Mr Jeremy Sedrick
Computer lab management and providing effective and efficient computer services to students requires constant decision making. Lab managers must determine which applications to purchase and include on station images, and where hardware resources should be placed to maximise utilisation. The availability of resources must then be effectively communicated to students for resources to be fully utilized. When computer lab management decisions are based on data, lab managers can be con dent that false assumptions are not being made.
For this study, we looked at how New York University (NYU) monitored their computer labs. We analysed what problems they were having and how they used a monitoring so ware to understand so ware and hardware usage. We also looked at what type of data was useful, and how different data sets allowed them to make decisions for their student computing resources.
Computer lab space is expensive and those in charge of computer lab management cannot afford to waste it on underutilised stations. Station images can become unmanageable and lab managers must decide which applications to exclude. Locating available hardware can be difficult for students and faculty, so lab managers need a way to help them quickly and easily identify open computers.
Usage data allows identification of so ware licenses that are being paid for each year but are not being used. This is crucial when imaging stations. Application licenses can be reallocated to different machines or labs where they are more likely to be fully utilised. The data shows which so ware is used and to what degree and has allowed NYU to negotiate better licensing agreements—more in-line with the actual application use. NYU invests heavily in expensive application packages; application usage data can help when it comes to negotiating renewal prices, and possibly investing money elsewhere. Whether buying licenses on a per-station basis or a campus-wide agreement, this information is key to decision-making. Gathering usage data is the most effective way to solve these problems and eliminate the guesswork associated with managing computer labs.