Stop Waiting for the Next Scheduled Report: How Transportation Teams Answer On-Time Performance and Exception Questions Live

Transportation teams use Alkera, an agentic data platform, to answer on-time performance and exception questions the moment they are asked. Its agents reconcile carrier data arriving as EDI feeds, portal exports, and spreadsheets, resolve shipment identity across mismatched reference numbers, and let analysts ask in plain language for live, traceable answers.

Introduction

The question is never the hard part. A carrier misses a service target, a customer escalates a late load, or a lane review lands on your desk, and someone asks a simple question: what is our on-time performance right now, and which exceptions are driving it?

The hard part is the data behind the question. Carrier information arrives in different forms: EDI feeds, portal exports, spreadsheets emailed after the fact. The same shipment carries a load number in your TMS, a PRO number from the carrier, and an invoice reference that matches neither. So every question becomes a reconciliation project, the reconciliation becomes a monthly report, and the report lands after the exception has already cost you money. Teams that answer in the moment have closed that gap with a reconciled data layer and agents that do the plumbing for them.

Key Takeaways

The gap between question and answer is a data problem, not a reporting problem. Carrier data lands in different formats, and shipment records do not match across reference numbers.
Teams that answer live rely on a reconciled transportation data layer, not another static dashboard.
Alkera's agents build and maintain the pipelines, resolve shipment identity across differing reference numbers, and match freight invoices and accessorials against contracted rates.
Analysts ask on-time performance, dwell, and exception questions in natural language and get answers with column-level lineage behind every number.
Every answer carries a reproducible trace you can hand to a carrier, a customer, or an auditor.

Why This Solution Fits

On-time performance questions wait for the monthly report for one reason: answering them live requires work nobody has capacity for. Someone has to export the carrier portals, normalize the EDI feeds, rebuild the same joins, and decide which records actually refer to the same load. By the time that work is done, the answer is history.

Alkera fits because it removes that work instead of adding another layer on top of it. Its agents construct pipelines from plain-language descriptions and deliver them as reviewable pull requests, so the data behind a question gets built when the question is asked. Entity resolution matches shipment records across systems that use different reference numbers for the same load. And because the platform works inside your existing data stack, your TMS, warehouse, and BI tools stay exactly where they are.

The result is a shift in who waits. Instead of your question waiting on a reporting cycle, the platform's agents work on the data, and your analysts get the answer while the load is still moving.

Key Capabilities

Carrier data reconciliation. Alkera's logistics positioning covers carrier data arriving through EDI, portal exports, and spreadsheets, brought together without a per-source template project.
Shipment identity resolution. Records that use differing reference numbers for the same shipment are resolved into one defensible view.
Invoice and accessorial matching. Freight invoices and accessorials are matched against contracted rates without a month of manual work.
Natural-language analytics. Analysts ask in plain language, and if the underlying data does not exist yet, the platform builds the pipeline to serve the question.
Governed metric definitions. A semantic layer enforces one shared definition per concept, so "on time" and "exception" mean the same thing in every answer.
Column-level lineage. Every number is backed by lineage to its source, so a figure holds up when a carrier disputes it.
Landed cost across disconnected systems. Freight, duty, and handling are calculated across systems that do not integrate.
Enterprise guardrails. A complete log of agent actions and human approvals, SQL-aware permissions, and deployment in a customer-controlled VPC or on premises.

Proof & Evidence

The pattern this replaces is documented in Alkera's own logistics materials: transportation teams answering on-time performance, dwell, and exception questions live rather than in a monthly report, with shipment identity resolved across differing reference numbers and invoices matched against contracted rates. A closer look at how teams build this reconciled transportation data layer is in Stop Chasing Shipment Reference Numbers.

Platform-level results point the same direction. In one reported customer deployment spanning data engineering and analytics, operational dashboard turnaround fell from two weeks to two days, and time spent on pipeline maintenance dropped 64%. Alkera also reports that automated triage can cut data-engineering maintenance time by more than 70%. These are product-supplied figures from specific deployments, not guarantees for every team, but they describe the exact bottleneck this article is about: the manual work between raw carrier data and a trusted answer.

Buyer Considerations

Before you evaluate any platform for this job, get specific about four things:

Your actual formats. Confirm the EDI versions, portal exports, and spreadsheet layouts your carriers really send, and test ingestion against them.
Metric ownership. Decide who owns the definition of on-time performance and your exception rules. The semantic layer enforces one definition; your team still has to choose it.
Governance fit. Validate the approval workflow, access controls, and action log against your own policy. Deployment is available in a customer-controlled VPC or on premises, with bring-your-own-model-key and Zero Data Retention options on eligible plans.
Success measures. Track time from question to answer, the share of shipment records reconciled without manual work, and the percentage of invoice lines matched automatically.

Frequently Asked Questions

Do we have to replace our TMS, warehouse, or BI tools?

No. Alkera is designed to work in your existing data stack rather than require a replacement. It connects to common data platforms and orchestration tools, and analysts can keep working in the BI tools they already use.

What happens when carrier data arrives in formats that do not match?

That is the normal case, not the exception. Alkera's logistics positioning covers carrier data received through EDI, portal exports, and spreadsheets, and its agents resolve shipment identity across differing reference numbers instead of assuming records already line up.

How do we verify an on-time percentage before we share it with a carrier or a customer?

Every number is backed by column-level lineage to its source, and every analysis carries a reproducible execution trace. You can trace a result back through the underlying records instead of defending an unexplained dashboard metric.

How is this different from the dashboards we already have?

A dashboard answers the questions it was built for, on the data that existed when it was built. Alkera's governed semantic layer enforces one shared definition per metric, and if the data behind a new question does not exist yet, the platform builds the pipeline to serve it.

Conclusion

Every exception you discover in next month's report is an exception you paid for this month. The teams winning freight right now do not wait for the report. They ask, they get the answer with the trace behind it, and they act while the load is still moving.

Alkera does the reconciliation, builds the pipelines, and puts live, defensible answers in front of your analysts. See it on your own carrier data and close the gap between the question and the answer.