Time Series (Trend) Analysis
Intermediate Course · Two half-days · Microsoft Excel and Power BI · Follows Introductory Course
A practical, hands-on course for housing analysts who want to understand what their monthly figures are really telling them. Using real repairs and complaints data, participants learn to separate trend from seasonality, build and test a simple forecast, and use Statistical Process Control to tell a genuine change from normal variation.
What's covered
Components of a time series: trend, seasonality and remainder, extracted in Excel
Forecasting: trend-plus-seasonal forecasts, Excel’s Forecast Sheet and R
Forecast accuracy: MAPE, and spotting when a model has stopped working
Statistical Process Control: XmR charts and the four SPC rules in Power BI
Acting on signals: raw or adjusted data, resetting limits, reporting to boards
Who it's for
Housing analysts and staff in performance, repairs, customer experience or business intelligence roles who produce regular monthly reports. Participants should have completed the Introductory course or be confident with Excel formulas, PivotTables and charts. No prior knowledge of forecasting or SPC is needed.
Requirements
A laptop with Microsoft Excel (Microsoft 365 or Excel 2019 or later)
Power BI Desktop (free) to open the supplied SPC report
Optional: three years or more of your own monthly KPI data
Format
Two afternoon sessions of 3½ hours each (13:00–16:30), delivered online or in person. The first afternoon covers time series and forecasting, the second Statistical Process Control. Theory is kept short — most of the time is spent on hands-on exercises with real housing data.
This course is part of the Musgrave Analytics training programme for social housing, which also includes the Introductory Data Analytics course, Sampling, an Advanced Power BI Workshop, and a Manager Data Skills course.