The Data Product Manager’s Role And Supporting Frameworks
The purpose of a data product manager is to monetize. They turn data into a product that generates revenue, reduces costs, or improves productivity. It’s a very tall order, but what’s mindboggling is how many businesses operate without a dedicated resource in the role.
It’s fair to say that a business isn’t serious about making money with data or machine learning until they hire a data product manager. When a company gets serious about monetizing a technology, three pieces always go into place. They hire leaders, strategists, and product managers.
I teach the data product manager’s role in three parts: vision, responsibilities, and frameworks. There are several differences between digital and data products, so new frameworks are critical to data science success.
Data Product Vision
Vision is too often overlooked. Early data maturity businesses have several competing visions for data and AI. It’s an inconsistent mess that makes alignment across the company and prioritization impossible.
Until the vision is in place, every initiative is a 1-off. Data product managers own the process of coming to a consensus. C-level leaders are the final decision-makers and vision-setters. The data product manager is the facilitator.
They extend the business’s vision for data and AI into a single vision for products built with the technology. Data product managers own the bridge between strategy and execution, and that will make a lasting impact on their companies’ futures.
Data Product Manager Critical Roles
Product managers’ core responsibilities are: