This is part two of a two-part post. Last week I talked about the importance of building a cash flow forecast. This week, I want to spend some time talking about two common mistakes I see in financial projections and how to improve them.
Mistake: Building from the Top Down
Starting with an assumption on growth (i.e. we’re going to grow 25% per month; or we’re going to grow 250% annually) and somehow backfilling expenses that support that growth assumption.
Why it’s a mistake:
This approach takes growth as a given and totally misses the point of what it’s going to take to drive that growth. It shouldn’t come as too much of a shock, but growing 250% year-over-year is really hard and it’s going to take a plan and probably a lot of cash.
Confession: this approach may work when you’re first getting started. After all, growing fast is easier when you’re starting from nothing. It’s much easier to go from $1K to $10K in revenue than from $1M to $10M. So, you might be able to take growth as a given. But, at some point you’re going to have to understand how to drive growth, so why not start now?
How to do it better:
Build your forecast from the bottom up. This is a subtle point and admittedly takes a lot of work, but puts you in a better position to understand your business (and makes you look better to investors).
When I say build from the bottom up I mean really think about what it’s going to take to drive growth:
- If you’re doing direct sales to large customers, come up with reasonable assumptions on how you’re generating leads and what that costs, conversion percentages, contract values, and how many deals one salesperson can close in a given time period. This will help you understand what resources you’ll need to generate a given amount of revenue.
- If you’re focused more on inbound lead generation and onboarding a high volume of small customers, understand what drives traffic to your site (AdWords, blog posts, visiting trade shows, etc.) and collect data/assumptions on how many visitors you get per (article, blog post, etc.), how many of those convert to free trials, how many free trials convert to paid customers, etc. Then you have an estimate of what activities you need to do to drive a given amount of revenue.
Now, it’s important to note that these assumptions will probably be wild guesses when you first start out and will become more concrete over time. They’ll be dynamic and need to be updated over time which brings me to my next point…
Mistake: Hard Coding Assumptions
Hard coding key assumptions into a model in the cells that reference them. (i.e. entering the assumptions directly into the cells and formulas where they’re used and nobody but you understands where they came from)
Why it’s a mistake:
There are a couple of problems here.
- Hard coding your assumptions is not user friendly. Inevitably, some of your key assumptions are going to change. When all of your assumptions are hidden within the model itself it’s easy to forget what cells need to be updated when things change. Then you’re left with a model that’s no longer based on reality. That’s a problem.
- When you give your model to investors, they’re going to want to understand your assumptions and play around with different scenarios. In fact, your assumptions are more important than the output of your model. Investors want to know that you understand what it’s going to take to scale your business (which takes us back to the previous point on “bottom-up” forecasting). If all of your assumptions are hidden — your investors can’t do either of those things. Needless to say, when you’re asking someone for money it’s not a great idea to make things more difficult for them.
How to do it better:
Lay out all of your assumptions in a separate tab. Any time those assumptions are used in the model, reference the cell in your “assumptions” tab. Now you only have to change one cell when you update your assumptions.
It’s also helpful to document how you came up with your assumptions. As I mentioned earlier, when you’re first starting out your assumptions are probably going to be wild guesses. But, at least they can be wild guesses tied to some kind of rationale (industry benchmarks, passed experience, analyst reports, etc.)
Note: I recently published an eBook on financial modeling called The Founder’s Guide to Financial Modeling. It provides a step-by-step guide to building a financial model and includes a sample Excel model to illustrate concepts.