This is a case study for Principle T4: Transparent processes and management.

The Department for Transport (DfT) has fostered a culture of innovation and improvement which has supported the application of core RAP principles and supported the quality management of its official statistics. This culture has been created through a combination of enthusiastic and driven individuals, strong senior support and strategic direction, and working in an open and transparent way. DfT’s RAP developments have been underpinned by a strategic goal to produce most of its statistics using a RAP approach.

DfT work transparently and openly using GitHub, to share code and host materials from DfT’s weekly coding meetings and signpost to useful resources online. DfT have developed and published an R cookbook of coding standards, that specify DfT’s minimum requirements for ‘good code’. DfT require that the master version of a script is not edited without going through a code review and encourage the use of automated testing (Continuous Integration) tools. The R cookbook is community edited, so standards can evolve as change as needed.

To introduce RAP principles to its official statistics, the DfT has focused on automating data tables and quality assurance processes. DfT identified these as the best areas for development in its existing processes since they would be the most prone to human error.

For example, by using R code to automatically run validation checks and identify issues for further exploration, quality assurance is now carried out in a more standardised and efficient way than it was before for DfT’s Road Safety statistics. DfT ensures that the R code to produce these statistics is peer reviewed, providing an additional layer of quality assurance. Peer review is often carried out by members of the RAP committee, the group which supports RAP developments in the department.

The committee has developed a template which is used as the basis for all new coding projects. This supports a standardised coding style across the department and results in improved quality, readability and reusability of code.

DfT has a strong community of statisticians and its RAP committee has been instrumental in supporting RAP developments. This includes running internal code clubs, inviting external speakers to share learning, and developing training and tools such as an R project template and an R cookbook which provides comprehensive coding examples (see Case study T5: Developing statisticians’ coding capabilities to meet future organisational needs). DfT has also developed a RAP training session for managers which focusses on quality assurance and gives managers the confidence they need to sign off publications which use a RAP approach.

This example shows how DfT has created a culture that supports RAP developments and continuous improvement. By working openly through GitHub, DfT is transparent about its approach to quality management. It has also established organisational tools that help it to manage quality to appropriate quality standards, strengthening of the quality management approach used in the production of its official statistics.