CFO Dashboards

Hi Team.

This content is aimed at reporting for CFOs, key stakeholders and decision-makers. 

The aim of a CFO Dashboard is to provide a clear single location where senior stakeholders can pull critical business levers (assumptions) and instantly assess the impact (presentation outputs). Within a larger, more expansive planning model, senior staff are unlikely to have the time / desire to scroll through tabs looking for assumptions and then their impacts. A CFO Dashboard is the perfect solution.

The above is taken from the attached file and shows a number of key areas:

1. sensitivity assumptions, with checks (top left);
2. tabular, numerical summary data (left and middle top); and
3. graphical all periods charts.

The benefit of such dashboards is that they facilitate a really clean segregation of activity within the same model. The wider Finance team can manage the detailed aspects of the model (core data, historicals, detailed forecast, etc.) in order to work up the core business plan. And the CFO has a single location in which they can not only review the key aspects of this latest business plan but understand the risks and variability in the business, i.e. what impact does a 5% drop in volume mean for NPAT, how does my equity value change for each 1% increase in salaries, and so on.

I'll put together a video on this at some point but the broad development sequence is as follows. I've included broad structural comments but will obviously leave then end design completely up to you!

1. Insert a new module with two components - All Periods Output (hold the data / typically lowest time period granularity) and Blank Presentation;
2. Schedule out all of the key sensitivity assumptions - I typically do this along the left-hand side and make them a column of assumptions - you will need to add links out to each and have one link out (row) per sensitivity, which I find gives more control when change requests come through (a single row of assumptions means only a single link out, which is easier in the first instance but becomes much more complicated to maintain and update);
3. Create the links out for each sensitivity and link this into the relevant modules and update the logic - this is the most time-consuming part of the process;
4. Add sensitivity checks to each assumption or across all assumptions depending on preference;
5. Bring in the financial statement data into the All Periods Output component - this can be done really quickly by temporarily inserting the Financial Statement Export module and then copying all of the rows of data from this module into the All Periods Output component of our CFO dashboard module (then delete the export module when done) - I tend to leave all the data in just in case someone asks for a ratio or other data point;
6. Build out the tables and graphs as you see fit...

Testing for these types of dashboards is pretty self-evident, so for each sensitivity assumption, enter a value and check the impact across the financials. In a rolling historical-forecast model, the sensitivities shouldn't be impacting the historical data.

If you're not across Category Charts yet, then check them out: https://www.modano.com/resources/user_guide/automation/developing_modules/categories_charts

And if you haven't used the Size Chart to Range tool yet then this is a must! https://www.modano.com/resources/user_guide/tools/charting

One other thing to consider is whether to fix the chart axis, rather than leaving their scale floating. Having a fixed axis scale has the advantage that the impact of the sensitivities is clearer - a change of scale can obscure the quantum / direction of sensitivities. However, fixing a scale can have the impact of making the charts less dynamic, with profiles moving out of the scale of the chart. If I make chart axes fixed then I usually give the fixed scale point a little more allowance.

Would love to see any results or ideas people have, so feel free to load up examples or images.

And if you're after some crazy inspiration then check out David McCandless' book Information is Beautiful: https://informationisbeautiful.net/ 

Cheers. J.