One set of numbers, and dashboards the floor will actually open

Most operations have the same number in four places and a different answer in each. We bring your scale, ERP, TMS and spreadsheet data into one governed place and build the views your managers need each morning. The aim is simple: when someone quotes a margin, nobody argues about where it came from.

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Sound familiar?

Situations this work is built for. If a few of them describe your operation, you are on the right page.

  • Finance and operations never agree on last month's numbers.

  • I cannot tell you our margin on a load until weeks after it ships.

  • We have a dashboard, but nobody opens it.

  • Half our reporting is someone copying exports into a spreadsheet.

What we build

Single source of truth
A governed data model that joins tickets, orders, inventory, costs and pricing across your systems, with agreed definitions for the terms people argue about.
Warehouse and pipelines
A cloud or on-prem warehouse fed by scheduled and near-real-time pipelines from your ERP, scale software, TMS, WMS and spreadsheets, with alerting when a feed breaks.
Dashboards operations reads
Short, task-based views for the yard boss, plant manager and dispatcher, designed around the decisions they make at 6 a.m., not around what the tool can draw.
Data quality
Automated checks for duplicates, missing weights, impossible values and late feeds, with exceptions sent to the person who can fix them at the source.
Margin by load, commodity and SKU
Landed cost, freight, handling and market price joined to each transaction, so you can see which loads, grades and customers actually make money.

How the work runs

  1. Assessment

    2–3 weeks

    We inventory your data sources, interview the people who build reports by hand, and agree the handful of questions the business most needs answered. You get a written findings report and a prioritized roadmap.

  2. Foundation

    4–8 weeks

    We stand up the warehouse, the first pipelines and the core data model, and reconcile it against numbers finance already trusts.

  3. Build

    6–12 weeks per phase

    We add sources and dashboards one decision at a time, showing working views every week and retiring the matching hand-built spreadsheet as each goes live.

  4. Run

    Monthly

    Pipeline monitoring, data quality follow-up, new metrics and user support on a monthly retainer.

Tools we commonly use

  • PostgreSQL
  • Snowflake
  • BigQuery
  • dbt
  • Airbyte
  • Apache Airflow
  • Metabase
  • Power BI
  • Python
  • SQL Server

We pick tools to fit what you already run and what your team can maintain.

Where this matters most

Questions buyers ask

Do we need a data warehouse, or is a spreadsheet enough?

A spreadsheet is enough until several systems must agree or someone spends days a month assembling reports. At that point a warehouse pays for itself in trust and time. For smaller operations we start with a single PostgreSQL database rather than an expensive platform.

Which BI tool should we use?

We are tool-neutral and recommend whatever fits your team and licenses. If you already use Power BI or Tableau, we build there, and if you do not, we suggest an open option like Metabase. The data model underneath stays the same either way.

How do you handle bad data in our source systems?

We measure it first, then fix it at the source where possible. Automated checks flag missing or impossible values daily and send each one to the person who owns the record. We do not hide bad data behind a polished dashboard.

Who owns the data and the models?

You do. The warehouse runs in your cloud account or your data center, and the pipeline code, data models and dashboards are delivered to you with documentation. You can switch providers or take it in-house at any point.

Other services

Further reading