

ng S

tudy

for

pr

ojec

ts l

arge

r th

an $

1 m

illio

n.

NI

NI

NI

LA: F

or p

roje

cts

> $1

0M

LB: A

s ne

eded

S

C: A

s ne

eded

S

D: A

s ne

eded

S

F: A

s ne

eded

S

J: F

or p

roje

cts

> $5

mill

ion

3.III

.a.

Use

a f

orm

al Q

ualit

y M

anag

emen

t Sys

tem

.

PI,

2010

N

I

20

10S

D: S

ome

Div

isio

ns o

nly

3.III

.bP

erfo

rm a

nd u

se p

ost-

proj

ect r

evie

ws

to id

entif

y le

sson

s le

arne

d.

2009

SC D

U: F

or s

elec

ted

proj

ects

in o

ne-o

n-on

e m

eetin

gs

with

des

ign

and

cons

truct

ion

staf

f. A

lso

incl

udes

fe

edba

ck f

rom

clie

nt.

Inte

nded

to

prom

ote

cand

id

disc

ussi

on.

3.III

.k

2007

Est

ab

lish

a

U

tili

ty

Coo

rdin

atin

g C

omm

ittee

w

ith m

embe

rs fr

om p

ublic

an

d pr

ivat

e en

titie

s.

P

I

NI

3.III

.l 20

07

Des

igna

te a

res

pons

ible

pe

rson

for

and

est

ablis

h a

proc

ess

of n

otifi

catio

ns

and

mile

ston

es f

or u

tility

re

loca

tions

.

N

ITB

DN

I

P

I, 20

10

Tabl

e 4-

2Im

plem

enta

tion

of B

MPs

(con

t’d)

Cat

egor

yR

ef:*

BM

PLA

LBO

KSC

SDSF

SJN

otes

DG

SD

TD

U

Qua

lity

Ass

uran

ce/

Qua

lity

Con

trol

3.III

.m20

08

Mai

ntai

n an

d re

gula

rly

upda

te e

lect

roni

c st

anda

rd

cont

ract

spe

cific

atio

ns a

nd

rela

ted

docu

men

ts a

s w

ell a

s te

chni

cal/s

peci

al p

rovi

sion

.

20

11

TBD

2009

Con

stru

ctio

n M

anag

emen

t4.

I.a.

Del

egat

e au

thor

ity t

o th

e C

ity E

ngin

eer/P

ublic

Wor

ks

Dire

ctor

or o

ther

dep

artm

ents

to

app

rove

cha

nge

orde

rs to

th

e co

ntin

genc

y am

ount

.

N

IN

I

S

D: I

ndiv

idua

l CO

< $

200,

000

SF:

At B

urea

u le

vel

SJ:

Indi

vidu

al C

O <

$10

0,00

0

4.I.m

.C

lass

ify t

ypes

of

chan

ge

orde

rs.

LA

: Dra

ft S

peci

al O

rder

pre

pare

d.

4.II.

a.In

clud

e a

form

al D

ispu

te

Res

olut

ion

Pro

cedu

re in

all

cont

ract

agr

eem

ents

.

NI

S

J: F

or p

roje

cts

> $1

0 M

4.III

.a.

Use

a te

am b

uild

ing

proc

ess

for

proj

ects

gre

ater

than

$5

mill

ion.

N

I

LB: A

s-ne

eded

S

D: A

s-ne

eded

S

F: A

s-ne

eded

S

J: F

or p

roje

cts

> $1

0 M

4.IV

.a.

Invo

lve

the

Con

stru

ctio

n M

anag

emen

t Te

am p

rior

to

com

plet

ion

of d

esig

n.

SD

: Som

e D

ivis

ions

onl

y

4.V.

a.

2003

Del

egat

e au

thor

ity b

elow

C

ounc

il to

mak

e co

ntra

ct

awar

ds u

nder

$1

mill

ion.

NI

NI

NI

NI

Key

: LA

: Los

Ang

eles

; LB

: Lon

g B

each

; OK

: Oak

land

; SC

: Sac

ram

ento

(DG

S: D

epar

tmen

t of G

ener

al S

ervi

ces,

DT:

Dep

artm

ent o

f Tra

nspo

rtatio

n, D

U: D

epar

tmen

t of

Util

ities

), SD

: San

Die

go, S

F: S

an F

ranc

isco

, and

SJ:

San

Jose

: I

mpl

emen

ted

PI: P

artia

lly im

plem

ente

d N

I: N

o pl

ans t

o im

plem

ent a

t thi

s tim

eTB

D: T

o be

det

erm

ined

yyyy

: Will

be

impl

emen

ted

in c

alen

dar y

ear “

yyyy

”*

See

Proc

ess Q

uest

ionn

aire

in A

ppen

dix

C o

f 200

2 R

epor

t; ye

ar n

oted

indi

cate

s thi

s BM

P w

as a

dded

late

r.


Tabl

e 4-

2Im

plem

enta

tion

of B

MPs

(con

t’d)

Cat

egor

yR

ef:*

BM

PLA

LBO

KSC

SDSF

SJN

otes

DG

SD

TD

U

Con

stru

ctio

n M

anag

emen

t4.

V.b

2003

Esta

blis

h a

pre-

qual

ifica

tion

proc

ess

for c

ontra

ctor

s on

la

rge,

com

plex

pro

ject

s.

NI

NI

4.V.

c 20

03M

ake

bid

docu

men

ts

avai

labl

e on

line.

2010

TB

DP

I, 20

08

PI.

2008

20

09

LA:

Req

uest

ed t

his

thro

ugh

our

ITA

Dep

t fo

r in

tegr

atio

n w

ith o

ur b

id o

utre

ach

appl

icat

ion,

but

im

plem

enta

tion

will

dep

end

on t

heir

reso

urce

av

aila

bilit

y.

SF:

Doc

umen

ts o

n C

D in

inte

rim

Proj

ect

Man

agem

ent

5.I.f

.A

ss

ign

a

c

lie

nt

repr

esen

tativ

e to

eve

ry

proj

ect.

S

D: O

nly

for l

arge

pro

ject

sS

F: D

ocum

ents

on

CD

in in

terim

5.I.j

20

03

Cre

ate

in-h

ouse

pro

ject

m

anag

emen

t te

am f

or

smal

l pro

ject

s.N

IN

I

N

IN

IN

I

SC

DU

: Not

eno

ugh

PMs

to ju

stify

this

. Don

’t w

ant

to re

stric

t sta

ff to

sm

all,

less

-rew

ardi

ng p

roje

cts.

5.I.k

20

04

Inst

itutio

naliz

e P

roje

ct

Man

ager

per

form

ance

and

ac

coun

tabi

lity.

2009

PI,

2009

PI,

2010

SC

DU

: The

re is

inte

rest

but

no

defin

ite p

lan.

5.II.

aP

rovi

de fo

rmal

trai

ning

for

Pro

ject

Man

ager

s on

a

regu

lar b

asis

.

TBD

N

I

P

I, 20

10LB

: Pro

gram

impl

emen

tatio

n pu

t on

hold

due

to

budg

et c

uts

5.II.

d 20

06

Impl

emen

t ve

rific

atio

n pr

oced

ures

to e

nsur

e th

at

PM tr

aini

ng in

clud

es a

genc

y po

licie

s, p

roce

dure

s, fo

rms,

an

d st

anda

rds

of p

ract

ice

(sch

edul

ing,

bud

getin

g,

clai

ms

avoi

danc

e, r

isk

anal

ysis

, etc

).

TB

D

NI

20

1020

10

Key

: LA

: Los

Ang

eles

; LB

: Lon

g B

each

; OK

: Oak

land

; SC

: Sac

ram

ento

(DG

S: D

epar

tmen

t of G

ener

al S

ervi

ces,

DT:

Dep

artm

ent o

f Tra

nspo

rtatio

n, D

U: D

epar

tmen

t of

Util

ities

), SD

: San

Die

go, S

F: S

an F

ranc

isco

, and

SJ:

San

Jose

: I

mpl

emen

ted

PI: P

artia

lly im

plem

ente

d N

I: N

o pl

ans t

o im

plem

ent a

t thi

s tim

eTB

D: T

o be

det

erm

ined

yyyy

: Will

be

impl

emen

ted

in c

alen

dar y

ear “

yyyy

”*

See

Proc

ess Q

uest

ionn

aire

in A

ppen

dix

C o

f 200

2 R

epor

t; ye

ar n

oted

indi

cate

s thi

s BM

P w

as a

dded

late

r.


Cat

egor

yR

ef:*

BM

PLA

LBO

KSC

SDSF

SJN

otes

DG

SD

TD

U

Con

stru

ctio

n M

anag

emen

t4.

V.b

2003

Esta

blis

h a

pre-

qual

ifica

tion

proc

ess

for c

ontra

ctor

s on

la

rge,

com

plex

pro

ject

s.

NI

NI

4.V.

c 20

03M

ake

bid

docu

men

ts

avai

labl

e on

line.

2010

TB

DP

I, 20

08

PI.

2008

20

09

LA:

Req

uest

ed t

his

thro

ugh

our

ITA

Dep

t fo

r in

tegr

atio

n w

ith o

ur b

id o

utre

ach

appl

icat

ion,

but

im

plem

enta

tion

will

dep

end

on t

heir

reso

urce

av

aila

bilit

y.

SF:

Doc

umen

ts o

n C

D in

inte

rim

Proj

ect

Man

agem

ent

5.I.f

.A

ss

ign

a

c

lie

nt

repr

esen

tativ

e to

eve

ry

proj

ect.

S

D: O

nly

for l

arge

pro

ject

sS

F: D

ocum

ents

on

CD

in in

terim

5.I.j

20

03

Cre

ate

in-h

ouse

pro

ject

m

anag

emen

t te

am f

or

smal

l pro

ject

s.N

IN

I

N

IN

IN

I

SC

DU

: Not

eno

ugh

PMs

to ju

stify

this

. Don

’t w

ant

to re

stric

t sta

ff to

sm

all,

less

-rew

ardi

ng p

roje

cts.

5.I.k

20

04

Inst

itutio

naliz

e P

roje

ct

Man

ager

per

form

ance

and

ac

coun

tabi

lity.

2009

PI,

2009

PI,

2010

SC

DU

: The

re is

inte

rest

but

no

defin

ite p

lan.

5.II.

aP

rovi

de fo

rmal

trai

ning

for

Pro

ject

Man

ager

s on

a

regu

lar b

asis

.

TBD

N

I

P

I, 20

10LB

: Pro

gram

impl

emen

tatio

n pu

t on

hold

due

to

budg

et c

uts

5.II.

d 20

06

Impl

emen

t ve

rific

atio

n pr

oced

ures

to e

nsur

e th

at

PM tr

aini

ng in

clud

es a

genc

y po

licie

s, p

roce

dure

s, fo

rms,

an

d st

anda

rds

of p

ract

ice

(sch

edul

ing,

bud

getin

g,

clai

ms

avoi

danc

e, r

isk

anal

ysis

, etc

).

TB

D

NI

20

1020

10

Key

: LA

: Los

Ang

eles

; LB

: Lon

g B

each

; OK

: Oak

land

; SC

: Sac

ram

ento

(DG

S: D

epar

tmen

t of G

ener

al S

ervi

ces,

DT:

Dep

artm

ent o

f Tra

nspo

rtatio

n, D

U: D

epar

tmen

t of

Util

ities

), SD

: San

Die

go, S

F: S

an F

ranc

isco

, and

SJ:

San

Jose

: I

mpl

emen

ted

PI: P

artia

lly im

plem

ente

d N

I: N

o pl

ans t

o im

plem

ent a

t thi

s tim

eTB

D: T

o be

det

erm

ined

yyyy

: Will

be

impl

emen

ted

in c

alen

dar y

ear “

yyyy

”*

See

Proc

ess Q

uest

ionn

aire

in A

ppen

dix

C o

f 200

2 R

epor

t; ye

ar n

oted

indi

cate

s thi

s BM

P w

as a

dded

late

r.

Tabl

e 4-

2Im

plem

enta

tion

of B

MPs

(con

t’d)

Cat

egor

yR

ef:*

BM

PLA

LBO

KSC

SDSF

SJN

otes

DG

SD

TD

UPr

ojec

t M

anag

emen

t5.

III.a

.A

dopt

and

use

a P

roje

ct C

ontro

l S

yste

m o

n al

l pro

ject

s.

NI

5.III

.e

2006

Impl

emen

t a fi

nanc

ial s

yste

m th

at

track

s ex

pend

iture

s by

cat

egor

y to

mon

itor p

roje

ct h

ard

and

soft

cost

s du

ring

proj

ect d

eliv

ery.

LA: U

PR

S, R

epor

ts, P

age

3 S

C D

T: W

ill c

ompl

ete

auto

mat

ed r

epor

t sy

stem

by

2006

. S

C D

U:

Inte

nd t

o ut

ilize

SC

DT’

s so

ftwar

e if

it pr

oves

to

func

tion

wel

l w

ith o

ur P

M

Dat

abas

e.

5.III

.f 20

06

Impl

emen

t a

Wor

k B

reak

dow

n S

truc

ture

(W

BS

) to

mea

sure

p

rog

res

s

on

p

roje

ct

deliv

erab

les.

2010

PI,

2009

PI,

2010

NI

PI,

2010

SC D

T: W

orki

ng to

/ Upd

ate:

Pro

vide

Mic

roso

ft P

roje

ct to

all

Pro

ject

Man

ager

s an

d pr

oduc

e sc

hedu

les

with

task

s/su

b-ta

sk s

ched

ules

5.III

.g

2006

Mon

itor

“ear

ned

valu

e” v

ersu

s bu

dget

ed a

nd a

ctua

l exp

endi

ture

s du

ring

proj

ect d

eliv

ery.

2010

NI

P

I, 20

08P

I, 20

10N

I P

I, 20

10

NI

5.III

.h

2007

Incl

ude

a fix

ed R

OW

acq

uisi

tion

mile

ston

e sc

hedu

le a

nd o

btai

n co

mm

itmen

ts fr

om p

artic

ipat

ing

City

dep

artm

ents

.

PI

TBD

TBD

NI

P

I, 20

08N

IN

I

SF:

No

addi

tiona

l RO

W re

quire

d ou

tsid

e m

ilita

ry

base

clo

sure

.

5.III

.i 20

08

Impl

emen

t an

elec

troni

c pr

ogre

ss

paym

ent

syst

em t

o im

prov

e ef

ficie

ncy.

TBD

NI

TBD

TBD

NI

TBD

TBD

TB

D

Key

: LA

: Los

Ang

eles

; LB

: Lon

g B

each

; OK

: Oak

land

; SC

: Sac

ram

ento

(DG

S: D

epar

tmen

t of G

ener

al S

ervi

ces,

DT:

Dep

artm

ent o

f Tra

nspo

rtatio

n, D

U: D

epar

tmen

t of

Util

ities

), SD

: San

Die

go, S

F: S

an F

ranc

isco

, and

SJ:

San

Jose

: I

mpl

emen

ted

PI: P

artia

lly im

plem

ente

d N

I: N

o pl

ans t

o im

plem

ent a

t thi

s tim

eTB

D: T

o be

det

erm

ined

yyyy

: Will

be

impl

emen

ted

in c

alen

dar y

ear “

yyyy

”*

See

Proc

ess Q

uest

ionn

aire

in A

ppen

dix

C o

f 200

2 R

epor

t; ye

ar n

oted

indi

cate

s thi

s BM

P w

as a

dded

late

r.


Tabl

e 4-

2Im

plem

enta

tion

of B

MPs

(con

t’d)

Cat

egor

yR

ef:*

BM

PLA

LBO

KSC

SDSF

SJN

otes

DG

SD

TD

U

Proj

ect

Man

agem

ent

5.IV

.a

2006

Bun

dle

smal

l pr

ojec

ts

whe

neve

r pos

sibl

e.

5.IV

.b

2007

Ha

ve

a

coo

rdin

ato

r w

ith

expe

rtis

e in

the

en

viro

nmen

tal

proc

ess

wit

hin

the

depa

rtm

ent

deliv

erin

g th

e en

gine

erin

g/ca

pita

l pro

ject

.

N

IN

IN

IN

IN

I

P

I, TB

D

Con

sulta

nt

Sele

ctio

n an

d U

se6.

c.

Incl

ud

e

a

sta

nd

ard

co

nsul

tant

con

trac

t in

th

e R

FQ

/RF

P w

ith

an

inde

mni

ficat

ion

clau

se.

S

D: S

ome

Div

isio

ns o

nly

6.e.

Del

egat

e au

thor

ity t

o th

e P

ublic

Wor

ks D

irec

tor/

City

Eng

inee

r to

app

rove

co

nsul

tant

con

tract

s un

der

$250

,000

whe

n a

form

al

RFP

sel

ectio

n pr

oces

s is

us

ed.

NI

NI

NI

NI

NI

NI

2009

SC

DU

: Thr

esho

ld is

$10

0,00

0.

Key

: LA

: Los

Ang

eles

; LB

: Lon

g B

each

; OK

: Oak

land

; SC

: Sac

ram

ento

(DG

S: D

epar

tmen

t of G

ener

al S

ervi

ces,

DT:

Dep

artm

ent o

f Tra

nspo

rtatio

n, D

U: D

epar

tmen

t of

Util

ities

), SD

: San

Die

go, S

F: S

an F

ranc

isco

, and

SJ:

San

Jose

: I

mpl

emen

ted

PI: P

artia

lly im

plem

ente

d N

I: N

o pl

ans t

o im

plem

ent a

t thi

s tim

eTB

D: T

o be

det

erm

ined

yyyy

: Will

be

impl

emen

ted

in c

alen

dar y

ear “

yyyy

”*

See

Proc

ess Q

uest

ionn

aire

in A

ppen

dix

C o

f 200

2 R

epor

t; ye

ar n

oted

indi

cate

s thi

s BM

P w

as a

dded

late

r.


Tabl

e 4-

2Im

plem

enta

tion

of B

MPs

(con

t’d)

Cat

egor

yR

ef:*

BM

PLA

LBO

KSC

SDSF

SJN

otes

DG

SD

TD

U

Con

sulta

nt

Sele

ctio

n an

d U

se6.

g.Im

plem

ent a

nd u

se a

con

sulta

nt

ratin

g sy

stem

that

iden

tifies

qua

lity

of c

onsu

ltant

per

form

ance

.

PI

NI

NI

PI

SC D

U: T

rack

per

form

ance

for t

hose

sel

ecte

d fo

r “su

ppor

t ser

vice

s.”

SJ:

Nee

d to

inco

rpor

ate

mor

e po

st-p

roje

ct

revi

ew.

6.m

20

06

Impl

emen

t as-

need

ed, r

otat

ing,

or

on-

call c

ontra

cts f

or d

esig

n an

d co

nstru

ctio

n m

anag

emen

t wor

k th

at a

llow

wor

k to

be

auth

oriz

ed

on a

task

ord

er b

asis

to e

xped

ite

the

deliv

ery

of s

mal

ler p

roje

cts.

P

I

Sust

aina

ble

Dev

elop

men

t7.

a.

2009

Iden

tify

the

env

iron

men

tal

bene

fits

of t

he p

roje

ct a

t th

e tim

e of

aw

ard

2010

TB

DTB

DTB

DTB

DTB

DP

I, TB

D20

10

Key

: LA

: Los

Ang

eles

; LB

: Lon

g B

each

; OK

: Oak

land

; SC

: Sac

ram

ento

(DG

S: D

epar

tmen

t of G

ener

al S

ervi

ces,

DT:

Dep

artm

ent o

f Tra

nspo

rtatio

n, D

U: D

epar

tmen

t of

Util

ities

), SD

: San

Die

go, S

F: S

an F

ranc

isco

, and

SJ:

San

Jose

: I

mpl

emen

ted

PI: P

artia

lly im

plem

ente

d N

I: N

o pl

ans t

o im

plem

ent a

t thi

s tim

eTB

D: T

o be

det

erm

ined

yyyy

: Will

be

impl

emen

ted

in c

alen

dar y

ear “

yyyy

”*

See

Proc

ess Q

uest

ionn

aire

in A

ppen

dix

C o

f 200

2 R

epor

t; ye

ar n

oted

indi

cate

s thi

s BM

P w

as a

dded

late

r.

chapter Online DiscussionForum5

Page 69

One of the benefits most appreciated by the Project Team is the ability to share issues or concerns in a web based forum and receive input from their fellow team members. During the year, a total of 14 topics were discussed. From this set of discussions, the following 9 topics are presented as an example of the types of informational exchanges that took place within the Update 2009 online discussion forum.

Infrastructure and Fixed Asset • Capitalization Policies

Permeable and • Pervious Pavements

Separate Section for Estimating • and Scheduling

Resource Level Scheduling•

Qualification Based • Consultant Selection (QBCS) Policy/Procedure

Materials Testing • Laboratory Services

Project Labor Agreement•

Covered Pedestrian Walkways•

Job Order Contracting•

A. INFRASTRUCTURE AND FIXED ASSET CAPITALIzATION POLICIES

The City of San Diego was seeking any formal policies pertaining to asset capitalization for infrastructure projects. So they asked the group for any relevant information on infrastructure and fixed asset capitalization policies, formal, informal or administrative. In addition, they wanted to know whether infrastructure assets were categorized into classes and if useful life was assigned to the various categories.

The City of Long Beach responded that they follow the provisions of the Governmental Financial Standards Board Statement (GASB) #34. Long Beach also provided the various classifications along with the useful life of newly installed items.

The City of San Jose completed a report in 2008 on their deferred maintenance and infrastructure backlog. For that report, they categorized their infrastructure assets into 13 categories. While each program is different and responsible for their own condition evaluation and asset management, they all try and use similar asset management programs wherever possible. GASB #34 requires the Finance Department to include the valuation of the City’s infrastructure in the Comprehensive Annual Financial Report (CAFR) which includes date of construction, costs, and useful life cycles to come up with a depreciated value.


The City of Los Angeles provided a copy of their Capitalization policy. Their programs either use the depreciated method or the modified approach. The Wastewater system uses four different category codes to help classify the assets. They are as follows:

Location1.

Cost Center2.

Asset Category3.

Asset Description4.

The Capitalization Policy provides useful life of newly constructed infrastructure along with a listing of various categories.

B. PERMEABLE AND PERVIOUS PAVEMENTS

The City of San Francisco is using pervious pavement in the parking strip of one street of which the contract was just awarded and is in the process of reviewing draft guidelines for pervious pavement for developers and staff.

The City of San Francisco, Department of Public Works, Bureau of Engineering inquired about other cities experience with the use of Permeable/pervious Pavements similar to their inquiry in 2004. Specifically, they asked the following three questions:

Has your jurisdiction imple-1. mented any design standards for the use of permeable/ pervious pavement?

If you are allowing the use of 2. permeable/pervious pavement, do you have any technical speci-fications that you can share?

Has your jurisdiction construct-3. ed roadway, sidewalk, parking strips, parking lots, etc…using permeable/pervious pavement? How is it holding up to use and how is it working with regards to reducing storm water runoff?

The City of San Diego has permitted two private projects about 3 years ago that tried porous paving, both of which ended in failure. These projects were not well thought out and didn’t use any previous design criteria. Currently the City allows site-specific designs on a case-by-case basis that are reviewed and approved through the review process. The City raised many good questions that should be considered when reviewing and approving projects of this nature. A Draft Technical Guidelines was provided for Geotechnical reports for infiltration devices to provide a guideline for the geotechnical consultant to evaluate feasibility of such systems on the permit side.

Chapter 5 Online Discussion Forum

The City of San Jose has used pervious materials in limited locations, such as porous concrete in a library courtyard and pavers in landscaped areas. This year, the City plans to evaluate the use of pervious concrete and asphalt for trail paving as well as permeable pavers in park strips between sidewalks and curbs. They noted that the Greenbook (copy provided with City’s response) recently added a pervious concrete spec that could be helpful in developing a City specification.

The City of Long Beach responded that while no projects of this nature had been completed to date, they were considering the use of permeable/pervious pavements on several projects next year. In addition, they were currently developing technical specifications.

The City of Los Angeles provided a copy of a City Council motion and a Bureau of Street Services report on this topic. Efforts thus far have been limited and mainly for evaluating performance. The City added that their focus has been geared more toward green street elements to direct runoff into planter areas for infiltration. In all cases, no permeable pavement has been installed in a roadway.

C. SEPARATE SECTION FOR ESTIMATING AND SCHEDULING

With estimating and scheduling services being provided by consultants and having separate divisions for each service, the City of San Francisco, Bureau of Construction Management was evaluating creating just one division to provide both services.. The City initiated this topic by asking the following series of questions:

Does your agency have a separate section for…

Estimating1.

Scheduling2.

Estimating and Scheduling3.

None of the Above4.

If you do have section(s) for estimating and/or scheduling, are the following done?

Engineer’s estimate1.

Project schedule2.

Change order estimating3.

Change order negotiations4.

Contractor schedule review 5. and approval


Nearly every City responded that they do not have a separate section for estimating and scheduling. Each City described their process. The City of Los Angeles stated that project scheduling and cost estimating is the responsibility of the Project Manager, while the City of Oakland stated it was the responsibility of the Project Engineer for in-house projects. The City of Sacramento DGS’s response was similar to the response of Los Angeles, however, they also use design consultants in addition to the Project Managers for preliminary estimating of scheduling activities. They added that change orders are estimated by the contractor and checked and negotiated by the Construction Manager. The City of Long Beach stated that in-house resources are used on projects designed in-house while consultants are responsible for estimating and scheduling efforts on projects that they design: however, they are managed by in-house Project Managers.

The City of San Diego stated it was the responsibility of the designer/project manager to prepare and maintain the cost estimate and schedule during phases of design. Their project implementation/technical services division helps the engineers with their estimates with historical bid data. The City utilizes Primavera supporting group for scheduling and generating the needed reports for the entire CIP program.

Generally estimates/schedules, for the City of San Jose, are performed by Project Managers using the Capital Project Management System (CPMS). Microsoft Project and Primavera may be

utilized in addition to CPMS on larger City-managed projects. When consultants are engaged for the design of a project, these services may be provided in whole or in part by those consultants. On very large projects, such as their recent airport project, where construction management consultants are engaged , those entities/consultants are using cost and schedule engineers to specifically track such matters and provide such information to the City Project Manager.

The City of San Francisco will not be creating a separate section at this time, but has a cost database and is training its project engineers in estimating using the database. Project Engineers are responsible for generating project estimates and schedules. Resident Engineers are responsible for change order estimating and contractor schedule review.

D. RESOURCE LEVEL SCHEDULINGThe City of San Diego was looking for a methodology to better plan and forecast their labor resources, given the peaks and valleys in the demand for said resources. With a potential to implement the resource level scheduling methodology, they asked the question below. They noted that they were using $100/hr as a weighted average cost.


Which labor resources meth-1. odology is your organization implementing? Are you using “Resource Level Scheduling” or “Composite Person Sched-uling” (weighted average cost of the classifications that worked on a CIP project) or some other methodology

If “Resource Level Scheduling” 2. is utilized by your organiza-tion; how is it working for you? Do you have a full time staff assigned to maintain it? Have you performed a cost benefit analysis of the methodology before implementation?

The City of Sacramento, DGS uses composite person They provided a spreadsheet that listed the blended hourly rates of divisions of General Services. They stated that this blended rate methodology works better with merged groups because it allows the in-house trades to remain competitive with outside construction and maintenance costs.

The City of San Jose replied that they use a “Cost Estimating/Resource Module” (CERM) which is built into their Capital Project Management System (CPMS), an in-house web-based database application. For each Capital project, the CERM is used to develop an estimate for the soft and hard costs. A Project Manager enters anticipated resources that will be used over the life of a project. Each resource (classification) has a fully loaded costs associated with it. Some resources are a composite rate such as Materials Testing resources. The CERM is used during the annual Capital Budget development cycle to develop a staffing plan, since all projects entered are rolled up to a composite report that will demonstrate

the staffing needs for the upcoming fiscal years. They noted some shortcomings with multiyear projects and a lack of schedule which would better articulate peaks and valleys of resource demands.

The City of Long Beach has always maintained a nominal workforce and use consultants to cover the peak demands in any given year. Projects are first assigned to in-house staff based on availability with all remaining work issued to on-call consultants.

The City of Los Angeles maintains Master Schedules for all their projects which show a three year period and are broken down into Programs. Their Work Program Resource Requirements is tied into the master schedules and is based on their Uniform Project Reporting System (UPRS). When first resourcing a project, they start with templates based on construction cost. As more detailed information is known, actual staff resources replace the template amounts.

The City of Oakland stated they were in the process of developing Resource Level Scheduling. They are currently writing a formula to determine the number of full time employees needed on each project per month. The formula is based on the schedule and staff costs allocated to the PM and CM for each project in their CIP database.

The City of San Francisco, Department of Public Works provided a sample histogram that they use. This monthly histogram is created in Excel and is updated by the Section Managers on a monthly basis. The work hours for each project for the duration of the project are entered into the spreadsheet. The Bureau’s histogram is created by combining all the sections’ data.


E. QUALIFICATION BASED CONSUL-TAnTSElECTIon(QBCS)PolICY/PROCEDURE

The City of San Jose was in the process of revisiting a council-approved Qualifications Based Consultant Selection (QBCS) Policy/Procedure that applied strictly to architectural/engineering services. This process prompted them to ask the project team whether they had an architectural/engineering consultant selection policy and/or procedure. There were also interested in obtaining information if a city has a general policy/procedure for professional services consultants if it did not have a policy that applied strictly to architectural/engineering consultants.

The City of Long Beach responded that it followed SB419, also known as the Mini Brooks Act, for consultant selection. The Mini Brooks Act outlines a qualifications based selection procedure. They referenced CELSOC and APWA as having great publications on this topic. They provided a 1991 legislative legal review which states that Charter cities are required to comply with the Mini Brooks Act.

The City of San Francisco, Department of Public Works provided excerpts from their departmental procedures manual which outline the procedures for request for qualification/proposals, consultant selection process and administering consultant contracts.

The City of San Diego provided a document from their Administrative Regulation 25.60 regarding consultant selection. This document lists all categories of services that are subject to Administrative Regulation 25.60.

The City of Los Angeles stated that their procedure for professional services can be found in their Project Delivery Manual. The document is on their webpage and can be found at http://eng.lacity.org/index.cfm. This site also includes a list of Pre-Qualified On-Call consultants.

The City of Sacramento, Department of Transportation provided sections 8.1 through 8.13 of their Project Delivery Manual which includes guidelines relating to professional services selection and management. The manual includes checklists and forms that are used throughout the process.

F. MATERIALS TESTING LABORATORY SERVICES

San Jose operates its own accredited materials testing laboratory which provides critical QA/QC services to both its capital improvement program and private development review program. From a budget planning analysis standpoint, San Jose was interested in determining whether the other participating agencies had an in-house materials testing laboratory to serve their capital improvement program and what scope of services were provided. Furthermore, San Jose was seeking to understand whether such agency labs provided testing for public improvements constructed by private developers in the public right-of-way, or if private developers were given the option of using an acceptable private laboratory. A total of five (5) questions were asked and responses were received from all six agencies. The detailed responses can be found in Table 5-1 below.


Ta

ble

5-1

City

of S

an J

ose

Surv

eyQuestions

1. D

oes

your

age

ncy

have

an

in-h

ouse

mat

eria

ls

test

ing

labo

rato

ry?

If so

, w

hat g

ener

al s

ervi

ces

are

prov

ided

?

2. If

not

, who

per

form

s m

ater

ials

test

ing

labo

rato

ry

serv

ices

for y

our C

apita

l Im

prov

emen

t pro

ject

s?

3. D

oes

your

City

allo

w

deve

lope

rs th

e op

tions

of

hiri

ng a

priv

ate

lab

vs.

usin

g yo

ur m

ater

ials

test

ing

lab

(if y

ou h

ave

one)

to

perf

orm

test

ing

on p

rivat

e de

velo

pmen

t pro

ject

s th

at

cons

truc

t im

prov

emen

ts (i

.e.

pave

men

t/con

cret

e w

ork)

in

the

publ

ic ri

ght-o

f-way

?

4. If

they

hav

e th

e op

tion,

do

es y

our C

ity e

stab

lish

an a

ppro

ved

list o

f pr

ivat

e m

ater

ial t

estin

g la

bs o

r lea

ve it

up

to th

e de

velo

per t

o hi

re a

nyon

e?

5. M

ay w

e co

ntac

t som

eone

in

you

r org

aniz

atio

n fo

r m

ore

info

rmat

ion?

If s

o,

plea

se p

rovi

de c

onta

ct in

fo.

City

of L

ong

Bea

chN

o, it

was

clo

sed

12 y

ears

ago

.

Use

priv

ate

labs

that

ar

e un

der a

s-ne

eded

m

ultiy

ear c

ontra

cts.

All

test

ing

done

in th

e pu

blic

rig

ht-o

f-way

is h

andl

ed b

y C

ity

cons

truct

ion

insp

ecto

rs u

sing

as

-nee

ded

cont

ract

s. T

his

incl

udes

CIP

rela

ted

cont

ract

s as

wel

l as

wor

k be

ing

done

by

dev

elop

ers

on u

tiliti

es.

Gill

is M

onro

eC

onst

ruct

ion

Ser

vice

s O

ffice

r(5

62) 5

70-6

537

City

of L

os

Ang

eles

Yes.

The

y te

st s

oil,

asph

alt a

nd P

ortla

nd c

emen

t con

cret

e,

grou

ndw

ater

, sew

age,

agg

rega

te, s

peci

al m

ater

ials

test

ing,

so

il an

d gr

ound

wat

er c

onta

min

atio

n, a

nd s

oil s

ampl

es. T

he

mat

eria

ls la

b ha

s lim

ited

capa

city

. The

mat

eria

ls te

stin

g la

bs w

ould

be

part

of th

e pr

e-qu

alifi

ed o

n-ca

ll G

eote

chni

cal

cons

ulta

nt li

st m

anag

ed b

y th

e B

urea

u’s

Geo

tech

nica

l E

ngin

eerin

g G

roup

giv

ing

the

abili

ty to

aug

men

t City

sta

ff.

Priv

ate

deve

lope

rs u

sual

ly

have

thei

r ow

n m

ater

ials

te

stin

g la

bs to

per

form

thei

r qu

ality

con

trol t

estin

g fo

r B

-per

mit

wor

k in

the

City

rig

ht-o

f-way

. How

ever

, the

C

ity w

ill u

se C

ity te

stin

g la

b to

pe

rform

ver

ifica

tion

test

ing

on

soil,

asp

halt,

con

cret

e, e

tc.

Dep

artm

ent o

f Bui

ldin

g an

d S

afet

y, fo

r wor

k ou

tsid

e of

th

e pu

blic

righ

t-of-w

ay, h

as

a lis

t of a

ppro

ved

mat

eria

ls

test

ing

labs

to d

o w

ork

on

priv

ate

prop

erty

with

in th

e C

ity. C

ity d

oesn

’t re

quire

an

appr

oved

list

sin

ce th

e C

ity

perfo

rms

verifi

catio

n te

stin

g w

ithin

the

publ

ic ri

ght-o

f-way

.

Con

tact

Mic

hael

Bro

wn

who

’ll d

irect

you

to th

e ap

prop

riate

per

son.

City

of S

an

Die

go

Yes,

Tre

nch

com

pact

ion,

su

b-gr

ade,

asp

halt

conc

rete

, co

ncre

te s

ampl

ing,

ear

thw

ork,

pl

ant i

nspe

ctio

n fo

r pip

e an

d as

phal

t, sl

urry

and

m

isc.

pro

duct

sam

plin

g

N/A

No,

this

opt

ion

is ty

pica

lly

only

con

side

red

on a

cas

e-by

-cas

e ba

sis

as p

art o

f a

disp

ute

reso

lutio

n pr

oces

s

N/A

Jose

Nav

arro

(858

) 627

-327

6jn

avar

ro@

sand

iego

.gov

City

of

Oak

land

Yes,

com

pact

ion,

asp

halt

conc

rete

, gra

datio

n on

all

City

eng

inee

ring

proj

ects

. H

owev

er, o

utsi

de la

b hi

red

to

perfo

rm s

peci

al in

spec

tions

an

d m

ater

ials

test

ing

on

City

bui

ldin

g pr

ojec

ts.

N/A

Insp

ectio

ns o

n pr

ivat

e pr

ojec

ts a

re h

andl

ed th

roug

h th

e B

uild

ing

Dep

artm

ent.

Doe

s no

t hav

e a

certi

fied

list.

Jose

ph T

anio

sM

ater

ials

test

ing

lab

Sup

ervi

sor

(510

) 615

-553

7


Questions

1. D

oes

your

age

ncy

have

an

in-h

ouse

mat

eria

ls

test

ing

labo

rato

ry?

If so

, w

hat g

ener

al s

ervi

ces

are

prov

ided

?

2. If

not

, who

per

form

s m

ater

ials

test

ing

labo

rato

ry

serv

ices

for y

our C

apita

l Im

prov

emen

t pro

ject

s?

3. D

oes

your

City

allo

w

deve

lope

rs th

e op

tions

of

hiri

ng a

priv

ate

lab

vs.

usin

g yo

ur m

ater

ials

test

ing

lab

(if y

ou h

ave

one)

to

perf

orm

test

ing

on p

rivat

e de

velo

pmen

t pro

ject

s th

at

cons

truc

t im

prov

emen

ts (i

.e.

pave

men

t/con

cret

e w

ork)

in

the

publ

ic ri

ght-o

f-way

?

4. If

they

hav

e th

e op

tion,

do

es y

our C

ity e

stab

lish

an a

ppro

ved

list o

f pr

ivat

e m

ater

ial t

estin

g la

bs o

r lea

ve it

up

to th

e de

velo

per t

o hi

re a

nyon

e?

5. M

ay w

e co

ntac

t som

eone

in

you

r org

aniz

atio

n fo

r m

ore

info

rmat

ion?

If s

o,

plea

se p

rovi

de c

onta

ct in

fo.

City

of

Sac

ram

ento

- D

OT

No

Priv

ate

cons

ulta

nt m

ater

ials

te

stin

g fir

ms

prov

idin

g ou

r m

ater

ials

test

ing

for a

ll w

ork

with

in th

e rig

ht-o

f-way

. C

onsu

ltant

list

is e

stab

lishe

d th

roug

h a

RFQ

pro

cess

.

Do

not a

llow

dev

elop

ers

to

hire

thei

r ow

n pr

ivat

e la

b to

pe

rform

test

ing.

Dev

elop

ers

pay

a fe

e w

hich

the

City

use

s to

en

gage

one

of t

heir

cont

ract

ed

mat

eria

ls te

stin

g fir

ms.

See

ans

wer

to q

uest

ion

#3.

Jon

Bla

nkS

uper

visi

ng E

ngin

eer

(916

) 808

-791

4

City

of S

an

Fran

cisc

o

Yes,

whi

ch fu

nctio

ns u

nder

th

e B

urea

u of

Con

stru

ctio

n M

anag

emen

t, D

epar

tmen

t of

Pub

lic W

orks

. Mat

eria

l Tes

ting

Lab

(MTL

) pro

vide

s qu

ality

co

ntro

l to

ensu

re c

onst

ruct

ion

proj

ects

are

bui

lt in

com

plia

nce

with

con

tract

pla

ns a

nd

spec

ifica

tions

. Ser

vice

s in

clud

e de

sign

con

sulta

tion,

pla

n an

d sp

ec re

view

, qua

lity

assu

ranc

e pl

ans,

con

cret

e/so

il/ag

greg

ates

sa

mpl

ing

and

test

ing,

and

m

ason

ry/a

spha

lt co

ncre

te/

wel

ding

/rein

forc

ing

stee

l tes

ting,

co

re-d

rillin

g of

con

cret

e an

d so

il sa

mpl

es d

urin

g th

e de

sign

ph

ase

for e

xplo

ratio

n pu

rpos

es.

For t

estin

g se

rvic

es n

ot

prov

ided

, hav

e as

-nee

ded

cont

ract

s w

ith p

rivat

e la

bs.

MTL

mai

nly

serv

ices

pub

lic

agen

cies

on

City

pro

ject

s.

MTL

usu

ally

doe

s no

t per

form

te

stin

g on

priv

ate

proj

ects

w

ithin

pub

lic ri

ght-o

f-way

.

Mai

ntai

ns a

n ap

prov

ed li

st

of p

rivat

e m

ater

ial t

estin

g la

bs fo

r diff

eren

t tes

ts.

Oph

elia

Lau

(415

) 748

-410

5(4

15) 5

54-8

351

Tabl

e 5-

1C

ity o

f San

Jos

e Su

rvey

(con

t’d)


G. PR

OJEC

T LAB

OR AG

REEM

ENT

In re

ceiv

ing

a re

ques

t fro

m re

pres

enta

tives

of t

he B

uild

ing

Trad

es to

est

ablis

h a

Proj

ect L

abor

Agr

eem

ent (

PLA)

for t

he fe

dera

l S

timul

us p

roje

cts

and

City

CIP

pro

ject

s, th

e C

ity o

f Oak

land

requ

este

d re

spon

ses

for o

ther

Age

ncie

s on

four

(4) q

uest

ions

. Th

ese

ques

tions

and

Age

ncy’

s re

spon

ses

are

liste

d in

Tab

le 5

-2 b

elow

.

Tabl

e 5-

2C

ity o

f Oak

land

Sur

vey

Questions

1. D

oes

your

City

cur

rent

ly

have

a P

roje

ct L

abor

A

gree

men

t (PL

A) f

or c

apita

l im

prov

emen

t pro

ject

s?

2. Is

you

r City

con

tem

plat

ing

a PL

A fo

r pro

ject

s in

th

e ne

ar fu

ture

?

3. Is

you

r City

co

ntem

plat

ing

a PL

A sp

ecifi

cally

for

stim

ulus

pro

ject

s?

4. D

o yo

u se

e be

nefit

s or

hav

e co

ncer

ns a

bout

a

PLA

< es

peci

ally

rela

tive

to s

timul

us p

roje

cts?

City

of L

ong

Bea

chN

oH

ave

been

in d

iscu

ssio

n fo

r ove

r tw

o ye

ars

but h

ave

not b

een

able

to w

ork

out a

ll th

e de

tails

.

Adv

ised

the

othe

r Citi

es th

at

prio

r Pre

side

nt p

rohi

bite

d P

LAs

on fe

dera

lly fu

nded

pr

ojec

ts w

hich

wou

ld

appl

y to

AR

RA

proj

ects

un

less

it’s

cha

nged

.

Una

ble

to p

rovi

de d

etai

ls s

ince

ne

gotia

tions

are

ong

oing

.

City

of L

os A

ngel

es

Yes,

vis

it ht

tp://

bca.

laci

ty.o

rg/

inde

x.cf

m?n

xt_b

ody=

loca

l_hi

ring.

cfm

for a

list

of p

roje

cts

and

the

actu

al a

gree

men

ts.

Yes,

cur

rent

ly th

ere

is n

o of

ficia

l po

licy

on w

hen

to u

se P

LAs.

Th

e B

oard

of P

ublic

Wor

ks,

thro

ugh

our B

urea

u of

Con

tract

A

dmin

istra

tion,

is w

orki

ng

to d

evel

op a

Dep

artm

ent o

f P

ublic

Wor

ks w

ide

PLA

.

No

Exp

ress

ed c

once

rn u

sing

a P

LA d

ue to

the

man

y sp

ecifi

c re

quire

men

ts o

n A

RR

A pr

ojec

ts. W

ith

non-

AR

RA

proj

ects

, pot

entia

l ben

efits

incl

ude

orde

rly s

ettle

men

t of l

abor

dis

pute

s an

d gr

ieva

nces

w

ithou

t stri

kes,

wor

k st

oppa

ges

or lo

ckou

ts.

Pot

entia

l dow

nsid

e is

it m

ay re

duce

bid

der p

ool.

City

of S

an D

iego

No

Exp

ress

ed c

once

rn a

bout

lim

iting

th

e co

ntra

ctor

bid

der p

ool.

City

of S

acra

men

to-

DO

TN

oN

oN

oN

o co

ncer

n as

City

pol

icy

is to

pay

pre

vaili

ng w

age.


Questions

1. D

oes

your

City

cur

rent

ly

have

a P

roje

ct L

abor

A

gree

men

t (PL

A) f

or c

apita

l im

prov

emen

t pro

ject

s?

2. Is

you

r City

con

tem

plat

ing

a PL

A fo

r pro

ject

s in

th

e ne

ar fu

ture

?

3. Is

you

r City

co

ntem

plat

ing

a PL

A sp

ecifi

cally

for

stim

ulus

pro

ject

s?

4. D

o yo

u se

e be

nefit

s or

hav

e co

ncer

ns a

bout

a

PLA

< es

peci

ally

rela

tive

to s

timul

us p

roje

cts?

City

of S

acra

men

to- D

UN

oN

one

that

they

are

aw

are

of.

Non

e th

at th

ey a

re a

war

e of

.E

xper

ienc

e w

ith li

miti

ng th

e bi

ddin

g po

ol b

ut fe

lt it

was

a m

inor

issu

e.

City

of S

an F

ranc

isco

Yes,

the

SFO

Mas

ter P

lan

had

an A

irpor

t Mas

ter P

lan

– P

roje

ct

Sta

biliz

atio

n A

gree

men

t (P

SA

)

Trie

d to

est

ablis

h an

othe

r P

SA

but w

as u

nsuc

cess

ful

due

to U

nion

inte

rnal

issu

es.

No

Onl

y us

ed o

n pr

ojec

ts o

ver $

250

mill

ion.

City

of S

an J

ose

Yes,

for t

heir

Airp

ort M

aste

r P

lan

proj

ects

. Als

o ha

d a

PLA

on

the

3-ye

ar o

ld C

ity

Hal

l. D

ue to

rela

tions

hip

of

Cou

ncilm

embe

r, a

kind

of

mor

ator

ium

exi

sts

on P

LA’s

.

Not

at t

his

time.

No

Ben

efit i

n te

rms

of a

void

ance

of l

abor

act

ions

affe

ctin

g co

nstru

ctio

n pr

ojec

ts. S

ome

cont

ract

ors

will

not

bid

P

LA p

roje

cts

whi

ch li

mits

the

com

petit

ive

pool

.

Tabl

e 5-

2C

ity o

f Oak

land

Sur

vey

(con

t’d)


H. CO

VERE

D PED

ESTR

IAN W

ALKW

AYS

The

City

of S

an D

iego

initi

ated

a s

ix (6

) que

stio

n su

rvey

on

the

subj

ect o

f per

mitt

ing

and

insp

ectio

n of

cov

ered

ped

estri

an

wal

kway

s in

the

publ

ic ri

ght-o

f-way

. Res

pons

es w

ere

rece

ived

by

5 ou

t of t

he 6

age

ncie

s. P

leas

e se

e Ta

ble

5-3

belo

w fo

r al

l six

que

stio

ns a

nd th

e A

genc

y re

spon

ses.

Tabl

e 5-

3C

ity o

f San

Die

go S

urve

y

Questions

1. H

ow d

oes

your

ag

ency

per

mit

cove

red

pede

stria

n w

alkw

ays

plac

ed in

the

publ

ic

right

-of-w

ay b

y pr

ivat

e pa

rtie

s du

ring

cons

truc

tion?

Is it

vi

a a

right

-of-w

ay

perm

it, a

traf

fic c

ontr

ol

perm

it, o

r som

e ot

her

type

of p

erm

it?

2. W

hat l

evel

of r

evie

w

does

you

r age

ncy

prov

ide

to a

pla

n sh

owin

g co

vere

d pe

dest

rian

wal

kway

s?

3. D

oes

your

ag

ency

requ

ire

insp

ectio

n of

cov

ered

pe

dest

rian

wal

kway

s w

hen

they

are

firs

t in

stal

led?

4. D

oes

your

age

ncy

requ

ire in

sura

nce

or p

ostin

g of

a b

ond

rela

ted

to c

over

ed

pede

stria

n w

alkw

ays?

5. In

gen

eral

, doe

s yo

ur

agen

cy in

spec

t priv

ate

traf

fic c

ontr

ol s

etup

s in

th

e pu

blic

righ

t-of-w

ay

on m

ajor

art

eria

ls w

hen

they

are

firs

t ins

talle

d?

6. H

ow d

oes

your

age

ncy

hand

le it

s ow

n w

ork

in

the

publ

ic ri

ght-o

f-way

in

term

s of

des

ign,

revi

ew a

nd

insp

ectio

n of

traf

fic c

ontr

ol

setu

ps fo

r con

stru

ctio

n?

Is it

han

dled

diff

eren

tly fo

r co

nstr

uctio

n ac

tiviti

es th

an

mai

nten

ance

act

iviti

es?

City

of L

ong

Bea

ch

Bui

ldin

g pe

rmits

for

stru

ctur

e an

d S

treet

O

ccup

ancy

Per

mit

(SO

P) f

or p

laci

ng

stru

ctur

e in

pub

lic

right

-of-w

ay. S

OP

is

obta

ined

thro

ugh

Pub

lic

Wor

ks D

epar

tmen

t. B

uild

ing

Dep

artm

ent

Insp

ecto

rs re

view

co

mpl

eted

stru

ctur

e fo

r com

plia

nce.

Pub

lic

Wor

ks In

spec

tors

revi

ew

wal

kway

to in

sure

co

mpl

ianc

e w

ith S

OP.

Stru

ctur

al re

view

s of

pla

ns a

re m

ade

at th

e tim

e of

per

mit

appl

icat

ion

by B

uild

ing

Dep

artm

ent.

Yes

Insu

ranc

e on

lyYe

s

All

traffi

c co

ntro

l pla

ns a

re

prep

ared

in-h

ouse

by

the

traffi

c en

gine

erin

g st

aff.

Traf

fic c

ontro

l w

ork

done

by

City

forc

es is

un

der t

he p

revu

e of

a tr

aine

d st

reet

mai

nten

ance

sup

ervi

sor

who

wor

ks d

irect

ly w

ith th

e tra

ffic

engi

neer

ing

staf

f.

City

of L

os

Ang

eles

Thro

ugh

a B

uild

ing

Mat

eria

ls p

erm

it w

hich

is

equ

ival

ent t

o a

right

-of-w

ay p

erm

it.

No

plan

revi

ew is

pe

rform

ed. C

ontra

ctor

is

pro

vide

d w

ith a

st

anda

rd p

lan

for

cove

red

wal

kway

s.

Yes

No

The

DO

T re

view

s a

nd

a

pp

rove

s tr

aff

ic

con

tro

l se

tups

.

The

sam

e re

quire

men

ts

and

stan

dard

s ap

ply

to c

ity

wor

k in

the

right

-of-w

ay

as to

priv

ate

cont

ract

ors

exce

pt fo

r per

mit

fees

.


Questions

1. H

ow d

oes

your

ag

ency

per

mit

cove

red

pede

stria

n w

alkw

ays

plac

ed in

the

publ

ic

right

-of-w

ay b

y pr

ivat

e pa

rtie

s du

ring

cons

truc

tion?

Is it

vi

a a

right

-of-w

ay

perm

it, a

traf

fic c

ontr

ol

perm

it, o

r som

e ot

her

type

of p

erm

it?

2. W

hat l

evel

of r

evie

w

does

you

r age

ncy

prov

ide

to a

pla

n sh

owin

g co

vere

d pe

dest

rian

wal

kway

s?

3. D

oes

your

ag

ency

requ

ire

insp

ectio

n of

cov

ered

pe

dest

rian

wal

kway

s w

hen

they

are

firs

t in

stal

led?

4. D

oes

your

age

ncy

requ

ire in

sura

nce

or p

ostin

g of

a b

ond

rela

ted

to c

over

ed

pede

stria

n w

alkw

ays?

5. In

gen

eral

, doe

s yo

ur

agen

cy in

spec

t priv

ate

traf

fic c

ontr

ol s

etup

s in

th

e pu

blic

righ

t-of-w

ay

on m

ajor

art

eria

ls w

hen

they

are

firs

t ins

talle

d?

6. H

ow d

oes

your

age

ncy

hand

le it

s ow

n w

ork

in

the

publ

ic ri

ght-o

f-way

in

term

s of

des

ign,

revi

ew a

nd

insp

ectio

n of

traf

fic c

ontr

ol

setu

ps fo

r con

stru

ctio

n?

Is it

han

dled

diff

eren

tly fo

r co

nstr

uctio

n ac

tiviti

es th

an

mai

nten

ance

act

iviti

es?

City

of

Oak

land

Thro

ugh

obst

ruct

ion

perm

it ac

com

pani

ed

with

traf

fic c

ontro

l pla

ns

Issu

ed o

ver t

he c

ount

er

with

min

imal

revi

ew.

Pro

pose

d pl

an m

ust

mee

t AD

A pr

ovis

ions

.

Yes

No

Yes

App

rove

d tra

ffic

cont

rol p

lans

ar

e re

quire

d fo

r City

pro

ject

s.

Con

tract

ors

follo

w p

roje

ct

spec

ifica

tions

and

pro

vide

tra

ffic

cont

rol p

lans

for r

evie

w

and

appr

oval

. Mai

nten

ance

pr

ojec

ts m

ust c

ompl

y w

ith

MU

TCD

han

dboo

k.

City

of

Sac

ram

ento

- D

OT

Issu

e bu

ildin

g pe

rmit

to in

stal

l ped

estri

an

wal

kway

s th

at a

re

atta

ched

to b

uild

ings

ov

er ri

ght-o

f-way

. If

not a

ttach

ed b

ut in

the

right

-of-w

ay, t

hey

issu

e a

revo

cabl

e pe

rmit.

Full

deta

iled

plan

s m

ust b

e su

bmitt

ed

for e

ither

per

mit.

Yes,

insp

ectio

n of

th

e im

prov

emen

t is

requ

ired

for

eith

er p

erm

it.

Yes

Yes,

the

City

doe

s in

spec

t all

traffi

c co

ntro

l set

ups

in th

e pu

blic

righ

t-of-w

ay.

Bef

ore

inst

allin

g, th

e co

ntra

ctor

mus

t sub

mit

a tra

ffic

and

pede

stria

n tra

ffic

cont

rol p

lan

for

revi

ew a

nd a

ppro

val.

City

of S

an

Jose

Thro

ugh

a re

voca

ble

encr

oach

men

t per

mit

proc

ess

that

may

incl

ude

a tra

ffic

cont

rol p

lan

if th

e pr

opos

ed c

over

ed

wal

kway

loca

tion

impa

cts

the

traffi

c la

nes.

Enc

roac

hmen

t per

mits

ar

e re

view

ed b

y en

try-

leve

l Civ

il E

ngin

eers

or

Eng

inee

ring

Tech

nici

ans

and

appr

oved

by

Ass

ocia

te E

ngin

eers

. If

a tra

ffic

cont

rol p

lan

is re

quire

d, th

e pl

an is

co

ordi

nate

d w

ith th

e P

roje

ct In

spec

tor (

PI).

Yes

Yes,

insu

ranc

e an

d su

rety

are

requ

ired

with

all

encr

oach

men

t pe

rmits

.

Yes

For c

apita

l pro

ject

s, tr

affic

co

ntro

l pla

ns a

re re

quire

d fro

m th

e co

ntra

ctor

prio

r to

con

stru

ctio

n. P

lans

are

su

bmitt

ed to

the

Pro

ject

E

ngin

eer f

or re

view

and

ap

prov

al a

nd c

oord

inat

ed

with

the

PI.

Pro

cess

sam

e fo

r mai

nten

ance

pro

ject

s ex

cept

chi

p se

al w

hich

are

do

ne in

-hou

se b

y D

OT.

Tabl

e 5-

3C

ity o

f San

Die

go S

urve

y (c

ont’d

)


I. JOB ORDER CONTRACTINGDue in part to the oncoming stimulus package, the City and County of San Francisco is in the process of streamlining the contract ing prov is ions of i ts administrative code, In addition, they had been planning to modify their Job Order Contracting (JOC) program for several years, so Bureau of Architecture sought input from the other agencies in this study. Detailed responses from participating agencies are summarized in Table 5-4.

Table 5-4City of San Francisco Survey

Que

stio

ns 1. Does your contracting authority require the JOC contractor to list subcontractors at time of bid or at time of task orders (job orders)?

2. If subcontractor listing is at time of task orders, what are the procedures for the

contractor’s solicitation of subcontractor bids to avoid/discourage “bid shopping”?

City of Long Beach

They must list them all at the time of task (job) orders.

There are no special JOC rules that apply to subcontractors other than those specified in the general conditions by the City of Long Beach for all contractors.

City of Los Angeles

Have a few different types of contracts that are similar. Some contracts are part of a pre-qualified list of prime contractors using an RFQ process awarded based on an evaluated value of markups or a low bid of assumed quantities. All cases require a good faith effort outreach. Prime contractor is allowed to list as many subcontractors as they wish for each area of subcontracting work.

There is no room for “bid shopping” since the prime and subcontractors all list their dollar amounts when submitting a bid for a task order.

City of Sacramento

- DOT

Yes, they are required to submit a list of subcontractors at the time of bid.

There are no procedures to avoid/discourage “bid shopping.”

City of San Diego

Requires listing of subs prior to issuance of each task order. Public contract code applies to each task order as if they were a regular contract.

Provided a portion of their contract documents related to this topic.

City of San Jose

Require JOC contactor to list subcontractors at the time they submit their initial cost proposal which is shortly before the time of the issuance of a task (job) order.

There are no procedures to avoid/discourage “bid shopping.”

chapter Conclusions6

Page 83

A. PERFORMANCE BENCHMARKINGThis year’s Study focused on refining the modeling methodology used to develop relationships between the different components that constitute project delivery costs and the TCC. Statistical studies to determine the best-fit curve for the projects in the database revealed that the linear trendline was the best-fit curve amongst the five types of curves (logarithmic, exponential, polynomial, power, and linear) selected for evaluation. In addition, the modeling methodology incorporated techniques to analyze project delivery costs over a range of TCCs. Improvements to the model also resulted in good R2 and p-values indicating good relationships between the project delivery components and the TCC.

In order to incorporate the agencies’ observations that on a percentage basis, projects with lower TCCs are more expensive to deliver than projects with higher TCCs, the Study Team conducted investigations with an objective to identify a subset of project size (in terms of TCC) that represented what was generally considered as the smaller projects. Regressions and statistical tests for the smaller projects revealed that the delivery costs for the smaller projects were higher than for the full range of projects. Therefore, in Update 2009, project data was analyzed in two ranges of TCC. The results of this analysis conformed to the agencies’ practical experiences.

Although the results of the performance analyses are based on historical data provided by the participating agencies, there are several factors that affect

project delivery and are not captured in the performance model. These external factors include personnel turnover in the agencies, competitive bids etc which impact project delivery. Since such factors are not captured in the performance model, the reader is cautioned that the improved results of the regression analyses only be used as a reference and not for prediction of future performance.

Due to the current economic conditions, agencies are receiving bids that are significantly lower than the engineer’s estimates. Therefore, it should be noted that project data collected over the next few Study cycles may exhibit higher project delivery costs as a percentage of the TCC as a result of the low construction bids due to the current economic crisis. It is recommended that the reader use best judgment in the context of the current economic crisis while using the Study results for planning and budgeting.

Increasing the size of the project database is a major challenge posed to the Study participants. This is primarily because of the 5-year rolling window criterion for project completion dates; even as new projects are added, old projects are excluded from analyses by the window of time. In addition, the agencies are also challenged to identify as many completed projects as possible that meet the rest of the Study criteria. The Project Team will identify and evaluate ways to address this issue as the Study continues in future phases.

Project delivery percentages (arithmetic averages) for the Update 2009 Study

Annual Report Update 2009 California Multi-Agency CIP Bench-Marking Study

varied between the following values for the full range and the smaller project subset of TCC respectively:

Municipal Projects: 36% - 39%

Parks Projects: 39% - 41%

Pipes Projects: 36% - 39%

Streets Projects: 46% - 49%

B. BEST MANAGEMENT PRACTICESThe agencies have continued to fully implement selected BMPs. Given the current state of the economy and due to staff reductions, furloughs, and the management’s increased involvement in resolving budgetary issues, progress on fully implementing BMPs has been impacted. The agencies have focused their efforts on tracking BMPs that have been implemented and which continue to provide efficiencies in project delivery processes for participating departments. As of Update 2009, the agencies have fully implemented about 72 percent of all BMPs. Many more have been partially implemented with the goal of complete implementation over the next two to three years.

In Update 2009, the Project Team added one new BMP under a new category called Sustainable Development to the BMP Implementation tracking list. This BMP was developed to address the growing need to incorporate environmental sustainability in engineering design and construction practices. The agencies felt that this new category should be added to Best Management Practices. BMPs in other areas will be discussed and developed during future Study phases.

As the BMPs are implemented the participating agencies should begin to realize project delivery efficiencies

including but not limited to reduction in delivery times, reduced change orders, and overall project cost reductions.

C. ONLINE DISCUSSION FORUMIn Update 2009, the Agencies transitioned from using emails to an online portal for collaboration on project delivery issues. There are several benefits of this transition one of which is the ability to archive all topics of discussion in a single location which is easily accessible. The use of the online portal also ensures that communication is not lost when a member leaves the Project Team.

The Online Discussion Forum continues to be an increasingly important feature for Study participants, with active exchanges occurring frequently and important issues addressed with changes to policy, approach, or BMP implementation. Participants will continue sharing information through the Online Discussion Forum and during the quarterly meetings, and presenting the more interesting results to the public through the Study reports. The continued sharing of challenges and solutions through the Online Discussion Forum remains a remarkable advantage to all participants.

D. PLANNING FOR UPDATE 2010Over the course of Update 2009, the Project Team identified a number of activities to consider including next year in Update 2010. These activities include:

Exploring the merits of capturing • alternative delivery methodolo-gies in the Study.

Continuing to focus on current • topic roundtable discussions.

Exploring the benefits of BMPs • and their impact on project delivery costs.

Chapter 6 Conclusions

E. ACKNOWLEDGEMENTSThe participation and contribution of the following individuals to the Study is gratefully acknowledged. This work would not have been possible without their contributions.

Study Team:

Mark Christoffels, Deputy Director/City EngineerCity of Long Beach, Department of Public Works333 W. Ocean Blvd., 9th FloorLong Beach, CA 90802(562) 570-6771 (562) 570-6012 (fax)[email protected]

Joseph Wojslaw, P.E., Consultant ManagerMWH618 Michillinda Avenue, Suite 200Arcadia, CA 91007(626) 568-6194 (626) 568-6101 (fax)[email protected]

Ganesh Krishnamurthy, ConsultantMWH618 Michillinda Avenue, Suite 200Arcadia, CA 91107 (626) 568-6170 (626) 568-6101 (fax)[email protected]

Robert Flory, ConsultantVanir Construction Management, Inc.1000 Broadway, Suite 475Oakland, CA. 94607Office: 510.663.1800Fax: 510.663.1881Mobile: [email protected]

Project Team:

Michael Conway, DirectorCity of Long Beach, Department of Public Works333 W. Ocean Blvd., 9th FloorLong Beach, CA 90802(562) 570-6522(562) 570-6012 (fax)[email protected]

Edward Villanueva, Capital Projects Coordinator City of Long Beach, Department of Public Works333 W. Ocean Blvd., 10th FloorLong Beach, CA 90802(562) 570-5793(562) 570-6012 (fax)[email protected]

J.R. “Rich” Suit, Administrative Analyst City of Long Beach, Department of Public Works333 W. Ocean Blvd., 9th FloorLong Beach, CA 90802(562) 570-6465 (562) 570-6012 (fax)[email protected]

Gary Lee Moore, P.E., City EngineerCity of Los Angeles, Department of Public Works, Bureau of Engineering1149 S. Broadway, Suite 700Los Angeles, CA 90015(213) 485-4935 (213) 485-4923 (fax) [email protected]


Michael Brown, P.E., Principal Civil EngineerCity of Los Angeles, Department of Public Works, Bureau of EngineeringProject Award and Control Division1149 S. Broadway, Suite 140Los Angeles, CA 90015(213) 847-0546 (213) 847-0703 (fax) [email protected]

Ted Allen, Interim Division ManagerCity of Los Angeles, Department of Public Works, Bureau of EngineeringProject Award and Control Division1149 S. Broadway, Suite 140Los Angeles, CA 90015(213) 847-0577(213) 847-0703 (fax)[email protected]

Raul Godinez, P.E., DirectorCity of Oakland, Department of Engineering and Construction250 Frank H. Ogawa Plaza, Suite 4314Oakland, CA 94612(510) 238-4470(510) 238-6412 (fax)[email protected]

Michael Neary, P.E., Assistant Director City of OaklandCommunity & Economic Development AgencyDepartment of Engineering & Construction 250 Frank H. Ogawa Plaza, Suite 4314Oakland, CA 94612(510) 238-6659(510) 238-7227 (fax)[email protected]

David Lau, P.E., Project Delivery ManagerCity of Oakland, Department of Engineering & ConstructionDepartment of Engineering & Construction 250 Frank H. Ogawa Plaza, Suite 4314Oakland, CA 94612(510) 238-7131(510) 238-2085 (fax)[email protected]

Gus Amirzehni, Engineering Design Manager City of Oakland, Department of Engineering & ConstructionDepartment of Engineering & Construction 250 Frank H. Ogawa Plaza, Suite 4314Oakland, CA 94612(510) 238-6601(510) 238-7227 (fax)[email protected]

David Ng, Civil Engineer City of OaklandCommunity & Economic Development AgencyDepartment of Engineering & Construction 250 Frank H. Ogawa Plaza, Suite 4314Oakland, CA 94612(510) 238-7267(510) 238-7227 (fax)[email protected]


Brian Reilly, Senior EngineerCity of Sacramento, Department of General Services5730 24th Street, Building 4Sacramento, CA 95822(916) 808-8427(916) 808-8337 (fax)[email protected]

Katherine Robbins, Administrative AnalystCity of Sacramento, Department of General Services5730 24th Street, Building 4Sacramento, CA 95822(916) 808-1562(916) 808-8337 (fax)[email protected]

Nicholas Theocharides, Engineering Division ManagerCity of Sacramento, Department of Transportation915 I Street, Room 2000Sacramento CA 95814(916) 808-5065 (916) 808-8281 (fax)[email protected]

Tim Mar, Supervising EngineerCity of Sacramento, Department of Transportation915 I Street, Room 2000Sacramento CA 95814(916) 808-7531(916) 808-8281 (fax)[email protected]

Ryan Moore, Supervising EngineerCity of Sacramento, Department of Transportation915 I Street, Room 2000Sacramento CA 95814(916) 808-8279 (916) 808-8281 (fax)[email protected]

Nicole Henderson, Supervising Financial AnalystCity of Sacramento, Department of Transportation915 I Street, Room 2000Sacramento CA 95814(916) 808-8242 (916) 808-8281 (fax)[email protected]

David Brent, Engineering Division ManagerCity of Sacramento, Department of Utilities, Engineering Services1395 35th Avenue Sacramento, CA 95822(916) 808-1420 (916) 808-1497 (fax)[email protected]

Richard S. Batha, Supervising EngineerCity of Sacramento, Department of Utilities, Engineering Services1395 35th Avenue Sacramento, CA 95822(916) 808-1448 (916) 808-1497 (fax)[email protected]


Patti Boekamp, P.E., DirectorCity of San DiegoEngineering & Capital Projects Department202 C Street, MS 9BSan Diego, CA 92101(619) 236-6274 (619) 533-4736 (Fax)[email protected]

Myrna Dayton, P.E., Senior Civil EngineerCity of San DiegoEngineering and Capital Projects DepartmentProject Implementation and Technical Services Division600 B Street, Suite 800San Diego, CA 92101(619) 533-6671(619) 533-4666 (fax)[email protected]

Alex Garcia, P.E., Senior Civil EngineerCity of San DiegoEngineering and Capital Projects DepartmentArchitectural Engineering and Parks Division600 B St, Suite 800San Diego, CA 92101(619) 533-4640(619) 533-4666 (fax)[email protected]

Rania Amen, P.E., Senior Civil EngineerCity of San DiegoEngineering and Capital Projects DepartmentRight-of-Way Design Division600 B St, Suite 800San Diego, CA 92101(619) 533-5492(619) 533-4666 (fax)[email protected]

George Qsar, P.E., Senior Civil EngineerCity of San DiegoEngineering and Capital Projects DepartmentField Engineering Division9485 Aero DriveSan Diego, CA 92123(858) 627-3240 (858) 627-3297 (fax)[email protected]

Fuad Sweiss, P.E., City Engineer and Deputy Director of EngineeringCity and County of San Francisco, Dept. of Public WorksCity Hall Room 3481 Carlton B. Goodlett PlSan Francisco, CA 94102(415) 554-6920 (415) 554-6944 (fax)[email protected]

Peg Divine, P.E., Bureau ManagerCity and County of San Francisco, Dept. of Public Works, Bureau of Engineering30 Van Ness Avenue, 5th FloorSan Francisco, CA 94102(415) 558-4084 (415) 558-4519 (fax)[email protected]


Steven T. Lee, P.E., Electrical EngineerCity and County of San Francisco, Department of Public Works, Bureau of Engineering30 Van Ness Avenue, 5th FloorSan Francisco, CA 94102(415) 558-5226 (415) 558-4590 (fax)[email protected]

Don Eng, P.E., Bureau ManagerCity and County of San Francisco, Department of Public Works, Bureau of Construction Management1680 Mission Street, 4th FloorSan Francisco, CA 94103(415) 554-8216(415) 554-8218 (fax)[email protected]

Mark Dorian, A.I.A., Assistant Bureau ManagerCity and County of San Francisco, Department of Public Works, Bureau of Architecture30 Van Ness Avenue, 4th FloorSan Francisco, CA 94102(415) 558-4713(415) [email protected]

Edgar Lopez, AIA, Bureau ManagerCity and County of San Francisco, Dept. of Public Works, Bureau of Project Management30 Van Ness Avenue, 4th FloorSan Francisco, CA 94102(415) 557-4675(415) 558-4519 (fax)[email protected]

David D. Sykes, P.E., Assistant DirectorCity of San Jose, Department of Public Works200 E. Santa Clara St.5th Fl. TowerSan Jose, CA 95113(408) 535-8440 (408) 292-6268 (fax)[email protected] Ng, P.E., L.S., Division ManagerCity of San Jose, Department of Public Works200 E. Santa Clara St.5th Floor TowerSan Jose, CA 95113(408) 535-8477(408) 292-6296 (fax)[email protected]

Katy Allen, P.E., DirectorCity of San Jose, Department of Public Works200 E. Santa Clara St.5th Fl. TowerSan Jose, CA 95113(408) 535-8444 (408) 292-6268 (fax)[email protected]

Ashwini Kantak, AIA, LEED AP, CIP Team Leader City of San Jose, Office of the City Manager200 E. Santa Clara St.16th Floor TowerSan Jose, CA 95113(408) 535-8147(408) 292-6724 (fax)[email protected]


Upd

ate

2009

Pro

ject

Tea

m

appendix PerformanceQuestionnaireA

Page a-1

California Multi-Agency Benchmarking Study Update 2009 Performance Questionnaire

Agency: Project Name:

Project type: LEED Green Building

New/Rehab Index:

Description:

Comments:

Planning Design Construction Total

DOLLAR % of TCC* DOLLAR % of TCC* DOLLAR % of TCC* DOLLAR % of TCC*

AGENCY LABOR

AGENCY COSTS(1)

Art Fees

SUB-TOTAL AGENCY

CONSULTANT

TOTALS

PHASE DURATION Months Months Months

AMOUNT OF CONSTRUCTION CONTRACT

COST OF CHANGE ORDERS Changed Conditions

Changed Bid Documents

Client-Initiated Changes:

Total Change Orders

$-

UTILITY RELOCATION COST

CITY FORCES CONSTRUCTION

TOTAL CONSTRUCTION COST (TCC)

LAND ACQUISITION

PROJECT COMPLETION DATE

TOTAL PROJECT COST $-

NUMBER OF BIDS RECEIVED

(1) Agency costs include other direct costs and can be listed underneath. This value is locked and it is calculated from its items (Rows 14 - 18)

Page a-2


appendix PerformanceCurvesB

Page B-1

Curves Group 1

Design Costvs

Total Construction Cost


Page B-2

Appendix B Performance Curves

Page B-3

y = 0.1726xR² = 0.9013

0

2

4

6

8

10

12

14

16

18

0 10 20 30 40 50 60 70 80 90

Design($Million)

Total ConstructionCost ($Million)

All ProjectsMunicipal Facilities All Classifications

Design ($ Million) Versus Total Construction Cost (N=116)

y = 0.1689xR² = 0.6431

0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

1.8

2

0 1 2 3 4 5 6 7 8

Design($Million)


Smaller ProjectsMunicipal Facilities All Classifications


y = 0.1726xR² = 0.9013

0

2

4

6

8

10

12

14

16

18

0 10 20 30 40 50 60 70 80 90

Design($Million)


All ProjectsMunicipal Facilities All Classifications


y = 0.1689xR² = 0.6431

0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

1.8

2

0 1 2 3 4 5 6 7 8

Design($Million)


Smaller ProjectsMunicipal Facilities All Classifications



Page B-4


Page B-5

y = 0.1703xR² = 0.7827

0

1

2

3

4

5

6

7

8

9

0 5 10 15 20 25 30 35

Design($Million)


All ProjectsMunicipal Facilities Police/Fire Stations


y = 0.1426xR² = 0.5444

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

0 1 2 3 4 5 6 7 8

Design($Million)


Smaller ProjectsMunicipal Facilities Police/Fire Stations


y = 0.1703xR² = 0.7827

0

1

2

3

4

5

6

7

8

9

0 5 10 15 20 25 30 35

Design($Million)


All ProjectsMunicipal Facilities Police/Fire Stations


y = 0.1426xR² = 0.5444

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

0 1 2 3 4 5 6 7 8

Design($Million)


Smaller ProjectsMunicipal Facilities Police/Fire Stations



Page B-6

y = 0.1671xR² = 0.7682

0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

1.8

2

0 2 4 6 8 10 12

Design($Million)


All ProjectsMunicipal Facilities Comm./Rec. Center/Child Care/GymsDesign ($ Million) Versus Total Construction Cost (N=50)

y = 0.194xR² = 0.4475

0

0.2

0.4

0.6

0.8

1

1.2

1.4

0 0.5 1 1.5 2 2.5 3 3.5

Design($Million)


Smaller ProjectsMunicipal Facilities Comm./Rec. Center/Child Care/GymsDesign ($ Million) Versus Total Construction Cost (N=40)

y = 0.1671xR² = 0.7682

0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

1.8

2

0 2 4 6 8 10 12

Design($Million)


All ProjectsMunicipal Facilities Comm./Rec. Center/Child Care/GymsDesign ($ Million) Versus Total Construction Cost (N=50)

y = 0.194xR² = 0.4475

0

0.2

0.4

0.6

0.8

1

1.2

1.4

0 0.5 1 1.5 2 2.5 3 3.5

Design($Million)


Smaller ProjectsMunicipal Facilities Comm./Rec. Center/Child Care/GymsDesign ($ Million) Versus Total Construction Cost (N=40)


Page B-7


Page B-8

y = 0.1648xR² = 0.6289

0

1

2

3

4

5

6

7

8

9

0 10 20 30 40 50 60

Design($Million)


All ProjectsStreets All Classifications


y = 0.1648xR² = 0.6289

0

1

2

3

4

5

6

7

8

9

0 10 20 30 40 50 60

Design($Million)





Page B-9


Page B-10


Page B-11


Page B-12

y = 0.2004xR² = 0.5321

0

0.5

1

1.5

2

2.5

0 1 2 3 4 5 6 7

Design($Million)


All ProjectsStreets Bike/Pedestrian/Streetscapes


y = 0.2004xR² = 0.5321

0

0.5

1

1.5

2

2.5

0 1 2 3 4 5 6 7

Design($Million)





Page B-13

y = 0.1631xR² = 0.4306

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0 0.5 1 1.5 2 2.5 3 3.5

Design($Million)


All ProjectsStreets Signals


y = 0.1631xR² = 0.4306

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0 0.5 1 1.5 2 2.5 3 3.5

Design($Million)





Page B-14

y = 0.0935xR² = 0.8806

0

5

10

15

20

25

0 50 100 150 200 250 300

Design($Million)


All ProjectsPipe Systems All Classifications


y = 0.1732xR² = 0.3071

0

0.1

0.2

0.3

0.4

0.5

0.6

0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8

Design($Million)


Smaller ProjectsPipe Systems All Classifications


y = 0.0935xR² = 0.8806

0

5

10

15

20

25

0 50 100 150 200 250 300

Design($Million)




y = 0.1732xR² = 0.3071

0

0.1

0.2

0.3

0.4

0.5

0.6

0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8

Design($Million)





Page B-15


Page B-16


Page B-17


Page B-18

y = 0.2477xR² = 0.8263

0

0.5

1

1.5

2

2.5

0 1 2 3 4 5 6 7

Design($Million)


All ProjectsParks All Classifications


y = 0.2477xR² = 0.8263

0

0.5

1

1.5

2

2.5

0 1 2 3 4 5 6 7

Design($Million)





Page B-19


Page B-20

y = 0.296xR² = 0.8441

0

0.5

1

1.5

2

2.5

0 1 2 3 4 5 6 7

Design($Million)


All ProjectsParks Sportfields


y = 0.1173xR² = 0.2552

0

0.05

0.1

0.15

0.2

0.25

0.3

0.35

0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 2

Design($Million)


Smaller ProjectsParks Sportfields


y = 0.296xR² = 0.8441

0

0.5

1

1.5

2

2.5

0 1 2 3 4 5 6 7

Design($Million)




y = 0.1173xR² = 0.2552

0

0.05

0.1

0.15

0.2

0.25

0.3

0.35

0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 2

Design($Million)





Page B-21


Page B-22


Page B-23

Curves Group 2

Construction Management Cost vs

Total Construction Cost


Page B-24


Page B-25


Page B-26


Page B-27


Page B-28


Page B-29


Page B-30

y = 0.1782xR² = 0.9443

0

2

4

6

8

10

12

0 10 20 30 40 50 60

Construction

Managem

ent($Million)



Construction Management Versus Total Construction Cost (N=263)

y = 0.1886xR² = 0.4996

0

0.05

0.1

0.15

0.2

0.25

0.3

0.35

0.4

0.45

0.5

0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8

Construction

Managem

ent($Million)


Smaller ProjectsStreets All Classifications


y = 0.1782xR² = 0.9443

0

2

4

6

8

10

12

0 10 20 30 40 50 60

Construction

Managem

ent($Million)




y = 0.1886xR² = 0.4996

0

0.05

0.1

0.15

0.2

0.25

0.3

0.35

0.4

0.45

0.5

0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8

Construction

Managem

ent($Million)





Page B-31


Page B-32


Page B-33


Page B-34

y = 0.135xR² = 0.6225

0

0.2

0.4

0.6

0.8

1

1.2

1.4

0 1 2 3 4 5 6 7

Construction

Managem

ent($Million)




y = 0.1871xR² = 0.4445

0

0.05

0.1

0.15

0.2

0.25

0.3

0.35

0.4

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9

Construction

Managem

ent($Million)


Smaller ProjectsStreets Bike/Pedestrian/Streetscapes


y = 0.135xR² = 0.6225

0

0.2

0.4

0.6

0.8

1

1.2

1.4

0 1 2 3 4 5 6 7

Construction

Managem

ent($Million)




y = 0.1871xR² = 0.4445

0

0.05

0.1

0.15

0.2

0.25

0.3

0.35

0.4

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9

Construction

Managem

ent($Million)





Page B-35

y = 0.1749xR² = 0.6093

0

0.05

0.1

0.15

0.2

0.25

0.3

0.35

0.4

0.45

0.5

0 0.5 1 1.5 2 2.5 3 3.5

Construction

Managem

ent($Million)




y = 0.2146xR² = 0.1687

0

0.02

0.04

0.06

0.08

0.1

0.12

0.14

0.16

0.18

0 0.1 0.2 0.3 0.4 0.5 0.6

Construction

Managem

ent($Million)


Smaller ProjectsStreets Signals


y = 0.1749xR² = 0.6093

0

0.05

0.1

0.15

0.2

0.25

0.3

0.35

0.4

0.45

0.5

0 0.5 1 1.5 2 2.5 3 3.5

Construction

Managem

ent($Million)




y = 0.2146xR² = 0.1687

0

0.02

0.04

0.06

0.08

0.1

0.12

0.14

0.16

0.18

0 0.1 0.2 0.3 0.4 0.5 0.6

Construction

Managem

ent($Million)


Smaller ProjectsStreets Signals



Page B-36


Page B-37


Page B-38


Page B-39


Page B-40


Page B-41


Page B-42


Page B-43


Page B-44


Page B-45

Curves Group 3Project Delivery Cost

vsTotal Construction Cost


Page B-46


Page B-47


Page B-48


Page B-49


Page B-50


Page B-51


Page B-52

y = 0.3429xR² = 0.9078

0

2

4

6

8

10

12

14

16

18

20

0 10 20 30 40 50 60

ProjectD

elivery($Million)



Project Delivery ($ Million) Versus Total Construction Cost (N=263)

y = 0.463xR² = 0.6147

0

0.2

0.4

0.6

0.8

1

1.2

1.4

0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8

ProjectD

elivery($Million)




y = 0.3429xR² = 0.9078

0

2

4

6

8

10

12

14

16

18

20

0 10 20 30 40 50 60

ProjectD

elivery($Million)




y = 0.463xR² = 0.6147

0

0.2

0.4

0.6

0.8

1

1.2

1.4

0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8

ProjectD

elivery($Million)





Page B-53


Page B-54


Page B-55


Page B-56

y = 0.3353xR² = 0.6188

0

0.5

1

1.5

2

2.5

3

3.5

0 1 2 3 4 5 6 7

ProjectD

elivery($Million)




y = 0.4673xR² = 0.4758

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9

ProjectD

elivery($Million)




y = 0.3353xR² = 0.6188

0

0.5

1

1.5

2

2.5

3

3.5

0 1 2 3 4 5 6 7

ProjectD

elivery($Million)




y = 0.4673xR² = 0.4758

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9

ProjectD

elivery($Million)





Page B-57

y = 0.3393xR² = 0.7531

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

0 0.5 1 1.5 2 2.5 3 3.5

ProjectD

elivery($Million)




y = 0.3393xR² = 0.7531

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

0 0.5 1 1.5 2 2.5 3 3.5

ProjectD

elivery($Million)





Page B-58

y = 0.1895xR² = 0.9623

0

5

10

15

20

25

30

35

40

45

50

0 50 100 150 200 250 300

ProjectD

elivery($Million)




y = 0.3465xR² = 0.5394

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8

ProjectD

elivery($Million)




y = 0.1895xR² = 0.9623

0

5

10

15

20

25

30

35

40

45

50

0 50 100 150 200 250 300

ProjectD

elivery($Million)




y = 0.3465xR² = 0.5394

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8

ProjectD

elivery($Million)





Page B-59

y = 0.189xR² = 0.9629

0

5

10

15

20

25

30

35

40

45

50

0 50 100 150 200 250 300

ProjectD

elivery($Million)


All ProjectsPipe Systems Gravity Systems (Storm Drains/Sewers)


y = 0.3487xR² = 0.5479

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8

ProjectD

elivery($Million)


Smaller ProjectsPipe Systems Gravity Systems (Storm Drains/Sewers)


y = 0.189xR² = 0.9629

0

5

10

15

20

25

30

35

40

45

50

0 50 100 150 200 250 300

ProjectD

elivery($Million)


All ProjectsPipe Systems Gravity Systems (Storm Drains/Sewers)


y = 0.3487xR² = 0.5479

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8

ProjectD

elivery($Million)


Smaller ProjectsPipe Systems Gravity Systems (Storm Drains/Sewers)



Page B-60


Page B-61


Page B-62

y = 0.3511xR² = 0.9102

0

0.5

1

1.5

2

2.5

0 1 2 3 4 5 6 7

ProjectD

elivery($Million)




y = 0.3489xR² = 0.4027

0

0.1

0.2

0.3

0.4

0.5

0.6

0 0.2 0.4 0.6 0.8 1 1.2

ProjectD

elivery($Million)


Smaller ProjectsParks All Classifications


y = 0.3511xR² = 0.9102

0

0.5

1

1.5

2

2.5

0 1 2 3 4 5 6 7

ProjectD

elivery($Million)




y = 0.3489xR² = 0.4027

0

0.1

0.2

0.3

0.4

0.5

0.6

0 0.2 0.4 0.6 0.8 1 1.2

ProjectD

elivery($Million)


Smaller ProjectsParks All Classifications



Page B-63


Page B-64

y = 0.3372xR² = 0.8973

0

0.5

1

1.5

2

2.5

0 1 2 3 4 5 6 7

ProjectD

elivery($Million)




y = 0.2145xR² = 0.004

0

0.05

0.1

0.15

0.2

0.25

0.3

0.35

0.4

0.45

0.5

0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 2

ProjectD

elivery($Million)




y = 0.3372xR² = 0.8973

0

0.5

1

1.5

2

2.5

0 1 2 3 4 5 6 7

ProjectD

elivery($Million)




y = 0.2145xR² = 0.004

0

0.05

0.1

0.15

0.2

0.25

0.3

0.35

0.4

0.45

0.5

0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 2

ProjectD

elivery($Million)





Page B-65


Page B-66

Proj

ect T

ype

or

Cla

ssifi

catio

n

Des

ign

Cos

t ($)

vs

. TC

C($

)Fu

ll R

ange

of T

CC

Des

ign

Cos

t ($)

vs

. TC

C($

)Sm

alle

r Pro

ject

Su

bset

of T

CC

CM

Cos

t ($)

vs

. TC

C($

)Fu

ll R

ange

of T

CC

CM

Cos

t ($)

vs

. TC

C($

)Sm

alle

r Pro

ject

Su

bset

of T

CC

Proj

ect D

eliv

ery

Cos

t ($)

vs.

TC

C($

)Fu

ll R

ange

of T

CC

Proj

ect D

eliv

ery

Cos

t ($

) vs.

TC

C($

)Sm

alle

r Pro

ject

Su

bset

of T

CC

Mun

icip

al P

roje

cts

y=0.

1726

xy=

0.16

89x

y=0.

1763

xy=

0.14

44x

y=0.

3489

xy=

0.31

32x

Libr

arie

sy=

0.16

12x

y=0.

1824

xy=

0.12

38x

y=0.

1195

xy=

0.28

49x

y=0.

3019

x

Polic

e/Fi

re S

tatio

nsy=

0.17

03x

y=0.

1426

xy=

0.16

3xy=

0.13

55x

y=0.

3333

xy=

0.27

79x

Com

m./R

ec.C

ente

r/C

hild

Car

e/G

yms

y=0.

1671

xy=

0.19

4xy=

0.10

88x

y=0.

1446

xy=

0.27

59x

y=0.

3386

x

Oth

er M

unic

ipal

y=0.

1754

xy=

0.16

75x

y=0.

1925

xy=

0.09

64x

y=0.

3679

xy=

0.26

39x

Stre

ets

Proj

ects

y=0.

1648

xy=

0.27

38x

y=0.

1782

xy=

0.18

86x

y=0.

3429

xy=

0.46

3x

Wid

enin

g/N

ew/

Gra

de S

epar

atio

nsy=

0.13

38x

y=0.

2586

xy=

0.18

73x

y=0.

1741

xy=

0.32

11x

y=0.

4326

x

Brid

ges

y=0.

3536

xy=

0.36

78x

y=0.

1204

xy=

0.16

37x

y=0.

474x

y=0.

5313

x

Rec

onst

ruct

ions

y=0.

2374

xy=

0.22

67x

y=0.

174x

y=0.

1382

xy=

0.41

15x

y=0.

365x

Bike

/Ped

estri

an/

Stre

etsc

apes

y=0.

2004

xy=

0.27

99x

y=0.

135x

y=0.

1871

xy=

0.33

53x

y=0.

4673

x

Sign

als

y=0.

1631

xy=

0.24

73x

y=0.

1749

xy=

0.21

46x

y=0.

3393

xy=

0.46

07x

Pipe

s Pr

ojec

tsy=

0.09

35x

y=0.

1732

xy=

0.09

6xy=

0.17

33x

y=0.

1895

xy=

0.34

65x

Gra

vity

Mai

nsy=

0.09

3xy=

0.17

37x

y=0.

096x

y=0.

175x

y=0.

189x

y=0.

3487

x

Pres

sure

Sys

tem

sy=

0.06

8xy=

0.11

19x

y=0.

0978

xy=

0.13

92x

y=0.

1658

xy=

0.25

11x

Pum

p St

atio

nsy=

0.14

13x

y=0.

2124

xy=

0.09

92x

y=0.

2198

xy=

0.24

04x

y=0.

4322

x

Park

s0.

2477

xy=

0.20

9xy=

0.10

34x

y=0.

14x

y=0.

3511

xy=

0.34

89x

Play

grou

nds

y=0.

2094

xy=

0.22

7xy=

0.14

95x

y=0.

1354

xy=

0.35

89x

y=0.

3625

x

Sportfields

y=0.

296x

0.11

73x

y=0.

0412

xy=

0.09

73x

y=0.

3372

xy=

0.21

45x

Res

troom

sy=

0.37

6xy=

0.11

44x

y=0.

1751

xy=

0.24

65x

y=0.

5511

xy=

0.36

1x

Tabl

e B

-1

Sum

mar

y of

Reg

ress

ion

Equa

tions

Not

es:

m =

slop

e of

the

regr

essio

n tre

ndlin

e w

hich

is th

e pr

ojec

t del

iver

y pe

rcen

tage

.

appendix IndirectratesC

Page C-1

Age

ncy

Frin

ge

Ben

efits

Com

pens

ated

Ti

me

Off

City

O

verh

ead

Dep

artm

ent

Ove

rhea

dA

genc

y O

verh

ead

Indi

rect

R

ate

Fact

or1

Rec

eive

G

ener

al

Fund

Su

ppor

t Fo

r CIP

City

of L

ong

Bea

chD

epar

tmen

t of P

ublic

Wor

ks39

.24%

19.4

0%0%

5.68

%42

.0%

106.

32%

YES

City

of L

os A

ngel

esD

epar

tmen

t of P

ublic

Wor

ksB

urea

u of

Eng

inee

ring2

37.0

4%19

.61%

21.5

5%18

.01%

70.7

8%16

6.98

%YE

S

City

of O

akla

ndD

epar

tmen

t of E

ngin

eerin

g &

Con

stru

ctio

n73

.85%

20.7

9%32

.40%

0%21

.57%

148.

61%

NO

City

of S

acra

men

toD

epar

tmen

t of

Gen

eral

Ser

vice

s3

Dep

artm

ent o

f Tra

nspo

rtat

ion

Dep

artm

ent o

f Util

ities

32.0

0%18

.70%

0%0%

73%

131.

9%N

O33

.26%

18.7

0%11

.90%

12.0

0%63

.00%

138.

86%

37.1

7%18

.70%

100.

36%

156.

23%

City

of S

an D

iego

Arc

hite

ctur

al E

ngin

eerin

g &

Con

trac

t Ser

vice

sTr

ansp

orta

tion

Engi

neer

ing

Div

isio

nW

ater

& W

aste

wat

er

Faci

litie

s D

ivis

ion

46.9

3%20

.50%

0%0%

88.0

5%15

5%

NO

47.3

2%18

.30%

0%0%

55.8

0%12

1%

49.7

6%18

.40%

0%0%

88.0

5%15

6%

City

and

Cou

nty

of

San

Fran

cisc

oD

epar

tmen

t of P

ublic

Wor

ksB

urea

u of

Eng

inee

ring

Bur

eau

of C

onst

ruct

ion

Man

agem

ent

Bur

eau

of A

rchi

tect

ure

21.8

5%23

.99%

0%36

.55%

63.9

2%14

6.31

%

NO

City

of S

an J

ose

Dep

artm

ent o

f Pub

lic W

orks

36.9

0%33

.11%

37.8

3%9.

27%

432

.70%

Incl

uded

149.

81%

NO

Tabl

e C

-1

Indi

rect

Rat

es A

pplie

d to

Cap

ital P

roje

cts

Not

es:

1 Thi

s val

ue m

ay b

e di

ffere

nt fr

om th

e su

m o

f ove

rhea

d va

lues

sinc

e th

e co

mpo

undi

ng fo

rmul

a m

ay v

ary

by a

genc

y.2 B

ased

on

aver

ages

of a

ll B

urea

u pr

ogra

m o

verh

ead

rate

s pro

vide

d un

der C

AP

28.

3 Ye

ar 2

008

Rat

es.

4 37.

83%

is th

e ra

te a

pplie

d to

Cap

ital P

roje

ct la

bor c

harg

es; 9

.27%

is th

e ra

te a

pplie

d to

Com

pens

ated

Tim

e O

ff

Page C-2

Annual Report Update 2009 California Multi-Agency CIP Benchmarking StudyAnnual Report Update 2003 California Multi-Agency CIP Benchmarking Study

Table of - Bureau of Engineeringeng.lacity.org/sites/g/files/wph726/f/CABM_Update_2009.pdf · Table...

Documents

Transcript of Table of - Bureau of Engineeringeng.lacity.org/sites/g/files/wph726/f/CABM_Update_2009.pdf · Table...