This is a reveal.js presentation, rendered using quarto and motion-canvas, used for my talks at LondonR and SatRdays, in London, during April 2024.

You can preview the slides at https://andrie.quarto.pub/pmds-londonr/

As a Data Scientist you build data products all the time. You may even have worked with a Product Manager to create analyses and dashboards for decision making.

But are you applying the skills of product management in your data science role?

In this talk Andrie provides an overview of Product Management (PM), and what he’s learnt over two decades of managing products, ranging from hardware (Psion PDAs) to software (Microsoft R Open, Posit Workbench) and hosted services (MRAN).

Every product manager must consider the new product adoption life cycle, managing the stages from finding the first innovators, managing growth and ultimately the end-of-life process.

During this process you must manage your product so that it’s usable (customers want it), feasible (you can build it) and valuable (you can do this sustainably). Many frameworks exist to think about discovering what customers want, the jobs they must get done, forming a value proposition, managing a product roadmap, working with dev teams to build it, and working with marketing and sales to create a compelling sales pitch.

As a data scientist, you can benefit from product management knowledge by thinking of your app as a product. You must convince your users (internal customers) to use this app (at the cost of changing their workflow).

I will leave you with a map to get started with classic resources, including Geoffrey Moore, Marty Cagan, Teresa Torres, April Dunford and Lenny’s Podcast.

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