Logistics Analytics
Most logistics operations we review have OTIF measured monthly. By the time you know you're off target, you've already missed 30 days of deliveries and the customer is calling to complain.
What we hear from operators
The problems we solve
Three systems, no single truth
Route data in the TMS. Proof of delivery in a separate WMS or carrier portal. Cost data in the ERP. Nobody has connected them. So freight cost per delivery unit is calculated quarterly in Excel by someone who has to export three reports, reconcile the columns, and pivot the result. By the time it's done, the quarter it describes is already history.
Carrier performance is managed by relationship, not data
Most logistics teams know which carriers perform well and which don't — by feel. The data to prove it exists in the TMS. But it's not aggregated, not trended, not shown to the carrier in a monthly review. So underperformance is tolerated longer than it should be, and renegotiations happen without leverage.
Last-mile visibility disappears at the handover point
The moment a shipment leaves the DC and goes to a third-party carrier, real-time visibility typically ends. The customer calls the logistics team. The logistics team calls the carrier. The carrier checks the driver. This is 2025, and this process is still how most operations handle last-mile exceptions.
Who this is for
Who logistics analytics is built for
The roles that feel the problem first — and what we build for each of them.
Logistics / Distribution Head
The problem
OTIF is measured monthly, so you find out you are off target after 30 days of missed deliveries — usually when the customer calls to complain.
What we build
Daily OTIF by lane, carrier and customer in Power BI over Microsoft Fabric, with the TMS, WMS and ERP unified through Azure Data Factory.
OTIF tracked daily by lane, not monthly in retrospect
Supply Chain Director
The problem
Carrier performance is managed by feel. The data to prove which carriers underperform sits in the TMS but is never aggregated, trended or put in front of the carrier.
What we build
Automated carrier scorecards generated from TMS data in Power BI, distributed each month through Power Automate without manual effort.
Renegotiations backed by 12 months of carrier data, not relationship
Operations Manager
The problem
The moment a shipment leaves the DC, visibility ends. Last-mile exceptions are chased by phone — the customer calls you, you call the carrier, the carrier calls the driver.
What we build
Carrier API integration into Microsoft Fabric with automated exception alerts through Power Automate the moment a delivery window is at risk.
Late-delivery exceptions caught within 24 hours, not at month-end
CFO / Financial Controller
The problem
Freight cost per delivery unit is calculated quarterly in Excel by someone reconciling three exports — and the quarter it describes is already gone.
What we build
An automated freight-cost dashboard in Power BI on Microsoft Fabric, with cost per unit by carrier and lane tracked against budget in real time.
Freight cost per unit on demand, not a quarterly reconciliation
Measurable outcomes
What changes after implementation
Specific shifts from delivered logistics analytics work — the before, and the after.
OTIF measurement: monthly retrospective → daily live tracking by lane
Logistics managers see OTIF performance as it unfolds, not after the month closes. Exceptions are caught within 24 hours of a delivery window being missed.
Freight cost reporting: quarterly Excel exercise → automated monthly dashboard
Cost per delivery unit, cost by carrier, cost by lane — available without manual extraction. Freight spend vs budget tracked against actuals in real time.
Carrier reviews: relationship-based → data-driven scorecards
Monthly carrier scorecards generated automatically. On-time rate, damage rate, cost vs contracted rate — per carrier, per lane, per customer tier. Renegotiations backed by 12 months of data.
By market
Logistics Analytics — market-specific pages
Each page below covers what logistics analytics looks like specifically in that market — the local ERP landscape, compliance context, and the operational patterns we actually see there.
Singapore & Malaysia
United Kingdom
North America
By industry
Logistics Analytics — industry-specific pages
How logistics analytics applies to the specific systems, metrics, and operational challenges of each vertical.
Technology stack
Common questions
Logistics Analytics — frequently asked
Our carriers don't have APIs. Can we still get real-time visibility?
Most carriers have some form of track-and-trace portal, even if they don't have a public API. In cases where there's no direct integration available, we work with carrier-provided data files, EDI feeds, or third-party visibility platforms that aggregate carrier data. It's rarely a binary situation.
We have a TMS already. Shouldn't that handle this?
TMS systems are designed to manage the logistics execution process — booking, routing, documentation. Most aren't built for cross-source analytics. The data sits in the TMS, but connecting it to the ERP for cost reconciliation, to the WMS for order fulfilment, and surfacing it in a management dashboard is a separate layer. The TMS doesn't replace that.
How do we handle multiple carriers with different data formats?
This is the integration layer we build. Every carrier sends data differently — some via EDI 214, some via portal exports, some via email with a PDF. We standardise it into a common shipment model so that the analytics layer sees one consistent format regardless of carrier. It's plumbing work, but it's the work that makes everything else possible.
Can you help us reduce our freight costs, not just measure them?
Measurement is step one, and it's where most analytics projects stop. Once you have clean freight data, we help identify the lanes where you're paying above market, the carriers where the cost/performance ratio is poor, and the order patterns that create expensive last-minute shipments. The recommendations come from the data, not from industry benchmarks that may not match your network.
Related FAQs
Go deeper on the questions buyers ask
Start with a conversation, not a proposal
First call is 30 minutes with Amit. We ask about your systems, your team, and your most pressing operational problem. You get a clear view of where the gap is and what closing it looks like. No slides. No pitch deck. No obligation to proceed.