Apply Product Thinking to Data
At Kin + Carta, we approach Data Mesh beyond the purely technical and architectural angle. Instead, as experts in Data and Product Thinking, we talk a lot about the organizational and people challenges involved in democratizing data. Moreover, thinking about data supply and consumption as well as the mindsets and responsibilities of data owners to create a better overall maturity level within global organizations. It is from this perspective that we explore cultivating a thriving data consumer experience by applying product thinking to data.
Consider the consumer experience — you don’t need actually need a Data Mesh to apply product thinking to data
Yes, there’s no doubt that Data Mesh is a core vision and is clearly the right way forward — it liberates data at scale and supports analytics, machine learning, and data-powered digital products.
And yet, there are organizations that have aspects of Data Mesh integrated and not quite ready to scrap or to restructure their entire data architecture just yet. Also, data consumers aren’t necessarily concerned with the implementation details. They just want reliable and trustworthy data, without having to be concerned with where their data is or where it’s being migrated. When technology is done well, it seamlessly integrates itself into our lives without having to think about it.
We love the vision of Data Mesh, but we are putting organizational and cultural challenges ahead of the pure technology and architectural paradigms, which for the average global organization will take some time to see it played out and fully embedded. Start-ups certainly would benefit from building a Data Mesh from the get-go — it’s one of the most important decisions a CTO could possibly make in this role!
Data as a Product — the key driving concept in packaged data for consumers
Part of cultivating a data-driven organization is to generate consumer demand. And we’ll need a magic ingredient that will drive data consumption and that is trusted, high quality, and useful packaged data. Certainly, the idea of saying “data is a product” feels like an abstract concept to the average person. So, where in real life, do we experience something like this?
The analogy is over-the-counter medicine. When one walks into a pharmacy, there’s a nice curated range of products. Everything’s trusted to deliver a positive outcome. The product is nicely packaged, branded, has clear instructions, and also easily identifiable. If you have a medical need, you identify the product or if you need additional help, you can speak to the pharmacist. You don’t need to be a scientist to buy over-the-counter medicine, and it just works.
This is a great analogy for data as a product — if data products and the packaged data were effectively available in this way and we trusted it in the same ways as over-the-counter medicines, that would be a fantastic platform on which to start democratizing data.
Data marketplaces — the pharmacy for data consumers.
More than just having a pharmacy and packaged products, you’ll need a data marketplace that’s easy for data consumers to access, so they find what they’re looking for in a reasonable amount of time, and to know which data products are worth taking a closer look. The key point is that everything you find in this data marketplace is trusted and curated. The product is designed to be sticky, developed iteratively, and have Product-Market Fit.
Based on actual discussions with colleagues, with clients, and research, our perspective is that a data marketplace would sit on top of a catalog because a data marketplace is a consumer-focused tool.
In fact, a marketplace might be the single place you go to in the future as your starting point with data. Whereas with a catalog, data consumers might be deterred because you might need to know a technical language and you have to be data literate.
Also, one of the things that I talk about a lot with Kin + Carta customers is the idea of data literacy. How do we enable everybody to make decisions with data? What are those tools? Oftentimes, users just want the insight or the KPI, not the data behind it. So, the marketplace is a way to discover data products that can appeal to a wide range of personas.
Great Data Tension: deriving value from data
Data is only going in one direction. For years, we’ve explored and discussed the gap between data creation and data value in any given organization as the Great Data Tension. Our objective for our clients is to incrementally close this gap and some of the ideas about applying product thinking to data and a data marketplace are a great way to start on that journey.
Looking back over my data career, I see a lot of the same themes and challenges in Data Mesh that have been around for a long time. Data projects which help someone deliver value, get their bonus but ultimately not really contribute to the common good. It’s the tragedy of the commons. Data owners need to be incentivized to manage data for the common good or we will never break this cycle.
One thing is for sure, with Data Mesh, we now have a movement which has us brought together. Some organizations will no doubt cope without a Data Mesh and they’ll manage to operate at a level which just makes it work for them.
But those that really make data products work are going to win in the longer term. Personally, I always look forward to meeting and working with the brave Data Leaders who see this and want to start making that change now.
And as a parting gift, I recently joined Adrian Estala, host of Data Mesh TV as we discussed some of these thoughts shared in this blog post.
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