Ticket Volume Analysis
Every September the desk at Larkhill Academy drowned. Four hundred new accounts, two hundred laptops, a timetable system that nobody had touched since June. The queue tripled in a fortnight while the desk, which had been quiet in August, remembered all over again that this happens every year. It had happened six years running. It was in the ticket system, in a shape so regular you could set a calendar by it. Nobody had drawn the line, because drawing the line is not a ticket. Volume is the oldest number a desk has, and the least read.
This series is about reading it. It covers counting tickets properly, because created, closed and open are three different numbers. It covers trends and seasonality, and separating one from the other with a rolling average. It covers per-department and per-user patterns, read as information about the system rather than about the people. Then comes volume by category over time, where a fix shows up as a line falling to nothing. It covers volume as an early-warning system, with the spike that means an outage and the drop that means users gave up. And it covers forecasting volume simply, with one spreadsheet and no models. The queue has been telling you about next September for six years. This is how to listen.
Articles in This Series
- Counting Tickets Properly: Created, Closed and Open
Created, closed and open are three different counts; by day, week and month; duplicates and merges; by channel; the count that changes when the definition changes; and the definition sheet. - Trends and Seasonality: Reading the Shape of Ticket Volume
The weekly shape, month-end, the start of term or the financial year, the quiet August; separating trend from season with a rolling average; and the seasonality calendar. - Per-Department and Per-User Ticket Patterns Without Blame
The department that raises half the tickets, the user who raises twenty a month, reading the pattern without blame, and the pattern table. - Volume by Category Over Time: The Trend Sheet
The category that grew, the one that vanished after a fix, the one that appeared with a new system, and the category trend sheet. - Volume as an Early-Warning System: Spikes, Rises and Drops
The spike that means an outage, the slow rise that means a failing system, and the drop that means users gave up. Covers the daily glance that catches each, and the warning signs table. - Forecasting Ticket Volume Simply, With One Spreadsheet
The rolling average, the seasonal multiplier, the growth line, the staffing implication, no models, one spreadsheet, and the forecast worksheet.
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This series is part of the QuerySolv helpdesk topic library. It covers the foundations, processes, communication, knowledge, tooling, metrics, classic ticket domains, people and strategy behind a support desk that works. The library pairs well with the software we build: QuerySolv. It is a self-hosted help desk that runs as one Windows service on your own network. It is licensed once per installation, not per agent per month.