I’ve just started a contract to head up a Data & Insight team with the goal of scaling from two team analysts up to six in the next six months. Naturally, my mind has been buzzing with ideas about what key things are needed to achieve successful scaling.
The team has been both stretched and under-resourced for the best part of a year and is about to lose one of the existing two analysts. They are a good team, recognised and respected for the value they add to the organisation. Their analytics practices are good – they have a well-managed Tableau server set up with processes and standards in place governing what is published there. They also have some of their main data sources housed in a data warehouse, feeding Tableau.
Working from the set up that this team already has, these are the elements that we are reviewing, improving and adapting in order to scale the team.
- Managing the delivery of the programme using Trello.
- Gathering requests from stakeholders using a shared email inbox.
- Documentation and communication focused around Microsoft Teams, OneDrive and Sharepoint.
- Using the website as a shop window communicating what the team offer.
- Building out a team structure based on domain areas, one for each new Senior Analyst to lead.
Reflecting on this list as a whole, there’s a strong theme here about creating smooth and effective flow. Flow of information or action into, out of, and across the team. Good flow owes more to establishing consistent behaviours from team members than it does to any particular tools used. Establishing well-flowing work practices takes:
- Agreeing collectively ways of working to test and iterate.
- Collectively setting expectations of behaviour.
- Setting up structures and tools to enable agreed ways of working.
- Agreeing some accountability mechanisms to help expectations to be met.
- Realising how much of the work boils down to building relationships based on trust and good communication.
The challenge to creating flow is to create structure that is easy, productive, logical and helpful to the people doing the work. Anything that feels onerous, tedious or overly dutiful will form rocks in the river, blocking the flow.
What are the stages of the analytics and insight pipeline?
- Request
- Triage and prioritisation
- Briefing
- Data, analysis and insight work
- Pre-delivery
- Delivery
- Retro
- Follow up
What are the flows that we want to make sure are smooth, easy and productive throughout the pipeline?
- Flows from stakeholders to the team
- Flows from the team to stakeholders
- Flows between multiple stakeholders
- Flows between analysts within the team
- Flows between analysts and other collaborators outside the team
- Flows between team leadership and analysts to support and guide
Photo by Ricardo Gomez Angel on Unsplash
Rachel Loves Data 