Information is different than knowledge. And the more information you have, the bigger the difference becomes.
Nowadays, you can summon a flood of information from wherever a user is interacting with a software product: simply connect your product to one of the hundreds of off-the-shelf solutions on the market. But getting knowledge out of that information requires more careful thinking.
To be useful, business analytics need to inform your ongoing product development. To get there, we trust in an iterative, scientific process. First, we write down hypotheses that challenge our gut feelings, after spending a substantial time mulling over the business. Only after that do we look at the data to test whether we were right. Usually, it turns out we weren’t — and there comes the iterative cycle of refining the hypothesis, then analyzing the data again.
So we have continuous product improvement, fed by iterative refinement of our knowledge. We need to automate this process for several reasons:
- Manually mining information isn’t reproducible and it doesn’t help us firm up our ideas and priorities.
- Automated analytics can be immediately shared across teams and divisions. You don’t just share a dashboard, you share a framework.
- Casual analyses and reports can struggle to keep pace with lean product development. Last week’s analyses might already be unrelated to today’s priorities.
Crucially, automated business analytics also empower product teams to democratically build custom views of the data. Why force everyone to share one perspective when any team member can access knowledge in real-time?
To learn more about the vision and framework underlying our automated business analytics, contact us.