10 questions that your data roadmap can answer
“What the heck is a data roadmap?” We’ll answer that first. (And we won’t count it against the 10.)
With a cool 28 million results for “big data” in the news section of Google, it’s no mystery that data and all it entails is becoming more pervasive in the landscape and lexicon of companies both big and small. And while multinational companies like AirbnbEng are blazing trails on how to leverage data, data-thinking, and data products for both tangible and nuanced business purposes, the journey for most companies who wish to navigate the data pathway remains uncharted.
“When and how should we really care about data?”
“What should we do with all the data we already have?”
“Do we need a data scientist? If so, what the heck do they really do?”
…and many, many more.
Consultants, and sometimes investors, are really good at helping to answer these types of questions. But they cost money, or equity, or both. What if you’re startup or Series A company who knows they need to embark on this data journey but don’t have a map (pun intended) for how to do it?
Product roadmaps are a (mostly) tried and true tool for communicating direction and progress to internal teams and external stakeholders. They show the high-level initiatives and the planned steps to get there. So…what about a data roadmap? (NOTE: There are plenty of other product roadmaps out there, so we’re not breaking new ground here.)
If you search for information about product roadmaps and simply replace the word “product” with “data”, you start to get the picture of how it could work. You can also use this exercise to determine how to build the data roadmap.
The TL;DR benefits of developing and using a data roadmap are:
1. Using data to solve problems consistently and efficiently
2. Building data capabilities within the company
3. Structuring data management and leadership
But to better explain the full utility of a data roadmap, here are 10 questions that companies — both big and small — can answer if they have a data roadmap.
Five of the questions can be answered through the process of developing the roadmap in the first place, and the other five can be answered by maintaining and using the roadmap once you have it.
In no particular order…
Developing the roadmap can help answer…
- How does the founder/CEO/stakeholders educate the entire company on the importance of data?
- Who owns the data pipeline?
- What are the current relationships between product, design, marketing, engineering, and data? What do we want them to look like in the future?
- How is the data team — formal or informal — structured? How does it interact with the rest of the company?
- What are the tools to use, best practices, and necessary infrastructure needed to become more data-centric — particularly as the company grows?
Using the roadmap can help answer…
- Have we structured our data and processes, explicitly and carefully, across different teams, roles, modules, codebases, and databases?
- Are we being consistent in our data practices as we grow?
- Are we solving current and future problems by making data-driven decisions, including but not limited to: naming and translating the problems accurately, ensuring valid and reliable research and reporting, and designing the product from the data up?
- Are we avoiding common data/reporting fallacies? If not, how can that be corrected?
- How does the data team field requests from stakeholders and prioritize its efforts?
What do you think? Do you see value in developing and using a data roadmap? (Do you already have one?) Would love to hear what you think — leave a comment and we swear to reply!
