Here is a dataset showing Project wise forecast of open opportunities.
- Topic is the Project Name
- Est. Close Date is the date by when the opportunity would be closed i.e. the project would be won from that Client
- Duration is the time (in months) for which the project would run
- Amount is the total amount that would be billed for that project
Clients are invoiced annually only. So in the example below:
- Project ABC is for US$1 million with a duration of 24 months and is expected to be closed in Oct. 2017. We need to model the data to show the billing every 12 months. So for ABC US$500K would be billed in Oct-2017 and another US$500K in Oct-2018.
- Project GEF is for US$2 million with a duration of 18 months and is expected to be closed in Feb. 2018. We need to model the data to show US$1.3 million in Feb-2018 and another US$666K in Feb-2019. The monthly billing is US$2 million divided by 18 and then multiplied by 12 - this amounts to US$1.3 million.
| Topic | Est. Close Date | Duration (Months) | Amount |
| ABC | 01-10-2017 | 24 | 1,000,000 |
| GEF | 01-02-2018 | 18 | 2,000,000 |
| XYZ | 01-03-2018 | 30 | 1,000,000 |
The expected result should look like this:
| Row Labels | Oct-17 | Feb-18 | Mar-18 | Oct-18 | Feb-19 | Mar-19 | Mar-20 | Total |
| ABC | 500,000 | 500,000 | 1,000,000 | |||||
| GEF | 1,333,333 | 666,667 | 2,000,000 | |||||
| XYZ | 400,000 | 400,000 | 200,000 | 1,000,000 | ||||
| Grand Total | 500,000 | 1,333,333 | 400,000 | 500,000 | 666,667 | 400,000 | 200,000 | 4,000,000 |
I have solved this problem using Power Query and PowerPivot. You may download my solution workbook from here.