General idea
- Run data team as if you were building a Data Product that helps guide decisions and all of your colleagues are your customers.
- So what is the Data Product? It is the collection of every piece of data, and the tools used to generate, access, and analyse that data, within an organisation. If people are using it to make decisions, then it’s a feature of the Data Product.
- The data and associated features have limited meaning and value within their own silo, but when integrated together within the Data Product, then superlinear value can be revealed. With this mindset, the data team’s role grows to include building and guiding the strategy and features of the Data Product. And because you’re building a product, you can take all of the best practices of product-led organisations to dramatically increase the value of the Data Team to the organisation.
- A user-centered focus is key.
Tips from Product Management
- Understand the root cause of a customer problem – a core principle of product management.
- Communicate with your colleagues (users) proactively and hear their feedback.
- Your success is a function of the impact you’re having on the business, measured in the number and volume of decisions you’re enabling or measured by the quality of those decisions with respect to a KPI. It is not the number of dashboards built; that is, it’s not the output of the Data Team. Write this definition in a team handbook and visit it frequently. Build a culture of continuous documentation so you’re regularly aligning with your business stakeholders.
- Users Stories are a simple way to define how a new feature (dashboard, chart, or metric) will provide value for the end user. User stories generally follow the framework of “As a (stakeholder), I want to (task) so that (desired result).”
- “As a Director of Customer Success, I want to understand a specific customer’s product usage in the past 3 months so I can help them gain more value out of our product.
- The user story then invites more conversation to further define what they actually mean by “product usage” and “value”.
- Consider using an issue tracker (Trello, GitLab, GitHub, Asana, etc.) to help organise and prioritise inbound requests, plan work, and refine requirements with stakeholders.
- Data teams should be 3-10% of the total headcount, depending on the nature of the business.
- Make the team multidisciplinary.
Immediate next-steps ideas
- Talk to a Product Manager to understand how they spend their time. Ask good questions and listen to how they work, what they prioritise, and what is a distraction.
- Ask questions to try and understand the problem they’re trying to solve.
- Take inventory to start identifying and documenting the different parts of your Data Product. This can be an excellent opportunity to talk to many different stakeholders across the company.
NB
- Not to confuse with this principal of data as a product that – similarly – talks about providing insights (DaaS), not just data (DaaP). That is to be real strategic decision partners, not just boring data-providers.
Hire Data Product Manager
We see a lot of value in separating the process of building the right thing (product) versus building the thing right (engineering). Currently, data teams rely on individuals to do both, but it’s rare to find such individuals that excel in both.
- Demonstrating business value
- Change management
- Evangelism
- Complex stakeholder management