The Minnesota Department of Transportation has implemented a new software system called SIMS (Structure Information Management System) to manage its over 20,000 bridges. SIMS allows for electronic data collection in the field, integrating inspection, management, and maintenance modules in one system. It addresses needs like improving communication between inspectors, engineers, and maintenance crews. Network analysis identified "silos" between these groups previously. SIMS provides a complete repository for all bridge data accessible to all relevant parties.

1. Minnesota DOT’s New Software for
Bridge Inspection and Management
JENNIFER L. ZINK, P.E., Minnesota Department of Transportation –
Bridge Office, Oakdale, Minnesota
IBC-12-76
KEYWORDS: Inspection, bridges, database, maintenance, technology, asset management
ABSTRACT: The Minnesota Department of Transportation has recently implemented a new software system called
SIMS – Structure Information Management System. The system is used for inspection and management of its
20,000+ bridges. It reduces the amount of clerical work by allowing data entry in the field and integrates
modules for structure management and maintenance. SIMS is a complete repository for all structure data. This
paper discusses the process leading to implementation and features of the application itself.
INTRODUCTION
There are over 20,000 bridges in Minnesota. Of these
bridges, almost 5,000 are owned by the state and the
remainder is owned by its 87 counties, townships,
cities, and other local entities. Counties and cities are
mandated to ensure that the inspections of these
structures are performed to federal standards, known
as the National Bridge Inspection Standards – NBIS
[1], as is the state. Further regulations are also
imposed by the state of Minnesota in respect to
inspection frequency, inspection jurisdiction, and
inspector qualifications [2, 3]. To accomplish this,
agencies must employ their own inspection staff in-
house or hire qualified private consulting firms with
inspection expertise to perform inspections and
generate detailed reports on each bridge. Typically
the state, counties, and larger cities employ their own
inspection staff. Additionally, each bridge owner must
report to the state on the basic inspection details
required by the Federal Highways Administration
(FHWA) for the annual National Bridge Inventory (NBI)
submission.
The Minnesota Department of Transportation (MnDOT)
Bridge Office is responsible for storing and managing
all bridge inspection data statewide. Prior to 2011, the
Bridge Office tracked data in the AASHTOWare Pontis
[4] application for routine bridge inspections, which
are regularly scheduled inspections not to exceed 24
months that consist of observations and/or
measurements needed to determine the physical and
functional condition of the bridge, that identifies any
changes from initial or previously recorded conditions,
and that ensures the structure continues to satisfy
present service requirements. Pontis is a
comprehensive bridge management system developed
as a tool to assist in the task of managing bridge data
(Figure 1). Pontis stores bridge inventory and
inspection data, formulates network-wide preservation
and improvement policies for use in evaluating the
needs of each bridge in the network, and makes
recommendations for what projects to include in an
agency’s capital plan for deriving the maximum benefit
from limited funds.
Figure 1 – AASHTOWare Pontis Screenshot

2. Data was entered into Pontis by MnDOT, county, and
city inspectors either remotely through web interface
or by manual means – recording on paper and sending
into the Bridge Office. Pontis does not have the full
capability to track all bridge data such as photos,
design plans, or load ratings. It also does not track
data gathered during other bridge inspection types.
Data for fracture critical, special, underwater and other
types of inspections were stored by other means.
Pontis also does not track ancillary structure data such
as overhead signs and high mast light poles. It does
not identify, prioritize, or track maintenance tasks
resulting from inspections. Agencies employed
multiple and varied methods to document and track
maintenance related data, including Excel
spreadsheets and programs developed in Microsoft
Access as seen in Figure 2 below. As such, the system
did not adequately store, manage, or communicate all
structure information collectively for inspectors,
engineers, and maintenance personnel in Minnesota.
Figure 2 – e-Bridge Screenshot
NEEDS
As such, the needs identified include:
 Address recommendations made by the State
Auditor in the report, “Minnesota Office of
Legislative Audit Evaluation Report – State
Highways and Bridges February 2008.” [5]
Recommendation that MNDOT, “Should
establish standard procedures for
documenting, communicating, and following
up on bridge inspectors’ maintenance
recommendations.”
 Address the State Auditor recommendation to
have a unified system for managing bridge
maintenance. The MnDOT Districts currently
employ multiple and varied means to
document and track maintenance related
data, including Excel spreadsheets, a program
developed in Microsoft Access and an Oracle
application.
 Aid in compliance with FHWA regulations;
specifically, “Code of Federal Regulations
Section 650.315 [6]: Inventory (b) For
routine, in-depth, fracture critical member,
underwater, damage and special inspections
enter the SI&A data into the State or Federal
agency inventory within 90 days of the date of
inspection for State or Federal agency bridges
and within 180 days of the date of inspection
for all other bridges.”
 Improve inspection documentation, timeliness,
and accuracy.
 Provide a unified system to store and retrieve
all data gathered during bridge and structure
inspections remotely from the inspection site.
 Provide a bridge inspector with all of the
resources at their fingertips as they are
performing bridge inspections.
 Record inspections of bridges, high mast light
poles, overhead sign structures, and other
ancillary structures in the state.
 Align with MnDOT’s key focus area of,
“Safeguard What Exists - Preserve Critical
Infrastructure.” [7]
 Align with MnDOT’s Strategic Vision of,
“Safety - Promote and maintain a safe,
reliable and modern transportation system.”
[7]
Additional business goals identified in regards to cost
savings and customer service include:
 Reduce manual or duplicate entry of structure
and inspection data
 Spend less time manipulating data and
preparing reports
 Reduce the time to perform, enter and review
a structure inspection
 Reduce the time that it takes to manage and
communicate maintenance recommendations
The needs to address are easily identifiable in lieu of a
significant bridge failure such as the 35W bridge, as it
then forces agencies to look at their current practices.
However, it does not fully explain why the practices
did not work in the first place. In order to explain this,
the State’s communication network in respect to
bridge inspection findings, maintenance, and
engineering was investigated and analyzed.
BRIDGE COMMUNICATION NETWORK ANALYSIS
USING NODEXL - To analyze the state’s bridge
communication network, a program was utilized that
analyzes social media networks. NodeXL is a free
program template for Excel 2007 that analyzes and
visualizes social media networks [8]. Social media
networks are communication venues such as e-mail,
texting, blogs, and wikis with the intent to share

3. knowledge. Voluminous user data, attachments, and
network connections between users consume the way
people communicate and ultimately create complex
social networks. Comprehending how these social
media networks develop, transform, fail, or thrive is a
rising concern to researchers and business
professionals. By applying network analysis to social
business systems, one can identify potential problems
and avenues to resolve them.
Figure 3 – NodeXL Sample Screenshot
Network relationships are represented as an edge list
in NodeXL, which contains pairs of vertices that are
connected in the network (Figure 3). A person may
enter their own edge list in the Edges worksheet tab or
one can be imported from an existing data source such
as a company e-mail network. It is important to note
that entry of two vertices (i.e. columns Vertex 1 and
Vertex 2) is necessary to make a connection.
Once an edge list is entered, a graph of the data is
shown by clicking the Show Graph button in the
program. The graph shows the network of
relationships between the vertices of the edge list.
The vertices can also be arranged in the graph pane.
There are several automatic layouts offered by the
program. The default layout is called Fruchterman-
Reingold. Other layout types include circle, spiral, and
grid. Manual layout is also an option. The vertices
can be clicked and dragged in the graph pane to
create arrangements that emphasize a more orderly
display. Experimenting with different layouts can
reveal important patterns and/or relationships.
Since social networks tend to be large, graph output
will be cluttered. Visual design changes can make the
network displays more meaningful. Vertex colors and
sizes can be changed. Descriptive information about
the data set can also be added along with text labels.
There is a filtering tool that can riddle out vertices and
edges to focus on certain sections only. NodeXL can
also identify vertices that are clusters of some
specified group, such as inspection employees as
opposed to maintenance employees. Clusters can be
created manually or identified automatically by the
program. Once a cluster is identified, then visual
design changes can be applied. Like the filter feature,
clusters can also be hidden with just a click of the
computer mouse.
Although tools and processes to analyze social
networks are just beginning to evolve, NodeXL is an
easy program to use, but it does take some advanced
knowledge of Excel. The online tutorial however, is
helpful in getting started. Even though it is free of
cost, NodeXL can only be used with Microsoft Excel
2007 and 2010. Earlier versions of Excel will not run
the program. Other implications of NodeXL include the
ability of the user to identify meaningful information in
the data sets and to customize them accordingly.
Much time can be spent trying to visualize and graph
data in a meaningful manner.
The NodeXL program was utilized for the social
network display of interactions between engineers,
bridge inspectors, and bridge maintenance workers in
the Minnesota Department of Transportation. The
goal was to pinpoint any visual gaps in communication
from engineers to inspectors and inspectors to
maintenance workers. Other key players involve
Central and District Bridge Engineers, bridge load
ratings personnel, bridge designers, and bridge data
management personnel. All are vital in how inspection
findings are evaluated and then distributed to others
for further analysis and/or bridge maintenance work
orders. The communication networks were developed
through individual observances of personnel and
through District organizational charts.
After entering the key personnel and communication
connections (i.e. edge lists) into the program, the data
was graphed into different layouts. Much time was
spent on visually reorganizing the data to show
meaningful communication gaps, or silo effects [9].
Clusters were created to show inspection and
maintenance personnel separately.
Figure 4 portrays communication that existed between
the MnDOT Bridge Office and the Districts prior to
2011. This figure illustrates the silo effects of each
District to itself, depicted by the ovals, with only one
connection to the Bridge Office.

4. Figure 4 – NodeXL MnDOT District Silo Effect
Not only is there disconnect between the Districts, but
there is also separation between engineers, inspectors,
and maintenance crews. Figure 5 shows the same
personnel as in Figure 4, but also shows which nodes
are engineers, inspectors, and maintenance personnel.
It shows a distinct surplus of engineers compared to
inspectors and maintenance staff.
Figure 5 – NodeXL District Engineers,
Inspectors, and Maintenance
To better visualize the communication breakdown
between key personnel in regards to inspection,
engineering, and maintenance, an alternate layout was
chosen as shown in Figure 6. This graph shows the
silo effect that exists between engineers, inspection,
and maintenance in the Districts, as depicted by the
ovals. It is also worthy to note that each District is not
structured the same. Some Districts have better
communication networks than others.
Figure 6 – NodeXL Inspection and
Maintenance Silo Effect
The graphs ultimately show a distinct breakdown of
communication between inspection, maintenance, and
engineers in the Districts with the Bridge Office. It
shows that inspection findings are not directly given to
the bridge maintenance crews. Another significant
finding is that typically one engineer is connected to
the State Bridge Engineer to relay important
information to other personnel. If that connection is
absent either permanently or temporarily by means of
illness or turnover, then there is no direct
communication line to that District or section.
The result of the bridge network graphs is explained
by the structural organizational dimensions of MnDOT
[10]. Organizations as large as MnDOT are
traditionally hierarchal in nature with one line of
communication connecting each employee level.
Hierarchal organizations are centralized in their
decision making, political in nature, and have clear
reporting lines with different levels of superiority as
depicted in Figure 7. They can be highly efficient
organizations but can also lack leadership strength
since personnel are often promoted by length of
service and not necessarily by quality of work.
Figure 7 – Hierarchal Organization
The complete opposite of a hierarchal organization is a
horizontal one. A horizontal organization is typically
comprised of task forces, project managers, and teams
with main lines of communication between all

5. members of the organization (Figure 8). It is
considered a learning organization. However, it can be
difficult to implement since there is a non-traditional
lack of authority or superiority. People are always
rewarded for quality of work and not length of service.
Figure 8 – Horizontal Organization
A combination of the two organizational structures is
the most practical on the road to change. The silos
that exist in the bridge network due to the hierarchal
nature of MnDOT inhibit efficient communication
between inspectors, engineers, and maintenance
personnel. The goal is then to take this information,
and explore communicative solutions to restructure the
organizational system creating more connections
without reinventing the organizational structure of
MnDOT (Figure 9).
Figure 9 – Ideal Connections
OBJECTIVE
The problems identified have been recognized by
MnDOT due to the bridge inspection program
investigations and recommendations made by the
State Auditor in lieu of the 35W bridge collapse. As a
result, a project is currently underway at MnDOT to
address these inspection program problems and
recommendations. The project involves a collaborative
effort of bridge inspection, bridge management, and
information technology staff.
The purpose of this project was to implement a bridge
inspection system as part of MnDOT’s effort to ensure
the availability of timely inspection data for bridges
and structures in Minnesota.
The new system provides electronic field data
collection capabilities to inspectors, streamlining the
inspection process and increasing data integrity by
eliminating the current delay between data collection,
data entry, and report generation. Types of additional
data that are tracked include load ratings,
maintenance work orders, and inspection related items
such as narrative descriptions, photos and design
plans. This project provides a link between all bridge
data, and also provides a means of tracking ancillary
structure data such as overhead signs and high mast
light poles. This project also provides a means to
identify, prioritize, and track maintenance tasks
resulting from inspections.
The system also must interface with the AASHTOWare
Pontis application, previously used by the Bridge Office
to track data from routine bridge inspections,
performed by MnDOT, County, City inspectors, and
consultants but now is used for solely modeling and
forecast capabilities.
In today’s fast-paced society, managers and decision-
makers need accurate data in a usable format
instantly. A web-centric system is one that is internet-
based and compatible with different data formats used
in engineering today through the use of smart
browsers and/or servers. It has the ability to manage,
store, and communicate data in seconds. MnDOT
undertook research and analysis including current
system failures and their cause or causes (as denoted
by the NodeXL social media network analysis), analysis
to substantiate or refute all possible solutions to the
problems, potential vendor questionnaires and on-site
demonstrations, benefit/risk investigation, return of
investment analysis, system implementation plan, and
future work. Before immersing into the research and
analysis, understanding of web-centric systems is
necessary.

6. Many characteristics differentiate a web-centric, or
automated, system from the traditional paper-based
inspection system [11, 12]. Ownership of the data, or
information, is central and independent of the people
who possess and employ it. Information is universally
accessible via the internet as opposed to data stored in
numerous physical locations with different people.
Furthermore, data based in a web-centric system is
always available. Customized reports are readily
obtainable by query. New participants can also be
easily incorporated through any internet connection.
There is no software to install on client computers or
extensive training involved.
An ideal development model first explicitly defines
what the process is supposed to do or accomplish that
the current process does not. For example, a web-
centric/automated system is ideal when there are no
consistent applications of technology for dispersed
information between different organizations or
sections, such as disconnect between inspection
recommendations and follow-up actions based on
those recommendations. To visualize and standardize
such processes, data flow diagrams are typically used
by illustrating the interactive steps between people
and/or tasks.
Once the process is defined, the next step is to define
how each task is implemented whether by way of web
servers, pen-based computers, or a combination
thereof. A pilot, or sample, project is then
recommended to evaluate the system created. This
enables evaluation and correction of any problems
prior to full system implementation.
Because web-centric systems typically involve newer
technologies, equipment and start-up costs can be
significant. Integrating different web-based formats
can also be a formidable and time-consuming task.
Many people need to be involved to successfully
implement the system. Top management support is
essential. Furthermore, security concerns are always a
factor with sensitive information displayed over the
internet. Precautions are necessary to ensure that
data is secure and not able to be tampered with.
Even ten years ago during the infancy of the World
Wide Web, web-centric systems were researched and
discussed as potential solutions to a growing network
of people, information, and the transfer of that
information between people. Obvious benefits in time,
accuracy, and money are probable. Today, technology
has vastly improved but unfortunately, the engineering
community has not evolved in comparison. There is so
much scattered data out in cyber space.
Problems have started to arise with storage, security,
and non-compatible formatting. Along with the
explosion of digital data, paper-based data is still used.
There are also scores of historical data not yet
incorporated into digital availability. As a result,
numerous forms of information are created and kept in
multiple systems and formats. Many current systems,
such as field inspection and reporting, are subdued by
endless information processing. Public service and
effective communication are ultimately compromised
by this hindrance. Now is the time for the engineering
community to hone in on web-centric technologies.
POTENTIAL SOLUTIONS
The following solutions were considered by MnDOT for
a structure management system:
1 – Modify the Pontis system
2 – Develop a new system
3 – Acquire and customize a commercial system
4 – Acquire and customize a system from another
agency
5 – Do Nothing
The selected option: #3 – Acquire and customize a
commercial system
A survey was developed and sent to other state
transportation departments to determine the current
status of bridge inspection and maintenance tracking
systems. Most states still utilize Pontis by
AASHTOWare, but with limited success. Many of these
states are in the initial phases of investigating other
potential products that are more comprehensive and
web-centric, as communication gaps (silos) are
likewise present. Pontis currently does not provide a
comprehensive system for both inspection and
maintenance data. Modification of Pontis to meet
these objectives is uncertain due to current software
implications, time, and cost. Furthermore, the present
environment within the Minnesota Department of
Transportation does not have the means to scope,
design, develop and build a comprehensive bridge
inspection and maintenance system.
Only two states declared comprehensive systems at
the time that encompass both inspection and
maintenance, one of which used a vendor product.
The Illinois Department of Transportation has a system
developed internally that is not available to other
states. The Wisconsin Department of Transportation
also has a system developed for their agency by a
computer software vendor that is maintained internally
and free of charge to other agencies, but it does not
include a maintenance tracking module. However,

7. total customization of another agency-owned system
would require extensive resources.
SWOT ANALYSIS - In order to substantiate the
selected solution, a SWOT analysis [13] was utilized to
verify the choice made. A SWOT analysis is a tactical
planning technique used to assess the Strengths,
Weaknesses, Opportunities, and Threats involved in a
project endeavor. It involves identifying the internal
and external aspects that are positive and negative to
achieving the objective of the project. The objective
here is to implement a web-centric/automated bridge
inspection system to ensure the availability of timely
inspection data for bridges and structures in
Minnesota.
A number of free templates are available to create a
SWOT analysis [14]. The input consists of the
strengths/weaknesses of MnDOT internal factors and
threats/opportunities of potential external commercial
systems as shown in Figure 10. Internal MnDOT
factors evaluated include people and skills, resources,
innovation, current systems, and finances. External
system factors evaluated include financing, product
complexity, technology, and consumers. The weights
assigned to strengths/weaknesses and
opportunities/threats range from -10 to 10, with -10
being a clear weakness or threat and 10 being a sound
strength or opportunity. Obviously, some factors are
not clearly on one end of the spectrum or the other.
Therefore, moderate values of 5 and -5 are employed.
Each factor was ranked based on problems noted by
the State Auditor and the research of potential
systems to remedy these problems.
Figure 10 – SWOT Table
In regards to communication, the opportunities for
better communication through a web-centric system
(external) can be depicted by improving existing
processes and external customer service. The current
bridge network system (internal) communication silos
are exhibited by qualities of the Pontis system, bridge
filing, and maintenance tracking.
Based on the weighted values in the SWOT Table,
Figure 11 shows the average internal factors (vertical
axis) graphed against the external factors (horizontal
axis). The yellow circle indicates current inspection
system characteristics in relation to the option chosen.
The green circle, which is located in the upper right-
hand corner of the chart, is the ideal inspection system
traits. The blue arrow is the strategic direction
towards the ideal situation over time – depicted by the
concentric circles. The chart ultimately shows that the
system was weak with little opportunity, and as a
result, was no longer functioning at the appropriate
level in regards to timely inspection data and bridge
information overall.
Figure 11 – SWOT Chart
Individual SWOT analyses were completed for the
other potential solutions as well; however, acquiring a
commercial system and customizing it is more
beneficial than the other options as shown graphically
in the comparison chart below (Figure 12). The
selected option, depicted by the yellow circle, has the
shortest line to the ideal situation. This means that
the combination of strengths and opportunities
outweighs the weaknesses and threats of the other 4
options.
Figure 12 – SWOT Comparison
RESEARCH AND STUDY

8. Once the solution was chosen to acquire and
customize an entirely new bridge management system,
the question evolved, “What systems are available that
will meet the needs and close the communication silos
of the MnDOT bridge network?” As a result, research
was conducted to solicit information from other
agencies that use different systems than Pontis. Since
bridge inspection automation is a relatively new field,
only three potential companies were found at the time.
A detailed questionnaire on data collection and bridge
management systems were sent to each company.
Out of the four questionnaires sent, two were
returned. Based on knowledge known about the
individual companies and the completed
questionnaires, a comparison chart was developed to
evaluate the current Pontis system against the other
systems as shown in Figure 13.
Figure 13 – Inspection System Comparison
Through the survey, it was revealed that the
Wisconsin Department of Transportation (Wis/DOT)
has a program internally developed by a software
consultant customized to their requirements.
Wis/DOT, along with the other companies solicited,
was petitioned to demonstrate their systems to
MnDOT bridge inspectors, engineers, and maintenance
staff.
AVAILABLE SYSTEMS - A brief overview of three
systems is given below based on the returned
questionnaires and onsite demonstrations.
InspectTech [15]
InspectTech provides secure software solutions for
structure inspection and management. The core
software is customizable to customer needs. It allows
incorporation of pictures, sketches, manuals, plans,
etc. It can be integrated with business processes and
programs and provides continual training and support.
The product can incorporate all types of structures,
such as bridges, culverts, overhead sign structures,
tunnels, retaining walls, sound walls, guard rail, and
high mast lighting. Typical customers include state
departments of transportation, numerous counties and
consultants, transit authorities, and the U.S. armed
forces. Main customers are those with large bridge
inventories. Other DOTs utilize this product for their
bridge inventory. A teleconference took place with
other DOTs to obtain their perspective of the product.
Overall, the perception was favorable.
InspectTech provides two software packages; one for
inspection and one for bridge management. The
inspection software runs on a laptop in the field and
through the internet in the office. It can be
customized to any agency’s needs. It is Pontis-
element ready and produces formatted reports. Other
data such as pictures and sketches can be loaded
directly into the program.
The manager software handles all bridge data such as
the inspection data, maintenance needs and work
orders, cost estimates, inspection scheduling, photos
and manuals accessible to inspectors, engineers, and
maintenance staff. There is even a GIS module to plot
bridge locations on a map to aid in inspection
scheduling efforts. Total cost is $200,000 - $800,000
depending on customization with an annual
maintenance fee of $30,000. An onsite demonstration
took place at the MnDOT Bridge Office in March 2009.
Advitam [16]
Advitam provides solutions for inspection, monitoring,
and management of structures. Customers include the
City of New York, South Carolina DOT, Canada, and
Greece to name a few. Although this company
provides services to large agencies, it caters mainly to
large specialized bridges and not an entire state bridge
inventory. The largest amount of structures managed
for any one agency at that time was around 2,100.
The software contains applications for structure
inventory, inspection, maintenance work and repairs,
reporting, and analysis. It is an infrastructure
management database system that provides mobile
site-inspection via tablet PC or a hand-held PDA
device, AutoCAD interface that allows the user to
store, retrieve, and update drawings and defects of
bridge components, comprehensive bridge inventory,
condition rating, deterioration analysis ability, and
multiple reporting abilities.
The software has a built in Quality Control Function as
the inspector must accept rating data for every
element and known defect. The system allows the
inspector to visually verify that all components had
been inspected and verified. The software also has a

9. procedure for documenting changes in known defects
over time. When linked to a CAD drawing, the
attributes of the defects can be directly entered into
the database from the drawing. This system would be
useful for both complex bridge inspections such as
large segmental box girder bridges, fracture critical
bridges, and for routine inspections.
Advitam also has bridge management and structural
health monitoring systems. Total cost with
customization is around $300,000 with an annual
maintenance fee of $30,000. A demonstration took
place at the MnDOT Bridge Office in April 2009.
Wisconsin DOT Highway Structures Information
System (HSI)
HSI is a comprehensive asset management system
that incorporates over 19,000 structures. This system
has similar abilities to that of InspectTech and
Advitam. It is Pontis ready, has the ability to attach
photos, incorporates a quality control effort, and can
map bridge locations using Google maps. Inspectors
can utilize the program in the field by checking out
bridges onto a laptop from the office.
All local agencies, consultants, and contractors use the
system. At this time, only inspection data and bridge
plans are in this system. It is the state’s goal for the
system to incorporate all structure data such as design
plans, shop drawings, reports, ratings, and photos.
The initial cost to develop this system was $500,000
with additional yearly maintenance around $75,000 to
$90,000. This system is available free to other states
in its current format; however, it is highly probable
that a surmountable effort to customize the system
would be needed to meet MnDOT’s objectives. An
onsite demonstration was held at the MnDOT Bridge
Office in March 2009.
BENEFITS & RISK
As with most state projects, approval is required
before any money can be spent. The state evaluates
projects and makes decisions upon completion of a
Project Charter [17], which is a statement of the
scope, objectives, and participants in a project. Its
purpose is to serve as the primary sales document to
the ranking stakeholders. In order to approve, a
project must bring the department enough benefits to
outweigh project costs and risks and be given a high-
enough priority to justify devoting limited resources to
the project instead of other competing projects.
Benefits and risks are outlined in Figures 14 and 15
and are compared by levels of low, medium, and high.
The specific benefit characteristics deemed essential to
this type of project include stakeholder impact,
breadth of business functions it will improve, level of
quality increase, customer service, and agency cost
savings. Based on the attributes of the available
systems, significant benefits are expected and the risk
of implementation is fairly low.
Figure 14 – Benefit Table
Figure 15 – Risk Table
RISK MITIGATION - Risk mitigation is the effort taken
to reduce the probability or consequences of a risk
which may include physical and/or financial measures.
Two medium-level risks identified in the previous table
include complexity and ownership support. Due to the
complexity of the project, higher costs are inevitable.
The lack of regular involvement of the office
director/project champion also poses danger in
identifying key milestones of the project along the way

10. to upper management, of who hold the approval to
funding. The explicit risk is that the Engineering
Services Division will not have the funds approved
from IT Development to allocate to the project in the
timeline in which it is needed. Mitigation would be to
seek funds from elsewhere in the department.
A less overt scenario of the project complexity is that
more staff and time is required to implement this
project. Therefore, a possible risk is that the Office of
Information & Technology Services doesn’t have the
resources to devote to the project in the timeframe in
which they are needed. Mitigation would be to delay
the project to a time that better fits with staff
availability. Likewise, the Bridge Office staff may not
have the time to devote to the project in the
timeframe in which it is needed. Mitigation would be to
delay the project to a time that better fits with staff
availability or staff would be augmented.
RETURN ON INVESTMENT
Return on investment is a quantity used to help make
project selection decisions. It is typically calculated by
dividing the cumulative annual costs of the project by
the tangible benefits. A return on investment was
calculated for this proposed project. Cost inputs
include vendor software, hardware, consulting and
state personnel labor costs, estimated training (both
initial and annual), and annual software maintenance
fees. Vendor software cost determined for this project
is the highest estimate provided by the most probable
available systems. These software costs refer to
statewide unlimited user licenses for both office
computer and field laptop versions.
The hardware costs are based on typical server
hardware costs and on the purchase of 50 fully rugged
Panasonic Toughbook laptops at $3,700 a piece for
inspection staff. Currently, there are a total of 86
certified inspectors working for MnDOT in the Districts.
Inspection teams are typically comprised of 2
inspectors; therefore, an estimate of 50 laptops is the
assumed need. Roughly 2000 hours were projected
for consultant customization of the product and 2000
hours spent by MnDOT staff to implement the system.
Other costs include training hours accumulated during
project initialization and yearly updates thereafter.
The tangible benefits/savings were calculated by
MnDOT statewide labor reports for hours invested by
inspection staff on bridge inspections, reports, and
reviews for the 2008 calendar year. Typical state
employee wage assumed is $50/hour, which includes
both salary and fringe benefits. Based on historical
consultant project costs performed for the state,
consultant wage assumed is $100/hour, which also
includes both salary and fringe benefits.
Once the amount of hours was determined for each
employee, percentages of time saved were applied
based on a Return of Investment analysis completed
by the Pennsylvania Department of Transportation
(PennDOT) in 2005. PennDOT compared field and
office hours spent in one District on inspections in
2001 and 2003 to the hours using InspectTech for the
same 124 bridges. The estimated time savings in
inspection-related office duties, such as report writing
and review, was up to 60%. Time savings in
inspection-related field duties was up to 15%.
As a result, a total of 21,798 hours was charged by
MnDOT employees to field inspections and 14,791
hours to report writing, data entry, and review in
2008. When applying 15% savings to 21,798 hours,
the calculated value is 3,270 hours. When applying
60% savings to 14,791 hours, the calculated value is
8,875 hours. In order to correct for inefficient transfer
of time based on the assumption that an hour saved is
not an additional hour worked, a correction factor of
0.75 was applied to the total hours saved as indicated
below in the Adjusted Hours Saved row.
ROI SUMMARY TABLE - The summary table in Figure
17 shows that the total savings is cumulative benefits
minus cumulative costs. As expected at project
initiation, there are no benefits and only costs.
However, due to the projected time savings, the
system is expected to pay for itself in about 2.5 years!
Figure 17 – Return of Investment
SIMS IMPLEMENTATION & FEATURES

11. Since there is a substantial positive return of
investment, MnDOT invested in the product from
InspectTech.
To first evaluate the benefits of using inspection
software, a pilot project began in early 2010. The new
system, named SIMS (Structure Information
Management System) was used to generate key parts
of routine documentation and reports generated for
five Minnesota fracture critical bridges. The software
was customized by InspectTech to support direct
generation of the primary sections in the MnDOT
inspection report format. Overall, the system provided
a platform to integrate information from disparate
sources/files into a unified format in a single, easily
usable, and accessible location.
The total fixed cost for completing the pilot project
was $30,000 and covered the cost of software
customization, unlimited usage (for scope and duration
of the pilot), support, and all travel and training
expenses incurred by InspectTech.
Upon successful completion of the pilot project, full
implementation of SIMS was then planned into phases.
PHASE I: INSPECTION MODULE – Complete
implementation of the inspection module included
integration of the current electronic data from Pontis
into SIMS, provide training to applicable users
statewide, identify and fix any data or programming
errors utilizing the pilot project data, integrate data
from SIMS back into Pontis for modeling capabilities,
and incorporate bridge documentation into SIMS such
as photos, load ratings, bridge plans, etc. Among
these items, specific inspection input forms and
reports were created and customized to state needs.
A sample screenshot of the typical inspection input
form is shown in Figure 18. The timeline to create and
implement Phase I was April 2010 to April 2011. Input
of inspection data into SIMS began with the 2011
inspection season.
Figure 18 – SIMS Inspection Input
PHASE II: MAINTENANCE MODULE – The
maintenance module of SIMS is directly linked to the
inspection module. Users are able to add/edit
maintenance tasks within an inspection based directly
on inspection data and assign priority level to the tasks
– see Figure 19. Like the inspection module, users are
also able to add photos and other documents in
relation to a maintenance task. Reporting abilities are
available by individual bridge, by area or owner of
bridges, by maintenance tasks, and by priority.
Creation of the maintenance module began in late
2011 and is currently ongoing at this time.
Figure 19 – SIMS Maintenance Input
PHASE III: 3D INSPECTION MODULE – Larger
structures contain multitudes of inspection
documentation. Viewing this information can be
cumbersome. In order to view this information in a
meaningful way, a 3D inspection module is planned for
2012 on major structures in Minnesota. This module
breaks down the bridge into specific element members
by 3D mapping, allowing data to be categorized and
easily searchable – see Figure 20.
Figure 20 – 3D Inspections
PHASE IV: ANCILLARY STRUCTURES – Future work
includes inspection and maintenance tracking of
ancillary structures such as retaining walls, light poles,
radio towers, and overhead signs. This phase is
projected to begin in 2013 at the earliest.
CONCLUSION

12. Pontis, previously utilized in Minnesota to gather
bridge data, did not adequately store, manage, and
communicate all structure information collectively. It
did not have the full capability to track all bridge data
such as photos, design plans, load ratings, etc. It also
did not track data gathered during other types of
bridge inspections or that of ancillary structures such
as overhead signs and high mast light poles. It did
not identify, prioritize, and track maintenance tasks
resulting from inspections. Agencies employed
multiple and varied methods to document and track
maintenance data, such as Excel spreadsheets.
The collection of inspection data itself is time
consuming. Traditional bridge inspection in the field is
paper-based. Due to aging infrastructure, more time
is needed to quantify and record defects to establish
maintenance needs. This leads to significant increases
in data. When coupled with the practice of data re-
entry in the office, the result is a loss of efficiency,
input errors, data redundancy, and communication
breakdowns between engineering, inspection, and
maintenance. The silos that exist in a state bridge
network due to hierarchal nature inhibit efficient
communication between inspectors, engineers, and
maintenance personnel. A web-centric/automated
system provides the solution to conform these silos
without reinventing the state organizational structure
and is expected to improve the accuracy and efficiency
of data collection and asset management.
REFERENCES
1. National Bridge Inspection Standards. Retrieved
2009 from
http://www.fhwa.dot.gov/bridge/nbis.htm.
2. 2009 Minnesota Statutes Chapter 165. Bridges.
Minnesota Office of the Revisor of Statutes.
Retrieved 2009 from
https://www.revisor.mn.gov/statutes/?id=165.
3. Minnesota Administrative Rules Chapter 8810
Bridge Inspection and Inventory. Minnesota
Office of the Revisor of Statutes. Retrieved
2009 from
https://www.revisor.mn.gov/rules/?id=8810&vie
w=chapter.
4. AASHTOWare. Retrieved 2009 from
http://www.aashtoware.org/.
5. Evaluation Report Summary/February 2008.
Minnesota Office of Legislative Auditor.
Retrieved 2009 from
http://www.auditor.leg.state.mn.us/ped/pedrep/
trunkhwysum.pdf.
6. Code of Federal Regulations. Retrieved 2009
from http://www.fhwa.dot.gov/legsregs.
7. Minnesota Department of Transportation
Strategic Vision. Retrieved 2009 from
http://www.dot.state.mn.us/strategicvision/visio
n.html.
8. NodeXL: Network Overview, Discovery and
Exploration for Excel. Retrieved 2009 from
http://www.codeplex.com/NodeXL/.
9. Bronczyk, Andy (2009). Temperature
Organizational Network Analysis [PowerPoint
Slides]. Retrieved 2009 from
http://www2.webvista.umn.edu/webct.
10. Gupta, Ashim. Structural Dimensions of an
Organization. Retrieved 2009 from
http://practical-management.com/Organization-
Development/Structural-Dimensions-of-an-
Organization.html.
11. Elzarka, Bell, and Floyd. (1999). Automated Data
Acquisition for Bridge Inspection. Journal of
Bridge Engineering, 4.4, 258-262.Retrieved
February 2, 2009, from ASCE,
http://pubs.asce.org/copyright.
12. Hammand, A. and Hu, Y. (2005). Location-Based
Mobile Bridge Inspection-Support System, 1st
CSCE Specialty Conference on Infrastructure
Technologies, Management and Policy, Toronto
(10 pages).
13. SWOT Analysis. Retrieved 2009 from
http://en.wikipedia.org/wiki/SWOT_analysis.
14. Inghenia SWOT Tool. Retrieved 2009 from
http://www.inghenia.com/gadgets/swot/swot
en.php.
15. InspectTech. Retrieved 2009 from
http://www.inspecttech.com/.
16. Advitam. Retrieved 2009 from
http://www.advitam-group.com/.
17. Project Charter (v 2007.4). MnDOT Office of
Decision Support, Enterprise Portfolio
Management (12 pages).