References
Acknowledgements
Appendix
A-Literature review
Appendix
B-Missoula Implementation Plan
Appendix
C- Spreadsheet for calculating effectiveness benefits
Appendix
D- Copies of Gillespie's papers describing the model
1 Introduction
1.1 Why
do the study?
The Montana Geographic
Information Council (MGIC) perceived a need for an economic analysis of
geographic information system (GIS) implementations at the state and county
government levels. This study was commissioned for the dual purpose of determining
the monetary benefits for justification of GIS implementation and devising
a set of guidelines for planning future GIS implementations at the state
and local government levels.
It is important to assess
the monetary benefits of GIS for a number of reasons. First and foremost,
managers will be more supportive of GIS implementation if they can see their
employees working more efficiently and effectively. Second, securing funding
for GIS projects either through legislative decree or private sector cost
sharing will be more accessible if a direct economic benefit can be identified.
Third, with the limited resources available for GIS, it is important to
prioritize GIS applications according to the expected B/C returns from each
of the applications.
The guidelines from
the study are also important to provide some resources for organizations
considering GIS. The report will provide a number of references to help
groups understand how to better quantify the benefits of GIS. Equally important,
the report summarizes a number of lessons which have been learned in existing
GIS implementations in Montana. If the report helps groups to avoid reinventing
the wheel on GIS implementation, it will have achieved its purpose.
1.2 Case
Study Methodology
MGIC determined that
a case study methodology would provide the most useful results of the study
at a reasonable cost. The case study approach has been used extensively
in the available GIS literature. MGIC decided that the study should include
case studies from both state government agencies and county or local governments.
Ten case studies in Montana were selected for the report, as described below.
1.3 Case
studies
1.3.1 Montana local
government case studies
The following four city/county
governments were selected as case studies for this report:
- Missoula/Missoula
County
- Butte/Silver Bow
County
- Lewis & Clark
County
- Billings/Yellowstone
County
These counties represent
the spectrum of local government GIS in populated counties of Montana, from
a reasonably mature system at Butte-Silver Bow to an up-and-coming system
at Lewis & Clark County. The Yellowstone County case study is not summarized
in this report, but the general findings contributed to the report's recommendations.
1.3.2 Montana State
government case studies
The following 6 state
government organizations were also selected as case studies:
- Montana Department
of Transportation (MDT)
- Montana State Library
Natural Resource Information System (NRIS)
- Montana Department
of Environmental Quality (DEQ) Remediation Division
- Montana DEQ Environmental
Management Bureau
- Montana DEQ Industrial
& Energy Minerals Bureau
- Montana Department
of Administration Information Services Division (ISD)
1.4 Report
organization
The body of this report
is organized into 6 main sections:
- 1(Introduction):
Provides background information and introduces the case studies
- 2 (Cost Benefit
Methodologies): Brief literature review, description of the methodology
used in this study
- 3 (Case Studies):
Discusses the data gathered from case studies
- 4 (Discussion of
Results): Summarizes the key findings of the report in the issues of
justifying GIS expenditures and planning for future GIS implementation
- 5 (Conclusions):
Analysis of the methods used to accomplish the goals of the report
- 6 (Recommendations):
How to justify and plan GIS implementations
2 Cost
benefit methodologies
2.1 Literature
Review
A literature on GIS
cost benefit analyses was conducted. Several of the most pertinent articles
are summarized in Appendix A
2.2 General cost
benefit approach adopted for this study
The literature review
revealed that the most effective way to obtain information on GIS costs
and benefits is to conduct personal interviews of key personnel in the selected
organization. With this in mind, our first duties were to identify a few
people in each case study and to determine what information we really needed
to gain in the interview process.
The Gillespie (1997)
model seemed to be ideally suited for the goals of this study. That study
comprised a comprehensive study of 62 GIS implementations at the federal
government level. The model provides a more straightforward and less time
intensive approach to estimating the benefits of GIS than the more traditional
approaches discussed in the literature. Furthermore, the Gillespie (1997)
model attempts to quantify both the efficiency benefits and effectiveness
benefits of GIS implementations. These two types of benefits will be defined
in the context of the Gillespie (1997) model in Section 2.4. Previously,
effectiveness benefits have typically been disregarded or at best described
qualitatively.
Most of the cost benefit
analyses located in the literature review were comprehensive studies that
required a great deal of time and resources to complete. Our budgetary limitations
mandated a much broader scope for this study, particularly because we hoped
to gain cost benefit information on a number of different case studies.
Our interviews sought to gain some general information about the system
and more detailed cost benefit information about one or more of the most
important GIS applications in the system. We hoped that this approach would
give us a representative sample of the level of benefits we could expect
to see in a given case study. However, we would not be able to determine
all the costs and benefits for an entire GIS installation.
2.3 What is a GIS
application?
GIS applications really
became focus of this study, so it is important at this point to define what
is meant by a GIS application. An application is some set of software, data,
GIS programming and a GIS user combined to produce a result that can solve
a particular problem. GIS should be implemented with the goal of solving
a known set of problems that could not previously be solved efficiently
or effectively.
2.4 Gillespie (1997)
model
The Gillespie (1997)
model provides equations for calculating efficiency and effectiveness benefits.
Gillespie (1994) states that efficiency benefits arise when GIS is used
to reduce costs of a task that, in the absence of GIS, would be handled
by some other method. The outputs must be equivalent. Effectiveness benefits
arise when GIS is used to perform a task that could not or would not be
done without GIS. The outputs are new or at least a significant improvement
over existing products.
Gillespie (1997) also
uses the term "pure" effectiveness benefits to indicate that effectiveness
benefits are the only type of benefits for an application. Some applications
produce both effectiveness and efficiency benefits. The net benefits of
the application are the sum of the net effectiveness and net efficiency
benefits.
2.4.1 Model equations
Two separate regression
equations are used to calculate pure effectiveness and pure efficiency benefits
per incident of an application (Gillespie, 1997).
- Pure effectiveness
benefits
LT = 3.752
+ 0.673 INPLEX1 + 0.045 INTERACT + 0.429 OUTPLEX +
3.147 SMALL + residual
where: (Gillespie, 1998):
LT = Natural
log of gross pure effectiveness benefits
INPLEX1 = Measure
of input complexity
=
LN (EXTENT) + LN (VOLUME)
- EXTENT refers to
the total study area, reported in map units
- A map unit is
the physical area adjusted for the viewing scale
- Number of map
units = number of map sheets required
- At a 1:24000
scale, 1 quad is 1 map unit
- Number of map
units = Study area/ Area per map (around 50 mi2 for a 1:24000
quad)
- VOLUME refers to
the Volume of relevant data, reported in megabytes
INTERACT = Measure
of analysis complexity
= 0.5 * ( MAX2
-MAX)
- MAX is the maximum
number of separate data themes overlaid concurrently
- Calculate this
for the single most complicated step in an application
OUTPLEX = Measure
of output complexity
= VARIETY
/ 3 + LIKELIHOOD / 25
- VARIETY is total
number of separate groups concerned about an application
- VARIETY ranged
from 1 to 12 with most falling in 3-5 range for federal case studies
- Potential concerns
include environmental, developers, homeowners, various government
agencies, real estate agents
- LIKELIHOOD is the
likelihood an application will be used in an adversarial hearing
- Examples include
a lawsuit or a challenging to a zoning decision
- Ranges from 0-100
SMALL = Dummy
variable reflecting overall complexity of Application
- SMALL either a
0 or 1
- Value of small
determined by changing previous 5 variables into size classes (S.C.)
EXTENT:
S.C. (1)
= LN (EXTENT)
VOLUME:
S.C. (2)
= LN (VOLUME)
INTERACT:
S.C. (3)
= INTERACT/3 and round up to nearest digit
VARIETY:
S.C. (4)
= VARIETY/3 and round up to nearest digit
LIKELIHOOD:
IF (LIKELIHOOD
= 0) S.C. (5) = 0
IF (LIKELIHOOD
< 50) S.C. (5) = 1
IF (100>LIKELIHOOD
>50) S.C. (5) = 2
IF (LIKELIHOOD
= 100) S.C. (5) = 3
- SIZE = S( S.C.
(i) where i= each of the 5 model variables)
- IF (SIZE>6)
SMALL = 0
- Otherwise, SMALL
= 1
Residual = Error
term for the regression equation
- This term is not
included in the model calculations; it is the error involved in estimating
the regression coefficients from the data collected from the 62 case
studies (Gillespie, 1998)
LT is the natural log
of the gross pure effectiveness benefits. To determine the net pure effectiveness
benefit, one must first take the antilog and then subtract the cost of running
the application with GIS.
The effectiveness benefit
calculated in this manner is the net effectiveness per incident of an application.
To determine the net annual effectiveness benefit of an application requires
that the benefit be multiplied by the annual frequency of use of the application.
For the purposes of this report, a new variable called FREQUENCY is
simply defined as the number of times an application is run annually.
- Pure efficiency
benefits:
RATIO = 0.477 + 0.100
INPLEX2 - 0.001 INTERACT + 0.051 OUTPLEX
+ 0.377
SMALL + 0.232 COST - 0.186 LAND + residual
where: (Gillespie,
1998)
RATIO = ratio
of efficiency benefits to the manual costs (pre-GIS costs)
INPLEX2 = Measure
of input complexity
=
LN( EXTENT)
INTERACT = Already
defined
OUTPLEX = Already
defined
SMALL = Already
defined
COST = Dummy
variable reflecting cost of performing application with manual methods
- COST = 1 if cost
of running the application without GIS is between $20k-$50k
- COST = 0 otherwise
LAND = Dummy
variable reflecting subject area of application
- LAND = 1 if the
application is concerned with the economic value of the land
- LAND = 0 if the
application is only concerned with land because it is the location of
other activities
- LAND = 0 for most
applications
RATIO is the ratio of
net efficiency benefits to the manual costs (pre-GIS). To determine the
net efficiency benefits per incident of an application, one simply must
multiply RATIO by the manual cost.
As with the effectiveness
model, the net efficiency benefit per incident must be multiplied by FREQUENCY
to determine the net annual effectiveness benefits of the application.
2.4.2 Using the model
to estimate benefits of a GIS application
It is important to realize
that by Gillespie (1994) definitions, a given GIS output can only
have either effectiveness or efficiency benefits, but not both. A GIS application
may produce both types of benefits, but only if the application generates
multiple types of outputs. For instance, an application may automate some
type of engineering calculation that was used previously, thus producing
an efficiency benefit. The same application may also be used to generate
a map of the area that could not be produced otherwise, thus producing effectiveness
benefits for the same application.
To quantify the net
annual benefits of this application, the net efficiency benefit should be
multiplied by the FREQUENCY of the engineering calculations and the net
effectiveness benefit should be multiplied by the FREQUENCY of map production.
The net annual benefit of the GIS application is the then the sum of the
net effectiveness and net efficiency benefit.
Another interesting
way to describe the benefits of a GIS application is to determine the benefit/cost
ratio. The benefit cost ratio is found by dividing the gross annual
benefit by the annual cost of the application. A benefit/cost ratio of 1
indicates that the benefit just offsets the cost of the application. In
this study, the benefits and costs of an application are typically compared
on an annual basis for the present year.
A very important point
to realize is that the discussions have focused thus far on the costs and
benefits of an application. To quantify the benefits of an entire
GIS installation, one would have to add up the net annual benefits of all
applications within the installation. One would also have to include some
estimate of the depreciation of all system components. Gillespie (1998)
recommended that depreciation costs for a system not be included in the
analysis because the model was really derived to determine the benefits
of a GIS system already up and running. This study only goes to the point
of estimating benefit/cost ratios of individual applications. To fully characterize
the benefits of up to 10 case studies would have been an extremely time-consuming
and unjustifiable task.
Another important point
to make is that estimation of the model variables is quite a subjective
process. It is important to estimate benefits conservatively, while at the
same time remaining true to the spirit of the information coming out of
the interview.
Additional information
needed to run the model is available in Gillespie's papers in Appendix D
of this report.
3 GIS Case Studies
The case study data
were obtained for the most part from personal interviews. An interview worksheet
was mailed to the interviewees ahead of time so that they could be prepared
to answer the questions.
3.1 Missoula City/County
GIS implementation plan
Missoula's Geographic
Information Management Implementation Plan appears in its entirety in
Appendix B of this report. The plan was compiled by Roy F. Weston, Inc.
Seattle, WA. The key elements of the plan are summarized in the following
sections. Additional information was provided by telephone conversations
with Doug Burreson, Missoula County GIS coordinator.
3.1.1 Overview of
the GIS implementation plan
Steps
in strategic GIS Plan
- Needs assessment
- Conceptual data model
for road network database
- Data development
and maintenance plan
- Organizational analysis
- Hardware and software
solutions
- Implementation plan
Missoula
County data development tasks
- Control database
- Real property
- Political districts
- Transportation
City
of Missoula Data Development Tasks
- Photogrammetry
- Digital orthophotos
- Digital elevation
model and contours
- Wastewater facilities
- Storm drain facilities
- Traffic control facilities
GIS applications
As part of the Implementation
Plan, GIS personnel for the City of Missoula and Missoula County came up
with a list of GIS applications and developed a ranking system to prioritize
them.
The first step in the
ranking system involved deriving 8 categories among which each of the applications
could be compared. Further, the categories were each assigned a weighting
factor to describe their relative importance. The categories and assigned
weighting factors were:
- Is the cost of the
application small? (10)
- Is the application
a cornerstone of the information system? (10)
- Does the application
produce intangible benefits? (5)
- Does the application
produce tangible benefits? (10)
- Does the application
promote public access? (6)
- Is the application
used by a large number of personnel? (7)
- Does the application
reduce redundancy? (6)
- Is the application
part of a continuing initiative for information services? (5)
For each application,
Missoula's GIS personnel were then asked to assign scores between 1-3 for
each category to describe how well the application answers the above questions.
For instance, an application with a relatively low cost would receive a
score of 3 for the cost category. A total score was calculated for each
application by multiplying the score for each category by the weighting
factor for the category and summing up these numbers for all 8 categories.
Finally, the applications were ranked by descending score. The highest scoring
applications would be implemented first.
The following is a partial
list of GIS applications for Missoula County. The applications are not in
any particular order of importance.
- Scan and index voter
registration cards
- Weekly ownership
update
- Survey document management
- Septic permit system
- Internet map browser
- County road maintenance
management system
The following is a partial
list of GIS applications for Missoula County. The applications are not in
any particular order of importance.
- Maintenance management
system (wastewater, drainage, traffic)
- Infrastructure map
maintenance (wastewater, drainage, traffic)
- Permit and development
tracking
- Web enabled parks
and recreation reservation
- Map index to project
plans
- Map index to park
plans
- Property owner notification
Lessons
learned
- Greatest expense
involved in data development and training, not hardware/software
- Organizational issues
in developing GIS more difficult to overcome than technical issues
- Cooperation between
governments (i.e. city and county) is critical
- Cooperation between
agencies in a government also critical. For example, agencies can dispute
the division of responsibilities associated with the GIS
- GIS implementation
requires excellent communication between all personnel involved
- City of Missoula/
Missoula County were able to overcome the organizational issues and cooperate
well in the project
- Important for personnel
to trust the process of GIS implementation and be flexible in the way
they do things
- GIS implementation
requires a great deal of time
- Training requirements
for GIS are intense; it is difficult to cut corners
- Important for GIS
to show immediate benefits from mapping capabilities in order to bring
all agencies and decision makers on board
3.1.2 Cost benefit
information
All cost benefit information
in this report was taken directly from Missoula's Implementation Plan. The
Gillespie (1997) model was not used in this case study.
Cost
- Total project cost
of $2.25 million after 10 years
- Net investment peaks
at $780,000 because benefits begin to accrue immediately
- Capital costs
- Organizational
activities
- Data development
- Hardware and software
- Application development
- Operation & maintenance
costs
- Hardware/software
maintenance (assumed equal to 15% of capital expenditure)
- Communication services
Efficiency
benefits
- 5 year break even
period (annual benefit> annual cost)
- 10 year payback period
(cumulative benefit>cumulative cost)
Effectiveness
benefits
Effectiveness benefits
were not determined for the Missoula GIS.
3.2 Butte/Silver
Bow County GIS
The information for
the Butte/Silver Bow (BSB) GIS case study was obtained by interviewing Jon
Sesso and Tom Tully of the BSB Planning Department and Rob Macioroski of
the BSB Land Records
Department.
3.2.1 Overview
of Butte/Silver Bow GIS
System
description
Butte-Silver Bow is
an example of one of the most advanced local government GIS implementations
in the State of Montana. The system presently includes 6 Arc/INFO licenses
and 4 ArcView licenses. GIS implementation at BSB began approximately 9
years ago. The Butte Superfund sites were the primary motivator for GIS
implementation. Atlantic Richfield Corporation (ARCO) provided much of the
funding so that there would be an adequate storage system for the Superfund-related
data.
List
of applications
The top four applications
of the BSB GIS are:
- Automated land records
searches
- Automated underground
utilities information
- Environmental cleanup
coverage
- Zoning issues
Lessons
learned
- Don't get hung up
on data accuracy
Example: GIS
applications like water and sewer pipe locations can still be very useful
even if the data is only accurate to a few meters
- Don't underestimate
the necessity to maintain data as it is created
Example: Topology and
building location data changes frequently and must be updated regularly
- Don't use topographic
data from aerial photographs for engineering works
- Surface depressions
are particularly unreliable
- In many GIS applications,
users should not over-rely on data accuracy
- Cooperation between
all offices involved is critical
- Cooperation has been
critical to the success of BSB GIS
- Requires cooperation
between many state and local government agencies and private organizations
- All agencies involved
must commit to using compatible systems
- Unexpected difficulty
in bringing GIS to the desktop of people not accustomed to GIS
- GIS implementation
should occur simultaneously with data processing
- GIS applications
must be as straightforward as manual methods or GIS will not be used
- GIS data must be
documented with metadata as it is produced
- Must have an organized
approach to data maintenance so that it won't get lost
3.2.2 Cost/benefit
information
Cost information is
provided below for the entire system. Additional cost and benefit information
for the Gillespie (1997) model was provided for the application of automated
land records searches. Mr. Sesso estimated that between 70-80% of his department's
work involves land ownership research, so this application is by far the
most important one.
The interview revealed
that there are two basic types of land records requests: some people simply
request verbal ownership information while others request a map to show
ownership. For the purposes of the Gillespie (1997) model, these two types
of requests were differentiated because they produce different types of
benefits. The verbal requests produce efficiency benefits because those
requests could be satisfied prior to GIS. The map requests produce effectiveness
benefits because these maps were not produced prior to GIS.
The interview further
revealed that there are approximately 40 requests per day for simple ownership
information. This figure corresponds to 250/week or 10,400/year.
The number of maps produced
per week was also roughly determined during the interview. The Land Records
Department receives 10-15 requests for blueline maps per week. The Planning
Department receives approximately 40-45 requests for maps per month. The
difficulty in estimating benefits is in determining what is a typical request
for maps. Some requests are for a single map, while some Superfund-related
requests could produce as many as 3 dozen maps.
Costs
The annual GIS budget
for BSB is currently approximately $200,000 per year.
Prior to GIS, the cost
to satisfy a verbal ownership request was approximately 10 minutes time
of a person making $7/hr. Assuming a benefits multiplier of 1.32, the cost
of a single request is $1.50. The cost of satisfying these requests with
GIS was not determined in the interview. This information is estimated from
the Gillespie (1997) model in the next section.
It was indicated in
the interview that the typical minimum charge to produce a map is $25. The
fee is charged primarily to cover the cost of plotter time and ink, but
apparently also includes some labor fees. The $25 figure is probably the
bare minimum cost for the simplest type of map request. No information was
given on the cost of the more detailed map requests.
Efficiency
benefits
As mentioned previously,
the simple verbal ownership requests produce an efficiency benefit. To calculate
the efficiency benefit from a single request requires a number of assumptions
in order to estimate the variables:
- Application run 10,400
times per year (FREQUENCY=10,400)
- 1 map sheet viewed
to satisfy the request (EXTENT=1 in model)
- 3 data themes (MAX=3)
- 2 groups concerned
about the results of the request (CONCERNS=2)
- 5% chance that the
results of the request would end up in an adversarial hearing (LIKELIHOOD=5)
- Application concerned
with the land primarily as a location of other activities (LAND=0)
- Cost much less than
$20,000 per occurrence (COST=0)
The model predicts an
efficiency benefit of 89% with these variables. The result was quite sensitive
to the choice of the LAND variable, which is somewhat of a subjective variable.
A value of 1 would shrink the efficiency savings to 70%. The net annual
efficiency benefit (with LAND=0) for 10,400 requests at an original cost
of $1.50 is $13,920.
Effectiveness
benefits
The production of ownership
maps results in effectiveness benefits for the agency, individual or private
company making the request. The Gillespie (1997) model was used to estimate
the level of effectiveness benefits for these map requests.
Due to the great variety
of map requests, the BSB personnel were not able to describe a "typical"
request. A number of assumptions were made in order to use the Gillespie
(1997) model to make conservative estimates of the effectiveness benefits.
Map requests were divided into bluelines for the Land Records Department
and more complicated planning maps for the Planning Department. It was assumed
that there are 12 bluelines requests per week for the Land Records Department
and 10 requests per week for the Planning Department maps.
In order to make a conservative
estimate of the effectiveness benefits; the following assumptions were made
about a typical blueline request in the Land Records Department
- Application run 624
times per year (FREQUENCY=624)
- 1 map sheet viewed
and/or printed to satisfy the request (EXTENT=1)
- Information requested
about a single parcel
- An average volume
of data per parcel was calculated by dividing the total volume of land
ownership data by the number of digitized parcels in the county (350 megabytes/19,000
digitized parcels; VOLUME= 0.018 megabytes)
- 4 data themes (MAX=4)
- 2 groups concerned
about the results of the request (CONCERNS=2)
- 10% chance that the
results of the request would end up in an adversarial hearing (LIKELIHOOD=10)
The gross effectiveness
benefits were conservatively estimated for each blueline request in the
Land Records Department at $140. The interviewees indicated that a simple
map request like this would require about an hour's time. The approximate
cost for this type of request is $25, resulting in a net effectiveness benefit
of $115 per request. The benefit cost ratio for the group making the request
is 5.6. Summed across 624 requests per year, the net annual effectiveness
benefit for this type of request is at least $71,760. Many requests come
from within the city/county governments or for Superfund-related data, so
those effectiveness benefits accrue to those responsible for funding and
maintaining BSB's GIS.
A number of assumptions
must be again made in order to estimate the effectiveness benefits from
the typical request for maps from the Planning Department. Based on the
interview, the following pieces of information were used to estimate the
model variables:
- Application run 520
times per year (FREQUENCY=520)
- 3 map sheets at 1:2400
scale (EXTENT=3)
- Calculate average
parcel size in county by dividing county area by 22,178 parcels (0.032
mi2/parcel)
- Estimate total number
of parcels per sheet by dividing the average number of square miles on
a sheet (0.6) by 0.032 mi2/parcel (19 parcels per sheet)
- Estimate volume of
data required to produce 3 map sheets by multiplying 57 parcels by .018
megabytes per parcel (VOLUME = 1.03 megabytes)
- 4 data themes (MAX=4)
- 3 groups concerned
about the results of the request (CONCERNS=3)
- 15% chance that the
results of the request would end up in an adversarial hearing (LIKELIHOOD=15)
The gross effectiveness
benefits for a Planning Department map request using these variables are
probably unreasonably high at $3580. The numbers could probably be refined
by a more in-depth interview to better determine what information is used
to satisfy the typical request. However, it might also be reasonable to
assume that the person requesting the map is not interested in every parcel
on a given map sheet. For instance, a request from ARCO for a map of streamside
tailings might show a wide area adjacent to the Clark Fork River, but the
only parcels that are really important are those near the river. If one
assumes that 10% of the parcels on a given map are important and all other
variables the same as shown above, the model predicts a gross effectiveness
benefit of $761 for this request.
This type of map request
might take about a day to fulfill, resulting in a cost of $200, assuming
$25 per hour for labor and plotter time as shown for the Land Records Department
maps. The net effectiveness benefit would then be $561 and the benefit cost
ratio would be 3.8. Summed across 520 such requests per year, the net annual
effectiveness benefit for the Planning Department would be $291,720. Adding
in the Land Records Department results estimates a net annual effectiveness
benefit of land records mapping of $363,480, or $10.71 per capita annually.
Cost
benefit summary
The net annual benefits
of automated land records searches can be determined by adding up the net
efficiency benefits for verbal ownership requests, net effectiveness benefits
for Land Records Department map requests and net effectiveness benefits
for Planning Department map requests. The net annual benefit of these GIS
applications is equal to $377,400 or $11.12 per capita annually.
3.3 Lewis & Clark
County GIS implementation
The information on Lewis
& Clark County GIS was provided by an interview with R.J. Zimmer, a
GIS analyst for the county.
3.3.1 Overview of
Lewis & Clark County GIS
System
description
Lewis & Clark County
is still in the process of implementing GIS. GIS activities have been going
on for about 3 years, but there has not been a lot to show for their efforts
so far. However, the County has recently been working on a Strategic Plan
to better coordinate their GIS efforts. The City of Helena has also recently
agreed to join the GIS effort.
Currently, Lewis &
Clark County maintains 2 Arc/INFO and 1 ArcView licenses, with 4-5 more
ArcView licenses planned for the coming year. Mr. Zimmer and an intern are
working with the system, in addition to a person in the assessor's office
working on parcel mapping.
List
of applications
Lewis & Clark County's
GIS efforts to date have been more data-driven than process-driven. They
are currently identifying and prioritizing their data needs before they
begin assessing applications for the data.
For most people in the
county, the GIS is so far a tool that will provide them with better access
to data. The next step will be for personnel to realize that GIS is also
an excellent mapping and analysis tool.
The first applications
for Lewis & Clark County GIS will be:
Some maps have already
been completed, including a watershed boundary map and a map showing the
locations of paved and unpaved roads in the county
- Rural addressing
- Flood plain delineation
Lessons
learned
- Must be able to show
GIS outputs early in the process or administrators making funding decisions
will lose faith
- Communication between
groups is critical, particularly about such matters as the great time
and money required to produce data
- Communication with
other local governments also very important in order to avoid reinventing
the wheel on projects like rural addressing
- GIS should be pushed
to the desktop; personnel should be able to produce their own GIS outputs
because they have a better understanding of the data
- Personnel must see
beyond GIS as simply a better way to access data
3.3.2 Cost/benefit
information
Cost and benefit information
was not discussed in the interview. The implementation is in the early stages
and no applications were available for further discussion.
3.4 Montana Department
of Transportation (MDT)
The information for
the MDT case study was obtained by interviewing Mr. Skip Nyberg, Information
Specialist III.
3.4.1 Overview of
MDT GIS
System
description
MDT first implemented
GIS in 1985. The system currently includes 10 floating ArcView licenses
and 1 Arc/INFO license. More licenses will be added as more personnel begin
to use the software. MDT is actively pursuing a policy of encouraging the
end user to become comfortable with ArcView and use its capabilities. MDT
currently has 1.2 FTE devoted to GIS support for the agency.
List
of applications
MDT is working with
Travel Montana to make updated road report data available at information
kiosks and eventually on the web. Automatic weather feeds will be included.
Roads will be tested
every 1/10 to 1/100 of a mile to determine the condition of the road. The
information will be used in prioritizing road repairs.
The Planning Department
must determine how money will be divided among 5 districts in the state
for road repairs. The project analysis incorporates the available data on
road conditions and financial considerations to decide which projects will
be undertaken in a given year.
Lessons
learned
- Better accuracy of
data corresponds to better decision-making
- ArcView requires
a steep learning curve; GIS personnel are attempting to automate mapping
processes so that not everyone needs to become ArcView experts
- Data redundancy can
kill you; sophisticated databases with cross-linked tables are critical
for organizations with large amounts of data
- Don't over-collect
data; only get the data really needed
- MDT's Environmental
Bureau data needs to be accessible to other MDT Bureaus so that environmental
concerns of a road project are better defined
- GIS should be more
than a cartography tool; it should also be used to help make better decisions
Recommendations
for other state agencies
- Oracle databases
are the way to go, particularly with a spatial database engine add-on
- MDT's data can only
be available to agencies using Oracle databases
- ArcView must be available
to the end user; sophisticated GIS support personnel must also be available
within the department to help with GIS and data management
3.4.2 Cost/benefit
information
MDT's GIS applications
did not fit well into the Gillespie (1997) model. The primary reason that
they don't work is that MDT's applications are almost strictly linear projects,
so it is difficult to determine an areal extent for the application. Another
difficulty is that some of them (i.e. road reports) are run continuously
statewide; it is difficult to determine what a single "run" of the
application consists of.
Costs
Detailed cost information
was not discussed in the interview.
Efficiency
benefits
One general type of
efficiency benefit described by Mr. Nyberg was the labor savings involved
in the project analysis application. Prior to GIS, this project required
2-3 people over a month. Now, this analysis can be conducted in a matter
of hours
Effectiveness
benefits
Efficiency benefits
were not calculated for MDT applications.
3.5 Montana State
Library Natural Resource Information System (NRIS)
The information for
the NRIS case study was obtained by interviewing Mr. Jim Stimson, NRIS director.
3.5.1 Overview of
NRIS GIS
System
description
The Montana State Library
implemented GIS through NRIS in 1989. NRIS maintains 10 GIS licenses, used
by about 15 personnel. About 500 databases are available for GIS applications.
NRIS provides a wide variety of GIS services, including providing GIS analyses
for private and government agencies and serving as a clearinghouse for the
state of Montana's natural resources data. State agencies utilizing NRIS'
contract GIS services include the Departments of Environmental Quality,
Fish, Wildlife & Parks and Public Health & Human Services. As some
of these agencies begin to consider implementing GIS in-house, NRIS also
serves an advisory role in selecting and purchasing software, maintaining
licensing agreements, building applications and providing training.
List
of applications
- Watershed analysis
- Interactive well-finder
on the web
- Drought monitoring
- Natural Heritage
Program
- Underground Storage
Tank (UST) analysis
Lessons
learned
- Internet GIS applications
are very successful for 4 main reasons;
- Users are more
comfortable with web browsers than GIS software
- They require little
technical support
- They reduce the
number of requests that have to be handled by agency personnel
- They provide an
easy means for tracking use, which in turn can be used to demonstrate
the benefits of the applications
- Attitude of management
must get beyond the idea that GIS is a program for making nice maps
- Attitude of management
can suffer from complicated issues related to GIS implementation
Example: Implementing
GIS on a new operating system (i.e. Unix) with expensive workstations (i.e.
Sun workstations) can make it difficult to keep management on board
- Critical to demonstrate
to management that GIS makes employees more efficient and more effective;
it is especially helpful to show quantitative monetary benefits
- GIS is just another
tool for improving decision-making
Example: legislative
and agency level committees responsible for determining statewide policies
use Drought and other maps
- GIS training requirements
are intense; it can take a year and a half to get a programmer/analyst
up to speed
- Data is very expensive
to generate and maintain
- GIS pilot studies
are very important to identify what works and what doesn't
- Web applications
also helpful to NRIS in justifying GIS expenditures because numbers of
users and web sessions are easy to determine
- Sometimes it is more
effective for an agency to use an outside entity for developing databases
and GIS applications; easier for the outside entity to see the bigger
picture about how databases will fit in with an agency's existing databases
Recommendations
for future GIS implementation in Montana State government
- It makes sense for
agencies to have some GIS capability in-house. There are different levels
of GIS deployment that can be considered. Some agencies may need to have
highly qualified GIS programmer/analysts in-house, others may choose to
contract with another entity for that level of service. For other agencies
it may be more efficient to deploy a desktop GIS application like ArcView
or ArcExplorer.
- Agencies' decision
whether or not to implement GIS in-house should depend partly on the level
of GIS sophistication required (Heavy-Arc/INFO; Moderate- ArcView; Light-ArcExplorer)
- It would be helpful
for someone to itemize the capabilities of the various GIS products (ArcView,
Arc/INFO, etc.) so agencies could compare their needs and select software
- Believes that NRIS'
contract GIS services may diminish with time, but should maintain role
as a clearinghouse for all of Montana's natural resource data
- Believes that establishing
a separate clearinghouse for non-natural resource information may not
be a realistic model for managing GIS data in a cost-effective manner.
Such a model should be examined closely to determine if it really makes
sense and is cost effective.
- A data clearinghouse
is important for agencies considering implementing GIS because it can
cut down on their initial costs of data generation and storage and provide
higher speed delivery of data
3.5.2 Cost/benefit
information
Mr. Stimson provided
cost benefit information on all of the applications listed in Section 3.5.1.
Two of the applications were chosen for further study with the Gillespie
(1997) model: watershed analysis and interactive well finder. The watershed
analysis application was completed for the Natural Resource Conservation
Service (NRCS). It allows them to choose a watershed of any extent within
the state and characterize and analyze the land use, vegetation and soils
types contained within the watershed. Among other things, the application
can be used for calculating runoff and sediment loads from a watershed.
The well finder application allows Internet users to locate wells within
a given area and obtain information on the productivity and depth of those
wells.
The watershed analyses
were conducted to some extent prior to the development of GIS. By Gillespie's
(1994) definitions of efficiency benefits, watershed analyses would produce
an efficiency benefit. Watershed analyses also produce effectiveness benefits,
however, because GIS allows many more of the analyses to be done and also
produces better analyses. Furthermore, the GIS application makes possible
analyses of larger watersheds that could not be done feasibly without the
tool. For the purposes of this study, only the effectiveness benefits were
considered because the GIS analyses were so much better than the previous
outputs. The watershed analyses are currently conducted approximately 18
times per year.
Like the watershed analyses,
the information on wells in a particular area could be obtained prior to
GIS. However, no information was available on the frequency of use of that
application before GIS was available. It is quite evident that the GIS application
allows many more users to determine that information. The application was
therefore assumed to produce only effectiveness benefits for this report.
The interactive well finder application is run on approximately a daily
basis.
Costs
Cost information was
not provided for the system as a whole. Cost information was provided per
incident of each of the applications, both with and without GIS.
Prior to GIS, a watershed
analysis would cost on the order of $3000 for a small watershed. With GIS,
the analysis costs an average of $65.
To obtain well information
on an area without the GIS application would cost an average of $300. The
well finder GIS application costs nothing to run because the user can do
it over the Internet.
Efficiency
benefits
As mentioned previously,
efficiency benefits were not analyzed with the Gillespie (1997) model for
either the watershed analysis or the interactive well finder. However, based
on the cost information provided by Mr. Stimson, it is possible to calculate
the efficiency benefit per incident of those applications. The GIS watershed
analysis produces an efficiency benefit of 98%, while the interactive well
finder saves 100% of the pre-GIS costs.
Effectiveness
benefits
The Gillespie (1997)
model was applied to the watershed analysis application to determine the
effectiveness benefits. The interview answers provided information on the
typical watershed analysis. The following parameters were used as typical
values. As with many model applications, it was necessary to use some judgment
on the chosen values in order to conservatively estimate the benefits and
still remain consistent with the interview findings:
- Application run 18
times per year (FREQUENCY=18)
- Areal extent of 600
mi2 displayed at 1:24K scale (11 map units, EXTENT=11)
- Volume of data: 35
megabytes (VOLUME=35)
- Number of data themes:
5 (MAX=5)
- Number of groups
concerned: 5 (CONCERNS=5)
- Likelihood of use
in adversarial hearing: 25% (LIKELIHOOD=25)
Using the typical numbers
for the parameters, the gross effectiveness benefits per occurrence of the
application are $7910. The gross annual effectiveness benefits of the application
are $141,210. The benefit cost ratio from the application appear to be outlandishly
high (i.e. 122). However, if one realizes that the cost of producing the
application prior to GIS was at least $3000, the number is not unreasonable.
If the gross effectiveness benefits were not at least $3000, the analysis
would never have been performed manually. If the cost of obtaining the remote
sensing data had been included in the cost of running the application, the
benefit cost ratio would have been much more in line with reasonable expectations.
The Gillespie (1997)
model was also applied to the interactive well finder application to determine
its effectiveness benefits. The following parameters were used in the model:
- Application run 365
times per year (FREQUENCY=365)
- One 1:24K map sheet
viewed in the typical incident of the application (EXTENT=1)
- Volume of data: 35
megabytes (VOLUME=35)
- Number of data themes:
3 (MAX=3)
- Number of groups
concerned: 4 (CONCERNS=4)
- Likelihood of use
in adversarial hearing: 5% (LIKELIHOOD=5)
The gross effectiveness
benefits per incident of the interactive well finder are $646. The cost
of the application (not including the cost of generating and maintaining
the data) is $0, so the net effectiveness benefits are also $646. The net
annual effectiveness benefits are $235,790. With a cost of $0, it is impossible
to determine a benefit cost ratio, although the number would have been reasonable
if the data costs had been included in the application. However, the gross
effectiveness benefits of $646 are in line with the $300 cost of doing the
analysis without GIS. As in the case of the watershed analyses, the well
finder analysis would never have been conducted manually if the effectiveness
benefits did not exceed the cost of producing the output.
Cost
benefit summary
The two GIS applications
studied for NRIS produce a net annual effectiveness benefit of $377,000.
Benefit cost ratios for the two applications are somewhat meaningless in
this case. The important concept to realize is that the applications continue
to generate a great deal of effectiveness benefits even though little cost
goes into each incident of the applications.
3.6 Montana Department
of Environmental Quality (DEQ) Remediation Division
The information for
the DEQ case study was obtained by interviewing Mr. Jim Hill, director of
the Remediation Division's Technical Services Bureau.
3.6.1 Overview of
DEQ Remediation Division GIS
System
description
Montana DEQ began using
GIS in 1988. Much of DEQ's GIS work has been performed by NRIS, which was
established in 1988 to deal with Superfund data. Up to this point, the programs
operating under DEQ have essentially compiled databases and GIS applications
that suit their own needs, rather than contributing to an enterprise-wide
system. As a result, communication is poor between databases and much repetitive
data is maintained.
DEQ has begun conducting
studies in-house and with BDM, Inc. in order to begin moving the organization's
IT capabilities (including GIS) towards an enterprise-wide system. A great
deal of effort will be required to convert more than 30 database platforms
to some compatible standard and to implement GIS so that the majority of
those services can be provided in-house. The IT Planning Team in the DEQ
is recommending a multi-tier approach to IT. By this, they seek to establish
an enterprise-wide system but they allow individual programs to make their
own decisions about GIS implementation. A trend of increasing appreciation
for compatibility should insure that certain minimum standards are met in
all programs. Ideally, DEQ will hire a GIS coordinator who will be responsible
for setting standards that all programs' applications and data should conform
to.
Applications
DEQ Remediation division's
GIS applications are primarily one-time applications. For instance, GIS
might be used to calculate the volume of material to be removed from a tailings
pile. After that application is run, the work is performed and there is
no need to re-run the application. No information was provided about other
applications.
Recommendations
for DEQ's GIS needs
- Everyone in DEQ needs
to work towards the enterprise model and standardization, but DEQ can't
afford to delay GIS implementation until standards are set and GIS personnel
are hired
- DEQ should hire GIS
coordinator as soon as possible to insure compatibility of data and GIS
applications
- Communication must
continue to be excellent between GIS coordinator, DEQ bureaus, DEQ's IT
Planning Team and IT technical users group, DEQ management
- Training must be
a coordinated effort; GIS users must have proficiency at basic computer
skills (directory structures, etc.)
3.6.2 Cost/benefit
information
Costs
DEQ began spending money
in 1988, establishing NRIS to maintain the spatial Superfund data. The Remediation
Division spent $300,000-$500,000 annually through the early 1990's and $100,000-$200,000
annually since then.
Efficiency
benefits
No information was provided
about efficiency benefits.
Effectiveness
benefits
Quantitative effectiveness
benefits were not calculated for the DEQ Remediation Division. One important
type of effectiveness benefit described by Mr. Hill is the future ability
of DEQ to integrate information from different bureaus. For instance, it
would be important for DEQ personnel permitting a subdivision to have information
about other DEQ sites in the area, such as a hazardous waste remediation
project. Currently, those types of information are separated along bureau
lines.
DEQ will also be able
to serve the public much better once all the databases can be interfaced
through a GIS. The public will be able to call up the DEQ and quickly obtain
information about any environmental problems associated with a particular
site. The DEQ does not presently have the ability to answer those types
of questions.
3.7 DEQ Environmental
Management Bureau
The information on DEQ
Environmental Management Bureau (of the Permitting and Compliance Division)
was obtained by interviewing Tom Ring, Environmental Specialist and Nancy
Johnson, Environmental Impact Specialist. Mr. Ring and Ms. Johnson are both
part time GIS analysts and the primary personnel in the Environmental Management
Bureau using GIS.
3.7.1 Overview of
DEQ Environmental Management Bureau GIS
System
description
The Environmental Management
Bureau began using GIS in 1993. The system originally ran on a Sun workstation,
but has recently been converted to run more economically on a Windows NT
Workstation. The system consists of 1 Arc/INFO, 1 TIN, 1 GRID and 1 NETWORK
license.
GIS has been used as
a tool for assessing impacts of proposed mines, water resources developments,
a wind farm and linear facilities like powerlines and pipelines. GIS has
also been used as a tool for comparing alternative routes for linear facilities.
List
of applications
The following list of
applications are some of the ways GIS has contributed to determining the
impacts of the projects mentioned previously.
Example: Viewshed analysis
for proposed mines
Example: Potential fishery
impacts of a proposed pipeline
Lessons
learned
- Up front training
investment is critical
- Well-trained system
maintenance personnel also critical
- GIS has become less
of a tool for GIS experts and more of a tool at the desktop of resource
specialists
- GIS is just another
tool for decision makers; there should be no expectation that GIS will
make decisions
Recommendations
for DEQ's GIS needs
- Critical for DEQ
as a whole to adopt uniform databases (currently 30+ different database
platforms within the agency)
- Programs within DEQ
must communicate better so that it easier to determine all types of historic
activities for a particular site (i.e. subdivisions, abandoned mine reclamation
work, hazardous waste facilities)
- Programs should develop
and use their own GIS applications, but technical support should be available
department wide (either supplied in-house or through a group like NRIS)
3.7.2 Cost/benefit
information
Cost information is
provided below for the entire system. More detailed cost benefit information
is provided for the Gillespie (1997) model for the application of viewshed
analyses.
Viewshed analyses are
conducted for high visibility projects that require DEQ permits, such as
mines or a windfarm. Viewshed analyses have been conducted on approximately
an annual basis since 1993. Viewshed analyses generate only effectiveness
benefits because they were very crude prior to GIS.
Costs
The current GIS costs
in the Environmental Management Bureau are around $4000 per year, including
hardware, software and training. The labor costs are quite small because
GIS takes up a small portion of the analysts' time. Expenditures were greater
in previous years due to the much greater costs of purchasing Sun workstations.
It is possible to estimate
the cost per incident of generating a viewshed analysis. The analysis takes
a total of up to 40 hours of an FTE, combining time of summer interns and
GIS analysts. The average salary was estimated at $20,000. Assuming a benefits
multiplier of 1.32 (used in the Missoula Implementation Plan), the total
annual cost of that employee would be $26,400. The total cost of 40 hours
labor is then $530. Finally, some fraction of annual system costs should
be added on to determine the total cost of the application. If one attributes
10% of the annual GIS budget (not including personnel) to a viewshed analysis,
the total cost of a single viewshed analysis would be about $1000.
Efficiency
benefits
Efficiency benefits
were not discussed for any GIS applications.
Effectiveness
benefits
The Gillespie (1997)
model was applied to the viewshed analysis application to determine the
effectiveness benefits. The interview answers provided information on a
typical viewshed analysis, which combined information from viewshed analyses
of the McDonald Gold Project near Lincoln and the proposed Asarco Rock Creek
Mine.
The following parameters
were suggested as typical values:
- Application run 1
time per year (FREQUENCY=1)
- Number of map units:
6 quads (EXTENT=6 )
- Volume of data: 9
megabytes (VOLUME=9)
- Number of data themes:
3 (MAX=3)
- Number of groups
concerned: 6 (CONCERNS=6)
- Likelihood of use
in adversarial hearing: 50% (LIKELIHOOD=50)
Using the typical numbers
for the parameters, the gross effectiveness benefits per occurrence of the
application are $4000. This figure is also the annual gross effectiveness
benefit from a viewshed analysis because they are completed approximately
once a year. This estimate of the gross effectiveness benefits results in
a benefit cost ratio of 4.0.
3.8 DEQ Industrial
& Energy Minerals
The information on DEQ
Industrial and Energy Minerals Bureau (of the Permitting and Compliance
Division) was obtained by interviewing Loretta Reichert, Information Systems
Specialist.
3.8.1 Overview of
DEQ Industrial & Energy Minerals Bureau GIS
System
description
The Industrial &
Energy Minerals Bureau established GIS in 1992. The original funding was
a $250,000 grant from the USGS to create base maps, purchase a workstation,
licenses and training, and fund GIS personnel. The system originally ran
on the Unix platform but is evolving to run on a Windows NT workstation.
Currently, the system includes 1 ArcView license, 1 local Arc/INFO license
and one shared Arc/INFO license provided by the federal Office of Surface
Mining (OSM) and 1 Earth Vision license also supplied by the OSM. OSM provides
other support as well, including 2/3 of Mrs. Reichert's salary.
GIS is a tool for permitting
of coal mines and assessing reclamation bonds, as well as maintaining all
the data related to the coal mines.
List
of applications
- Volumetric analysis
for coal mine reclamation
- Reclamation plan
analysis
Example: Assessing the
potential for revegetation based on slope, aspect and vegetation type
- Database of groundwater
wells in vicinity of coal mines
Lessons
learned
- Developing databases
takes a longer time than expected
- Better to have a
dedicated GIS person than to train new people who may not stay long enough
to justify the training expenditures
- "If you build
it, they will come"- new GIS applications arise once the system is
established
- Better relationships
have resulted with coal mining companies because DEQ has helped them to
clean up data through GIS
- AutoCAD data doesn't
always go into Arc/INFO smoothly
- GIS greatly improves
the ability to establish an electronic permitting system
- GIS is a necessity
to provide a scientifically sound analysis of mine reclamation
- Some tasks are still
easier to do by hand than to use GIS
Recommendations
for DEQ's GIS needs
- DEQ must implement
a centralized GIS structure, but programs must be able to maintain their
individual applications
Example: OSM provides
much of the funding for the Industrial & Energy Materials Bureau's GIS.
Those tools can only be used for coal mining projects.
- Important for personnel
doing the GIS work to be familiar with the material and the DEQ program
conducting the work
- GIS personnel dedicated
to a particular DEQ program will have a better vision of future GIS needs
for that program
3.8.2 Cost/benefit
information
Cost information is
provided for the system as a whole. More detailed cost and benefit information
is provided for two GIS applications: volumetric analysis and reclamation
plan analysis.
Volumetric analysis
is the process by which cut and fill volumes are calculated in order to
establish reclamation bonds. The application is used approximately once
a month. For this cost benefit analysis, the volumetric analysis is divided
into two parts: volumetric calculations that generate efficiency benefits
and difference maps that generate effectiveness benefits. The net benefit
of GIS for volumetric analyses is then the sum of the efficiency and effectiveness
benefits.
Reclamation plan analysis
is a GIS application in which the potential for revegetation of coal mining
excavations is assessed based on the slope and aspect of the ground and
the type of vegetation. This information will then be used in decisions
to release reclamation bonds. This application only generates effectiveness
benefits because it could not be done prior to GIS.
Reclamation plan analyses
are a new GIS application for the Industrial & Energy Materials Bureau.
It is not clear yet how often this application will be used, what level
of resources will be required to complete them and how they will be used
in the process of releasing reclamation bonds. The uncertainties inherent
in this application make the model predictions quite uncertain as well.
Costs
The annual GIS expenditures
for the Industrial & Energy Materials Bureau include a $7000 support
contract through NRIS to provide hardware and software maintenance, plus
roughly $2000 per year for workstation upgrades, plus half of Mrs. Reichert's
time at a salary of $30,000.
A volumetric analysis
requires approximately 2 days of an engineer's time and 1 day of Mrs. Reichert's
time. The engineer's annual salary is around $35,000. Assuming a benefits
multiplier of 1.32, 2 days of the engineer's time is worth $370 and one
day of Mrs. Reichert's time is worth $160. The total cost of a volumetric
analysis is $530 plus some percentage of the annual system costs of $9000.
As a rough guess, one could assume that no more than 4% of the system cost
should be attributed to a single volumetric calculation, resulting in an
additional cost of $360. The ballpark 4% figure was estimated by first realizing
that the volumetric analysis is performed once a month. If volumetric analyses
were the only application, each occurrence would be responsible for 8% of
the annual cost. Assuming quite conservatively that volumetric analyses
comprises half of the annual GIS budget, 4% of the annual costs could be
attributed to each occurrence of the volumetric analysis. The total cost
of the analysis is then $890.
It is also possible
to estimate the cost of volumetric calculations in the absence of a GIS.
Mrs. Reichert indicated the analysis formerly required 20 days of an engineer's
time. Assuming an annual salary of $35,000 and a benefit multiplier of 1.32,
the cost of the analysis would be $4000.
The costs of conducting
a reclamation plan analysis are now discussed. Only one reclamation plan
analysis has been conducted to date. The project consumed approximately
6 months of Mrs. Reichert's time. The cost of this time is worth approximately
$19,800 using a benefit multiplier of 1.32.
Efficiency
benefits
The volumetric calculations
generate efficiency benefits because those calculations were performed prior
to GIS. The following pieces of information were obtained in the interview
or were assumed in order to estimate all variables in the efficiency model:
- Application run 12
times per year (FREQUENCY=12)
- Areal extent and
map scale: 5500 acres @ 1:4800 scale (EXTENT= 5 map units)
- 4 data themes (MAX=4)
- 6 groups concerned
about the results of the analysis (CONCERNS=6)
- Not very likely that
the results will end up in an adversarial hearing (LIKELIHOOD=10)
- Application concerned
with the value of the land itself (LAND=1)
- Manual methods to
perform volumetric analysis cost less than $20,000 (COST=0)
With these variables,
the efficiency model predicts an efficiency benefit of 57%. As in the Butte-Silver
Bow analysis of efficiency benefits, the result was sensitive to the choice
of the somewhat arbitrary LAND variable. With a value of 0 for LAND, the
efficiency savings would increase to 75%.
In this case, there
is a more appropriate way to determine the efficiency savings of volumetric
calculations due to GIS. As mentioned in the previous section, the analysis
costs $890 with GIS and $4000 prior to GIS. This analysis is assuming that
all of the analysis costs can be attributed to the volumetric calculations
and not to the production of difference maps. From the interviews, it appeared
that the difference maps were a product that essentially fell out of the
volumetric calculations and didn't require much extra work. Thus, GIS results
in a net efficiency benefit of $3110 or 78% of the manual cost for the volumetric
calculations. It is interesting to note that this value nearly corresponds
to the model prediction when LAND=0. Based on the measured estimate (as
opposed to the predicted estimate) of the net efficiency benefit, the net
annual efficiency benefit of GIS for the volumetric calculations is $37,320
($3110 per analysis x 12 analyses per year).
Effectiveness
benefits
The Gillespie (1997)
model is now used to estimate the effectiveness benefits resulting from
the difference maps produced during the volumetric analyses. The net benefits
of GIS for the application of volumetric analyses can then be estimated
from the sum of net efficiency benefits for volumetric calculations and
net effectiveness benefits for difference maps.
The pure effectiveness
benefits model is now used to estimate the net effectiveness benefits of
the difference maps. The same variables were used as above for determining
the efficiency benefits of the volumetric calculations. In addition to those
variables, the effectiveness benefit model requires a value for VOLUME,
or the total volume of data required for the analysis. A value of 7.5 megabytes
for VOLUME was reported by Mrs. Reichert.
The effectiveness benefits
model estimated a value of $1790 per occurrence of difference map production.
Recall that this value is a gross benefit by definition. However, in the
previous section it was described that the difference maps resulted in essentially
no additional cost. Thus, the net annual effectiveness benefit for difference
maps is $10,750 (1790 x 6 difference maps per year).
The effectiveness benefits
model is now also used to assess the application of reclamation bond analyses.
The following pieces of information were used in the effectiveness benefits
model.
- Application run 1
time per year (FREQUENCY=1)
- Areal extent and
map scale: 5500 acres @1:4800 scale (EXTENT=5 map units)
- 6 data themes (MAX=4)
- 6 groups concerned
about the results of the analysis (CONCERNS=6)
- Reasonably likely
that the results will end up in an adversarial hearing (LIKELIHOOD=60)
- 52 megabytes of data
required for the analysis (VOLUME=52)
The effectiveness benefits
model predicted gross effectiveness benefits of $23,320 per incident of
the reclamation plan analysis. Compared with a cost per incident of $19,800,
the application produces a net effectiveness benefit of $3520. A benefit
cost ratio of 1.2 results from the application. The ratio may well increase
as the process becomes better defined and is used more frequently.
Cost
benefit summary
It is now possible to
determine the net annual benefits for the volumetric analyses. The volumetric
calculations resulted in a net efficiency benefit of $37,320. The difference
maps resulted in a net effectiveness benefit of $10,740. The net benefit
is therefore $48,060, compared with a total cost of producing 12 volumetric
analyses of $10,680. The volumetric analysis application generates a benefit
cost ratio of 5.5.
As stated previously,
the reclamation plan analysis resulted in a net efficiency benefit of $3520
and a benefit cost ratio of 1.2. Between the two applications, GIS produces
a net effectiveness benefit of $51,080 and a benefit cost ratio of 2.7.
The spreadsheet used
to calculate the benefits for these applications is attached electronically
to this document as an Excel spreadsheet in Appendix C. Those results are
slightly different than the results reported here for the efficiency benefits
from volumetric calculations. The spreadsheet reports the results of the
Gillespie (1997) model for efficiency benefits. This analysis used a direct
measure of the efficiency benefits in summarizing the system benefits.
3.9 Montana Department
of Administration Information Services Division
The information for
the Cadastral Mapping Project case study was obtained by interviewing Mr.
Stu Kirkpatrick, GIS services section manager for the Department of Administration's
Information Services Division (ISD).
The effort to develop
the land ownership database is called the Cadastral Mapping Project. It
is the only GIS application in ISD that this report will focus on.
3.9.1 Overview of
the cadastral mapping project
Project
description
The Cadastral Mapping
Project is a cooperative public/private partnership to produce a digital
land ownership database that can be accessed through GIS. The project is
managed by the Information Services Division of the Department of Administration.
The project receives funding from state and federal government agencies
and private sector groups. The data will be available for the public and
private sectors and will contribute to a great variety of applications.
List
of applications
These are some of the
applications of digital land ownership data that were provided by Mr. Kirkpatrick.
- Property maps
- Disaster and emergency
planning
- Automated tax assessment
using other data sets such as soil, topography and climate to describe
land productivity
- Right-of-way assessments
- Internet property
research
- Growth analysis
- Wildlife habitat
monitoring and protection
- Resolving areas of
public/private conflict such as hunting and fishing access
This list of applications
of the land ownership for local governments was provided during the interviews
with Butte-Silver Bow personnel and Doug Burreson from Missoula County.
- Tax assessment- Locating
untaxed parcels
- Establish institutional
controls on land use near Butte Superfund sites
- Zoning/master planning
- Address information
can be included in enhanced 9-1-1
- Weekly ownership
updates for county government
- Septic permitting
system
- Automated property
owner notification
- Automated permit
and development tracking
Lessons
learned
- Multiple partner
projects move very slowly
- Political issues
are more difficult to overcome than are technical issues
3.9.2 Cost/benefit
information
Cost information is
readily available on the entire cadastral mapping project. The project was
not particularly well suited for analysis with the Gillespie (1997) model
because it is essentially a database and not a GIS. Another difficulty with
applying the Gillespie (1997) model is the fact that the project is just
underway whereas the Gillespie (1997) model was developed to analyze systems
that are already in place.
Despite these caveats,
the Gillespie (1997) model was used to analyze the benefits of the cadastral
project. The project was divided into two distinct applications for the
purposes of the study. The first application is the act of creating the
database of land ownership records. This application partially uses an automated
process and produces an efficiency benefit over the manual methods used
previously to digitize parcels. The efficiencies inherent in this application
can be well quantified without the use of the model.
The second application
is the act of accessing the digital land records. These benefits were described
previously in Section 3.2.2 for Butte-Silver Bow. Both efficiency and effectiveness
benefits resulted from the accessing of digital land records. Information
is not available to make statewide estimates of the benefits that can be
expected. However, some attempts will be made in this section to estimate
the benefits throughout the state based on the Butte-Silver Bow results.
Costs
The costs of building
the database are estimated currently at around $4 million, with 50% coming
from the private sector, 25% from state government funds and 25% from federal
government funds. Furthermore, the annual maintenance costs for the data
have been estimated at $300,000-$500,000.
Efficiency
benefits
The efficiency benefits
from the automated parcel digitization application can be calculated by
comparing the costs of generating parcels with and without this process.
The International Association of Assessing Offices has adopted a standard
of ten minutes per parcel generated. A normal person might work efficiently
for 5/6 of the day, resulting in creation of 40 parcels per day. Assuming
a salary of $10/hr and a benefit multiplier of 1.32, results in a cost of
$2.64 per parcel.
Currently, the automated
process for digitizing parcels from the Department of Revenue's CAMA database
results in the creation of 60 parcels/hr. Assuming the same work efficiency
and salary, results in a cost of $0.26/parcel or a 90% efficiency benefit.
It is difficult at this
point to determine how many parcels in Montana can be created using the
automated process. Mr. Kirkpatrick estimated that about 350,000 parcels
could be generated using the automated methods. The net efficiency benefit
of generating these parcels would be $831,600.
An additional efficiency
benefit of the land records database will result when counties or other
agencies access the data. The Butte-Silver Bow case study estimated a net
annual efficiency benefit of $13,920, or $0.41 per capita. A number of assumptions
were required to abstract these results to the entire state.
It is probably reasonable
to assume that there are fewer requests per capita in rural eastern Montana
counties than in Silver Bow County. As a best guess, the counties were lumped
into 4 population groups:
- Group A: Less than
5000 residents (21 counties)
- Group B: Between
5000 and 10,000 residents (15 counties)
- Group C: Between
10,000 and 20,000 residents (11 counties)
- Group D: Greater
than 20,000 residents (9 counties)
Silver Bow County is
in Group D, so all 9 of those counties were assumed to gain the same efficiency
benefit per capita. Groups C, B and A were assumed to gain 75%, 50% and
25%, respectively of Silver Bow county's per capita benefit.
With these assumptions,
the net annual efficiency benefit for the state would be $277,150. It should
be pointed out that this is the efficiency benefit for simple land records
requests at county governments. It does not include efficiency benefits
for other government agencies.
Effectiveness
benefits
Quantifying the monetary
effectiveness benefits of digital land ownership data is an extremely difficult
process because the data will be used for so many different purposes. The
following list demonstrates qualitatively some effectiveness benefits that
have already occurred.
- Add value to other
data sets
Example: Makes Department
of Revenue's forestry inventory database accessible
- Business development
opportunities
Example: Helped locate
ASiMI Silicon Manufacturing Complex in Butte
- Better emergency
services
Example: Flathead County
developed flood evacuation and utility shutoff plans
- More efficient tax
assessment
Example: Analysis of
Silver Bow County Mosquito Control District located 25 untaxed parcels
- Improved coordination
between participating groups
It is also possible
to quantitatively estimate the effectiveness benefits of the land records
database based on the findings of the Butte-Silver Bow case study. In that
study, net effectiveness benefits were estimated as $363,480 annually, or
$10.71 per capita annually. Using the same population groups and assumptions
as in the efficiency benefits, the net annual effectiveness benefit in the
state was estimated to be $7.24 million. Again, this figure represents the
effectiveness benefits of land records maps produced by county governments.
It does not include land records mapping in other government or private
agencies.
Cost
benefit summary
The net benefit of the
land records database is equal to the sum of the efficiency benefits in
generating the database with the automated methods, plus the efficiency
and effectiveness benefits resulting from people accessing the completed
database through county governments or other agencies. The efficiency benefits
that result from the process of developing the database are reported as
a total benefit of $831,600, not an annual benefit. Therefore, that number
cannot be readily added onto the annual savings estimated for land records
requests from the Butte-Silver Bow case study.
The net annual benefit
of statewide land records requests at county governments is estimated as
$7.52 million ($11.12 per capita). This does not include the lump sum savings
in developing the database, nor does it include land records research conducted
elsewhere besides the county governments. Furthermore, there is a great
deal of uncertainty inherent in the Butte-Silver Bow estimates and in estimating
the % of per capita benefits at other counties based on their population.
However, the assumptions in this and all cost benefit calculations in this
report were made as conservatively as the data would support.
The net annual benefit
of the land records database of $7.52 million, or $11.12 per capita, might
seem like a very high number, especially considering that the figure does
not include the benefits which would accrue from people accessing the data
elsewhere besides the county government. However, it is useful to put this
figure in perspective of the Larsen Report from Wisconsin, which is summarized
in Appendix A. Back in 1978, local, state and federal agencies and some
private utilities were annually spending more than $17 per Wisconsin resident
for land records information. In that context, a benefit of $11.12 per capita
for an automated system that can be used for many types of analysis and
map making does not seem inappropriate.
4 Discussion of results
4.1 Cost benefit
analyses: Justification for GIS implementation
Justification of GIS
expenditures was the overriding goal of this study. All GIS organizations
should begin to perceive a need to quantify the costs and benefits of their
system. This section summarizes the model used to estimate benefits, comments
on the robustness of the model for this purpose, summarizes the case study
results and finally describes what organizations should do to go beyond
this work to fully characterize the benefits of their GIS.
4.1.1 Description
of the Gillespie (1997) model
The Gillespie (1997)
model is a regression model incorporating the results of 62 case studies
of GIS at the federal government level. The model has not previously been
used at the state or local government levels, but Mr. Gillespie was confident
that the model would work for these case studies. The magnitude of the GIS
applications described in this report appear to be consistent with the magnitude
of the federal GIS applications.
The basic premise of
the model is that the benefits of GIS are related to the complexity of the
model inputs, analysis and outputs. Upon this premise, two separate model
equations can be used to estimate efficiency and effectiveness benefits
per incident of a GIS application. An application can produce both types
of benefits, but by the definitions a single output of the application can
produce either efficiency or effectiveness benefits, but not both. For both
types of benefits to result from an application, at least one output must
produce efficiency benefits and at least one must produce effectiveness
benefits.
The benefits (efficiency
or effectiveness) per incident of an application must be multiplied by the
frequency of use of the application to estimate the annual benefits. The
net annual benefit of an application is equal to the sum of the net annual
efficiency and effectiveness benefits. The net annual benefits of a GIS
installation are equal to the sum of the net annual benefits of all applications
within the installation.
Surprisingly, one of
the greatest difficulties of using the model to assess these case studies
was determining what the applications were and what one occurrence of the
application comprises. Until that point, people tend to answer interview
questions in an aggregate fashion. For instance, when determining the benefits
of requests for digital land records data, one cannot use the entire volume
of land records data as the value of the VOLUME parameter because the benefits
would be huge for each occurrence of the application. Instead, one has to
determine what volume is data is used in a "typical" request for
land records data and then calculate the benefits of the typical occurrence.
The net annual benefit of the application can then be determined by estimating
the annual number of requests and multiplying by the benefit for each request.
Once the application
and an individual occurrence of the application have been defined, most
of the other required information can be determined more easily. However,
that is not to say that the values of the variables are easy to pin down.
4.1.2 Model strengths
and weaknesses
Weaknesses
The greatest weaknesses
of the model discovered in this analysis can be summarized as subjectivity
and sensitivity. Subjectivity refers to the "tweaking" of model
parameters that is required of the person running the model. To get reasonable
results out of the model sometimes requires that the operator play around
with the parameters within the range suggested during the interview. For
every case study in this report, the variables were estimated as conservatively
based on the interview. Some parameters are particularly subjective, such
as the value of the CONCERNS parameter. There is no uniform way to define
what types of groups can be included in that variable.
In addition to subjectivity,
the model sensitivity warrants some concern. For instance, the LAND variable
in the efficiency model changed the results of the Butte-Silver Bow case
study by 20% depending on the choice of a 0 or 1. An additional area of
sensitivity not discussed previously involves the SMALL variable. SMALL
goes from 0 to 1 when the sum of the size classes for the model variables
becomes less than 7 (see Section 2.3.1). The result is that as the values
of variables get smaller, the effectiveness benefit shrinks. However, when
the variables get small enough to make SMALL go up to 1, the effectiveness
benefit jumps up again. Therefore, the predicted benefits are not always
nice continuous functions of the complexity variables. When using the model,
one must be careful to look for consistent results.
Strengths
Despite the weaknesses
described in the previous section, the model is an excellent tool for assessing
the benefits of GIS installations. The greatest attribute of the model is
that it can be used to estimate effectiveness benefits, which are very difficult
to assess directly. Most groups are not willing to spend the time to make
good estimates of the effectiveness benefits. The result is that effectiveness
benefits are typically ignored and the benefits of GIS are drastically underestimated.
More attention should be placed in the future on estimating effectiveness
benefit and the Gillespie (1997) model provides one nice tool for doing
so in a low-cost fashion.
Perhaps the greatest
strength of the Gillespie (1997) model is one that was not perceived until
the data had been run through the model. The model forces one to focus on
the applications of a GIS, rather than the data. It was a surprising realization
in some of the interviews that the applications were not always easy to
define. If the model were used to assess a system prior to implementation,
it would help to identify the most important applications. By assessing
the potential benefits of each application, the most beneficial applications
would receive attention first. More importantly, the applications would
drive the data collection process and unnecessary data would not be collected.
4.1.3 Results obtained
with the model
The benefits estimated
for the case studies are summarized in Table 1 below. As mentioned previously,
benefits were calculated for up to one or two applications within a case
study. No case studies were assessed for their total benefits and costs.
Table 1 : Benefit/cost
summary for case studies
|
Case study
|
Application
|
Type of benefit
|
Net annual benefit
|
Benefit cost ratio
|
|
Butte Silver-Bow |
Automated land
records |
Both |
$377,400 |
3.8-5.6 |
|
NRIS |
Watershed analyses |
Effectiveness |
$141,210 |
N/A |
|
NRIS |
Interactive well
finder |
Effectiveness |
$235,790 |
N/A |
|
DEQ- Env. Management
Bureau
|
Viewshed analysis |
Effectiveness |
$4000 |
4.0 |
|
DEQ- Industrial
& Energy Minerals Bureau
|
Volumetric analysis |
Both |
$48,060 |
5.5 |
|
DEQ- Industrial
& Energy Minerals Bureau |
Reclamation plan
analysis |
Effectiveness |
$3520 |
1.2 |
|
Information Services
Division |
Generating land
ownership database |
Efficiency |
$831,600 (lump
sum, not annually) |
N/A
|
|
Information Services
Division |
Accessing land
ownership database statewide |
Both |
$7.52 million |
3.8-5.6 (assume
the same as Butte-Silver Bow) |
4.1.4 Going beyond
our results
The benefit/cost information
from the case studies were obtained for only one or two applications. For
an agency to estimate the total benefits would require an assessment of
all applications. The Missoula Implementation Plan in Appendix D is an excellent
example of a study estimating the cumulative benefits (efficiency only)
for an entire GIS installation. In that study, the system costs and benefits
were estimated on an annual basis for the first 10 years of operation. That
type of analysis allows the agency to determine additional information like
the payback period for the GIS investment.
The Gillespie (1997)
model could certainly be used in a complete study like the Missoula Implementation
Plan. In that case, the group conducting the study would need to determine
the system costs and benefits on an annual basis for some period of time.
The model has only been used to assess the benefits of existing GIS installations,
but it is conceivable that the model could be used to assess the benefits
of an installation prior to implementation. In that case, the group conducting
the study would need to be in contact with Mr. Gillespie to discuss how
the model might used to forecast the benefits. As mentioned in Section 4.1.2,
this type of preliminary analysis could then be used to prioritize applications
and data collection.
Another unexpected strength
of the Gillespie (1997) model is that it also highlights the need for better
tracking of GIS use. Organizations interested in justifying GIS expenditures
should be keeping track of the frequency at which an application is used.
4.2 Planning for
GIS implementation: Lessons learned
This section of the
report summarizes the lessons learned from each of the case studies. The
lessons are divided along the lines of data issues, IT structure issues
and organizational issues.
4.2.1 Data issues
- Agency-wide data
standards should be adopted to insure compatibility of databases and GIS
applications
- There should be a
clear understanding of who is responsible for each type of data to avoid
data redundancy and insure maintenance of the data
- Data creation and
maintenance is the greatest expense in developing GIS applications
4.2.2 Issues in IT
structure
- An agency's IT structure
should be well organized so that GIS applications and databases can be
accessed through intranets and the internet
- Internet GIS applications
are very successful for 4 main reasons;
- Users are more
comfortable with web browsers than GIS software
- They require little
technical support
- They reduce the
number of requests that have to be handled by agency personnel
- They provide an
easy means for tracking use, which in turn can be used to demonstrate
the benefits of the applications
4.2.3 Organizational
issues
- Communication between
participating groups or agencies is critical to the success of GIS
- Political issues
are more difficult to overcome than technical issues related to GIS implementation
- Small local governments
should consider a number of options for obtaining GIS services, including:
- Contract services
through private consultants
- Contract services
through neighboring counties with GIS already available
- Entering into cooperatives
with other counties to share GIS costs
- Joint city/county
GIS implementations make sense in order to avoid redundancy and share
costs
- Each agency implementing
GIS should have at least one GIS coordinator to avoid redundancy and insure
compatibility between databases and GIS application
- GIS analysts should
be available within each division or program of a state agency to build
applications and provide end-user support
- GIS analysis should
be performed at the desktop of the decision-maker
5 Conclusions
5.1 Did the study
accomplish its goals?
The primary focus of
our study was to identify benefit/cost analysis methods and apply them to
a number of case studies in Montana State and local governments. We hoped
to develop a set of tools that could be used by other groups to simplify
the process of estimating costs and benefits. The Gillespie (1997) model,
the Missoula Implementation Plan and the other literature reviewed provide
those tools. The 9 case studies described in Section 3 provide excellent
examples on how to apply the Gillespie (1997) model and the Excel spreadsheet
in Appendix C will perform the calculations automatically.
The study did not set
out to develop bottom-line cost and benefit numbers for any or all case
studies. In times of tight budgets, however, agencies should consider going
to that detail with their own GIS installations in order to justify past
and future expenditures. Hopefully this report provides all of the necessary
information for the agency to accomplish that task.
The other goal of the
study was to summarize the lessons agencies have learned thus far in their
efforts to implement GIS. If there was one question that was easy for the
interviewees to answer, it was the question about the lessons they have
learned. Every person we talked to was certain about what things had caused
the greatest problems. GIS implementation does not happen smoothly without
a great deal of planning and coordination. If this report can save other
agencies from experiencing some of these same difficulties, then it has
achieved its second goal as well.
5.2 Analysis of the
Gillespie (1997) model as a tool for justifying GIS
The Gillespie (1997)
was shown to have a number of strengths and weaknesses. Like any model,
the answers are not perfect but they offer a more reasonable alternative
than adding up every single benefit and cost. Used with care, the model
can provide sensible answers in line with reasonable expectations of the
benefits of GIS. The model is also useful for focusing the GIS agency's
attention on what applications are most important and what pieces are needed
to accomplish that application.
To fully characterize
the costs and benefits of a GIS installation would require a more detailed
study than the one conducted for this report. A study like the Missoula
Implementation Plan is excellent to identify the applications and data needs
and estimate the efficiency savings from those applications. A report combining
the methods of the Missoula Plan with the Gillespie (1997) model would provide
an excellent analysis of the costs and benefits of GIS.
6 Recommendations
- The Gillespie (1997)
model or other methods should be used to assess both efficiency and effectiveness
benefits of GIS
- GIS implementation
should focus first on applications, not data
- Costs and benefits
of GIS should be determined prior to implementation and should also be
an ongoing process
- In new GIS installations,
applications should be prioritized in order of expected benefits to focus
resources where the returns are greatest
- Data should be collected
to satisfy the needs of the most beneficial applications
- Applications should
be built so that their frequency of use is automatically tracked
- Agencies serving
the public are well-served to develop GIS applications in order to cut
their costs and quantify benefits of the application
- GIS should be pushed
to low-levels within an agency
References
Gillespie, Stephen R.,
personal communications, 1998.
Gillespie, Stephen R.,
A model approach to estimating GIS benefits, United States Geological Survey,
Reston, VA 22092, unpublished article, 1997.
Gillespie, Stephen R.,
GIS Technology Benefits: Efficiency and effectiveness gains, United States
Geological Survey, Reston, VA 22092, 1994.
Korte, G., Weighing
GIS benefits with financial analysis, GIS World, p. 48-52, July,
1996.
Larsen, B., Land Records:
The cost to the citizen to maintain the present land information base; a
case study of Wisconsin. Department of Administration, Office of Program
& Management Analysis, 1978.
Silva, E., Cost Benefit
Analysis for Geographic Information System Implementation Justification:
Literature Review, 1998.
http://gis.ny.gov/gis/costanal.htm
Worral, Les. 1994. "Justifying
investment in GIS: a local government perspective." International
Journal of Geographical Information Systems, Vol. 8, No. 6, 545-565.
GIS Business Plan, Imaging
and CADD Technology Team, EESB, FSED, Langley Research Center, Hampton,
VA, February 16, 1995
Acknowledgements
The authors would like
to acknowledge and thank all of the participants and contributors to this
study. Montana Geographic Information Council members Dr. Richard Aspinall,
Dan Sullivan, Don Childress and Harold Blattie all serve on the Economic
Analysis Workgroup and have provided invaluable support for the development
of this report. Lois Menzies and Stu Kirkpatrick of the Montana Department
of Administration have been instrumental in providing financial support,
technical oversight, and encouragement for completion of this study.
Doug Burreson of Missoula
County, Jon Sesso, Rob Macioroski and Tom Tully of Butte-Silver Bow County,
R.J. "Zim" Zimmerman of Lewis and Clark County, and Steve Hellenthal
of Yellowstone County all provided their time and thoughtful responses to
help develop the benefit-cost analyses, which form the core of this work.
A number of participants from Montana State government also participated
in the study, including: Jim Stimson from the Natural Resource and Information
System (NRIS), Jim Hill, Tom Ring, Nancy Johnson, and Loretta Reichert from
the Montana Department of Environmental Quality and Skip Nyberg from the
Montana Department of Transportation.
Finally, we would especially
like to thank Steve Gillespie from the United States Geological Survey who
has generously provided his time and support in our application of his regression
model to this study.
Appendix A-Literature
review
Silva, E., Cost Benefit
Analysis for Geographic Information System Implementation Justification:
Literature Review, 1998.
http://gis.ny.gov/costanal.htm
- Advocate this approach:
- Calculate tangible
costs
- Calculate tangible
benefits
- Intangible benefits
= Potential benefits x probability of achieving the benefit
- Net benefits= Tangible
costs-tangible benefits-Intangible benefits
- Tangible benefits
include labor savings, material cost savings and minimization of out-house
expenditures
- Intangible benefits:
- Reduced potential
for maladministration and liability
- More rigorous data
management
- Enhanced visualization
of graphical data
- Improved analytical
procedures
- Improved data security
- The provision of
better information
- More consistent access
to data
- Improved services
to customers
- Ability to integrate
data
- Ability to generate
new 'understandings' and easier access to data
- Advocate the option
of a data-sharing cooperative (enterprise-wide option)
Worral, Les. 1994. "Justifying
investment in GIS: a local government perspective." Internation Journal
of Geographical Information Systems, Vol. 8, No. 6, 545-565.
- Costs of GIS implementation
- Hardware integration
with pre-existing computing infrastructure
- Evaluation, selection,
acquisition and installation of software
- Undertaking requirements/needs
analysis
- Contractual aspects
- Consultancy support
- Systems customization
- Applications portfolio
development (and/or customization)
- Interfacing to
other 'data servers' and operational systems
- Training, human
resources planning, skills development and re-skilling
- Additional vendor
services (e.g. possible turnkey development)
- Business analysis
- Project management
- Delivery and installation
- Communications
- Business process
re-engineering
- Documentation redesign
- Transitional costs
(i.e. parallel running of old and new systems)
- On-going revenue
implications (i.e. staff costs and consumables)
- Data modeling,
data flows analysis and redesign
- Data purchase (e.g.
Address Point, Census)
- Data capture, data
conversion
- Data re-survey
and validation
Korte, G., Weighing
GIS benefits with financial analysis, GIS World, July 1996, p. 48-52
- Three steps involved
in a GIS financial analysis:
- Estimate GIS program
costs
- Estimate GIS cost
savings
- Estimate current
costs of using maps & map related attribute data; include employee
benefits and overhead
- Estimate portion
of costs saved through increased productivity and decreased contracted
costs
- Employ standard
techniques to determine attractiveness of investment
- Tabulate GIS
costs and savings
- Calculate net
present value, payback period, or real rate of return
- Assume 3% discount
rate (OMB recommendation)
- Intangible benefits
and residual value of the investment are not included in this analysis
- Included an example
GIS cost benefit study from Edwards AFB
- 8 year payback
period after project initiation (4 years after full implementation
- 7.5% real rate
of return after 10 years
- greatest savings
in construction change orders
Costs:
- Implementation:
services, hardware/software, database creation
- Maintenance: updating
data, hardware replacement every 4-6 years, software upgrades
Benefits:
- "Conservative"
assumption of 50% increase in employee productivity
- Decrease in contracted
services
- Reported results
of Joint Nordic Report on 16 GIS projects in North America and 2 in Italy
- GIS systems used
for mapping and updating: B/C=1
- GIS systems used
for planning and engineering: B/C=2 (4 if all commonly used data sets
have been automated)
- GIS system used
for information sharing between relevant organizations: B/C=4
- GIS system replaces
a poor system for manual map production: B/C=7
GIS Business Plan, Imaging
and CADD Technology Team, EESB, FSED, Langley Research Center, Hampton,
VA, February 16, 1995
- Development resources
over 5 years- $4.06 million total
- Hardware (25%)
- New licenses (2%)
- License maintenance
(3%)
- Personnel (38%)
- Training (1%)
- Conversion (31%)
- GIS Operational resources-
- Manpower (50 elements
identified in which GIS will be applied)
- Software maintenance
- Hardware maintenance
- Training
- Resource reduction
(benefits)
- Predicted GIS usage
in each element classified as low, medium, high
- Number of FTE's
required after GIS implementation calculated from these classifications
- Total annual operating
costs for GIS related elements reduced by 43%
- Savings of $2.28
million/year after full implementation
- Break even analysis
- Payback period
of 3 years
- Despite $4 million
cost, total net investment never exceeds $1 million
- Net savings of
$3.9 million by end of 5 year development period (B/C=2)
- Categories of Benefits
- Differentiate between
efficiency savings and effectiveness savings
- Effectiveness benefits
categories: visualization, complex analysis, information access, increased
accuracy
- Effectiveness benefits
are less tangible, not necessarily intangible
- Other
- Assumes $70K/FTE
- All $ values reported
in 1995 dollars
- Redundant databases
should be maintained by organization requiring most detailed information
- Quotes a USGS report
(an unpublished Gillespie report) which estimated an 80% efficiency
savings in federal GIS implementations achieving efficiency benefits
- USGS report estimated
effectiveness savings as 8x greater than efficiency savings in
federal GIS implementations achieving effectiveness benefits
Larsen, B. et al.
1978. Land Records: The cost to the citizen to maintain the present land
information base; a case study of Wisconsin. Department of Administration,
Office of Program & Management Analysis, 64pp.
- Determined that annual
expenditures on land records by local, state and federal governments and
some private utilities totaled $17 per resident or $2.25 per acre
- The study also identified
a significant number of problems with the way the current (manual) system
functioned
- The categories of
problems with the existing system:
- Accessibility
- Lack of data aggregatability
- Nonintegratability
of information
- Duplication of
efforts to gather and record land information
- Questionable cost-effectiveness
or need for some land records
- Confusing confidentiality
requirements
- Vertically organized,
single-purpose land record-creating institutions
- Some causes for governmental
land record problems
- Government is "problem
oriented" instead of planning for the future
- Agencies are organized
along single program lines
- Government agencies
operate in a vertical structure
- On each level of
government, no one agency is charged with integrating land data and
records within and between government levels
- Types of intangible
benefits of land records modernization
- Provides the needed
information to regulate from an informed basis
- System is an aid
to economic development
- System contributes
to a campaign for energy conservation
- Overcomes institutional
problems plaguing those using the present system
- Better foundation
for value judgments upon which decisions are made
- Specific benefits
- Money saved with
improved methods for collecting, storing and displaying land information
- More useful data
and products from integrated information
- More informed public
decisions
- Reduced duplication
of effort and compatibility of products
- Dollar savings
in product sales, map production, research and development and remote
sensing
- Gaps in land information
system will become apparent
- Advanced manual
systems would lead to computerized systems at the local government levels
Gillespie, Stephen R.,
GIS Technology Benefits: Efficiency and effectiveness gains, United States
Geological Survey, Reston, VA 22092, 1994.
- Efficiency
benefits arise when GIS is used to reduce costs of a task that, in the
absence of GIS, would be handled by some other method; equivalent outputs
- Effectiveness
benefits arise when GIS is used to perform a task that could not or would
not be done without GIS
- Most federal government
GIS applications are single purpose (either efficiency benefits or effectiveness
benefits)
- At federal government
level, GIS is primarily important because it helps agencies work better,
not cheaper (i.e. effectiveness >> efficiency)
- Failure to quantify
effectiveness benefits weakens a study and distorts its results
- USGS developed a
model which predicts efficiency and effectiveness benefits for GIS applications
based on easily measurable characteristics of the application's complexity
Gillespie, Stephen R.,
A model approach to estimating GIS benefits, United States Geological Survey,
Reston, VA 22092, unpublished article, 1997.
- Creates and applies
a framework for analysis of factors affecting the value of GIS technology
- Complexity of a GIS
application key factor influencing level of benefits
- Input complexity-
number of data themes, volume of input data, areal extent of application
- Analysis complexity-
maximum number of concurrent overlays, number of steps in analysis,
number of intermediate data themes, number of potential interactions
between data themes
- Output complexity-
number of distinct uses for outputs, likelihood that outputs will be
used in adversarial hearings
- General relationships
between complexity and level of benefits
- Input complexity
- Input complexities
log linearly related with both efficiency and effectiveness due to
economies of scale.
- Analysis complexity
- Analysis complexity
linearly related with efficiency benefits (no economies of scale)
- Analysis complexity
curvilinearly related with effectiveness benefits due to diminishing
returns
- Number of interactions
between data themes increases geometrically as number of data themes
increases arithmetically
- Output complexity
- Output complexities
linearly related to both efficiency and effectiveness benefits
- Benefits model
- Two independent
multiple regression equations for calculating efficiency and effectiveness
benefits based on 62 cost/benefit studies of federal GIS implementations
- Equations used
to calculate benefits for individual applications; benefits aggregated
across applications to compute total system benefits
Appendix
B-Missoula Implementation Plan
The linsk below
open up the spreadsheets containing the cost benefit calculations.
Cost
Benefit Calculations - Part 1
Cost Benefit Calculations - Part 2
Appendix C- Spreadsheet
for calculating effectiveness benefits
The attached spreadsheet
contains the information gained in the DEQ Industrial & Energy Minerals
Bureau interview. The file contains 3 different worksheets. The "Questions"
worksheet is the list of questions sent out to each interview candidate
and then discussed in the interview. The "Answers" worksheet contains
the answers to the questions required in the model. Answers to questions
not required in the model were not included in this file. The "Calcs"
worksheet contains the model equations and summarizes the efficiency and/or
efficiency benefits for the DEQ Industrial & Energy Minerals Bureau.
Spreadsheet
for Calculating Effectiveness Benefits
Appendix D- Copies of
Gillespie's papers describing the model
These papers were only
available in hard copy.
