Logistics Support Ticket Overview
Logistics Support Ticket Overview
This dashboard was built for the customer-support team of a worldwide third-party logistics provider, using ticket data from 2021 to 2024.
1. Project purpose
Logistics providers live and die by how fast—and how well—they solve customer issues. The goal of this report is to give ops leaders and CS managers a one-page pulse on the four service channels (Calls, Chats, Emails, Escalations):
Work-load – ticket volumes & YoY change
Speed – average resolution time and SLA compliance
Quality – customer-rated satisfaction
Root cause – top categories driving contacts
2. Data & modelling
| Source | 73 402 anonymised tickets (CSV, 2021-01-01 → 2024-12-31) |
| Fields | Dates opened/resolved, Channel, Category, Priority, Region, Shipment type, SLA days, Resolution days, CSAT |
| Model | FactTickets (one row per ticket) + DimDate + slim lookup tables (Channel, Category, Region…) → star schema |
| Measures | Explicit DAX with VAR pattern (e.g. Tickets YoY %, Avg Resolution, SLA Met). DIVIDE used for safe ratios. |
3. Page design choices (see screenshot)
| Column-per-channel layout (4 cards) | Instant side-by-side comparison; uniform reading path |
| KPI card + YoY badge | At-a-glance headline plus directional cue (green ▲ / red ▼) |
| Quarterly mini-bars | Quick seasonality check without leaving the page |
| Resolution-time histogram | Reveals skew & long-tail outliers better than a single average |
| SLA annotation | Inline reminder of contractual target per channel |
| Top-5 category bars | Zero-ink alternative to tables; drives conversation on root causes |
| Custom theme & icons | Consistent brand colours (teal, amber, olive, cyan) and intuitive glyphs |
| Year slicer (top-right) | Lets users time-travel while keeping the canvas uncluttered |
4. Key insights (demo data)
Calls remain the busiest (5 417 in 2023) but volume slipped -2 % YoY, hinting at channel-shift to chat.
Chats grew +1 % and show the fastest average resolution (3 days) thanks to simpler issues like Live Tracking.
Emails hover around 5 400 tickets; resolution time skews wider (long tail up to 18 days).
Escalations are <15 % of load, yet SLA compliance lags (only 79 %)—risk area for the COO.
6. How to use the report
Pick a year in the slicer (defaults to current).
Scan the YoY badges to spot channels needing attention.
Hover over a bar chart for exact ticket count & % within SLA.
Click any category bar to cross-filter the entire page (e.g., isolate Damaged Goods issues).
Export to PowerPoint for exec meetings or subscribe to a Power BI alert on SLA < 85 %.
Why this matters: In logistics, every delayed resolution compounds downstream costs. This dashboard distils four years of ticket data into a 30-second situational briefing—so leaders can move from gut feel to data-driven decisions.
A big thank you to Injae Park for his guidance on this project.
3 Replies
Hi Bro , great dashboard with clear & good insights pls share me the PBIX file
I like the clean look. If you can share the PBIX, I would like to check it out more. Thanks for sharing your project.
Hello, good morning. I'm from Brazil, and I'm one more person who joins the chorus in saying that your work was very good. I don't know if you shared the pbix with the guys, but if you could, I'd be extremely grateful. Thank you.
