Someone asked before: “How to cultivate data sensitivity?”
The questioner’s background is that he does not often use egypt phone number library data and does not know where to start developing sensitivity to data. He wants to know, how can someone like him who has no data-related background at all start to develop sensitivity to data?
If you have the same trouble, let me tell you a good news: data sensitivity has nothing to do with your math level. It purely comes from your level of understanding of the indicator. As long as you have a basic understanding of the mean, median, and common comparison methods of indicators, you can develop your own data sensitivity in the long run.
Then, there’s no bad news, so let’s get straight to it!
What is data sensitivity?
To put data sensitivity in a simpler way, it actually refers to the ability to discover problems . To give a simple example, when I was working out, I would often go to the vegetable market to buy ingredients, so I would have a vague idea that half a pound of chicken breast is about x yuan. When I went to another stall to buy stay accessible anytime, anywhere it and found that it was higher than x yuan, I would know that I might have overpaid. Or if I went to buy it again the next week and found that it was lower than x yuan, I would feel that it had become cheaper.
But I haven’t worked out for a very long time now, so if I go to the market to buy chicken breast and am charged a very high price for it , I won’t know, because I haven’t observed the price of chicken breast for a long time, and I have no sense of this number anymore.
The same situation applies to the workplace. When an indicator appears, are you aware of the number ? Can you see that there is something wrong with the numbers? Being able to identify anomalies and ask questions is a sign of data sensitivity.
What does data sensitivity mean?
From the examples mentioned above, we can understand that data sensitivity basically includes the following three points:
1. Know if the data makes sense
When you see a number, can you spot at a glance switzerland leads that it’s irrational? There are many reasons for unreasonableness. The most basic one is that there is a problem with the data source, or there is an error in marketing execution, or even an irrelevant data is placed in the report. When these numbers appear, if you can sense whether they are reasonable, it is the first step to having data sensitivity.
2. Understand the business formula/meaning behind the data
This is actually the core of data sensitivity. How to cultivate data the ability to discover problems, and whether you can discover problems depends on whether you know what the number means and whether you have the ability to interpret it. For example, in terms of revenue, within a company it may represent number of users x conversion rate x average order value, so you will also look to see if there is any problem with these three numbers.
But if you don’t have this understanding of revenue, then you will only be stuck at the state of what to do if revenue decreases.
