Your carrier already produces data all day long: the TMS knows every pickup and every CT-e, telemetry knows where each vehicle is, the ERP knows how much the freight cost. The problem is rarely a lack of data — it's that the data lives scattered across systems that don't talk to each other, and reading the operation ends up hostage to a spreadsheet someone updates on Friday. When the answer to "how did the month close?" depends on re-keying, the decision always arrives late.
Our Power BI and BI consulting for logistics brings these sources together into dashboards the team opens every day — fleet, deliveries, incidents, freight, and margin — with indicators that measure what matters: OTIF, cost per km, idle time. No spreadsheet in the middle, no number that diverges depending on who exported it. Raw data goes in on one side; decisions come out the other.
From raw data to dashboard: how it works
A beautiful dashboard built on bad data is just a better-presented mistake. That's why the work begins before the screen, in the engineering that holds up the number. The path is always the same:
- Extraction — we connect to the sources at the origin (the TMS database, the telemetry API, the ERP) instead of relying on manual exports.
- Processing — cleaning, deduplication, and standardization: a canceled CT-e doesn't count as billed, a reopened incident doesn't become two.
- Modeling — a single data model, with business rules written once. Cost per km means the same thing for operations and for finance.
- Visualization — the dashboards the team actually uses, with the right indicator up front and the detail one click away.
- Refresh — scheduled and automatic. The morning dashboard already reflects what happened yesterday.
The technology disappears so the operation can appear. Whoever uses the dashboard doesn't need to know where the data lives — only to trust it.
The sources we connect
The value of BI in logistics comes from cross-referencing what each system knows on its own. We work with the sources your operation already has:
- TMS — RODOPAR and similar: pickups, CT-e, manifests, incidents, freight reconciliation.
- Telemetry and tracking — SASCAR, Autotrac, Omnilink, Onixsat, Cobli, Geotab: position, driving hours, odometer, events, fuel consumption.
- ERP — SAP, TOTVS, Sankhya, Omie: costs, accounts payable/receivable, cost center, margin.
- Spreadsheets and customer portals — when they're still part of the process, they come in a controlled way, not as a permanent workaround.
Cross-referencing telemetry with the TMS answers what each route really cost. Cross-referencing the TMS with the ERP shows the margin by customer and by region. It's in that cross-referencing that the dashboard stops being decoration and becomes a management tool.
The indicators that truly measure logistics
A good indicator is one that changes a decision. The dashboards are designed around the numbers the industry really holds you to:
- OTIF (On Time In Full) — deliveries on time and complete, the service-level yardstick the shipper watches.
- Cost per km and cost per delivery — the real freight cost after fuel, maintenance, and idle time, not the budget estimate.
- Fleet idle time — parked vehicles, empty km, idle capacity: money going out without moving.
- Incidents and damage — by type, by route, by driver, by customer — to attack the cause, not just record the symptom.
- Average lead time and SLA — pickup to delivery, with alerts on whatever is breaking the agreement.
- Margin by customer and by region — where freight actually turns a profit and where it only generates activity.
Each dashboard is organized around who uses it: operations sees fleet, deliveries, and incidents; leadership sees freight, margin, and trend. The same data, at the right altitude for each decision.
Data governance: one number, one version
What kills trust in a dashboard isn't the wrong chart — it's the number that diverges. When operations and finance arrive at different totals, no one uses either. Governance is what prevents that.
- Written and versioned definitions — every indicator has a documented formula. "On-time delivery" doesn't change meaning between reports.
- Data lineage — you can trace each number back to the source that originated it.
- Access control — each area sees what it needs; sensitive data stays protected. Privacy by design, not by patch.
- Monitored quality — alerts when a source stops updating or a value strays from what's expected, before it becomes a wrong decision.
The result is a single source of truth — one version of the number, where meetings don't turn into debates over whose spreadsheet is right.
Power BI, and the right tool for each case
Power BI is the natural choice for a good share of operations: it integrates well with the Microsoft ecosystem the company already pays for, has a low entry cost, and the business team quickly learns to explore it. It's where most of our logistics projects live.
But the tool serves the problem, not the other way around. Tableau, when visual exploration is the focus. Metabase, when the team wants autonomy over the database with open costs. Grafana, when what matters is near-real-time operational monitoring — fleet and events minute by minute. And PostgreSQL as the reliable data layer underneath, where the processed model sits ready for any of them. We recommend what makes sense for your operation and your team — not what earns the most in licenses.
Why Meta Dados
We're not a dashboard agency. We're data engineering with 26 years on the road and a specialty in transportation and logistics — we know RODOPAR, SASCAR, the CT-e, and freight reconciliation from the inside. When the dashboard needs a cross-reference no one else knows how to build, that's exactly our work.
The consulting is led by people who master both ends: an engineering background (ITA) and research (USP PhD), with the same discipline of governance and security we apply across the rest of the operation. We start with a free assessment in 48h: you show us your sources and your pain points, and we hand back a concrete path — which indicators, which integrations, and in how much time.
Frequently asked questions
How long until the first dashboard is ready?
After the assessment, a first operational dashboard usually ships within a few weeks — we start with the indicator that hurts most (typically OTIF or freight cost) and deliver something useful early. More complete models, cross-referencing TMS, telemetry, and ERP, evolve in stages from there, always with something running in production instead of waiting for the entire project.
Do we have to stop the operation or switch systems?
No. The BI reads the systems you already use — RODOPAR, SASCAR, SAP, TOTVS, and the rest — without requiring you to change your TMS, ERP, or tracker. The connections are built so they don't interfere with day-to-day operations: the dashboard consumes the data, it doesn't disrupt whoever generates it.
What data does the dashboard sync, and how often?
Fleet, position, and driving hours (from telemetry), pickups, CT-e, and incidents (from the TMS), costs and margin (from the ERP). The frequency adjusts to the decision: management indicators usually refresh a few times a day, while operational fleet monitoring can go near real time when it makes sense.
We already have control spreadsheets. Why switch to BI?
A spreadsheet doesn't scale and has no single owner: every version diverges, no one knows which is the right one, and the update depends on someone remembering. BI centralizes the sources, applies the business rule just once, and updates on its own — the end of re-keying and of the spreadsheet in the middle. You gain a reliable number, not one more file to maintain.
Power BI, Tableau, Metabase, or Grafana — which to choose?
It depends on the operation and the team. Power BI is usually the best value for those already on Microsoft who want business-side autonomy; Tableau shines at visual exploration; Metabase gives autonomy over the database with open costs; Grafana is strong at near-real-time operational monitoring. In the assessment, we recommend the one that makes sense for you — not the one that sells the most licenses.
How do you guarantee the dashboard number is correct?
With governance: every indicator has a documented, versioned formula, lineage lets you trace the number back to the source, and quality monitoring alerts you when a source stops updating. The goal is a single source of truth — the same total for operations and for finance, without meetings turning into spreadsheet debates.