E2 fx 7.00
A
B
C
D
E
F
G
H
Case Variables
Value
Damages Start Date
01/01/22
Damages End Date
12/31/25
Off the Clock hours
7.00
Chance of Success
Full Value
%
Discounted
Unpaid Straight Time Up to 40H
$2,046,543
0%
$2,046,543
Unpaid Straight Time Over 40H
$4,153,122
0%
$4,153,122
Unpaid Overtime Premium
$6,199,665
0%
$6,199,665
Liquidated Damages
$12,399,330
0%
$12,399,330
Global Discounts
%
Amount
Global Discount 1
0%
$0
Global Discount 2
0%
$0
Global Discount 3
0%
$0
Extrapolations
Full Value
%
Discounted
Before Data Period
$683,217
0%
$683,217
Within Data Period
$231,594
0%
$231,594
After Data Period
$1,387,452
0%
$1,387,452
Damage Total After Discount $27,100,922
Settlement Authority
Damages
Walker, Jordan
$17,214
Romero, Sofia
$14,044
Front End
Weekly Damages
Extrapolations
Allocations
Click anywhere to advance
Extrapolations Automatically Respond To Your Discounts
From The Front End
Chance of Success
Full Value
%
Discounted
Unpaid Straight Time Up to 40H
$4,093,086
0%
$4,093,086
Unpaid Straight Time Over 40H
$8,306,243
0%
$8,306,243
Unpaid Overtime Premium
$12,399,330
0%
$12,399,330
Extrapolations
Full Value
%
Discounted
Before Data Period
$683,217
0%
$683,217
Within Data Period
$231,594
0%
$231,594
After Data Period
$1,387,452
0%
$1,387,452
Final Allocation Builder

Enter the gross settlement, fees, costs, service payments, and base payment. Every final award distributes automatically.

Gross Settlement Amount
$1,400,000
Attorney Fees
$465,000
Litigation Costs
$195,000
Plaintiff Service Awards
$10,000
Base Payment
$250
Net Settlement Fund
$730,000
From The Front End
E4 fx 7.00
A
B
C
D
E
F
G
H
Case Variables
Value
Damages Start Date
01/01/22
Damages End Date
12/31/25
Off the Clock hours
7.00
Chance of Success
Full Value
%
Discounted
Unpaid Straight Time Up to 40H
$4,093,086
0%
$4,093,086
Unpaid Straight Time Over 40H
$8,306,243
0%
$8,306,243
Unpaid Overtime Premium
$12,399,330
0%
$12,399,330
Global Discounts
%
Amount
Global Discount 1
0%
$0
Global Discount 2
0%
$0
Extrapolations
Full Value
%
Discounted
Before Data Period
$683,217
0%
$683,217

Part 1: Identify Missing Weeks

Identify missing time periods and choose the level of detail to track.

Part 2: Value Missing Weeks

Determine how to assign a dollar amount to each missing week.

Part 3: Discount Missing Weeks

Incorporate additional discounts for the chance of success of the extrapolations.

Valuing Missing Weeks

There are many ways to value missing weeks. The methods below can help guide the right choice for any matter.

01
Overall

Overall Weekly Average

When To Use

When the class is uniform and a single defensible number is preferred over per-group rates.

How It Works

All six case members pool together. One per-week number applies to everyone.

#
Name
Job Title
Weeks
Damages
1
Diaz
Driver
100
$40,000
2
Patel
Driver
100
$44,000
3
Nguyen
Manager
100
$44,000
4
Brooks
Manager
100
$48,000
5
Romero
Office
100
$25,000
6
Lopez
Office
100
$30,000
Diaz
$385
Patel
$385
Nguyen
$385
Brooks
$385
Romero
$385
Lopez
$385
02
By Role

Job Title Weekly Average

When To Use

When pay varies by role, a single overall rate would blur the differences between roles.

How It Works

Damages pool by role. Each role shares one per-week number.

#
Name
Job Title
Weeks
Damages
1
Diaz
Driver
100
$40,000
2
Patel
Driver
100
$44,000
3
Nguyen
Manager
100
$44,000
4
Brooks
Manager
100
$48,000
5
Romero
Office
100
$25,000
6
Lopez
Office
100
$30,000
Diaz
$420
Patel
$420
Nguyen
$460
Brooks
$460
Romero
$275
Lopez
$275
03
Individual

Individual Case Member Average

When To Use

When member-level data is reliable, a pooled average would mask real differences between case members.

How It Works

Damages and weeks are tracked per case member, so each member gets a unique per-week number.

#
Name
Job Title
Weeks
Damages
1
Diaz
Driver
100
$40,000
2
Patel
Driver
100
$44,000
3
Nguyen
Manager
100
$44,000
4
Brooks
Manager
100
$48,000
5
Romero
Office
100
$25,000
6
Lopez
Office
100
$30,000
Diaz
$400
Patel
$440
Nguyen
$440
Brooks
$480
Romero
$250
Lopez
$300
04
Time Period

Time Period Weekly Average

When To Use

When wages at the beginning of the damages period differ from wages at the end, a single overall rate would overstate one extreme.

How It Works

The first 6 months of records set the rate for before-data missing weeks; the last 6 months set the rate for after-data missing weeks.

First 6 Months
avg $340 / wk
Last 6 Months
avg $430 / wk
Before-Data
$340
After-Data
$430
05
By Year

Year-Specific Average

When To Use

When pay rates shifted year over year across the damages window, a flat overall rate would hide the actual trajectory.

How It Works

Each year in the damages window has its own per-week rate, computed from data inside that year. A missing week takes the rate of the year it falls in.

#
Year
Weeks Worked
Damages
Per Wk
1
2022
150
$52,500
$350
2
2023
150
$56,250
$375
3
2024
150
$60,000
$400
4
2025
150
$62,250
$415
2022
$350
2023
$375
2024
$400
2025
$415
06
By Tenure

Tenure-Adjusted Average

When To Use

When pay scales with tenure and the class spans new hires through long-tenured staff, a pooled rate would overstate new-hire damages.

How It Works

Per-week value depends on tenure band. Newer hires take the first-year average; mid-tenure and senior members take their own band averages.

#
Name
Tenure
Weeks
Damages
1
Diaz
8 mo
100
$40,000
2
Brooks
11 mo
100
$48,000
3
Romero
3.5 yr
100
$25,000
4
Lopez
2.8 yr
100
$30,000
5
Patel
5.0 yr
100
$44,000
6
Nguyen
7.0 yr
100
$44,000
Diaz
$440
Brooks
$440
Romero
$275
Lopez
$275
Patel
$440
Nguyen
$440
07
By Location

Location Average

When To Use

When pay structures differ across sites within the class, a pooled rate would overlook the location effect.

How It Works

Case members pool by location. Each site shares one per-week number, independent of role or tenure.

#
Name
Location
Weeks
Damages
1
Diaz
Eastside
100
$40,000
2
Brooks
Eastside
100
$48,000
3
Patel
Westside
100
$44,000
4
Romero
Westside
100
$25,000
5
Nguyen
HQ
100
$44,000
6
Lopez
HQ
100
$30,000
Diaz
$440
Brooks
$440
Patel
$345
Romero
$345
Nguyen
$370
Lopez
$370

Organizing Extrapolations

Extrapolations can be built to any level of granularity. This example sorts missing weeks into three categories so each can be valued and discounted separately.

Recorded Data

This bar represents the time period covered by the data set.

Data Pull
Data Start Data End

Post Data Extrapolations

Weeks of damages for workers still on payroll after the recorded data ends.

Data Pull
Post Data
Extraps
Data Start Data End Damages End

Pre Data Extrapolations

Weeks of damages for case members working before the recorded data starts.

Pre Data
Extraps
Data Pull
Damages Start Data Start Data End

Inside Data Extrapolations

Weeks of damages for case members with unexplained gaps within the recorded data.

Data Pull
Data Start Data End
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