What to do with weekly exported data reports

We'll skip the daily data analysis because there's very little to see in terms of "days".

It is enough to focus on the completion of the "goal" on a daily basis, without having to take care of all activities.

After a week, we need to look at all the time spent from a whole-event perspective and get it right. Clicking on campaign details one by one in TimeTrack works, but is too cumbersome, so we chose to export the data to Excel and analyze it.

I'm used to sharing data to QQ My Computer, here's a tip, if you also share to QQ, then it's recommended to set "My Computer" to the top to avoid posting errors.

After getting this data table, we find that the data of the export cycle is divided into two areas, the first area is "Detailed Data", which contains the data name, start time, end time, duration, notes and labels.

The second area is the ratio data, which shows only the activity type, duration and ratio, in descending order by default.

The first step in data analysis is for us to be clear about what the baseline is?

The baseline is the proportion of time we allocate to our different activities in the section "Polishing your categories and fixing in 1 month", break it down into weeks and you get a baseline of consumption for each activity week as shown below.

Then we compare the baseline to your actual data for the week and see which activities are overtime, which are not enough and which are flat?

Naked eye comparison is not impossible, but Excel is still more convenient to match comparison directly with the vlookup function.

Paste the baseline data into the next column, use the function to extract the duration of each category, and if it's not formatted correctly, brush it with the format:

Filtered, descending order is shown in Fig:

If you still find it inconvenient to see, you can set the conditional format or use the if function to highlight it.

I'm used to making a source table that stores data once a week and can customize the periodical analysis, as shown in the figure:

The benefit of this is that pivot tables can be created that not only compare baseline values, but also see time trends for each type.

Drag the activity category and detail to "row", drag "year" and "week" to the column, drag the duration to "value", select the sum, set the time format, then select the nearly 7 weeks (according to their own preferences) data, and finally add the 0th week, which is the base value, to get this table:

Select the data area, in descending order, and you'll see the time movement of all the data.

We need to identify the "outliers" for each category, the activities that deviate disproportionately from our baseline, and ask ourselves why this is happening. Write them down after you find the answers, stick to them for a long time, and these are your behavioral records.

If, for example, I go through the May Day holiday, and when I go through May Day time, I find that during the holiday, my recreational time goes up significantly and my writing time goes down significantly, then this would suggest (corroboration #1) that I don't invest much time in studying during the holiday.

This actual behaviour creates a gap with our expectations, as we often assume that "I will study well for the next holiday", thus giving ourselves a lot of to-do list. The reality is, however, that it's embarrassing to not get it done at all.

That's the beauty of an honest record, helping you find your baseline.