When your data is in five places, your decisions are based on one of them.
Logistics companies move fast. Data that lives in separate systems, from a TMS to a CRM to accounting software, means decisions are often based on a partial picture. SmartWay Transportation fixed that with Power BI.
Does this describe your reporting?
- Executive reports are assembled by hand from multiple department exports
- The sales team tracks performance in spreadsheets alongside the CRM
- You cannot see carrier performance and sales profitability in the same view
- Leadership receives periodic reports that are outdated before they act on them
- Identifying which customers or lanes are actually profitable requires manual analysis
- No one trusts the numbers because everyone built them differently
What Armely built for SmartWay
SmartWay Transportation is a non-asset-based logistics provider in Kansas City, managing full and partial truckloads across a national carrier network. Their data was scattered across their TMS, CRM, and accounting software with no unified view.
Armely connected all three systems to a centralized data warehouse and built three Power BI dashboards: a Load Factoring Dashboard for freight operations, a Sales Performance Dashboard for the sales team, and an Executive Dashboard for leadership with real-time financial and operational KPIs.
At a glance
| Before | After |
|---|---|
| Data scattered across TMS, CRM, and accounting with no unified view | All three sources connected to a centralized data warehouse through Power BI |
| Hours spent assembling periodic reports manually | Live dashboards provide a real-time view for stakeholders |
| No visibility into carrier performance versus cost | Load Factoring Dashboard shows revenue per load, cost per load, and carrier metrics |
| Sales team tracked performance in separate spreadsheets | Sales Performance Dashboard shows revenue, win/loss rates, and customer engagement |
| Executive team received fragmented, delayed reports | Executive Dashboard shows real-time financial and operational KPIs in one view |
| No path to scenario planning or trend forecasting | Data models support trend analysis, scenario planning, and forecasting |