This survey was conducted to understand the level of data maturity in selected county governments and come up with a tool for county governments to assess their own levels of data maturity.
Department heads from the governance, health, agriculture and education sectors of the eight counties included in this survey responded to a digital questionnaire either at in person interviews or online. Questions on data quality and availability were included to paint a picture of the current situation and the causality section was designed to investigate why the departments are at that level.
The results show that data maturity is highest in the health and governance sectors where systems are set in place by the national government to regularly collect and report detailed data to the public for use and transparency.
Each department has its own system for data management which is geared towards populating quarterly and annual reports of progress towards the goals outlined in each county’s development plan for the term of their elected officials. Most of the data is collected in physical forms and templates and collated at the sub county and county levels in digital form.
We recommend that counties work towards formalising data management manuals for all departments to ensure that counties are collecting, reporting and analysing data in the same format. These frameworks should look to digitise these processes as much as possible to improve access and accountability.
The pilot study involved interviewing officials from different sectors in the governments of eight participating counties and noting any additional information proffered by the respondents. Data was collected through a prototype of the tool (online questionnaire) that will be transformed into a toolkit as the end product of the exercise. The initial goal was to travel to each county and conduct in-person interviews, with researchers filling in the form to avoid getting inaccurate responses due to different interpretations of the questions. It was crucial to understand how the questions would be interpreted and how the questionnaire could be adapted for improved clarity and efficiency.
