I have a dataset, which is recorded monthly. Another is recorded per 8 day. The problem asks me to forecast the first one with the second one in the model. i.e, the monthly production of apples and overall precipitation per week. How to use precipitation to forecast apple's production?
Another follow-up questions is that if we have a new daily recorded datasets. How to link them together? For example, the monthly production of apples, weekly precipitation and daily temperature.
Related
In short, how do i calculate yearly unit production cost based on fixed cost divided by amount produced?
I am making dashboard in power BI for a video production studio company. They have a fixed cost per month and year based on the salary of the employees, production equipment etc. Lets say that the monthly fixed cost is $20 000. As tables show below i have a column called videos recorded, which i need to tie to the month, and then divided on the fixed cost which will be cost per video on a given month and in summary production cost per video in year 2022. So i want to visualize on a card or table, for July fixed cost were $20.000, we made 30 videos which is $667 per video.
Tables below
I have a dataset in excel which shows headcount by employee level and which department each employee would fall under (sales, ops, or support). I would like to send a survey to each employee once every 26 weeks (2 times a year), but I would also like to keep sending surveys every week to ensure continuation of surveys to a certain amount of population split between sales, ops, and support departments based on their weight of the total population.
This way, I am sending surveys every week to a tiny bit of my overall headcount but only repeating people every 26 weeks.
Can anyone please help on how to solve this in excel with a formula?
From attached sample data, how can I split the headcount to send surverys for 26 weeks straight but to different population every week and not repeat? This different population should be split by % of department out of total headcount. Meaning if I have 10 people every week and % split is 40% sales, 30% operations, and 20% support, the survey should be sent to 4 sales, 3 operations, and 2 support people. Please note that the 10 people and the %s may vary every week because of new hires and resignations.
Thank you!
Sample Data
In the data sheet, ceate a helper column D, where you hand out the numbers to each employee, label it MOD. Use the formula for each employee, enter to cell D2:
=MOD(ROWS(A$2:A2)-1;$H$2)+1
That way each employee is assign a number from 1 to whatever is in the cell H2, e.g. 26. Then contact list all employees with 1 and you have the first batch and so you continue each week to get to employees with 26 in 26 weeks. This way all get the survey but just once.
Of course the share of the individual depts cannot be achieved each time, as there are less employees in some. If you wanted to keeps the shares, some employees of the smaller departments would get the survey more times.
If you want to get some randomness into the order, just mix the order of MOD numbers, e.g. start with 7, continue with 23 etc.
I hope I got the question right, I am not sure in some parts.
I'm currently looking at daily sales data of a specific brand over the course of the past year. My objective is to create a formula to roughly estimate the sales growth for future months.
My project isn't going very well, as the brand is very volatile in monthly sales, making it impossible to predict with a basic linear formula. I'm arriving at the conclusion that a single year's worth of sales isn't enough data, and I may have to result to provide a specific formula depending on the month. Is there anything I haven't thought of?
Note: Recording of sales start on the 15th of every month
Your sales are showing seasonality. Consider using sasonal ARIMA models.
Below is the brand preference metric data for two overlapped time periods (Week 1-3 and Week 2-4 data). I wanted do a significance test between these two overlapped groups, please provide me the details of the method and formula’s to use. We are doing these activities in excel format.
Here is the my data :
Roll Up Week 1-3 Roll Up Week 2-4
Count 697 706
Brand Preference 43% 40%
Thanks,
Tanuvi
am struggling with the application of goal seek function in excel. Am forecasting production for an oil well however we have a target cumulative production expected after say 20 years of production. I have produced table columns of monthly production rate and cumulative production. I would like to play (create sensitivity scenarios) with my expected cumulative production.
Can i use goal seek to change the production forecast profile per month by just changing the cumulative production at the end.
Also advise alternative functions should goal seek not be the right function for this task.
Appreciate your support
This is really just an example of what #DanK has already mentioned. Say ColumnB figures are actual production (in black) and estimates (in blue). The estimates in this case computed as number of days in the month times the factor in D1 ("daily production"). To ramp up production so that the total cumulative production (in the example below, for 1-1/2 years, rather than all 20 as in the example above), presently estimated to be 115,620 units is instead 150,000 then Goal Seek might be applied so:
whereupon the D1 value (200) should change to 287 (and the total in B19 to 150,000, and all the blue values change also). The principle should work if, say, June 2015 were calculated as 16*D1 rather than 30*D1 to allow for planned suspension of production. If that fortnight were an intervention to add production from another reservoir anticipated to be 100 per day then Goal Seek would not adjust "100 per day" but would adjust a new daily rate of 1.5*D1.