FACILITIES MANAGEMENT WHITE PAPERS

Optimizing Your Facility Investment Strategy

Good Planning Will Extend Building Life Cycles,
Decrease Ownership Costs

Russ Watson
Program Manager
Facility Lifecycle Group
MACTEC, Inc.

Applying sound financial planning methodologies is not only crucial for your personal portfolio, but is also essential in facility asset management. When properly implemented, facility asset management can extend facility and building life cycles, lower annual funding requirements and decrease facility ownership costs.

Buildings are a significant investment for any organization. Many facility investment strategies lack a baseline facility annualized cost of ownership. By establishing an annual cost of ownership (ACO), you can set a baseline for facility planners to evaluate facility sustainment investment rates. Today, facility planners develop funding strategies based on traditional measures such as historical spending factors, subjective condition assessments, industry trends and drivers. But owners need to adopt commercially available technology tools that provide the same financial planning services for your building as they do for your business planning or personal retirement plan.

Decision support tools are becoming commonplace in the technology toolbox. Decision support technology is based on data-driven calculations and mathematical algorithms that can be reviewed, audited and improved upon as programs mature. Much like the annual audit by your personal financial planner, decision support systems assist building owners and managers in determining financially prudent investment strategies.

There are five key formulas or calculations that support decision support technology for facility assets:

1. Identifying the Design Life Curve
2. Calculating a numeric Condition Index rating on auditable objective data
3. Forecasting asset Service Life based on current condition
4. Applying Life Cycle Cost analysis and benefit-to-cost ratio analysis
5. Calculating Return on Investment (ROI) and aligning investment strategy with business objectives

Design Life

Understanding and documenting the intended design life of a given facility system and/or component is crucial in developing the baseline 'As-Is' Condition Index. Within a decision support application, each asset is associated with a design life curve derived from recognized industry standards and trade groups such as HUD, Means, Whitestone Group, Fannie Mae, AASHTO, RIEI and others. Most design life curves follow an 80/20 rule where 80 percent of asset failure occurs in the last 20 percent of asset life.

Condition Index

To develop a condition index, a visual survey has to be performed on each unique component asset. Condition assessments are based on quantifying visually identified distresses, and determining the severity of that distress from objective choices. These existing distresses provide a measure of the assets' condition and performance integrity. They also provide an early indication of possible system failures, maintenance and repair requirements, and a basis for scheduling a more comprehensive evaluation, if appropriate. Condition Index is based on a scale of 1 to 100, with 100 representing a new, defect-free asset or component.

The degree of system component deterioration is a function of:

1. Types of distress
2. Severity of distress (i.e. size, extent of deterioration, etc.)
3. Amount or density of distress, which can be expressed as a percentage of the total size or value of the inventoried asset

Each of these distress characteristics is significant in determining the overall amount of physical deterioration. If any of these characteristics are ignored, developing a meaningful Condition Index is not possible.

For each system/component there are several different types of visual distresses and possible degrees of severity for each type of distress, and a range of density for each combination. Combining the effects of these three characteristics into a single index requires using computer algorithms that generate numerical deduct values.

Deduct values calculated from distress type, severity level, and density are determined and subtracted from 100 to create a Condition Index.

Service Life

Predicting services life is a direct result of the Condition Index. For example, if an asset in year 11 has a Condition Index of 73, then plotting this index against the design life curve will indicate if the asset is "on the curve" or "off the curve". The following graph depicts this scenario with the green line representing the design life and the red line representing the current service life of this asset with a Condition Index of 73 at year 11.

In this example, the asset with a Condition Index (CI) of 73 at year 11 is projected to have a useful service life that is five years less than the design life, the anticipated service at the time it was first placed in service.

Our approach follows the functional steps listed below to determine current condition and to project the remaining useful service life of any known asset:

1. Perform objective visual surveys of discrete physical asset components
2. Determine original design life and current replacement value (what is the investment at risk?)
3. Quantify visual observed defects that are adverse to the life cycle of the asset (create deduct values)
4. Determine the Annual Cost of Ownership (the baseline) by amortizing the replacement value over the design live including cost of capital
5. Apply deduct values against the life cycle to determine 'as-is' condition-based age
6. Subtract 'as-is' condition-based age from design life to determine remaining service life.

Given the 'As-Is' condition-based age and remaining life expectancy of an asset, the question becomes …what are the options to extend the life of this asset and are the options cost effective?

Life Cycle Costs

Return on investment (ROI) analysis is the underlying basis for the decision process. Critical in performing this analysis is converting a facility asset into an annual cost of ownership.

To adequately convert facility data into financial terms, you first establish the value of the asset being managed. For example, a roof asset that is 35,000 square feet with a replacement value of $5 per square foot would have a current replacement value (CRV) of $175,000. But what is the value of this roof when it is 12 years old?

Depending on the definition of Capital Depreciation and Expense Allocation, from an accounting standpoint, it is likely that a 12-year-old roof asset has little, if no book value, to the owner.

However, every year that the roof is performing represents another 12 months that the owner does not have to purchase a new roof. If there was an opportunity to invest $12,000 in repairs to this roof asset and it is estimated that this $12,000 would buy two more years of serviceability, would the investment generate a positive return on investment? Our approach is to value each year of a facility component's life (in this example a roof) by amortizing the replacement cost combined with an internal cost of capital or bond-rate over the design life of the asset. This calculation, while perhaps not valid from generally accepted accounting principles, is extremely valid when determining whether or not to make an investment in repair.

Given the example above, the $175,000 roof asset amortized over a design life of 20 years at an assumed bond rate of 10 percent represents an annual cost of ownership of $20,555. If an investment of $12,000 would 'buy' the owner two additional years of service life, then the owner would benefit by $29,110 in economic value added or a 242 percent return on investment. The following calculation depicts this value:

Conversely, the decision to not invest $12,000 in the strategic repair would be at a cost to the owner of $29,110 in premature failure of roof life.

The net results from this analysis will demonstrate a significant ROI contribution to the owner's facility management success and serve to justify both funding requests and investment decisions to the owner's constituency.

Simply put, the analysis follows seven basic steps:

1. Quantified conditions (deficiencies) drive condition-based age
2. Model various scenarios of repair to determine the best value received for the available budget (repair or replace)
3. Recalculate the condition-based age with each scenario
4. Apply the cost to remove defects (because we measured them)
5. Measure the benefit (life extending results) of repairing the asset
6. Compare the benefits of repair versus replacement versus doing nothing (preventative maintenance only)
7. Optimize the investment required based on the best value

Return on Investment (ROI)

The 80/20 aspect of a design life curve and understanding that the longer deficiencies go untreated, the greater the gap between design verses performance curve, it is then easy to recognize that the sooner an asset can be repaired, the less the investment cost and the greater the return. Therefore by identifying the spending strategies with the greatest ROI will allow the owner to achieve the biggest bang for their buck.

Summary

Applying financial management techniques to facility maintenance, repair and replacement plans will optimize your facility investment strategy and help plan a successful sustainment and ultimate retirement of your facility assets. Applying a decision support financial planning methodology will enable you to determine your facility objectives and formulate the best financial strategies.

Russ Watson is a Program Manager for MACTEC Engineering and Consulting, Inc.'s Facility Lifecycle Group (FLG, www.mactecflg.com), which provides facilities asset management software and services. MACTEC has developed a decision support product called Vertex, currently used by major organizations to provide financial investment strategies for facility asset management. MACTEC (www.mactec.com), based in Alpharetta, GA, is an environmental, engineering, construction management, and infrastructure services firm with more than $500 million in annual revenue, and 3,000 employees in over 90 offices nationwide.