Data, data, data. This has become the buzzword of the year. Everybody is talking about it, using the word, but most people don’t know how to drill it down to how it affects them or what it does for them or their products. For many people, data feels like an avalanche of information. And we know what information overload does to us, it weighs us down. So, the real question is, what should data do for me? The report I’m about to compile, how and what does it affect? Data is not just information for information sake. It is applied science, it is applying information gotten to cure the ailment that led you to it. Going beyond answering the question, what is data? The major thing is how to analyse the data you have so it brings more meaning and answer to your pressing demands and consequently moves you forward. Here are some guidelines on how to extract meaning from your data and data analysis.
Ask Yourself these Questions Before You Start Analysing
What am I looking for?
Am I going to find it in this report?
Will I understand the actions I need to take if I find the data?
Let These Questions Guide You
After asking the questions above, use them to extract and analyse the data to pull out what you need and filter out what you don’t need. The essence of getting data and data analysis is so that you have good ROI and you don’t end up shooting darts in the dark. So, drill down your massive ROIs into smaller chunks and then use the smaller ROIs to get the data that you need, which will in turn lead you to answers that’ll guide your decision making.
Define Your Metrics and Measurement
The most important thing apart from ROI is your metrics. Your metrics are pointers that you are hitting the mark or not. Analysing your data will help you tackle your biggest challenges and explore your biggest opportunities. So, make your you have your metrics and indications set right, run focused experiments and tackle things head on. You never know what will come out of data. As Ritika Puri of General Assembly says “Failures can lead to successes, successes can be failures, and data is in the eye of the beholder.”
Here is a video of Dan McKinley discussing how to make Data-driven decisions: