Likewise, the K-12 responses jumped from 47 percent to 64 percent.
3 Technologies That Education Groups Implement
Both higher education and K-12 started using the same three technologies to cut energy costs. The only difference was that virtualized servers and storage came in at No. 1 in higher education.
1. Server consolidation
2. Virtual servers and storage
3. Hardware that uses newer, low-power and low-wattage processors
5 Barriers to Becoming More Energy Efficient
But not every organization is actually pushing IT departments to cut energy costs. Slightly more than half of the IT departments in all five industries have been asked to save on energy. Nearly a third say no one's made that request.
When asked to cite the major barriers that keep them from using energy more efficiently, respondents cited five factors:
1. They don't have enough money for more efficient systems.
2. Senior managers prioritize investments in other areas rather than in saving energy.
3. They can't isolate and measure the energy they use.
4. The organization's bill payers don't look at IT's energy use.
5. They don't know all the ways to save energy.
When the first energy-efficient IT report came out in 2008, 43 percent of IT executives said the people who pay their bills don't pay attention to how much energy IT departments use. Four years later, that percentage has not changed.
But more survey respondents do know all the ways they can make their IT organization more efficient. In the 2008 report, 49 percent said they didn't know everything about saving energy. The K-12 sub-group was even higher at 57 percent. In this year's report, the all-industry percentage dropped to 42 percent.
Overall, organizations are taking steps to save energy in their data centers as well as in their entire IT operations. On their way down this path, they're figuring out what technologies could give them the most energy-efficient results, realizing that cloud computing has energy-saving potential and overcoming some major barriers.
*Industry sub-groups have a margin of error of ±7.9% at a 95% confidence level. Each sub-group had 152 respondents.
Sarah Rich contributed to this article.