In my last post, we covered our rules for software selection and how we found the right pieces for our software ecosystem. Choosing the software is just the beginning, stitching them into a cohesive end to end system takes trust, effort, and time. Our teams have been hard building towards new workflows. In this post, we will cover some of our design principles around our data ecosystem. These keep us aligned in our goals and allow us to decentralized our decisions.
Why Data Native Teams?
Have you ever been in a situation where you printed a spreadsheet? Even to a slide deck? Do you do it often?
Each time that happens, the data you are trying to communicate is already outdated. The "freshness" of the report becomes important, with each passing day making the analysis less relevant. Magnify that across every person in a company and we see that dead data can become a huge problem. The reactiveness of the organization becomes trapped in the rhythm of reporting.
For us the solution to this thorny issue is to build data natives from top to bottom. The issue of reporting exists on both sides. A more data literate consumer means higher bandwidth communication can be used. Furthermore, the more capable everyone becomes the more our data infrastructure mirrors our process. As our team moves from users to builders, better integrations will exist both in platform and in protocol.
Our Data Pillars
Every team member has a shared responsibility for the quality of the information that's part of our data ecosystem. Just as a company mission rallies the team around a common goal, data pillars help align every data decision. From file naming to collaborative documents, every piece of information is a data touchpoint. These pillars establish a culture around data excellence.
1. Single Source of Truth
One of the most wasteful processes in any business is data comparison between two individuals. Connecting filtered views to a common data source of truth is the first step towards reclaiming time towards better decision making. In our new data ecosystem, something as simple as a google sheet can serve as a source of truth for many team members.
With a source of truth, different conclusions present factually accurate divergent perspectives. This puts the focus on the method of analysis and reasoning behind the result, not the accuracy of the numbers. It's also a mental switch for the team to think on a systems and structure level, rather than point to point manual workflows.
2. Data for All
Everyone can make better decisions with better data. Our system should be able to serve any stakeholder regardless of technical proficiency. We will cover the implementation in-depth with a later post, but we've designed our data system to allow a progressive approach for data adoption. From looking up a dashboard to programming an internal application, a connection point is available to the rest of our data ecosystem.
Going from document hand-off-based workflows to integrated workflows isn't an easy transition. Entire processes require redesigning to untangle the knots that are no longer needed. This is why we try to empower every member of our team to use the tools available. The people who understand the process most intimately are those that are doing the work.
3. Data Native Teams
Through the first two pillars, we can achieve the third. Data native teams drive themselves based on the changing context around them, leveraging analysis to prioritize their next step. Small incremental steps can lead to huge gains in a short amount of time. Because we are learning together, our team can always count on each other for support.
Communicating faster with better quality benefits all of our work. Data native teams make a company sensitive to the changes of the world. Information can be quickly acted on with the right response. We always joke that we are building a hive mind. With an aligned mission and connected communication, it's definitely starting to feel like it.
The Journey has Just Begun
We're just getting started. In pursuit of those pillars, we have a lot of learning and building to do. We trust that a more data-driven organization is more efficient, productive, and sensitive. If our last 5 months have been any indication, it can also just be plain more fun.