Many companies believe “being data-driven” means having a lot of dashboards. But dashboards only tell you what happened yesterday; they don’t help you win tomorrow. True data maturity is measured by how decisions are made.
Based on my experience, organizations evolve through three clear levels. Let’s use an e-commerce platform like OLX or eBay Kleinanzeigen as a case study.
Level 1: The Reporter (Knowing What Happened)
At this level, the company has visibility into its key metrics. Teams use dashboards (in Looker, Tableau, etc.) to answer descriptive questions.
- Case Study (OLX/eBay): A dashboard shows in real-time how many car ads were listed yesterday, the number of daily active users, or the most popular categories.
- Value: This is fundamental for basic business health monitoring.
- Limitation: It’s reactive, not proactive.
Level 2: The Investigator (Understanding Why it Happened and What Will Happen)
The organization moves from describing to diagnosing and predicting. Data teams don’t just report metrics; they connect different data sources to explain the causes and anticipate the future.
- Case Study (OLX/eBay): Instead of just seeing that listings went up, the team can now cross-reference that data with marketing campaigns and conclude that car listings increased by 20% due to the new social media campaign. Furthermore, they build a model that predicts which users are at high risk of churning next month.
- Value: You shift from a reactive to a proactive operation. You can take action to prevent problems or capitalize on opportunities.
Level 3: The Automated Decision-Maker (Making Something Happen)
This is the highest level and where the most value is generated. The data platform doesn’t just inform decisions—it makes them automatically at scale.
- Case Study (OLX/eBay): The system identifies that a user is searching for a “BMW 3 Series.” Automatically, the next time the user visits, the homepage shows them the most relevant new listings for that model. Or, if a user is identified by the Level 2 model as “at risk of churn,” the system automatically sends them an email with an offer to post their next ad for free.
- Value: The business scales without needing human intervention for every micro-decision. Intelligence is embedded directly into the product.
Conclusion
Data maturity isn’t about the number of dashboards you have; it’s about the autonomy and impact of your data systems. Where is your company on this journey, and what’s your plan to get to the next level?