This overview outlines how we forecast a business with the 📝Integrated Financial Model (IFM): the business-model drivers it tracks, the instrumentation around it, and the forecasting philosophy behind it.
- Business Models
- DTC
- Web traffic, conversion rate, orders, (units per order) average order value, average margin
- Ad spend, CAC, % of customers who return each month, LTV
- Key metric that people forget about: Contribution Margin = (Gross Profit less ad spend) / revenue. DTC businesses should not believe that they can be unprofitable on their customers' first purchase; this is a mistake.
- Subscription Businesses
- Web traffic, conversion rate, new customers, lost customers, active customers
- 1 / monthly churn rate = average months of customer life
- Ad spend, CAC, LTV
- Full 📝Instrumentation Pyramid
- Integrated Financial Model (IFM)
- Revenue Recognition Tool
- Payroll Journal Entry Tool
- 📝Inventory Rollfoward
- Financial Reporting Tool
- Weekly Metrics: 📝Monday Morning Metrics (MMM)
- 13-Week Cash Forecast
- Sales Pipeline Forecast
- Weekly deal stage pipeline report
- Weekly Client Review
- Forecasting Philosophy
- Forecasting from the perspective of digital signal processing. Think about a business as a flow of information that is updated in real time, daily, weekly, monthly or annually.
- Except pre-revenue, always start with real data, displayed weekly or monthly, before forecasting. You can’t forecast from annual information. For big companies, quarterly information is really all you get, and this is not sufficient to do operational forecasting.
- The goal of a forecast is to use the least amount of information to forecast the business most accurately.
- 📝Level 1 Metrics: the minimum metrics required to forecast business results reasonably accurately.
- Level 2 Metrics: additional metrics required to oversee a department.
- We update the IFM monthly at a minimum. This is a key step. Where our forecasts are way off, we need to “double click” on the organization to get more information to improve the accuracy of the forecast in the next period.
- Sampling Frequency