Sales Driven Financial Model for Start-Ups . Part 1: Ramp Up & Attrition

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While many companies recognize the importance of tracking metrics like MRR/ARR, Churn, and Growth, some crucial factors often go unnoticed in the process.

One area that is frequently neglected is how companies incorporate Attrition and Ramp Up when forecasting their revenue. This is either completely disregarded or done with numerous mistakes or overly complex Excel formulas. You can read about the importance of these factors in my previous blog “Avoid these mistakes in your start-ups financial model”.

This is the first part of a series of blogs where I build a the “SaaS Growth Capacity Model” a SaaS financial model that is actually useful, rather than a simple amalgamation of repeating Excel formulas. With this model, you will be able to accurately answer the question: how much capacity for growth does my start-up have?

You can download the template here.

What are the goals of this model?

The main objective of this model is to create a practical and effective forecasting tool. By incorporating attrition and ramp up periods, we can accurately project how a hiring plan will contribute to the company’s growth. Without this understanding, it becomes challenging to forecast how investments in sales will drive company expansion. And without a convincing growth forecast, securing investment capital can be an uphill battle.

Having downloaded numerous “SaaS Excel Templates,” it’s evident that most of them fail to account either ramp up and attrition, let alone both. These templates also tend to have other shortcomings and lack depth, which we will address and rectify in this series.

In this initial installment, we will focus on building a revenue model for your SaaS company. This model will incorporate essential factors such as new revenue, churn, upsells, downgrades, ramp up, and attrition. Although the initial model will primarily focus on revenue generation, we will expand on this foundation in future installments to include cost modeling, cohort analysis, and other valuable insights. Our aim is to construct the ultimate SaaS financial model and present all the information in a comprehensive dashboard.

Sheet 1: The Assumptions

The assumption sheet will serve as the primary area where we manipulate our numbers to ensure the functionality of our financial model. As the project progresses, we will expand upon this sheet. A significant aspect is the division of sales metrics into three categories, basic, advanced and pro, representing the diverse range of product plans offered by the company. Additionally, we have included a “Blended” category to encompass salespeople in early-stage start-ups who sell multiple products.

Most categories are explained in column i. However, the most important to understand are:

• Attrition Yearly: Calculated as the number of sales people that leave your company/sales team every year over the total amount of people that stay at the company (typically ranging from 50% to 20% as a rule of thumb).
• MRR Quota: Monthly sales quota multiplied by the average monthly revenue per account.
• Quota Achievement: Historical quota achievement level (usually below 100%).
• Churn: Calculated as 1 divided by the average customer lifetime (generally around 5% to 10% for early-stage and lower for later stages).
• Full Ramp Up Months: Represents the time it takes for a newly onboarded salesperson to reach their full potential in sales quota.

With these assumptions in mind, we can proceed to the next sheet, where we will forecast the lifetime performance of each salesperson category at the company and estimate the amount of new MRR one of them is expected to generate each month.

Sheet 2: Salesperson Lifetime

In this worksheet, we expand on the previously made assumptions for each salesperson over a period of 3 years (36 periods). The calculations are relatively straightforward if followed from top to bottom. Additionally, explanatory boxes are included in each sheet to provide further clarification. However, certain derived factors such as “Expected Yield”, “Monthly Closed MRR”, “Attrition”, “Months to Fully Ramp Up”, “MRR Attributable to AE Cumulative”, and “Churn” are particularly important in this model.

Expected yield represents the anticipated performance of a fully ramped-up salesperson, taking into account the quota achievement input. On the other hand, Monthly Closed MRR indicates the amount of new MRR that a salesperson will bring into the company during a given period, considering their level of ramp-up, upsells, downgrades, and attrition.

Attrition is applied similarly to depreciation. Every 12 months, attrition depreciation is applied, causing the Monthly Closed MRR to decrease by the cumulative attrition factor. This is a critical aspect of the model as it reflects the fact that a salesperson hired today is unlikely to generate new revenue for the company in (e.g.) five years, as they will have likely left. Therefore, the model accounts for this by factoring in the hiring of new salespeople.

Months to Fully Ramp Up represents another significant implication of this model. A new salesperson does not immediately achieve their full potential. In fact, it may take up to one year for some salespeople to reach their highest performance level. Hence, the capacity of the sales team is taken into consideration, indicating at what stage of ramp-up the salesperson is. This impacts Monthly Closed MRR, as it influences the forecasted amount of revenue the salesperson will effectively bring into the company each month.

MRR Attributable to AE Cumulative addresses another common issue with financial models. They often blend “New MRR” and “Cumulative MRR” together. In some cases, a sheet lists the MRR of each salesperson per month and simply adds them together to derive “Total MRR.” However, it is crucial to distinguish between the MRR closed in a particular month and the total MRR brought in by a salesperson. A salesperson closes new deals every month, but the deals closed in past months do not disappear, as they contribute to the monthly recurring revenue. Therefore, the company’s MRR is not the sum of the MRR closed by the sales team each month (Total New MRR), but rather the sum of all MRR (considering churn and net upsells) over time (Total Cumulative MRR).

Finally, Churn is applied similarly to attrition, acting as a depreciation factor triggered every 12 months. However, differently to attrition, Churn is only applied to the Cumulative MRR, not the Monthly Closed MRR.

Sheet 3: The Capacity Planning Model

The capacity planning model sheet consists of three parts: a blue section, a black section, and a green section, with the green section being more technical in nature but necessary for the functionality of the worksheet.

There are four blue blocks and four green blocks, two for each product plan (basic, advanced, pro, and blended). Each block represents four account executives/salespeople with a variable onboarding date (note: only modify the onboarding date in the blue section, as the green section references it).

Once the onboarding date is established, the technical green section determines the starting point for forecasting the salesperson’s lifetime at the company and tracks the months spent at the company since onboarding (displaying 0 before onboarding). The blue section utilizes the green section as a reference to run an index/match function on the “AE Sales Lifetime” sheet, enabling us to simulate and forecast the new MRR that a salesperson hired on a specific date will bring into the company.

Lastly, the black section combines all four product plans to provide an overview of the total revenue capacity for each month over the next three years. This takes into account the timing of new hires, their ramp-up time, and attrition.

Next Steps

Having incorporated capacity planning with ramp-up and attrition, the next step is to reconcile this with churn and net upsells to obtain the true cumulative MRR.

Following that, we will develop a robust cost model that considers onboarding costs, OTE variable wages, and recruiting expenses. We will also integrate these statistics into a dashboard and connect this model with a typical 3-statement model. Additionally, features such as a comprehensive cohort analysis, CAC model, and CAC attribution model can be implemented.

By covering all of these topics, we will have constructed a financial model that proves to be genuinely valuable for SaaS start-ups aiming for sales-led growth.