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Javelin Software Corporation
One Kendall Square
Cambridge, MA 02139
Year Founded:
Year Defunct:
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Javelin Software Corporation (1984-1988) was a company in Cambridge, Massachusetts which developed an innovative modeling and data analysis product, also called Javelin, and later Javelin Plus. Seen as the successor technology to spreadsheet software in reviews of the time, and rival to the then-dominant Lotus 1-2-3, Javelin won numerous industry awards, including besting Microsoft's new Excel for the InfoWorld Software Product of the Year award.

Javelin Software fell on difficult times when their Initial public offering had to be cancelled due to it being scheduled for only a few days after the stock market crash of 1987. The company's assets were later purchased by Information Resources, Incorporated (IRI), which sold enhancements to Javelin until 1994 when IRI was itself purchased by Oracle Corporation, who promptly discontinued the product.

Unlike models in a spreadsheet, Javelin models are built on objects called variables, not on data in cells of a report. For example, a time series, or any variable, is an object in itself, not a collection of cells which happen to appear in a row or column. Variables have many attributes, including complete awareness of their connections to all other variables, data references, and text and image notes. Calculations are performed on these objects, as opposed to a range of cells, so adding two time series automatically aligns them in calendar time, or in a user-defined time frame.

Data are independent of worksheets—variables, and therefore data, cannot be destroyed by deleting a row, column or entire worksheet. For instance, January's costs are subtracted from January's revenues, regardless of where or whether either appears in a worksheet. This permits actions later used in pivot tables, except that flexible manipulation of report tables is but one of many capabilities supported by variables. Moreover, if costs are entered by week and revenues by month, Javelin can allocate or interpolate as appropriate. This object design enabled variables and whole models to reference each other with user-defined variable names, and to perform multidimensional analysis and massive, but easily editable consolidations.