As a venture-backed start-up, we raise money with the expectation of reaching certain milestones in X amount of months. As such, managing expenses couldn’t be more critical.
The minute the cash hits the bank, there’s a set timer, a death sentence until the company runs out of money. You raise that money on a plan, but….since when do things go according to plan? Every adjustment or change could significantly impact how long you survive.
In the first few months, you quickly learn what’s going well, what’s going great, and what’s going terribly. You double down on the things that are going great and you then continue to place other bets. But everything requires someone at the company to do something. And…headcount is extremely expensive.
With so many unknowns, the unique challenge for any startup is forecasting organizational growth for the next two to three years amidst the clamor of hiring requests from various department heads.
Our objective was clear: to develop a model that could accurately predict headcount needs over time, thereby providing a realistic picture of our future costs and informing our next fundraising timeline.
Balancing immediate hiring requests with long-term financial projections
Post-funding, the leadership team sent us their "wish lists" of all the roles they wanted to hire for in the next few months.
While understanding their immediate needs was manageable, being able to project them over the next 2-3 years is what became tricky. Without a clear understanding of what was driving the need for headcount in the long-term, forecasting these expenses was almost impossible.
This uncertainty severely impaired our ability to plan effectively for the future. Essentially, we didn’t know how long our money would last us since we were only confident in the forecast for up to three months.
Projecting headcount growth through collaborative forecasting
We initiated a process of collaborative forecasting by engaging with every business leader to understand the drivers behind their hiring needs. Different departments had different drivers for headcount requirements. For instance:
- Sales: Driven by quotas.
- Recruiting: Based on the number of open requisitions.
- IT: Determined by the total number of employees.
- HR: Driven by employee count.
- Customer support: Determined by customer count.
The insights gleaned from these interactions were utilized to develop a unified model to project headcount growth across the organization. So, instead of throwing random headcount in a model throughout a year, we relied on these metrics to tell us when a new head should be added to the plan.
Analyzing headcount drivers to extend runway
As budget seasons rolled around, discussions with department heads evolved from merely reviewing wish-lists to evaluating the assumptions driving their headcount projections.
For example, we met with the head of customer support and agreed that he could get one rep for every 500 accounts.
We also learned that different sized accounts required different amounts of attention.
The ratio needed additional specificity that included time to resolution and the type of customer. As we adjusted the ratios, we learned more about that department and better ways to track their performance.
New resource requests were now analyzed in the context of their impact on headcount assumptions. For example, if recruiting proposed a new applicant tracking system (ATS) to improve efficiency, the discussion would center around how this would affect their ability to handle more open requisitions.
By shifting the focus from approving headcount to analyzing headcount drivers, we significantly enhanced operational efficiency and kept our headcount growth under control. This approach fostered a culture of informed decision-making, ensuring resources were allocated based on a thorough understanding of underlying needs and long-term implications.
Ultimately, the improved visibility into future costs extended our runway, thereby providing a solid foundation for planning our next fundraising endeavor.
Our approach could be benchmarked against industry standards for operational efficiency and cost management. Adopting a culture of continuous improvement and learning from industry benchmarks, we continually refined our model to stay aligned with our evolving organizational needs.
This structured approach, based on collaborative forecasting, customized metrics, and iterative evaluations, not only aided in extending our runway, but also ingrained a culture of informed decision-making within the organization.
It underscored the importance of understanding the dynamics driving headcount needs across different departments and paved the way for a sustainable growth trajectory.