My sheet:
+---------+-----------+---------+---------+-----------+
| product | value 1 | value 2 | value 3 | value 4 |
+---------+-----------+---------+---------+-----------+
| name 1 | 700,000 | 500 | 10,000 | 2,000,000 |
+---------+-----------+---------+---------+-----------+
| name 2 | 200,000 | 800 | 20,000 | ? |
+---------+-----------+---------+---------+-----------+
| name 3 | 100,000 | 150 | 6,000 | ? |
+---------+-----------+---------+---------+-----------+
| name 4 | 1,000,000 | 1,000 | 25,000 | ? |
+---------+-----------+---------+---------+-----------+
| name 5 | 2,000,000 | 1,500 | 30,000 | ? |
+---------+-----------+---------+---------+-----------+
| name 6 | 2,500,000 | 3,000 | 65,000 | ? |
+---------+-----------+---------+---------+-----------+
| name 7 | 300,000 | 300 | 12,000 | ? |
+---------+-----------+---------+---------+-----------+
| name 8 | 350,000 | 200 | 9,000 | ? |
+---------+-----------+---------+---------+-----------+
| name 9 | 900,000 | 1,200 | 28,000 | ? |
+---------+-----------+---------+---------+-----------+
| name 10 | 150,000 | 100 | 5,000 | ? |
+---------+-----------+---------+---------+-----------+
What I am attempting is to predict the empty columns based on the data that I do have. Maybe just one of the columns that contain data in every row or maybe I should be only focusing on one column that contains data in every row?
I have used FORECAST previously but had more data in the column that I was predicting values for which the lack of data I think is my root problem(?). Not sure if FORECAST is best for this so any recommendations for other functions are most welcome.
The last thing I can add though is that the known value in column E (value 4) is a confident number and ideally it's used in any formula that I end up with (although I am open to any other recommendations).
The formula I was using:
=FORECAST(D3,E2,$D$2:$D$11)
I don't think this is possible without more information. If you think about it, Value 4 can be a constant (always 2,000,000), be dependent on only one other value (say 200 times value 3), or be a complex formula (say add values 1, 2, and 3 with a constant). Each of these 3 models agree with the values for name 1, however they generate vastly different value 4 predictions.
In the case of name 2, the models would output the following for value 4: Constant: 2,000,000 Value 3: 8,000,000 Sum: 2,489,700
Each of those values could be valid without providing further constraints (either through data points or specifying the kind of model, but probably both).