Technically not that technical
How to become a Data Product Manager without writing a single line of code
As a team we’re passionate about encouraging diversity within data and technical product management. Not only because this makes it a more fun and supportive environment for us to work in, but it also makes us better at our jobs. We strongly believe that a broad range of experiences and backgrounds in the team enables us to build the best products and services (you can read more this here).
To support this, we speak a lot at non-data/non-tech events and conferences in order to access audiences outside of the industry and promote entry points into data. The one question we always get asked is ‘what technical skills do I need?’. This is natural. As a Product Manager you want to secure the trust and respect of your team by showcasing a deep understanding of the products that are being built. And this can feel like a huge hurdle when you’re from a non-technical background and what we mostly see in response to this is either PMs not entering the industry or resorting to learning the basics of Python, SQL etc to build the skills they think they will need.
In this blog post, we argue that not only do you not need to be technically-trained, but that using your time and energy to learn coding is actually a suboptimal choice, with your efforts being better spent on an alternative (and more accessible) learning journey.
Learning approach
Whilst most want to gain technical knowledge resembling that of today’s buzzword profession of the Data Scientist (learning to write a few lines of code), we believe you should strive for knowledge similar to a commonly overlooked and less hyped profession — the Data Architect.
Let’s review the picture below. This shows a summarised overview of the data technology landscape (an illustrative view only… it does not encompass all the technologies available and their adoption sequence can be debated).
Here are our main takeaways:
- There are lots of different technologies out there and it is almost impossible to master everything
- Over the last 20 years the technologies used have radically changed, and this rate of change is accelerating
- As a result, any competitive advantages you might create by familiarising yourself with any of these technologies will only be temporary. Unless this was your full-time role (such as Data Scientist, rather than a PM) you will never keep up
What is more useful to you, in your role as PM, is trying to get a holistic understanding of the entire delivery landscape rather than trying to gain depth in a few random things. Because the landscape is more static, your knowledge will remain relevant for longer. You can reduce the learning clutter by zoning-in on the main delivery pillars and focusing on the principles of technologies, fundamental questions and consideration points that are prevalent in each. Think of your knowledge as a T shape — it’s more important to focus on the top of the T, the breadth of how the different tools interact and how they come together to form data products, than the depth of expertise in a single area.
Pitfalls to be aware of
There is, however, a common problem we encounter using this this approach. Taking a broader learning approach can place the PM in an uncomfortable mental state, landing them right in the middle of the Dunning-Kruger curve.
Whilst this effect is typically used to demonstrate people who assess their cognitive ability as greater than it is (the left-hand side), we’re more concerned with the effect that happens in the middle ‘valley of despair’. By taking a broader approach, the PM might start to develop imposter syndrome: they begin to doubt their own skills and the value they bring resulting in their creativity and engagement reducing.
Avoiding the trap
This is not a desirable state and the key to avoiding this mental trap is to remember that the technical delivery is only one part of the overall project success. A Data PM brings value in many other areas throughout the entire lifecycle of delivery. You work with, and often manage, colleagues that have more technical experience by:
- Being a leader — managing the product end to end, setting the direction and keeping the team on course
- Unlocking barriers — being clear on what you’re trying to solve and helping to navigate blockers
- Respecting and supporting the team — provide the tools and freedom the team need to solve the problem, and help to facilitate the process
Think about your role as similar to that of a CEO. You may not know what each department does in detail, but you understand their roles and functions and you treat them as the highly talented experts they are — seeking their input to help you solve complex problems.
Overall, holistic systems learning is a powerful way of improving your performance as a PM because the approach allows you to be flexible in your learning, focuses on the big picture thinking that PMs need and ensures a competitive advantage, over knowledge gained, for longer. However, a good Data PM also combines their technical skills with leadership, support and guidance to gracefully lead their team to success.
Co-written with Justinas Cirtautas
