Forecasting discovery costs based on interpolation of historic event patterns
First Claim
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1. A computer-implemented method of forecasting litigation discovery costs for a litigation matter that includes a number of business events, comprising:
- capturing historical business events for the litigation matter;
aggregating the historical business events, with an aggregation module, and statistically analyzing the captured historical business events by matter type, time period, and business event type to produce statistical data specific to a time period;
aggregating the statistical data for matter type and event type;
extrapolating future business events using the statistical data provided by the statistical analysis to calculate probabilities of occurrence of future business events;
forecasting an extrapolated volume of production at the time of a forecasted export event, wherein an export event is an event representing when a document page is being exported; and
forecasting costs for future discovery from the extrapolated volume of production by applying a culling rate and average review cost.
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Abstract
A computer-implemented method of forecasting discovery costs captures historical business events, which are aggregated and statistically analyzed by matter type and business event types. Statistical data is used to calculate probabilities of occurrence of future business events and to extrapolate occurrence of those future business events. The method forecasts an extrapolated volume of production at the time of a forecasted export event. The method further forecasts costs for future discovery from the extrapolated volume of production.
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Citations
19 Claims
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1. A computer-implemented method of forecasting litigation discovery costs for a litigation matter that includes a number of business events, comprising:
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capturing historical business events for the litigation matter; aggregating the historical business events, with an aggregation module, and statistically analyzing the captured historical business events by matter type, time period, and business event type to produce statistical data specific to a time period; aggregating the statistical data for matter type and event type; extrapolating future business events using the statistical data provided by the statistical analysis to calculate probabilities of occurrence of future business events; forecasting an extrapolated volume of production at the time of a forecasted export event, wherein an export event is an event representing when a document page is being exported; and forecasting costs for future discovery from the extrapolated volume of production by applying a culling rate and average review cost. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17)
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18. A computer-implemented method of forecasting litigation discovery costs for a litigation matter that includes a number of business events, comprising:
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capturing historical business events for the litigation matter; aggregating the historical business events, with an aggregation module, and statistically analyzing the captured historical business events by matter type, time period, and business event type to produce statistical data specific to a time period; aggregating the statistical data for matter type and event type; extrapolating future business events using the statistical data provided by the statistical analysis to calculate probabilities of occurrence of future business events; forecasting an extrapolated volume of production at the time of a forecasted export event, wherein an export event is an event representing when a document page is being exported; and forecasting costs for future discovery from the extrapolated volume of production; wherein forecasting an extrapolated volume of production at the time of a forecasted export event includes applying typical collection-to-export volume ratio to estimate the volume of export.
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19. A computer-implemented method of forecasting litigation discovery costs for a litigation matter that includes a number of business events, comprising:
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capturing historical business events for the litigation matter; aggregating the historical business events, with an aggregation module and statistically analyzing the captured historical business events by matter type, time period, and business event type to produce statistical data specific to a time period; aggregating the statistical data for matter type and event type; extrapolating future business events using the statistical data provided by the statistical analysis to calculate probabilities of occurrence of future business events; forecasting an extrapolated volume of production at the time of a forecasted export event, wherein an export event is an event representing when a document page is being exported; and forecasting costs for future discovery from the extrapolated volume of production; wherein forecasting an extrapolated volume of production at the time of a forecasted export event includes applying a gigabyte per page mapping to the collected volume according to the collection make up ratio to estimate the size of the export in pages.
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Specification