My initial observations follow.
The available data points are stated to include (my notes in parentheses):
- Activities (This is activity codes for billing, not items from the “Activity” tab of SB Desktop).
- Contacts
- Expenses
- Fees
- Invoices
- Matters
- Matter Types
- Payments
- Roles (This is Staff assigned to matters)
- Staff
- Transactions
Left out then are:
- Tasks
- Activity items (from Activity tab - this could be useful in monitoring or evaluating employee performance)
- Calendar / Events
- Communicates (not sure why these would matter)
- Matter Files (not sure why these would matter)
It is unclear from my initial review how exactly fees/expenses, invoices, and payments work together to attribute income to fee earners. This is necessary for useful financial reporting. Perhaps @Sara Sultan can shed some insight on how the fields and calculations in the related tables are used to attribute payments to fee earners.
Hi @JKibler!
Have you had a play around with the available Smokeball data in Power BI already? We can get you set up with access, if not.
We have exposed some of the data that is currently available in our Billing reports in Power BI. You can join data from the Fees/Expenses tables to the Staff tables and this will help you to create dashboards. It is probably easiest to have a play around and see what you can create in the first instance, and then we can always expose further data points as needed in the future.
Alternatively, I have a partner in Australia that is working with a couple of our Australian firms to build reports in Power BI that I could connect you with, if you wanted to speak to experts in Power BI dashboard building.
Cheers,
Emma
This integration has so much potential. Some thoughts after playing around with it for a few minutes.
First, for contingency fee cases, there is no way to track our revenue within Power BI or Smokeball. We should be able to find a way to get reports on settlements to include settlements, date fees expected, and date settled. This is a problem with Smokeball generally that carries through to this integration.
In addition, the power BI integration does not format the dates in a way that Power Bi recognizes as a date and the fee total is missing the decimal so all fees are inflated by two decimal places. As a result we had to manipulate the data in order to get meaningful visualizations. Dates for fees came in as 20220108 which was not recognized as a date, so you cannot visualize say a month of fees. The total fees column showed 250 dollars as 25000, which obviously caused data issues. we had to run a formula to manually correct the decimal and dump the data in a new column.