My job is to gather, study, and understand data and its implications, and then make recommendations to help the business improve – in short, to deliver business value from data.
One of the things you learn when you work in analytics is that there’s an endless depth to virtually any problem – you can keep digging deeper and deeper forever. One of the most valuable skills you can learn is deciphering what’s needed to solve the real problem – when has the bulk of the business value been delivered, and when are you doing things that are just intellectual interesting but not actually valuable?
I’ve found that I end up performing analyses in one of four different levels of detail:
- The quick ‘n dirty: These are short and simple – for example, a designer wants to know what the distribution of the number of posts on a project is because they’re designing a new screen, or David or Jason wants to know how our support ticket response time is trending. These are some mix of data retrieval and analysis, but the results don’t need a lot of explanation or interpretation. Most of the time, the results are communicated via IM or Campfire, and I end up spending between 30 seconds and 30 minutes.
- The basic look: The most common analysis I do is a moderate depth one – something like a look at conversion rates and retention by traffic source, or a basic overview of how people are using a specific feature in the new Basecamp compared to how they used a similar feature in Basecamp Classic. The results here are more involved and need some interpretation or “color commentary”, and may come with specific recommendations. This sort of analysis gets written up in a post on one of our Basecamp projects, and usually takes somewhere between a couple hours and a day.
- The deep dive: When it comes to understanding root causes and developing significant recommendations, a more in depth analysis is called for. For things like understanding the root causes of cancellation or support cases, the bulk of the work tends to be on analysis, interpretation, and then actionable recommendations to address those causes. Frequently, there’s some instrumentation or reporting project that spins off from this as well – I may add a report to our dashboard on the topic so we can more easily track it over time. These analyses usually get written up in a longer document with significantly more detail, and sometimes come with a live or recorded video explanation and discussion as well. This sort of analysis usually takes between 1 and 3 weeks.
- The boiled ocean: If you want to understand a substantive issue from every single possible angle, try every statistical technique in the book, and write a report with every possible visualization, then you’re probably looking at investing multiple months in a problem. We haven’t done anything like this in the 18 months I’ve been here at 37signals, and that’s by design: in most cases, this type of analysis ends up providing essentially the same business value as a deep dive that takes a fraction of the time.
Next time you’re faced with an analytical problem, ask yourself what the real underlying problem you’re trying to solve is, and figure out what depth of analysis is the required to deliver the bulk of the business value; after all, your job is probably really about improving the business.