Housing Analytics Courses

We offer a range of data skills training courses in partnership with HouseMark, one of the UK's largest housing sector membership organisations. These packages are designed to help social housing providers to improve their understanding of data analytics, including exploratory analysis, data presentation, relationships between metrics and predictive analytics. All the examples are framed in a social housing context, making them relevant and accessible to those in the sector.

Common social housing questions featured in the courses include:

  • How do we know whether arrears performance is good, average or poor?
  • Can we identify the causes of variations between different housing areas or officers?
  • How significant are monthly changes in voids?
  • Which factors drive repairs and how can we predict the number of repairs a property might need?
  • Can we forecast the turnover in six months' time?

Upcoming courses

Housing Analytics:

  • 19 September 2018 (London)
  • 3 October 2018 (Edinburgh)
  • 7 November 2018 (Manchester)

Introduction to Predictive Analytics:

  • 25 September 2018 (London)
  • 17 October 2018 (Edinburgh)
  • 14 November 2018 (Manchester)

Places on each course are limited. All bookings should be made via HouseMark.

It was refreshing to attend a course where examples from the sector were used throughout.
— Housing Analytics, Coventry, 14 June 2018

HOUSING ANALYTICS (1 day)

Our Housing Analytics course aims to give an introduction to statistics for those who work in the social housing sector but who have not had formal statistical training. All the examples are framed within a social housing context to demonstrate the practical value of analytics. This course will enable you to improve your skills in various analytical methods, data presentation and exploring the relationship between different housing metrics. Some knowledge of Microsoft Excel (including pivot tables) is expected.

Modules

  • Introduction - analytics and social housing
  • Exploratory data analysis - exploring data through graphs and charts
  • Descriptive statistics - using statistics to characterise a data set
  • Identifying outliers - analytical methods
  • Relationships between variables - pivot tables, correlation and causation
     

Introduction to predictive analytics
(1 day)

Aimed at those who already use analytics but want to take their understanding to the next level, our Introduction to Predictive Analytics course explores the role of predictive analytics with the context of social housing and introduces a variety of modelling and forecasting techniques, enabling analysts to make predictions about future performance and make data-driven decisions. We also identify potential software solutions that can be used in this space.

Modules

  • Introduction to predictive analytics
  • Linear regression - using relationships between metrics to make predictions
  • Logistic regression - finding the probability of a tenant being in arrears
  • Time series forecasting - creating forecasts using past trends and patterns
Excellent course, well presented. Great focus on housing analytics.
— Introduction to Predictive Analytics, Coventry, 21 June 2018