Forecasting Discovery Costs Using Historic Data

1 . A method of forecasting discovery costs, comprising the steps of:

capturing historic stage transition data for each matter stage, said historic stage transition data including information regarding the duration of each historic matter stage and regarding the number of new custodians and data sources added during that matter stage;

statistically analyzing the stage transition data for each existing matter stage and aggregating existing stage transition data for each matter type;

extrapolating progress for existing matters;

forecasting initiation of future matters by extrapolating how many new matters are expected to be initiated over the duration of a forecasting period;

extrapolating the average pace of progress that the future matters are expected to experience within the forecasting period; and

forecasting the volume of production by extrapolation using quantitative characteristics of said historic stage transition data.

2 . A computer implemented method for forecasting litigation discovery costs using historic data for each stage of existing litigation matters, comprising the steps of:

providing historic data for the duration of each stage of existing matters;

calculating historic statistical information from said historic data;

aggregating the historic statistical information by matter type;

calculating probability distributions for reaching production stages for each matter type from the historic statistical information;

extrapolating future progress for each type of existing matter using the historic statistical information;

extrapolating how many new matters will be created using the historical statistical information;

extrapolating an average pace of progresses for each of the new matters during the forecasted future time periods using the historic statistical information; and

forecasting the volumes of production using the number of custodians and data sources.

3 . A computer implemented method for forecasting litigation discovery costs using historic data and probability-based forecasting, comprising the steps of:

capturing stage transition data, which includes information on the duration of each matter stage and the number of new custodians and data sources added during a given stage;

analyzing and aggregating by matter type the captured transition data to provide statistical information; and

extrapolating progress on known existing matters using the statistical information; and

forecasting how many new matters are likely to be created over the duration of a forecast period and extrapolating the average pace of progress that matters are likely to go through within the forecast period.

4 . The method of claim 3 including forecasting the volumes of production based on the historic data.

5 . The method of claim 4 including forecasting discovery costs by applying a culling rate and average review cost.

6 . The method of claim 3 wherein the data for each matter stage is analyzed and aggregated by matter type in one or more of the following:

mean duration of the stages,

standard deviation of the duration of the stages

added custodians,

standard deviation of added custodians,

added data sources,

standard deviation of added data sources,

gigabytes collected per custodian,

gigabytes collected per data source, and

fallout rate percent.

7 . The method of claim 3 including using statistical data for calculating probability distributions for reaching a production stage for existing matters.

8 . The method of claim 3 including extrapolating progress on existing matters.

9 . The method of claim 3 including extrapolating with exponential smoothing.

10 . A system for forecasting litigation discovery costs using historic data and probability-based forecasting, comprising:

a forecasting data base; and

a forecasting module including a raw data analysis and aggregation module and an existing matter forecasting module.

11 . The system of claim 10 including a future matter forecasting module that extrapolates progress for known existing matters.

12 . The system of claim 10 including a cost modeling module that uses an extrapolated collection volume along with a culling rate and average estimated review costs.

13 . The system of claim 10 including a trend analysis module that analyzes historical data to determine if longer term trends occur and if seasonal or cyclical patterns occur.

14 . The system of claim 10 including an event correlation analysis module that analyzes patterns of litigation events.

15 . The system of claim 10 including an error tracking module for costs that compares forecasted cost to actual costs and makes appropriate changes to calibrate the forecasting module with historical data.

16 . The system of claim 10 including a 3 rd party system module that provides to the forecasting model outside information, including matter management information, billing information, and other external data.

17 . The system of claim 10 including a model calibration tools module that provides calibration tools for tuning model variables.

18 . The system of claim 10 including a reporting module that receives information from the forecasting module and provides reports to users

19 . An automated system for forecasting litigation discovery costs using historic data and probability-based forecasting, comprising:

a forecasting data base;

a forecasting module including a raw data analysis and aggregation module and an existing matter forecasting module.;

a litigation database that provides relevant data to an automated data collection module; and

a reporting module that receives information from the forecasting module and provides reports to users.

20 . The system of claim 20 including a 3 rd party system module that provides to the forecasting model outside information, including matter management information, billing information, and other external data.

21 . The system of claim 20 including a model calibration tools module that provides calibration tools for tuning model variables.