Skip to main content

Why do you need a PM in your Data team?

 

Most modern businesses already realised how important data is for their success. Data science is one of the hottest roles in today's job market. Product managers work with data teams daily, however, should a data team itself have a product manager?

On a classical product team, PM is usually responsible, among other things, for product discovery. As part of this effort - the PM would dig into problems their customers are having, do enough market research and define the product to address the problems. In a data science case, it might not work this way as PM might not have enough expertise to define a solution. Data science is deemed a highly technical discipline that aims to solve problems with machine learning and advanced data engineering. Still, many teams opt to have a PM on a data team. Why and what value even a non-technical PM could bring to a data team?

Evangelise data science within the company

Data science is a hot topic, however, it is also often misunderstood. People either ask for miracles from the data team or ignore their input altogether. A PM could help to promote and explain the data team to the rest of the organisation. They can communicate the goal of the team, their working methods, the inputs they're expecting and the outcomes people could get from a data team.

When the data team needs to change certain processes or acquire some resources to achieve their goals - PM could facilitate these efforts and work with stakeholders to ensure the smooth operations of the data team.

A PM on a data team should also be in close contact with their peers in other teams. They need to know other product areas and the challenges they're facing. A data team PM should be proactive in helping their peers make data-informed decisions and supercharge their products with the clever uses of data.

Lead by example with data-informed decisions

It's incredibly helpful to lead by example. Hence a PM on a data team should be the pioneer in data-informed decision-making. They should be ready to showcase their working practices and help other teams to adopt them.

A data team PM should do data discovery regularly and incentivise their peers to think deeply about the insights they're finding. Moreover, a PM on a data team should be a champion when it comes to all things data, including data security, handling, and ethics. They need to educate the rest of the company to not only make sure the organisation is compliant with the best data governance practices but also that everyone is using data to the best of their abilities.

Ask the right questions

When it comes to working with the data team directly, a PM could add a lot of value by asking the right questions. Data scientists and engineers are fantastic at finding solutions and answers with the help of data. However, at times they are struggling to apply their knowledge and skills to the right problems. A PM on a data team should work ahead of the rest of the team and constantly find new problems to solve or questions to answer.

Good data questions could help an organisation to better understand their customers, create delightful experiences and advance their business. A PM on a data team should ask those questions and facilitate other people to follow suit.

Help me help you

A data team could benefit from having a PM in multiple ways. A PM could help in promoting the best data practices around the company and manage the inputs coming towards the data team.

They also could lead by example and educate their peers in using data to create better products for customers. A PM could become the champion of all things data within the company, helping to establish the best data practices.

Working directly with the data team and being close to all other products, PM could ask the right questions towards the data to deepen the understanding of customers and to increase product quality. Through data discovery they could uncover new value streams an organisation could offer, advancing the business and delighting the customers.

Popular posts from this blog

Product Vision: an elevator pitch for your product

On this blog, I write a lot about making data-driven decisions . But what if you just starting to think about your product? You have a vague idea and nothing more. No point to go for prototyping or even talking to customers as you don't know yet who to talk to and what to talk about. In such situation - start from creating a product vision.

7 steps of Product Discovery

Before building a product - how do you know what product to build? While building a product - how do you know what features are the most valuable? After you've built a product - how do you know if to tune stuff or add a new one?

3 ways to prioritize a Product Discovery backlog

Discovering the right product is a vital part of a product development process. To do that effectively best product teams use a Product Discovery process. This process foresees you having a Discovery Backlog with a list of ideas, concepts, and hypothesis in need of validation. But how to decide what ideas to validate first ?