Altering Forecasts

[Mattyn]

Hello all,

I have a simple problem I can't seem to solve.

I forecast income at monthly intervals for financial years. Income changes based on rent cost and occupancy levels.

My table includes Total Units, Units Let, % Units occupied. Total available income per month, actual income per month, % income per month (repeated for annual).

1. Is there a way to connect occupancy levels with income? Based on total available income per month. Essentially like a 'What If'?

2. Can I make adjustments for future rent amounts? For example rent goes up in November, so without the forecast adapting for that, the rest of the information for the financial year isn't useful at face value unless transformed.

There is a caveat that all Units are not the same cost, however this should still give a good ballpark number.

[lbendlin]

Please provide sample data (with sensitive information removed) that covers your issue or question completely, in a usable format (not as a screenshot). Leave out anything not related to the issue.
https://community.fabric.microsoft.com/t5/Community-Blog/How-to-provide-sample-data-in-the-Power-BI-...
Please show the expected outcome based on the sample data you provided.

https://community.fabric.microsoft.com/t5/Desktop/How-to-Get-Your-Question-Answered-Quickly/m-p/1447...

[Mattyn]

Apologies for the delayed response, long weekend.

Please see attached for trimmed down, relevant dataset with sensitive information removed / altered accordingly.

The desired outcome is to be able to influence the forecast further. For example currently I only seem to be able to base a monthly income pcm forecast on just that column. Whereas that is influenced by pct units occupied, total available income, etc. So for example I am aware of tenants terminating or joining ahead of time, or rent going up in future.. as well as due to market forces there are times I would expect a drop in occupancy... I'd like the forecast to be able to take these things into account.

Database 

[lbendlin]

The data isn't statistically significant enough but here's what the Key Influencers visual came up with.

see attached