Zoom in and the issue is forecasting new unit sales.
In the example, this line does a lot of the work in the model: "Forecasting New Subscriptions (line 10). We've just entered hardcodes here for simplicity, but these could be the result of calculations related to a marketing / sales funnel"
I submit that this single assumption will carry more weight than the rest of the model, and is the most difficult to forecast.
Broadly speaking you should have a MQL -> SQL -> Deal model (i.e assumptions for ratios between the three) and assumptions for CPL and SQL per SDR/AE.
With these you can tie sales forecasts to marketing spend and sales hires.
Obviously these won't be perfect, but when you're off target you can see why (i.e which assumption was false) and then either try to fix it or correct the false assumption giving you a more accurate model going forward.
Yes, that is the unknown variable. However, your costs can be steered pretty accurately in software startups through hiring and firing. This means you can easily track whether your sales are still hitting the targets you expected, and if not, how much reduction you can accept into on the costs side before you need to look into getting additional capital investments.
Edit: For existing businesses this metric is much more predictable by the way, but especially in B2B it might be obfuscated because the finance department does not know how much value has been provided for which there was not an invoice created for it yet.
Indeed, but when your sales don't meet expectations in month one the model gives you a very strong clue as to what to cut or defer in future months. The model is not the business, it is something to measure the business against.
Comments
The issue is forecasting revenues.
Zoom in and the issue is forecasting unit sales.
Zoom in and the issue is forecasting new unit sales.
In the example, this line does a lot of the work in the model: "Forecasting New Subscriptions (line 10). We've just entered hardcodes here for simplicity, but these could be the result of calculations related to a marketing / sales funnel"
I submit that this single assumption will carry more weight than the rest of the model, and is the most difficult to forecast.
Broadly speaking you should have a MQL -> SQL -> Deal model (i.e assumptions for ratios between the three) and assumptions for CPL and SQL per SDR/AE.
With these you can tie sales forecasts to marketing spend and sales hires.
Obviously these won't be perfect, but when you're off target you can see why (i.e which assumption was false) and then either try to fix it or correct the false assumption giving you a more accurate model going forward.
Yes, that is the unknown variable. However, your costs can be steered pretty accurately in software startups through hiring and firing. This means you can easily track whether your sales are still hitting the targets you expected, and if not, how much reduction you can accept into on the costs side before you need to look into getting additional capital investments.
Edit: For existing businesses this metric is much more predictable by the way, but especially in B2B it might be obfuscated because the finance department does not know how much value has been provided for which there was not an invoice created for it yet.
Indeed, but when your sales don't meet expectations in month one the model gives you a very strong clue as to what to cut or defer in future months. The model is not the business, it is something to measure the business against.
Won't argue with that, but it's nice to be able to put bounds on the result by using best- and worst-case guesses here.