A Culture of Partnership During my time leading an analytics and data science team, I spent a lot of time thinking about how an ideal analytics team should operate – how the team should work together, how the team should prioritize their work, and how the team can most effectively partner with the broader organization to generate business value. I believe that for an analytics team to be effective, the team must develop a strong culture of partnership in order to actually drive business value.

The first data hires at an early stage startup face numerous challenges — an infrastructure built to run the business but not analyze it, an organization hungry for information without a process for requesting and prioritizing it, and little documentation on how anything is done. What should they do first?

Everyone has their own reaction when discovering wrong data. It might start with a double take or maybe an itching feeling that the number should be a higher. However it starts, it usually leads to an investigation to discover what went wrong. While this is a very normal reaction, I offer an alternative. Before turning over every stone in your ETL, ask a few questions to discover if your “wrong” data really is wrong. In this post I explore what wrong means when it comes to data (spoiler alert: it is not black and white). I also offer a few tricks to diagnose which of the buckets of wrong your problem falls into. Yes, this approach may add an extra step or two in your process, but it can also save a day of work trying to fix something that isn’t even broken.

Poor communication within an Analytics team and between that team and the rest of the company, leaves highly skilled Analysts solving the wrong questions, lacking support for big ideas and and ultimately departing the company unfulfilled by their work. In this post I will discuss ways a team can improve performance and employee satisfaction by focusing on constructive conversations.