Doing competitive analysis is never easy. Some information is just hard to find. And when find information, it’s tempting to dive straight into our analysis. But how do we manage the incompleteness of our information? Data Robot!
I have researched the competition many times. I find some great information (annual reports, consultancy reports, SEC filings or some other trove of information) and start to dive deep into it to gain as much insight as I can.
But now I take a step back.
Rather than look at the information I have available, I ask myself a question before I do anything. I imagine that there is a Data Robot. Whatever data I ask Data Robot for, he will give me. (actually I’m not sure if its a “he” or a “she” and I’m not sure that’s an appropriate question to ask). I can have whatever data I want. I just have to ask.
The thing is, I don’t have a Data Robot. So in real life, I just get a sheet of blank paper and write down what I would ask Data Robot.
This has a number of benefits:
- I don’t get trapped in the fallacy of available information. I don’t just study the data I have just because I have it. Rather, I make a list of what I want and then see if I can get it.
- I think about a hierarchy of what is the most important data and rank the data (whether available or not) in terms of most important. This gives me an ordering that is important.
- For missing data, knowing what we don’t know is a good start. If data powers decisions, then missing data means a missing dimension to some decisions. Let’s at least be aware of that.
- I get a sense of ‘completeness’ as I collect the data. Once I have what’s on my list (or I know I can’t get parts) then I know I am done with data collection and analysis can start.
- Conversations improve. I know some data isn’t there. We can talk and decide based on that.
Anyway, I don’t have a Data Robot. But I pretend like I do. Anyone out there want to build one for me?