Logistics KPI Dashboard — Delivery Performance From the Exports Your Systems Already Produce

What is a logistics KPI dashboard?

A logistics KPI dashboard is a single operational view of the metrics that determine whether a transport operation makes money: on-time delivery rate (OTD, or OTIF where in-full matters), cost per mile or per drop, fleet utilisation, empty running, and delay patterns by lane, customer and driver. It answers the questions an ops manager gets asked daily — "how are we performing for our biggest customer?", "why did costs jump last month?" — from data instead of recollection.

The data is rarely the problem. A typical operation already has a TMS logging every consignment, telematics recording every mile, fuel-card statements itemising every litre, and a workshop system tracking maintenance. All of them export CSV or Excel. The problem is that each system reports only on itself: the TMS knows the late delivery happened but not what it cost; the fuel system knows the spend but not the revenue it carried. The joined-up picture lives, if anywhere, in a spreadsheet someone rebuilds monthly.

That monthly rebuild is where margin hides. Logistics runs on thin percentages, and the difference between a profitable lane and a loss-making one is often invisible in aggregate numbers — it only appears when delivery performance, vehicle cost and utilisation are computed per lane, per vehicle, per customer. By the time a quarterly review finds it, a quarter's losses are booked.

DataHub Pro shortens that loop to minutes. Upload the TMS export, telematics summary and cost data — or point the platform at the SharePoint library where they land — and it builds the KPI dashboard, computes cost per mile and utilisation, runs anomaly detection on delays and cost spikes, and generates the weekly ops report as an editable document. No data warehouse, no integration project, no BI backlog.

The reporting problems transport operators know well

From owner-driver fleets to 3PLs, the same patterns repeat:

• Each system reports only on itself. TMS, telematics, fuel cards and the workshop system all export data — but the questions that matter (is this lane profitable? is this customer worth the service level?) need them joined, and nothing joins them.
• Late deliveries are explained after the customer complains. Without delay-pattern analysis, OTD problems surface as escalations. The data that would have flagged the deteriorating lane three weeks earlier was sitting in the TMS export all along.
• Cost per mile is a yearly guess, not a weekly number. Fuel, maintenance, driver hours and finance costs get combined once a year for rate-setting. Costs drift monthly; rates do not.
• Fleet utilisation hides in plain sight. Vehicles that run half-empty or sit idle on weekdays are invisible in aggregate revenue figures. Utilisation analysis by vehicle and day usually surprises everyone.
• The weekly ops pack is a manual ritual. Someone spends Monday assembling OTD, volumes and cost numbers into the same spreadsheet and slide deck, every week, by hand.
• Customer KPI reviews run on the customer's numbers. When the customer's scorecard says 91% OTD and you have no independent figure, the rate negotiation starts from their data.

DataHub Pro features mapped to logistics work

From the platform's 50 analysis tools, these earn their keep in transport operations:

Worked example: from deliveries.csv to three operational findings

You upload deliveries.csv — three months of consignments with planned and actual delivery times, lane, vehicle and customer — plus a vehicle-cost file from fuel cards and the workshop system. Three findings come back in minutes:

Every figure traces to the source export via the audit trail — useful when the customer's scorecard disagrees with yours. Auto Report turns the same analysis into the weekly ops pack, on schedule, and the pivot-table grind it replaces goes away.

How it works — three steps, no implementation project

There is no onboarding call, no integration scoping and nothing for IT to install. The workflow is the same whether you are testing on one file or running scheduled reporting across a team:

• 1. Bring your data. Upload an Excel or CSV export from the systems you already use, or connect Google Sheets, SharePoint or Shopify for sources that should stay live. DataHub Pro auto-detects your columns — no template to conform to.
• 2. Run the analysis. The KPI dashboard builds itself on upload. From there, pick from 50 analysis tools — Pareto, cohort, RFM, anomaly detection, variance, what-if, Holt-Winters forecasting — or ask questions in plain English with Ask Your Data, where every answer shows the operations behind it.
• 3. Ship the report. Auto Report turns the analysis into an editable Word or PowerPoint document with charts and AI-written commentary. Schedule it, and the recurring version arrives without you — same method, fresh data, every time.

Plans that scale from a single file to a whole team

• Free — $0, forever. One user, 3 uploads a month, 8 core analysis tools and watermarked PDF export. No AI features, no credit card — but a genuine way to test the workflow on your real data before paying anything.
• Pro — $14.99/mo, or $9.99/mo billed annually. All 50 analysis tools, Ask Your Data auditable AI, Auto Report DOCX/PPTX export, scheduled reports and team roles. This is the plan most teams on this page run.
• Enterprise — custom pricing. Everything in Pro, plus white-label reporting, SSO, unlimited usage, multi-client workspaces and organisation-level audit-log governance.

Every plan runs on UK/EU infrastructure under GDPR, and uploaded data is never used to train AI models — on any tier.

Frequently asked questions