Some serious big bets were made on a VERY thick and academic and experimentation-heavy approach to data in even small companies. Would love to have you on our podcast to discuss in more depth. Excellent piece. https://syncari.com/distributed-truth-podcast/
A culture of reviewing metrics weekly would probably also motivate stakeholders to take more ownership of the data generating processes, building value for the DE function overall. I really like this thinking.
This, to me, is why clear partnerships with stakeholders in the organization are key. It is presumptive to think that a data team can find the right answer and make the recommendation without really understanding how decisions are made without data the team is producing. Sure sometimes parts of the org might not want to hear results that confirm their existing biases. Though with good partnership, eventually they might trust and understand findings that don't sync with their prior assumptions. This journey is super rewarding, though can take a while and isn't guaranteed.
Yes that’s often forgotten but also hard to replicate in smaller orgs. Unless executives have the necessary self awareness of the difference in experience between them and the data team, they won’t be able to direct the analytics effort towards productive outcomes. The best analysis I’ve produced has been when the stakeholders fully clued me in on the context and their hypotheses before starting the analysis.
Great synopsis
Some serious big bets were made on a VERY thick and academic and experimentation-heavy approach to data in even small companies. Would love to have you on our podcast to discuss in more depth. Excellent piece. https://syncari.com/distributed-truth-podcast/
A culture of reviewing metrics weekly would probably also motivate stakeholders to take more ownership of the data generating processes, building value for the DE function overall. I really like this thinking.
Agreed. It incentivizes a lot of good things.
This, to me, is why clear partnerships with stakeholders in the organization are key. It is presumptive to think that a data team can find the right answer and make the recommendation without really understanding how decisions are made without data the team is producing. Sure sometimes parts of the org might not want to hear results that confirm their existing biases. Though with good partnership, eventually they might trust and understand findings that don't sync with their prior assumptions. This journey is super rewarding, though can take a while and isn't guaranteed.
Yes that’s often forgotten but also hard to replicate in smaller orgs. Unless executives have the necessary self awareness of the difference in experience between them and the data team, they won’t be able to direct the analytics effort towards productive outcomes. The best analysis I’ve produced has been when the stakeholders fully clued me in on the context and their hypotheses before starting the analysis.