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In academic libraries, where performance accountability is routinely expected, managers rely on quantitative data to help them make and fine-tune all kinds of decisions. The utility of both interlibrary loan (ILL) borrowing and document delivery (DD) data for making crucial collection development decisions was recognized and described in the library literature well before ILL processes were automated. But automated ILL systems like OCLC do not retain or compile transaction information data. Librarians who wanted this kind of information had to manually compile the data or purchase separate software packages. Compiling and analyzing these records was a laborious and time consuming process that did not permit ready input from ILL when important collection development decisions were needed.



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