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7
Implementing a Risk-Based Strategy
for Investments in Federal Facilities’
Maintenance and Repair
The implementation of a more strategic, risk-based approach to investments
in maintenance and repair will require changes in procedures and mindsets. It may
also require a substantial investment of staff time and expertise up-front. Each
agency will need to determine the most effective way to move to a risk-based
investment strategy, depending on the information that it has available and its
processes, resources, and culture. Once the key elements are established, however,
a risk-based approach should provide for a much more effective and transparent
process for decision-making about the allocation of resources for maintenance and
repair activities. As the new procedures are repeated, they will become ingrained
in the organizational culture and in the workforce and will require less time and
effort to execute.
This chapter shows how some of the committee’s recommendations could be
put into action by federal facilities program managers. Topics include measures of
outcomes, linking maintenance and repair investments and outcomes to a mission,
guidelines for developing an annual funding request, predicting outcomes of a
given level of investment in maintenance and repair, and methods for identifying
risks related to deteriorating facilities.
Because missions, programs, culture, and practices vary widely among
federal agencies, each agency will need to adapt the committee’s guidance and
examples to its own situation. It may be wise to begin with pilot projects to work
through the approach before applying it to an entire organization. In addition,
collaboration among agencies on pilot projects could help to identify and resolve
issues more quickly and thereby help to implement risk-based approaches in all
federal agencies.
88
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IMPLEMENTING A RISK-BASED STRATEGY FOR INVESTMENTS 89
MEASURES OF OUTCOMES
Outcomes of individual projects (project goals) are identified during the
project planning and definition phase and can range from maintaining a heating,
ventilation, and air-conditioning (HVAC) system to operate at the manufacturer’s
specified (or original) level of efficiency, or repairing or replacing a roof, to repair-
ing or replacing groups of systems to achieve a higher level of efficiency (over
that originally specified). Whether the project is being accomplished to conserve
energy, to ensure mission capability or productivity, to lower operating costs, to
improve the condition of military housing, or for any other reason, an individual
project, if approached correctly, will have a defined set of outcomes. The outcomes
of day-to-day activities (not on a project scale)—such as service calls, preventive
maintenance (for example, lubrication and filter changes), and minor equipment
replacements—are equally important because of the potential cumulative effect
of neglecting them.
Identifying outcomes and the decision-making that leads to them occurs at
two levels: portfolio-based (strategic) and project (tactical). Some of the outcomes
identified (such as operating costs, energy use, and reliability) are more easily
quantified at the portfolio level and others are more easily applied at the project
level. Some (depending on the specific measure used for a given outcome) have
meaning at only one of the two levels.
Regardless of how an agency goes about defining the outcomes to be achieved
through its maintenance and repair program, appropriate measures are needed for
planning and programming, budget development, and identifying the results of
investments.
In Chapter 2, the committee identified an array of beneficial outcomes that
can result from investments in maintenance and repair. All of them can be mea-
sured by using available data, technologies, and tools. Most of the measurements
will be based on information that is developed after the fact (lagging measures).
However, some outcomes, such as reliability and physical condition can be pre-
dicted (leading measures), that is, the outcomes of investments can be estimated
before an investment is made, or before it is decided not to make the investment
(the do-nothing case).
Governmentwide measures have been developed for operating costs, building
condition (in the form of an index modeled on financial measures), energy use,
water use, and space utilization. Deferred maintenance and repairs is also being
reported, although the methods for estimating deferred maintenance and repairs
vary. Government-wide measures to track greenhouse gas emissions are being
developed.
In Chapter 3, the committee identified engineering-research-based indexes
and models that can be used to measure the physical condition of buildings,
building components, and some types of infrastructure. Risk assessment and con-
sequence are embedded into the indexes. The indexes can also be used to predict
the future physical condition of components and their remaining service lives. In
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90 PREDICTING OUTCOMES OF INVESTMENTS IN FEDERAL FACILITIES
doing so, they can help to identify the best time to invest in maintenance and repair
so that service lives are optimized and so that systems and components can be
replaced before they fail. Condition-index values can be rolled up to determine the
physical condition of systems, buildings, groups of buildings or entire portfolios
of buildings and infrastructure. An index to measure outcomes related to building
functionality was also identified.
In this chapter, the committee identifies data sources and methods for devel
oping measures related to reliability, accidents and injuries, building-related
illnesses, claims and lawsuits, efficient operations, life-cycle costs, customer
satisfaction, and public image. Because those outcomes are not now typically
measured by federal agencies, they present an opportunity to collaborate to de-
velop government-wide measures based on evidence-based empirical information.
Ideally, such measures would quantify the relationships between the amount of
resources invested in maintenance and repair and different levels of outcomes and
risk. Such measures may require the development of models and more empirical
evidence than is now available.
Table 7.1 replicates the beneficial outcomes identified in Chapter 2 and identi-
fies related performance measures. The data, tools, and technologies that can be
used to develop outcome-related measures are described in greater detail in the
following section. The committee cautions that agencies should, to the extent pos-
sible, ensure that performance measures are aligned to achieve complementary
objectives. Conflicts in performance measures should occur only when tradeoffs
are indicated.
Measures of Mission-Related Outcomes
Reliability. Reliability of individual systems and components can be quanti-
fied as a percentage of time that they were operating in support of an agency’s
mission or programs. It can also be tracked as the percentage and cost of un-
planned outages. Unplanned outages would need to be consistently defined but
could include such events as loss of power because of faulty electrical systems,
time lost when all or parts of a facility must be evacuated because of flooding from
deteriorated water lines or as a result of faulty alarm systems, and the like. The
number and type of unplanned outages can be measured by using data collected
by computerized maintenance management systems (CMMS), building automa-
tion systems (BAS), or another asset management systems. The percentage can be
measured as a ratio of hours of unplanned downtime (X hours, X days) to hours of
required operating time (X hours per year, X days per year). The cost of unplanned
outages could be estimated by applying an average hourly labor rate to the number
of people affected and multiplying by the number of hours of downtime (this cal-
culation could also be used to track loss of productivity). If an outage resulted in
damage to equipment, research, artifacts or other property, these costs could also
be quantified and added to the cost of bringing all systems back online.
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IMPLEMENTING A RISK-BASED STRATEGY FOR INVESTMENTS 91
TABLE 7.1 Beneficial Outcomes That Can Result from Investments in
Maintenance and Repair and Outcome-Related Measures
Objectives Outcomes Measures
Mission- Improved reliability Percentage of downtime
related Cost of downtime
Cost of damage
Service life or remaining service life
Improved productivity Output measures
Functionality Building functionality index
Efficient space utilization Space utilization as specified by Federal Real
Property Council
Cost per person (General Services Administration
model)
Compliance- Fewer accidents and injuries Recordable incident rate
related Lost time incident rate
Number and cost of worker compensation claims
Fewer building-related Number and cost of worker compensation claims
illnesses
Fewer insurance claims, Number and cost of worker compensation claims
lawsuits, and regulatory Number and cost of citations or violations
violations of regulations (such as regulations of
the Occupational Safety and Health
Administration)
Condition- Improved condition Facility condition index (financial)
related Building condition indexes (physical) and other
engineering-based condition indexes identified
in Chapter 3
Reduced backlog of deferred Total cost of deferred maintenance and repairs
maintenance and repairs as reported to Federal Accounting Standards
Advisory Board
Efficient Less reactive or unplanned Ratio of planned maintenance to reactive
operations maintenance maintenance
Lower operating costs Operating costs
Lower life-cycle costs Return on investment
Net present value
Service life extension (years)
Cost avoidance Net present value of maintenance and repair
Reduced energy use Total energy use in British thermal units (Btu)
Energy intensity (Btu/sq. ft); kilowatt hours; oil
equivalents (gallons)
Reduced water use Total gallons used
Cost per gallon
Reduced greenhouse gas Measure under development
emissions
Stakeholder- Customer satisfaction Surveys
driven Customer service calls
Improved public image Surveys
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92 PREDICTING OUTCOMES OF INVESTMENTS IN FEDERAL FACILITIES
This is an instance in which agencies could collaborate to define various
categories of outages more specifically and “mine” their CMMS and other sys-
tems to develop empirical credible data to make the case for timely investments
in maintenance and repair.
Tools and technologies to predict the reliability of equipment and systems
have been developed. Reliability-centered-maintenance (RCM), which is used by
private-sector organizations and by the National Aeronautics and Space Admin-
istration (NASA) and the Smithsonian Institution, takes into account the service
lives of equipment and components, the probability of failure, and results. With an
RCM approach, it is possible to predict the reliability of some types of equipment
and components on the basis of the probability of their failure.
Reliability of building systems and components and some types of infrastruc-
ture can also be predicted from the probability of failure by using the physical
condition indexes and models of service life and remaining service life described
in Chapter 3.
Productivity. Loss of productivity of administrative, office, or similar types
of facilities can be measured as downtime or unplanned outages, as discussed
above. Predictive measures of productivity could be developed for manufacturing,
some test facilities, or some operations facilities on the basis of the amount of out-
put that can be expected if systems are 100 percent reliable. Loss of roductivity
p
could be measured as ratios of output to time and cost.
Functionality. As noted in Chapter 3, an index of the functionality of build-
ings and building functional areas (such as those for administration, laboratory,
storage, and production) that can be used for measuring 14 categories of function-
ality has been developed. Some of the categories—for example, environmental
life-safety, comfort, efficiency, and obsolescence—are directly related to mainte-
nance and repair activities and investments.
Space Utilization. Most agencies are tracking space utilization but the
m
ethods for defining and calculating utilization vary. A tool that could be used
to track space utilization is the cost-per-person-model (CPPM) developed by
the General Services Administration (GSA). The CPPM is an Excel-based tool
designed to enable users to benchmark and compute the cost per person for work-
space, information technology, telecommunications, telework and other alterna-
tive work environments. It can also calculate potential cost savings for different
workspace scenarios, such as those which would support telework. Additional
information is available at http://www.gsa.gov/portal/content/105134.
Measures of Compliance-Related Outcomes
Accidents and Injuries. In accordance with the Occupational Safety and
Health Act of 1970 as amended, and Executive Order 12196 Occupational Safety
and Health Programs for Federal Employees, signed on February 26, 1980,
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IMPLEMENTING A RISK-BASED STRATEGY FOR INVESTMENTS 93
federal agencies are required to track workplace accidents and submit an annual
report to the Department of Labor. Federal facilities program managers in con-
cert with the safety office could request access to this information to be able to
review accident causes (such as slips, trips, and falls) and determine which ones
could be prevented through maintenance and repair investments. They could then
track the outcomes of maintenance and repair investments through such measures
as recordable incident rate, lost-time incident rate, or by the number of related
worker compensation claims or lawsuits.
The costs of accidents and injuries could be quantified by gathering data from
worker compensation claims and lawsuits, if allowed by law, or by the number
and cost of citations or violations of regulations (for example, violations of Occu
pational Safety and Health Administration standards).
Through a collaborative multiyear effort, federal agencies could potentially
develop empirical information that compares the cost of maintenance activities
required to prevent accidents and injuries with liability and other costs associated
with accidents and injuries. Data on the costs of slips, trips, falls, and other acci
dents may be available from the insurance industry or from research conducted
by such federal agencies as the National Institute for Occupational Safety and
Health or the National Institutes of Health or from disciplines other than facili-
ties management.
Building-Related Illnesses. Although building-related illnesses are substan-
tially preventable through appropriate operation of building systems and compo-
nents, including timely maintenance and repair activities, tracking and measuring
such illnesses directly is difficult, except for major incidents, such as outbreaks
of Legionnaires’ disease. The costs of building-related illnesses could potentially
be measured by gathering data from worker compensation claims and lawsuits,
if that is allowed by law.
Building-related illnesses are closely related to indoor environmental quality
(for example, temperature, humidity, ventilation rates, air particles, and water
quality). Data related to those factors can be collected through building automa-
tion and energy management systems. Facilities managers should be able to cut
down on building-related illnesses by gathering and carefully tracking tempera-
ture and other indoor environmental attributes to ensure that they stay within
acceptable ranges according to scientific studies or state-of-the-art industry
standards and through preventive maintenance activities like those identified in
Chapter 2.
One indicator of potential problems related to indoor environmental quality is
the type of customer service calls received. Typically, customer service calls are
tracked with a CMMS. Calls related to temperature (too hot or too cold), humidity
levels, moisture intrusion, air quality (odors), lack of ventilation, or water quality
(tastes bad) could indicate that systems are not operating properly and require
maintenance, repair, or replacement.
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94 PREDICTING OUTCOMES OF INVESTMENTS IN FEDERAL FACILITIES
Measures of Condition-Related Outcomes
Most federal agencies already measure condition by using a facilities condition
index (FCI) or a Condition Index (CI) as recommended by the Federal Real Prop-
erty Council (FRPC). Both are lagging measures and they are based on financial
data, not on the physical condition of facilities. Agencies also track total backlog of
deferred maintenance and repairs and report it to the Federal Accounting Standards
Advisory Board, although they use different methods for quantifying backlog.
An array of engineering-based empirically derived condition indexes for
specific types of facilities and infrastructure have been developed (see Chapter 3).
They can be used not only to quantify physical condition but to predict the prob-
ability of failure of building and infrastructure components on the basis of service
life and remaining service life.
Measures of Outcomes Related to Efficient Operations
Measures of operating costs, energy use, and water use are already being
tracked by most federal agencies as recommended by the FRPC and in accord with
other federal directives. A governmentwide method for measuring greenhouse gas
emissions is being developed.
Life-Cycle Cost. Life-Cycle Cost (LCC) analyses are generally not used
for routine day-to-day maintenance and repair activities. However, most agency-
wide maintenance and repair programs also include nonroutine large projects of
which LCC analyses could be used to determine return on investment. Circular
A-94 of the Office of Management and Budget, Guidelines and Discount Rates
for Benefit-Cost Analysis of Federal Programs provides a method that could be
adapted for this purpose.
Cost Avoidance. Cost avoidance results from making an investment in the
near term that avoids the need for a larger investment later. One method of quanti-
fying cost avoidance would be to analyze project scopes and develop estimates of
the cost to an organization if the project is not implemented. Alternatively, failure
probability analyses based on models of service life and remaining service life
can be conducted. The costs of the probable failure and the costs of immediate
investment can be compared on the basis of net present value.
Ratio of Planned Maintenance to Reactive Maintenance. One measure of
efficient operations is the ratio of planned or programmed maintenance to reactive
(unscheduled) maintenance and repair (such as emergency service calls). The ratio
can be an indication of whether a facilities management organization is running
smoothly through logically scheduled allocations of manpower and resources or is
reacting to unexpected crisis after crisis and wasting resources through inefficient
work efforts. The Association of Higher Education Facilities Officers-APPA has
suggested that an appropriate ratio of planned maintenance to reactive mainte-
nance is 75 percent or more to 25 percent or less (Rose, 2007), but there is no
industry-accepted standard for the appropriate breakdowns of work. Nonetheless,
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IMPLEMENTING A RISK-BASED STRATEGY FOR INVESTMENTS 95
in the present committee’s opinion, it is safe to say that an organization that is
performing more than 50 percent of its maintenance and repair on a reactive basis
is not operating efficiently.
CMMS data can be used to track this measure. Comparing rates over time
and by season can add definition to the measure through comparisons of similar
times and weather conditions. High rates of unscheduled work could also be an
indicator of deteriorating condition (which would lead to a higher rate of service
calls), although they could also indicate poor workmanship, poor maintenance
and repair planning, or other factors.
Measures of Stakeholder-Driven Outcomes
Customer Satisfaction. Customer satisfaction data can be tracked through on-
line surveys which are conducted by many facilities management organizations. The
number and type of customer service calls could also be tracked through a CMMS.
Public Image. Similar to customer satisfaction, data related to public image
can be tracked through surveys of visitors to federal facilities.
LINKING MAINTENANCE AND REPAIR INVESTMENTS AND
OUTCOMES TO MISSION
As noted in Chapter 1, most federal agencies have developed asset manage-
ment plans that are intended to “help agencies take a more strategic approach to
real property management by indicating how real property moves the agency’s
mission forward, outlining the agency’s capital management plans, and describing
how the agency plans to operate its facilities and dispose of unneeded real prop-
erty, including listing current and future disposal plans” (GAO, 2011b, pp. 6-7).
The committee recommends that each agency also develop a longer-term
plan for maintenance and repair investment. A longer-range plan can be used to
link maintenance and repair investment clearly to organizational mission and can
make maintenance and repair investment a more visible and integral component
of portfolio-based facilities management. Ideally, such a plan will be developed
in conjunction with and will be approved by the agency’s senior executives so
that there is “buy-in” from all levels of the organization. The Bureau of Overseas
Buildings Operations of the U.S. Department of State has developed a longer-
term (5- to 10-year) maintenance plan for its facilities portfolio that provides one
example of how this could be done.
A well-developed longer-range maintenance and repair plan should provide
for the following:
• Outcomes of maintenance and repair activities and investments that are
aligned with the organization’s mission and programs.
• A basis of communication and planning throughout the organization and
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96 PREDICTING OUTCOMES OF INVESTMENTS IN FEDERAL FACILITIES
with oversight groups, including OMB and Congress.
• A framework for developing annual funding requests and budget
submissions.
• Continuity in direction through organizational change and leadership
turnover.
The committee recognizes that differences in agencies’ missions, programs,
facilities, and resources will lead to differences in the format and content of
longer-range strategic maintenance plans. However, a longer-range plan should
include the following basic elements:
• A clear statement of the organization’s maintenance and repair investment
objectives.
• An agreed-on set of outcomes related to each objective.
• Priority-setting or weighting of those outcomes.
• Identification of the types of facilities that are mission-critical or
mission-supportive.
• Identification of critical types of systems and components.
• Performance goals, performance indicators, and a baseline for each
outcome.
• Methods to be used for implementing maintenance and repair investments
(such as preventive maintenance, recurring maintenance, and third-party
financing).
• Identification of the types of risks posed by lack of timely investment.
Table 7.2 provides a hypothetical example of the items to be included in a
longer-range maintenance and repair strategic plan. Guidance for developing the
basic elements of a plan follows.
Step 1. Establish investment objectives and outcomes related to each objec-
tive. Five broad objectives for maintenance and repair investments were identified
in Chapter 1 (shown in column 1 of Table 7.1). An array of beneficial outcomes
that can be achieved and measured have also been identified (Chapters 2 and 7).
Individual agencies should not expect to achieve all the identified outcomes.
Rather, each agency should choose a set of outcomes that are most closely related
to its investment objectives. In some cases, an agency may want to add investment
objectives or categories of outcomes that are more closely related to its mission.
The emphasis should be on appropriate outcomes that are agreed to at all
l
evels of the organization and that can be predicted, measured, defended, and
verified by audit. An agency should always consider the credibility, accuracy,
and value of data for developing and evaluating funding requests and for com-
municating with others in the agency when determining which data to collect and
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TABLE 7.2 Hypothetical Example of Elements to be Included in a Longer-Range Strategic Plan for Maintenance and Repair
Activities
Importance Mission Critical
Outcomes of Outcomes Facilities (Type or Performance Goals, Methods for
Related (Priority or Specific Facility); Critical Baselines for Outcomes, Delivering Types of Risks
Investment to Each Weighting Mission Supportive Systems and and Performance Maintenance and Posed by Lack
Objectives Objective Factor) Facilities (Type) Components Measures Repair Activities of Investment
Enable Reliability X percent To be determined Electrical X percent reliability on Preventive Loss of power
mission of critical (TBD) by agency systems an annual basis; to be maintenance during essential
systems measured by hours of operations
unplanned outages.
Provide Fewer X percent TBD by agency
safe, healthy accidents and
and secure injuries
workplaces
Support Lower X percent TBD by agency
fiscal operating
soundness costs
Operate Improved X percent TBD by agency
efficiently condition
Less X percent TBD by agency
unscheduled
work
Support Reduced X percent TBD by agency Lighting Reduce energy use by Third-party
public policy energy use systems 30 percent by 2015 financing, ESPCs,
goals and programmed
major maintenance
97
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98 PREDICTING OUTCOMES OF INVESTMENTS IN FEDERAL FACILITIES
how best to collect them. Other considerations should include the time, effort, and
cost of gathering data.
Step 2. Set priorities among the outcomes to be achieved. Each agency will
need to determine which outcomes are most important to achieve and set priorities
among them accordingly. One method for setting priorities is to assign weights
that can be expressed as percentages. Some outcomes will be related to more than
one objective and can produce multiple benefits. For example, reducing energy
use may also reduce operating costs. Such relationships should be considered in
the weighting process.
Final weights should not be uniformly applied without knowledge of the
available resources and the demand for them. For example, a 32 percent weight
for activity X may make perfect sense for a budget of $100 million. But if the
budget were suddenly cut to $50 million, a 32 percent investment in activity X
might produce only two-thirds of a mission-critical building. Likewise, if the
budget were increased to $150 million, 32 percent might be too high, and some
resources could be allocated to other projects. If weights are established in the
longer-range maintenance plan, the assumptions related to the level of available
resources should be clearly documented.
Step 3. Identify types of facilities or specific buildings that are mission-
critical and mission-supportive. To optimize investments, agencies will need to
identify the types of facilities (such as piers, museums, and hospitals) or specific
buildings (such as the Pentagon) that are mission-critical or mission-supportive.
Many agencies have already done that through their critical infrastructure plans,
through other documents, or through the use of the mission dependency index
(MDI). Such a classification will help to establish where maintenance and repair
investments should be targeted to ensure that funds are being used effectively. If
agencies are still targeting maintenance and repair investments to facilities that
are excess, obsolete, underutilized, or slated for disposition or demolition, they
should clearly indicate where and why.
Step 4. Identify critical systems and components that are most important
for achieving outcomes. Agencies will need to identify the types of systems
and components that are critical for achieving desired outcomes or that pose the
greatest risks. As noted in Chapter 4, best-practice organizations aggregate their
maintenance and repair requests by types of systems and components to create a
more transparent linkage to specific building performance. Aggregating requests
that way also allows decision-makers to understand more easily the relative im-
portance of systems and components for various investment outcomes. Agencies
that use the MDI can extrapolate critical systems and components from it. The
Army’s Engineering Research and Development Center-Construction Engineering
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IMPLEMENTING A RISK-BASED STRATEGY FOR INVESTMENTS 99
Research Laboratory has also created a research-based Component Importance
Index that can be used to identify critical components (Uzarski et al, 2007).
Critical systems and components would likely include the following:
• Enclosures—façades, windows, and doors,
• Roofs,
• Heating, ventilation, and air-conditioning (HVAC),
• Lighting,
• Electrical distribution,
• Fire protection systems,
• Security systems,
• Plumbing and water fixtures,
• Roadways, parking, and paving,
• Industrial type systems—cranes, conveyors, and the like.
Step 5. Establish performance goals, baselines for outcomes, and perfor-
mance measures. Establishing performance goals, baselines for outcomes, and
performance measures is essential for tracking the effectiveness of maintenance
and repair investments, for providing feedback on progress, and for indicat-
ing where investment objectives, outcomes, or procedures require adjustment.
“Buy-in” at all levels of the organization is needed if sustained progress is to be
achieved.
Step 6. Identify the primary methods to be used for delivering maintenance
and repair activities. Maintenance and repair activities can be delivered through
programs for preventive maintenance, programmed major maintenance, replace-
ment, or in some cases, public-private partnerships or third-party financing (such
as through energy savings performance contracts). Identification of the methods
of delivery will help agencies to determine the level of resources that should
be allocated to each type of maintenance activity and to repair projects and to
determine when repair projects can be funded through methods other than direct
appropriations.
Step 7. Identify the types of risks posed by lack of timely investment. Identify-
ing the types of risks posed by not investing in deteriorating facilities, systems,
and components is important for providing more transparency in the decision-
making process and for communicating with staff at all organizational levels. For
a longer-range maintenance plan, a general description of the types of risks, as
opposed to the level or quantification of risks, will be appropriate because risks
may change every year or more often. In all cases, the description of risks should
be credible. Methods for identifying risks related to deteriorating facilities, sys-
tems, and components are described later in this chapter.
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100 PREDICTING OUTCOMES OF INVESTMENTS IN FEDERAL FACILITIES
GUIDELINES FOR DEVELOPING AN ANNUAL
RISK-BASED FUNDING REQUEST
In any given year, the number of required maintenance activities and re-
pair projects will exceed available funding. A longer-range maintenance and
repair strategic plan can provide the framework for determining the types of
activities and projects that are the most critical to fund for a sustained period.
Determinng the level of funding for maintenance activities and identifying spe-
i
cific repair projects that should be funded in a given budget year require a more
detailed analysis—one that still recognizes that budget requests are generally
developed 2 years in advance of funding.
Table 7.3 lists the types of elements that should be identified in annual fund-
ing requests. A standard template could be developed and then used by facilities
managers at the field level and rolled up to headquarters. The headquarters staff
can use the same template to reset priorities among projects across an agency to
align with organizational objectives and to present a unified request to decision-
makers in the agency.
Using the same template at all levels of the organization will help to embed
new processes, provide for more consistent communication and messages, and
provide transparency about how budget submissions are being developed.
Step 1: Categorize identified maintenance activities and repair projects in an
organizational framework for investment. Facilities program managers at the
field level or at headquarters should group all their identified maintenance activi-
ties and repair projects by categories of critical systems and components and by
whether they are mission-critical or mission-supportive facilities as identified in
longer-range maintenance plan (if available). At the field level, it should be pos-
sible to identify the specific facility or groups of facilities where the maintenance
activities and repair projects will be implemented.
Step 2. Determine the cost of the maintenance activities and repair projects
and identify the method of delivery. The costs of maintenance activities and
repair projects can be verified through parametric estimates, estimates by agency
experts, collection of estimates from subordinate organizations, knowledge-based
condition assessments, or any other method that facilities program managers
might use that has credibility in the organization. The methods to be used for
executing maintenance activities or repair projects (such as programmed major
maintenance or third-party financing) should also be identified.
Step 3. Identify the outcomes to be achieved. This can be done in two phases.
First, list the outcomes specifically identified in the longer-range maintenance
plan that have highest priority in the organization. Second, identify other credible
outcomes for a specific project that could also have an organizational benefit that
is not called out in the longer-range maintenance plan. That can take the form of
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TABLE 7.3 Hypothetical Template for Setting Priorities Among Maintenance and Repair Activities to Be Included in an
Annual Funding Request
Projects
Classified Type and Level
by Critical Mission- Mission- Outcomes Other of Potential
Systems and Critical Supportive Method of to Be Potential Risks If Not
Components Facilities Facilities Costs of Projects Delivery Achieved Benefits Funded Risk Ratings
By category By category By category Determined at Preventive All the Additional Narrative with As calculated
established established established time of funding maintenance outcomes information supporting using CRR or
in longer- in longer- by longer- request (conduct programmed major that apply as required quantitative other process
range range range knowledge- maintenance; established for well- data (see below)
maintenance maintenance maintenance based condition energy savings in longer- informed
strategic plan strategic plan strategic plan assessments performance range decision
where contract; public- maintenance making
appropriate) private partnership strategic plan
101
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102 PREDICTING OUTCOMES OF INVESTMENTS IN FEDERAL FACILITIES
a narrative with backup evidence-based information that can be verified. The pro-
cess should ensure that critical, credible information is available for well-informed
decision-making on behalf of the entire organization.
Step 4. Identify the type and level of risks incurred if the maintenance activi-
ties and repair projects are not funded in the relevant fiscal year. This step is
intended to ensure that the most critical requirements rise to the top of the funding
requests and that senior decision-makers understand the implications of not fund-
ing maintenance activities or particular repair projects in the relevant fiscal year.
It is also intended to provide greater transparency, credibility, and accountability
in budget formulation and execution.
Step 5. Setting priorities among projects. A variety of methods are available for
ranking all the proposed repair projects and setting priorities among maintenance
and repair activities. They include the Analytic Hierarchy Method and the Delphi
Method.
The Analytic Hierarchy Method (ASTM 1765-07e1) allows consideration
of multiple decision-making criteria in the priority-setting process. The multiple
ranking criteria are weighted through pairwise comparisons, and the relative
importance of each criterion becomes established. Through this process, the vari-
ous decision-making criteria are weighted to provide an objective measure of the
priority of a specific activity or project.
The Delphi Method (Linstone and Turoff, 1975) is another approach whereby
a multiple-stage protocol is used to obtain a consensus expert opinion. Experts are
asked to respond to questions, and after each stage a facilitator summarizes the
results. Eventually, with revision of responses, the range of responses decreases
and the group as a whole converges toward a consensus. Typically, the process has
guidelines about what constitutes a consensus and about the number of rounds.
The method can be applied with face-to-face meetings or questionnaires.
Whatever process is used, it should be documented and used consistently by
the various field offices to ensure that when a request is sent to headquarters, it is
credible and easily communicated.
PREDICTING OUTCOMES OF A GIVEN LEVEL OF INVESTMENT
IN MAINTENANCE AND REPAIR
Depending on the outcomes selected in Step 3, one or more applicable
prediction models (see Chapter 3) should be used to create projects and develop
priorities for programs at the field level. Additionally, a consequence (what-if)
analysis should be made that considers different possible investment levels (such
as likely, lower limit, and upper limit).
After the field-level requests have been submitted to the facilities manage-
ment office at headquarters, the headquarters staff will need to reset priorities
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IMPLEMENTING A RISK-BASED STRATEGY FOR INVESTMENTS 103
among the requests to meet overall organizational objectives. They should also
roll up the predicted outcomes of maintenance activities and repair projects to
quantify the expected results on a portfolio-wide basis to the extent possible (for
example, total energy reductions across all facilities). Once the overall funding
request is prepared, the headquarters staff can use a funding “cutoff” line (such
as $3 million or $5 million) to show which activities and projects can be funded
at a given level of investment and which ones cannot. Performing a consequence
analysis through the use of applicable prediction models can change the project
mix to maximize desired outcomes. A funding request in this type of format will
provide greater transparency about the repair projects that are considered to have
highest priority, their costs, and the benefits that the organization can expect. It
will also make clear the risks posed by not funding projects.
METHODS FOR IDENTIFYING RISKS RELATED TO
DETERIORATING FACILITIES
The risk-analysis literature offers multiple entry points into answering the
following questions:
1. What can go wrong?
2. What are the chances that something with serious consequences will go
wrong?
3. What are the consequences if something does go wrong?
4. What can be done and what options are available? How can the conse-
quences be prevented or reduced?
5. What are the associated tradeoffs in costs, benefits, and risks? How can
recovery be enhanced if the scenario occurs?
6. What are the effects of current management decisions on future options?
How can key local officials, expert staff, and the public be informed to
reduce concern and increase trust and confidence?
Some entry points are entirely quantitative and others mix quantitative and
qualitative data. Given the reality that federal agencies have offices and properties
around the world, a risk-based approach to investment is most logically imple-
mented in two phases: screening to set priorities among the maintenance activities
and repair projects and then detailed analyses from among those chosen as having
high priority. The information developed during the overall screening process can
be used to identify types of risks and can be used in the longer-range maintenance
plan. More detailed analyses will be more appropriate for the development of
annual funding requests.
It is essential first to identify the vulnerabilities of federal facilities, systems
and components, and then evaluate the vulnerabilities in the context of importance
to mission fulfillment. The mission dependency index and the USACE’s asset
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104 PREDICTING OUTCOMES OF INVESTMENTS IN FEDERAL FACILITIES
management strategy (see Chapter 4) incorporate risk-based screening processes
to determine which facilities and components are the most critical for an agency’s
mission and the failure of which poses the greatest risks to operations and mission
achievement.
Two additional examples identified by the committee clearly illustrate the
screening process and are based on a combination of science, engineering, and
legibility. Both examples deal with vulnerability to terrorism but the principles
of how to set priorities are transferable to building and infrastructure failures.
Apostolakis and Lemon (2005) developed a screening model to identify vul-
nerabilities of a university-centered community on a single campus. The authors
rated asset vulnerability on a continuum that began with red (most vulnerable)
and proceeded through orange, yellow, blue, to green (least vulnerable). Then
they studied how the elements of the infrastructure—such as natural gas, water,
and electricity—were interconnected. Next, they developed a “value tree” that
reflected the values and perceptions of the decision-makers and other important
stakeholders about each asset. The value categories included health, safety and
environmental effects; economic effects on property, academic-institution opera-
tions; stakeholder effects; and effects on public image.
The values were then weighted. The greatest weights were assigned to effects
on people, followed by effects on the environment, university programs, and so
on. The vulnerability and value data were then connected to produce a priority list
of campus projects that the university could act on. Those projects ranged from
welding manhole covers to building independent infrastructure supply lines to
adding backup components.
Leung, Lambert, and Mosenthal (2004) built a screening tool to set priorities
for investments to protect bridges in Virginia. Their analysis was more complex
than the first one in that it considered multiple major assets in different uncon-
nected locations as well as specific singular assets, but the logic was the same.
Scenarios that could degrade the system were identified, ranked according to their
potential adverse events, and then compared with the system’s existing resilience,
robustness, and redundancy. At every step, analysts integrated historical data and
expert judgment. After completing the initial risk assessment, they gathered infor-
mation on the cost, on engineering feasibility, and on policy options. The security,
economic, and safety implications of options were then studied at the national,
regional, and local levels. Simple decision trees were built to aid decision-makers
in understanding the options before priorities were set.
Although the first method was applied to a single area and the second was
applied at regional and national levels, both followed risk-analysis principles,
including identifying critical assets, examining their vulnerability, and setting
priorities for their protection.
For individual facilities, systems, and components, traditional engineering
approaches can be applied to priority projects. It requires setting numerical per-
formance measures in a risk-related framework (see Ellingwood, 1994). In civil or
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IMPLEMENTING A RISK-BASED STRATEGY FOR INVESTMENTS 105
structural engineering, reliability is defined with a “reliability index” or a “safety
index” (see Ang and Cornell, 1974), which is related explicitly to an underlying
probability of performance. For example, in designing a building, structural engi-
neers often apply numerical “factors of safety” or “load and resistance factors” to
ensure the safety of the building against external loads, including earthquakes or
windstorms. That design procedure can be integrated with estimates of probability
of failure. Indeed, engineering standards for the design of buildings and bridges
are now widely based on this approach (see ASCE, 2005; and ASCE/ANSI, 2006).
Inspection and repair intervals may be optimized or nearly optimized by
decision-makers in order to maintain reliability of function. Engineered components
and systems deteriorate with time and use. To maintain a given level of reliability
(probability of performance), inspection and repair of the critical components at pre-
scribed time intervals are necessary. For example, to maintain the performance of a
bridge component against fatigue failure, the interval of inspection and repair can be
altered to ensure that a specified reliability (probability of nonfailure) is maintained
(see discussion of knowledge-based condition assessments in Chapter 3).
An important but sometimes overlooked aspect of risk analysis is that of
probability of occurrence. For example, the consequences (such as lives lost,
dollar value, or mission interruption) of an adverse event may be very high, but
if the probability of the event is extremely small, the risk will be minimal. (See
Appendix C for further discussion.)
At the individual asset level, a critical complication is uncertainty and how it
affects performance (Ang and Tang, 2007; Frangopol et al., 2001). It may be that a
critical component should perform flawlessly for 5 years. However, some perform
beyond expectations and others fail far more rapidly than expected. Consequently,
it is essential that facilities program managers use knowledge-based inspection
practices and set inspection, maintenance and repair schedules that recognize the
reality that some critical components of important assets will fail before they are
expected to.
The committee recognizes that many federal agencies will not have the
r
esources to undertake detailed engineering-based analyses for the majority of
maintenance activities and repair projects that they must evaluate annually. One
method of analysis and priority-setting that could potentially be used by agencies
involves the use of risk-rating charts developed for reliability-centered mainte-
nance (RCM) processes. The process is relatively simple and does not require the
collection of large amounts of data, but it does require knowledgeable, experi-
enced facilities management professionals.
In this type of process, risk ratings are established for specific types of com-
ponents (for example, roofs, HVAC systems, and some equipment) and for sub
categories of them. Each risk rating for a specific component includes two primary
elements of risk: probability of failure (POF), and failure consequence (FC). The
component risk rating (CRR) is the product of POF and FC, or CRR = POF × FC
(Figure 7.1).
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106 PREDICTING OUTCOMES OF INVESTMENTS IN FEDERAL FACILITIES
Failure
Consequences 5
4
3
2
1
1 2 3 4 5
Probability of Failure
FIGURE 7.1 Component risk rating chart.
Some organizations have standard facility categories.1 In addition, each
a
gency might have several mission-specific categories of components. For exam-
ple, runways, air traffic control towers, and airplane hangars are mission-specific
for the Air Force, piers and cargo loading cranes are mission-specific for the Navy,
and museums are mission-specific for the Smithsonian Institution.
Assigning Probability of Failure Ratings. Typical POF ratings are shown below:
• 5—The probability of a failure in the given fiscal year is high.
• 3—The probability of a failure in the given fiscal year is moderate.
• 1—The probability of a failure in the given fiscal year is low.
• 2 and 4—Variances between the other three ratings as determined by
expert opinion.
1Standard facility asset or component groupings for an agency can follow the ASTM Uniformat II
classification approach (ASTM E-1557) or any other standardized approach recognized or used by the
agency. Uniformat II recognizes 17 building systems. The Department of Defense and other agencies
have methodologies for grouping facilities by importance (mission-specific) or use (category codes).
It is not the intent of the present committee to suggest that agencies “reinvent” groupings, rather
they should use a logical, reasonably comprehensive approach that is compatible with their facilities
management approach and regulations.
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IMPLEMENTING A RISK-BASED STRATEGY FOR INVESTMENTS 107
The literature includes many ways of quantifying risk that are based on how
people describe it. See, for example, Reagan et al., 1989.
Assigning Failure Consequence Ratings. Examples of typical FC ratings are
shown below:
• 5—Serious consequences, such as death, injury, illness, extended shut-
down of an agency’s mission, substantial costs, substantial environmental
effects, or noncompliance with regulations.
• 3—Moderate consequences, such as reduced comfort, increase in long-
term ownership costs, or delay in mission-completion date by some
n
umber of days or weeks.
• 1—Minimal consequences.
• 2 and 4—Variances between the other three ratings as determined by
expert opinion.
Example 1: With HVAC as a component category, the subcategories (defined as
a type of facilities that have similar risk characteristics) are defined and a risk
rating is assigned:
• Warehouse ventilation where multiple air-supply units supply air to the
same large space. Failure of a single unit will have a small effect on
mission-related operations and the FC rating would be 1.
• Laboratory air supply in which air cleanliness and temperature and
umidity are critical for accurate results. Laboratories are usually of such
h
a size that only one HVAC unit supplies a specific laboratory and the FC
rating for this subcategory of components might be 4 or 5.
Example 2: With roofs as a component category, a specific agency might identify
the subcategories and assign a risk rating as follows:
• Roofs on aircraft hangars. If a serious leak occurs in the roof of an air-
craft hanger, it may have a small effect on the assets within (airplanes and
related components), because such assets are designed to withstand the
elements. The FC rating might be 1.
• Roofs on central data centers. Roof leaks on data centers could shut down
an agency’s operations for an extended period and the FC rating might be 5.
Once the POF and FC ratings are established for each component category
and for the subcategories, the component risk rating (CRR) can be calculated.
In the committee’s experience, an agency would typically have no more than
20 categories of critical components and perhaps 10 subcategories of facility types
with an average of about two risk ratings each. That would mean establishing
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108 PREDICTING OUTCOMES OF INVESTMENTS IN FEDERAL FACILITIES
about 60 CRRs per agency. Once the CRRs ratings have been established by the
facility management program, they should be reviewed by senior-decision-makers
to ensure “buy-in” at all levels of the organization.
The CRRs can now be used for all facility components and types. Although the
task of establishing the CRRs will require an investment of time and effort upfront,
established CRRs can be used in future years with little additional effort.
