Spotlight on Discovery: Tech Rating Analysis Drives Funding Increase

In the continuous struggle to maintain facilities operating budgets and accurately convey current and future needs, finding the right data to tell your story is important. With an eye towards securing appropriate operations funding for his campus, one associate vice president of facilities  needed a way to differentiate his institution and its funding story. Like at many institutions, both his operating and capitals budgets were under continual pressure. When he was shown the breakdown of his campus by tech rating, he finally had evidence of what he suspected: the complex buildings on his campus, despite being the youngest, were the most cost intensive to maintain and operate. Armed with complexity drives operating coststhis data, he was able to make the case for increased funding and better balance risk levels in the future.

What is tech rating?

Sightlines’ tech rating is the relative mechanical complexity of a campus based on a scale of 1 to 5, with 5 being the most complex. Most houses would be rated 1 because they have simple, Tech 2independent mechanical systems. On the other end of the spectrum, a building with tech rating 5 could receive high pressure steam from a central plant, year-round cooling, 100% outside air and have complex controls. Hospitals, animal care facilities, or bio-containment labs are considered tech rating 5 buildings.

The technical complexity of a campus often has a direct correlation on energy consumption, maintenance staffing, and replacement values. A higher complexity often results in higher consumption, replacement costs, stewardship targets and increased operational demand.

A campus with mostly tech 4 or 5 rated buildings will likely have higher operations and maintenance costs than a similarly sized campus with less technically complex buildings.

How was this discovery put into action?

The image at right shows the complexity breakdown for the AVP’s institution. While the complex buildings are younger, they are more cost intensive and they will face potentially expensive lifecycle demands at the same time. For this campus, 31% of its space is less than 10 years old, but 55% of space is rated tech 4 or 5. While the current space profile is favorable, levels of risk will shift quickly over the next 5 to 10 years; operations funding levels will need to shift accordingly. Not only was his campus significantly more complex than peers, but those buildings would be crossing thresholds over the coming years and would require sizeable investments.

The AVP now had the context and data needed to keep his capital and operational budgets intact while making the case for increased maintenance funding for these spaces, which will help extend lifecycles. He is also using predictive analytics to make the case for the creation of a reserve fund to provide for future appropriations of these expensive buildings and their components age. While it is important to understand families of benchmarks and their interaction as a whole, this institution was able to improve their stewardship funding model simply by adding one key benchmark to their annual budget request.

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