No clue,That's because you're not asking the right questions.
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In the time data analysis methodology, "get the data, process the data, visualize, make a guess, verify" in these five steps, the most "useful" should be to make a guess and verify, because only action, time data has played its due value.
But before you act, you need to know where the problem is. There's feedback from trainees, a bunch of data saved up, and no idea where to start with the analysis. In fact, ask the right questions and you'll find the answers, so try these classic ways of asking questions.
For example, the most classic "5W2H model".
(1) What - what? What's the purpose? Do what work?
(2) WHY - Why do it? Can we not do it? Is there an alternative?
(3) WHO - Who? Who will do it?
(4) WHEN - When? What time to do it? What's the best time?
(5) WHERE - Where? Where to do it?
(6) HOW - How? How to improve efficiency? How is it implemented? What is the method?
(7) HOW MUCH - How much? To what extent? What are the numbers? What is the level of quality? What are the cost outputs?
This is the way to ask the question, and then the angle of the cut, which can be divided into three segments: peak, fluctuation, and anomaly.
First the peaks, start with the big picture.
Of all your categories, which is the most time-consuming activity item?
I sifted through the data for 2019 to date, in descending order of time, as follows:
"Sleep" takes the first place, but sleep has a single component, which is sleep, and we leave it for now and go to "work", which comes second.
The time-consuming peak of "work" is identified, and then we analyse its "fluctuations".
In chronological terms.
1) Monthly
Detail screening retains only "work", "rows" are placed in months, work is dragged to "columns", and the duration is maintained by summing to "values".
Insert folded line perspective view.
Among the questions we can ask about this chart are.
Why is January the lowest? (WHY)
Why is March the highest? (WHY)
What happens from January to March? (what)
Will the "work" fluctuate in the later months of the year?
2) Weekdays & Weekends
Insert a column in the monthly statement, use the WEEKDAY formula, take the week value of the start time, and get Sunday, October 9, 2016 (7).
Refresh the monthly pivot chart, drag "Day" to "Row" and insert the histogram.
Questions on the chart.
Which weekday do I put the most effort into? (what)
With less time to work on the weekends, is the extra time spent studying or having fun? (where)
What can I do if I want to increase my weekend work time commitment? (how)
Will the level of time commitment at work now support a 20% increase in my annual salary? (how much)
3) hours
Insert a column in the monthly report and use the HOUR formula to take the hourly value of the start time to get an hourly integer.
Refresh the monthly pivot chart, drag "Hours" to "Rows" and insert the histogram:
Questions on the chart.
Who do I spend more of my time on during the 9-18 period at work? (who)
What is the reason for the low time commitment of these hours on 10/11/14 and how can it be improved? (how)
In the above example, the fluctuations are mostly in terms of time, ask how the ups and downs in the line graph appear? And the anomaly is comparing existing data to past historical data or others, what's the difference?
Only by asking the right questions can you act on them.
The 5W2H model mentioned in this article and the questioning of the three-part formula, I hope you can use the combination flexibly.
In the next chapter, I will use examples to show what we can analyze when we have time data.
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