“Engineered management systems are fast becoming the trend in decision support systems, because they are data driven, and you cannot manage what you cannot measure,” says Russ Watson, national account manager for MACTEC Engineering and Consulting Inc., a large engineering consulting firm with more than 90 offices in 35 states. MACTEC has developed an EMS called Vertex®, which is used by the U.S. Navy.

It replaces the old paradigm in which facilities managers used subjective rating systems to judge the viability of assets, and unwittingly continued to invest in facilities that were slated for closure.

“An EMS integrates the facility management plan with the corporate objectives,” says Watson. “I can’t emphasize that enough.”

It also allows facility asset managers to leverage technology to support business case funding for facility investment.

“It helps deliver the message upstream that facilities are important to the mission, and budget reductions do not lower the cost of ownership,” he says.

A Tried and True Approach

The EMS concept was originally developed in the 1970s by the Federal Highway Administration as an objective way to prioritize countless dollars’ worth of infrastructure across municipal, county, and state lines. The Air Force followed suit with a manual to manage roofing needs command-wide, which was so successful that the Department of Defense decided to invest $50 million studying all its building systems and components in this way. Commercially, General Motors Worldwide Facilities Group has been employing an EMS since the mid-1990s for roofing; in the early 2000s, the company broadened it to cover all building components in one division. Bell South Telecommunications has taken similar action.

In early 2005, the Department of Navy selected Vertex as the only off-the-shelf, commercially available product that met the General Accounting Office standards and the President’s mandate that everything be objective, repeatable, verifiable, and most importantly, defensible, says Watson.

An EMS is an expert modeling system, a computer-database decision support tool. It creates an inventory of physical assets, assigns a lifecycle to each asset, and calculates current replacement value, typically through a national costing database such as R.S. Means. It generates a numeric condition index, forecasts the asset’s remaining useful service life, predicts the future condition of an asset along a timeline, and updates the asset’s condition following repair or replacement investments.

“You put data in, and the computer gives you an opinion that is consistent and very repeatable.  Humans can’t give you consistent opinions like computer programs can,” says Watson.

This information can be used to determine the condition of a facility; the requirements and timing for sustaining, restoring, and modernizing the facility; project prioritization; the benefits of optimized investments; and the consequences of deferring work. As such, it can support “what-if” modeling of multiple funding scenarios to present to the corporate funding officers.

Condition Index Rating

One of the most critical pieces of information generated and used by an EMS is the condition index rating, which is an empirical reflection of the physical and operational degradation that has occurred in any building asset.

Every new component or system, if it is properly designed and installed, starts with a condition index rating of 100 and an estimated life expectancy. As time passes, points are deducted from the condition index rating based on a quantified inventory of standardized component defects and distresses. An EMS comes with predefined deficiencies that can be categorized as low, medium, or high in severity. Roofing, for example, can suffer blisters, ridges, and splits. Mechanical equipment can become rusted, bent, missing, or broken.

“You look at the density of those conditions, based on the type of defect, its quantity, and the severity level. The EMS goes through engineering calculations and algorithms to generate a deduct value that translates into a condition index rating,” explains Watson. “There’s a lot of math going on behind the scenes.”

These condition index ratings are placed on the design life curve that starts at the point of purchase with a 100 rating and arcs downward with time. A straight line on the bottom of the graph delineates the replacement threshold, which is an economic point in time where the predicted cost of maintenance and repair exceeds the annualized cost of ownership of the asset. If all goes well, and the asset has been properly maintained, the design life curve should intersect the replacement threshold at the end of the predicted lifespan of the asset.

For example, an asset with a current replacement value of $230,000 and a life expectancy of 23 years will have an annualized cost of ownership of $10,000 a year.

“This becomes the baseline by which we make financial investment decisions,” says Watson. “This is a solely financial consideration; when is an economically valuable time to replace this asset or ask for a renewal?”

The condition of an asset should be evaluated every three to five years, says Watson. If the owner assessed the condition of that $230,000 asset at age 13 and received a condition index rating of 80, for example, the EMS program might recalculate the service life projection to 18 years if nothing is done to improve its condition. Somewhere along the line, perhaps due to unexpected adverse conditions or a lack of proper maintenance, five years was lost from that asset’s initial life expectancy. The question then becomes, do you fix it or replace it?

“We can go in and model what it would cost to make repairs in order to get it back to a 23-year asset,” he says. “Let’s say that I want to buy back five years, and the computer says you need to spend $40,000 to do it. I can get $50,000 in asset value by investing $40,000. This decision would result in a 25-percent return on investment.”

Sounds great, but is this the best use of your available funds? That depends on how critical the asset is to the mission of the organization, a question that can be answered with the system criticality index. Not all systems are created equal. In a building that houses the computer network for a corporation, the electrical system would be critical, as would the roof overhead. The parking lot, however, would not be. Each system is assigned a system criticality index to maintain a focus on its importance in the larger picture.

“This enables you as the owner, in your agile work business environment that might change from quarter to quarter or year to year, to place metrics on systems that are critical to the function of that particular facility,” says Watson. “The system criticality might override the purely financial analysis. By having this database-driven EMS, you can begin to link decisions about how to maintain electrical in this building so that it never falls below a condition index (CI) of 95; if it does, that triggers an action. Roofing might be set at a CI of 75. Pavement is not really important to me and thus might be set to a CI of 25.

“Those levels can be adjusted based on not only economical and marketplace considerations, but also on business goals,” he says. “Are you going to stay in that facility for another 10 years?”

All of this data is used to generate an optimized sustainment budget, which lays out over several years the amount that should be invested in an asset to garner the greatest return on the investment. A five-year optimized sustainment budget calling for more than $1 million in facility investment can be defended back to a specific deficiency and its impact on an asset. If the owner does not agree to full funding, the EMS can calculate the long-term impact on the facility, and how it actually will cost more in the long run to defer investing in the short term.

Looking at multi-year optimized budgets for maintenance, repair, and capital renewal enables an asset manager to model an investment strategy consistent with the business goals and objectives, which change not only on an annual basis but sometimes on a monthly or a quarterly basis. Because it is data-driven, it removes the political influences from prioritizing spending across regions, divisions, sites, facilities, and components.

“We are trying to achieve the optimum blend of expense money, at the right time, with the right amount of capital year to year, which lowers the overall need for expense and capital,” concludes Watson.

Historically, expense and maintenance funding is based on some unit of measure, such as cost per square foot or cost per widget out the door, explains Watson, while capital is determined by how well the company did last year, how much money the board wants to reinvest, and how the stock is doing on Wall Street.

“The synergies between those two funding streams typically is not being managed at an optimum level,” he concludes. “The requirement for facilities and facilities management should not be based on trend. It should be based on age and need, with a database like an EMS application that can forecast requirements out five, 10, and 15 years. You can identify opportunities to push projects ahead and pull projects forward consistent with the business strategy that helps you get to a more levelized funding scenario.”

By Lisa Wesel

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ISSN: 1096-4894