Contract analysis

I. Executive Summary This memorandum presents a detailed analysis of RouteSync dispatch records and GPS telematics data for (a) the named plaintiff, Marcus Delano, during his tenure at the Fort Worth distribution hub (HUB-01) from March 2021 through September 2024, and (b) a representative sample of 50 drivers across five of SLG's fourteen distribution hubs during the relevant FLSA limitations period (April 30, 2022

II. Data Sources and Methodology A. RouteSync Dispatch Platform Data RouteSync is SLG's proprietary dispatch platform, developed internally and deployed across all 14 distribution hubs beginning in 2018. The platform serves three primary functions: (1) assigning deliveries to drivers based on geographic proximity, delivery type, and driver availability; (2) providing suggested route sequencing — that is, an algorithm

1. Hours-Worked Patterns: Average weekly hours, variability in weekly hours, and distribution of weekly hours across the driver sample. This metric bears on both the similarly-situated inquiry (whether drivers worked comparable hours) and the economic reality test (whether SLG dictated the amount of time drivers devoted to SLG work).

2. Route Deviation Frequency: The percentage of delivery days on which a driver deviated from the RouteSync-suggested delivery sequence by three or more positions. This metric bears directly on the degree-of-control factor, as it measures the extent to which drivers exercised independent judgment in organizing their work rather than following SLG's suggested routing.

3. Delivery Refusal/Acceptance Rates: Each driver's rolling 30-day acceptance rate relative to the 85% minimum acceptance rate threshold in the ICOA. This metric addresses both the degree of control (whether drivers were compelled to accept all assignments) and the opportunity for profit or loss (whether drivers could exercise economic judgment in selecting higher-value deliveries).

4. Schedule Variability: Analysis of daily start times, end times, days worked per week, Saturday participation rates, and multi-day breaks. This metric speaks to whether SLG controlled when drivers worked or whether drivers exercised genuine scheduling discretion. These four metrics map to key factors in the FLSA economic reality test as applied by the Fifth Circuit, particularly the degree of control exercised by t

III. Analysis of Named Plaintiff Marcus Delano A. Hours-Worked Patterns Marcus Delano operated out of HUB-01, SLG's Fort Worth distribution hub located at 1015 Railhead Parkway, Fort Worth, TX 76106, from March 2021 through September 2024. Delano executed ICOA v2.0 upon commencement of his engagement in March 2021, and subsequently executed ICOA v3.0 in January 2023 when the updated agreement was rolled out across al

IV. Analysis of 50-Driver Sample Across Five Hubs A. Hours-Worked Patterns — Inter-Driver and Inter-Hub Variation The hours-worked analysis of the 50-driver sample reveals substantial variation both across hubs and among individual drivers within the same hub. The overall sample statistics for the relevant FLSA limitations period are as follows: • Mean weekly hours: 49.3 hours. • Median weekly hours: 47.8 hours. • St

V. Comparison to Plaintiff's Allegations A. Allegations vs. Data — Named Plaintiff The following chart compares plaintiff's key allegations in the complaint to the data findings for Marcus Delano: Allegation: Delano "regularly worked 55–65 hours per week." Data Finding: Delano's average weekly hours of 58 falls within the alleged range, confirming the general accuracy of this allegation as to the average. However, th

VI. Implications for Conditional Certification Opposition A. Supporting "Not Similarly Situated" Argument The data analysis presented in this memorandum provides substantial evidentiary support for the argument that SLG's drivers are not similarly situated for purposes of FLSA conditional certification under 29 U.S.C. § 216(b). In Swales v. KLLM Transport Services, L.L.C., 985 F.3d 430, 441–43 (5th Cir. 2021), the Fi

VII. Data Limitations and Caveats This analysis is subject to several limitations that should be kept in mind when relying on its findings:

1. Sample scope. This analysis covers 50 drivers across 5 of SLG's 14 hubs. The remaining 9 hubs — San Antonio, Austin, Tulsa, Baton Rouge, Shreveport, Little Rock, El Paso, Lubbock, and Corpus Christi — are not included in this preliminary review. These hubs collectively account for approximately 524 of the 1,187 drivers in the proposed collective and may exhibit operational characteristics, delivery mixes, geograph

2. GPS data as a proxy for hours worked. GPS ignition on/off timestamps are used as a proxy for hours worked, but they may not perfectly capture all work time. Specifically, pre-trip vehicle inspections, post-delivery administrative tasks (such as completing delivery logs or responding to customer inquiries), and other work performed without the vehicle ignition in the "on" position would not be reflected in the GPS

3. Limitations of RouteSync data. RouteSync data reflects delivery assignments and completions recorded through the platform, but it does not capture all communications between hub managers and drivers. Phone calls, text messages, in-person conversations, and other informal communications that may bear on the degree of control exercised by SLG are not reflected in the RouteSync data. To the extent that hub managers i

4. Informal delivery refusals. Delivery refusal data reflects only explicit declines recorded through the RouteSync platform. If drivers informally communicated refusals to hub managers by phone, text, or in person — and those refusals were processed by the hub manager without being recorded as driver-initiated declines in RouteSync — the data may understate the actual frequency of delivery refusals. This limitation

5. Data integrity. SLG's IT department has confirmed that there are no known data gaps in the RouteSync or GPS records for the relevant period. However, minor data transmission interruptions — estimated at less than 0.5% of all data points — may exist due to telematics hardware issues, cellular connectivity problems in rural delivery areas, or software glitches. These interruptions are unlikely to materially affect t