Generating data and ideas with analysts
The Observatory team explain the experience of receiving and responding to requests for analytics, after holding 2 co-design sessions with Australian Public Service (APS) agencies in May.
- data scientists
- content designers
- content managers
- web performance analysts
- other data practitioners
Insights from previous Discovery research suggested that various reporting demands created challenges for APS analysts. We wanted to explore this to see if we could find common challenges and solutions together.
What is Co-Design?
Co-design is short for ‘co-operative design’. It is a way to explore problems and possible solutions with users and stakeholders.
Co-design allow us to share perspectives and reach agreements between a large and diverse group. This often results in more robust and reliable solutions.
What we heard
We ran 2 sessions with approximately 4 to 6 people in each group. We began by discussing how agencies initiated analytics requests. This confirmed our original research – the unstructured nature of analytics requests greatly reduced analyst capabilities to deliver value to teams.
There were also no formalised processes or tools for reporting and responding to these requests. Analysts would screenshot data or copy and paste important statistics and share back using inconsistent methods such as email, messenger platforms, and in-person reporting.
Stakeholders often didn’t explain the broader organisational objectives of their analytic requests. This meant that analysts were producing insights that may not help solve the problems or deliver bigger value.
Key themes from this research included:
- A need for more streamlining, speeding up, and prioritisation of requests.
- Helping people make better requests that explain the business problems they are trying to solve.
- There are benefits to anything that provides answers quickly and simply, with minimal effort from analysts.
- More help for those asking for insights, such as prompts for insights and action in response to data, so they know what to do next.
What we came up with
Some of the co-designed solutions shared some common factors:
- Increasing data literacy within organisations.
- Improving organisational self-service capability to make data easier to find and interpret, so analysts can focus on deeper insights.
- Using templates and frameworks to streamline and improve information going into and coming out of analytics requests.
Our next challenge
The biggest challenge for the Observatory team is acknowledging that we are talking about organisational culture and processes. These are some of the hardest things to shift as an external team.
Our goal is to empower analysts to improve the services they work on. We are working towards building essential tools and resources to give the right kind of support. This means that analysts can have a positive influence in changing their organisation’s relationship with data.
Research and co-design showed that despite challenges, many organisations have similar problems. We are beginning to explore what solutions might ease these challenges in future.
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