Demonstration · Illustrative data · BI Consulting Services

Excargo Services × BI Consulting Services

TMS Drayage Operations Board — Port Houston terminals → Genoa Red Bluff yard → customer
Prepared for Ronnie
September 2026 · Interactive demo

Every number here is recalculated live from the TMS-shaped data behind the page when you change period, terminal or freight segment. It answers the question from your original note — "a lot of data in the TMS, but the reporting is lacking" — with a single board: containers moved, on-time performance, terminal turn time, revenue per load, driver utilisation, and detention & demurrage exposure by customer.

Signature view · Houston dray network

Port-to-yard-to-customer lane map

Lane width = loads in the selected window. Left legs run terminal → Excargo's 35-acre yard on Genoa Red Bluff Rd; right legs run yard → customer cluster. Hover any lane.

Selected terminal / laneOther lanesRail rampsExcargo yard
Terminal turn time

Container turn at the gate, by terminal

Average minutes from arrival in the queue to gate-out, split into the three legs the TMS timestamps. Dashed line = 90-minute target turn.

Queue to gate-inGate-in to liftLift to gate-out
Trend · trailing 12 months

Loads moved and on-time delivery, by month

Bars = loads (containers moved). Line = on-time delivery %. Shaded band = the period you have selected.

LoadsLoads in selected periodOn-time delivery %
What this board answers

Three questions, three numbers

Ranking · customers

Top customers by loads, with revenue per load

Red bars flag customers whose detention & demurrage exposure exceeds 6% of their revenue in the window.

Exposure · detention & demurrage

Detention (chassis / driver wait) vs demurrage (container at terminal)

Dollars accrued in the window and how much was recovered from customers. The gap is margin leaking out of the yard.

Detention accruedDemurrage accruedRecovered from customer
Fleet · driver utilisation

Turns per driver-day and idle hours

Distribution of the ~85-driver fleet by turns per working day in the window. Target is 2.5 turns; drivers below 1.5 are mostly waiting on chassis or gate queues.

AI layer · ask the data

Ask the board a question in plain English

Illustration of the natural-language layer that sits on top of the TMS model. The answer below is generated from the same numbers as the panels above and changes with your filters.

Which customers drove detention charges last month, and how much did we recover?
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Private AI on your own server

The "ask the data" ideas on this board are designed to run on a GPU server inside your own network — an open-weight model over your own documents, cited answers, no per-seat licence, nothing leaving the building. The short deck below explains how it works. Scroll through, or download it as a PDF.

Private AI Servers — slide 1 of 14
Private AI Servers — slide 2 of 14
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