Run Your Data Team Like a Product Team
- Author: Emilie Schario and Taylor A. Murphy, PhD
- Full Title: Run Your Data Team Like a Product Team
- Document Note:
Q: What is the Data Product?
A: The Data Product is the collection of every piece of data, and the tools used to generate, access, and analyze that data, within an organization.
Q: How should a Data Team be funded?
A: A Data Team can be funded directly by the company or by the departments who are supported by the Data Team. Explaining the ROI to business partners can be a useful tool in securing funding.
- URL: run-your-data-team-like-a-product-team
- Data teams aim to help the people in their organization make better decisions. Many data teams aren’t doing this as well as they could and are missing out on a huge opportunity, both for the organization and the team. This gap is due to teams not being set up for success, which undermines trust in the data and the insights the team generates (View Highlight)
- Service-oriented data teams aren’t effective
Most data teams aren’t set up for success. For many years, data teams have been buried in the IT function. Like IT functions, those data teams handled getting data out of their systems and presenting them to the stakeholder as CSVs from which the stakeholders could work their magic and come up with conclusions (View Highlight)
- submit a ticket with a question, get a very specific answer” mindset. Data folks who are bound to this model rarely spend time being proactive. (View Highlight)
- When you view your colleagues as your customer and the Data Team as building and supporting a Data Product, then you’re able to unlock the opportunity of your data and data team (View Highlight)
- So what is the Data Product? It is the collection of every piece of data, and the tools used to generate, access, and analyze that data, within an organization. (View Highlight)
- Every internal tool or app that gives people the ability to generate, access, and analyze data is also a part of the Data Product. These can be thought of as “features” of the Data Product. A simple heuristic is this: if people are using it to make decisions, then it’s a feature of the Data Product (View Highlight)
- 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 organizations to dramatically increase the value of the Data Team to the organization (View Highlight)
- When moving your Data Team to the product model, you should expect some pushback from other people in the organization. As a leader you must have strong 2-way communication. This will require a great deal of empathy as you’ll have to constantly balance the need to share your vision and goals with the need to integrate the feedback from your users (colleagues). (View Highlight)
- continually communicate what you’re working on, what you’re not working on, and why you’ve made these decisions in order to bring your stakeholders along on the journey. (View Highlight)
- Tip: Communicate with your colleagues (users) proactively and hear their feedback (View Highlight)
- It’s the business impact of the work that the Data Team produces that matters, which can be difficult to measure. If you have a strong foundation of 2-way communication, it is worthwhile to align with your stakeholders on what that measurement looks like to them; for example, what KPIs is your team supporting and how are your initiatives supporting them. (View Highlight)
- 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. (View Highlight)
- With a strong user focus, 2-way communication, and a solid definition of success, you can start to drive business impact through better decisions by using many of the tactics of product management. (View Highlight)
- user stories and other tactics should be deployed in such a way that you and your Data Team are focused on deeply understanding what your colleagues are trying to do. When you understand their needs and what solutions are possible, then you’ll be able to match the problem with the right solution more effectively than the requester imagined, thereby building something that will scale and have long term value. (View Highlight)
- If your company is forward thinking, they’ll pay for the Data team directly. You can also experiment with data funding coming from the departments who are supported by the Data team. Explain to your business partners what folks on your team do to support them and what it would take for them to get (View Highlight)
- 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. (View Highlight)