While there may be room for debate around being “data-driven” in the ideation process, no one can dispute the power of metrics in reflecting resultant business performance.
The discussion about whether to rely on data-driven decision-making or human judgment often takes extreme positions. On one side, organizations are portrayed as blindly letting data dictate every decision, and on the other, as if decisions are made in a vacuum without any numerical context. This debate largely centers around how data impacts the ideation process.
Since measurements and metrics are based on historical data, they are inherently inadequate when it comes to assessing new ideas, especially as those ideas diverge from past patterns.
While data can certainly play a valuable, qualifying role in ideation, no one can dispute the importance of metrics in providing clarity about how these ideas ultimately translate into actual business outcomes.
Metrics and analytics around it can do more than just capture performance —they can offer insights into the causal mechanisms of the business. By understanding how input metrics influence desired output metrics, organizations can use this knowledge to iterate on their strategy and tactics, pull the right levers, and drive desired performance.
In this context, the high value role of data and metrics in the ongoing operational feedback loop is unquestionable.
