Goodbye Data Teams, Welcome Data Product Teams to the Commercial Circle



Building more data product teams than data teams to improve collaborative teamwork

It was suggested by Emilie Schario and Taylor Murphy last year to “manage your data team like a product team.” The article’s thesis was that data teams would benefit from adopting many of the excellent techniques now used by product teams. The product team is led by a product manager.

Somewhere along the line, we lost sight of this and cheerfully replaced it with strawmen, like building data teams, maintaining production-grade systems for our data assets, or rigorously defining what production means in the service of hardening data contracts. While each of these is undoubtedly important, they are more focused on the correct management of data and data assets than on the data product teams who generate the impact.  The main goal of this article was not to debate the parameters and definition of a “Data Product” or to impose SLAs on data producers, but rather to force them.

Let’s talk about the specifics of running your data team like a product team. User-centricity and proactivity are the two main concepts that product teams uphold. Each will be discussed in turn.



User-centric product teams are the finest. They regularly communicate with their customers and allow direct user feedback to immediately affect their roadmap. Any successful product relies on this flywheel to ensure that it is solving problems as well as providing features.

The same methods must be used by data teams. We’ve become too infatuated with how technically fascinating our work can be, and we’ve forgotten that we are a business unit hired to deliver economic value, not a solitary haven for scientific or engineering interests. Additionally, our metaphorical “data product”—all of our data work—fails if we, like product teams, do not use data to solve business challenges.

This does not include acting impulsively in response to requests. This does not entail avoiding all scientific activities, either. It just entails remaining aware of the company’s requirements and seeking out possibilities to further those goals. Taylor and Emilie argue that your coworkers are your customers; nevertheless, we believe that this is not sufficient and that your true customer is the company. You must be aware of it, comprehend it, and base all you do on it.



Second, the top product teams have proactive procedures in place to aid in the creation of the products. They intentionally give themselves room to form the vision, conceive ideas, and work on passion projects that fall beyond the purview of taking on direct client demands.

On the other hand, analytics teams rarely work this way. We should at the very least spend some time investigating the data independently of incoming queries. We should also be on the lookout for trends at the team level so that we can deliberately design our roadmap and complete high-value tasks.

Despite this, reactive work is still important because analysts are the company’s main tool for data exploration, therefore we frequently find ourselves playing a supporting role. However, the secret is to always strive to comprehend the context of this work and to allow this context to inspire smart, high-impact projects.


What is the Structure of the Product Team?

Because it enables the business to distribute duties and responsibilities as effectively as possible, an effective team structure is essential. Teams can be created in a variety of ways that have proven successful for other businesses.

Product teams require a strong framework and well-defined roles. But it all begins with a crystal-clear product vision and a transparent product strategy that lays out shared objectives. All team members will be aware of what they are working on and what the group will produce as a result of the project.


How can a Product Team be Formed?

When assembling a product team, be aware that its composition will evolve to project requirements.

And be ready to respond to the following inquiries from time to time:

How many items should be controlled?

Which (s) have a higher priority in terms of needs for development and revenue generation?

How complicated are these products?

Which stage of a product’s lifetime is it in?

By responding to these inquiries, you can get a sense of the kind of team structure that might be appropriate for your group.

The post Goodbye Data Teams, Welcome Data Product Teams to the Commercial Circle appeared first on Analytics Insight.