Recently, I engaged in a dialogue regarding the applicability of unit economics to financial modeling. The conversation felt more like a public flogging aimed at me for not considering a sufficient number of parameters to describe the model adequately. Let me provide some context on what the conversation entailed. My counterpart argued that my approach overlooks external factors affecting the team, such as emerging competitors, market shifts, and so forth. Yet, as is often the case, no one seemed interested in hearing my perspective.

In this situation, I see two key questions: first, how effectively does my approach describe the business model of a startup? And second, what factors should be incorporated into the model? To address these questions, I need to understand the rationale behind my approach. If the current system functions well, why fix something that isn't broken? 

The motivation behind my new approach stems from the challenges faced by startups and early-stage entrepreneurs when tasked with creating a financial model. Team members typically lack experience in crafting such documents and struggle to grasp the necessary parameters. Traditional models entail numerous parameters, some of which are less evident, like growth dynamics. Many teams resort to arbitrary monthly growth figures, while some parameters leave room for speculation. Consequently, we end up with either poorly constructed models or models tailored to investor expectations, where numerous parameters are adjusted to align with the desired outcomes.

Consider parameters like the number of leads the company aims to attract to its product each month; ideally, these should reflect market conditions and competitor activity. While this approach seems logical, how can a team predict the number of competitors it will face three years down the line? Or forecast its market share six months into operation? And why should these parameters serve as the drivers of the model? 

This issue is crucial because model drivers represent parameters within the team's control. But can a team truly be held accountable for parameters beyond its influence? Is this approach even viable? It has always been my belief that responsibility lies only with what one can influence and control. Can a startup team manage the emergence of competitors in the market three years from now? Clearly, exerting influence over such factors is virtually impossible.

Therefore, I propose using drivers that the team can fully control to construct a model. This approach ensures alignment with the team's capabilities, experience, skills, and ambitions — all of which are realistically measurable and manageable. Unit economics, described by metrics, bridge the team's experience and competencies with the financial indicators of the model. By building the model based on unit economics metrics, we gain insight into how precisely the team plans to achieve the stated model values. 

In unit economics, each parameter corresponds to a specific process within the project, with a designated person responsible for its execution. Thus, constructing a financial model based on unit economics boils down to each individual explaining how they intend to achieve the stated value. 

Persona    Process    Metric    Unit economics    Money 

It's crucial to emphasize that these values aren't arbitrary but directly linked to the team's abilities. For instance, if the model dictates that the product should attract 100,000 leads, the person responsible for this parameter must outline their plan for achieving this value. Importantly, they must also assess whether such a volume of leads is feasible in the market. While they can anticipate market competition, they cannot accurately predict competitor numbers three years ahead due to a lack of data. However, if 100,000 leads represent 100% of the market, there's a risk of falling short. Hence, the individual accountable for lead generation must justify their confidence in achieving this metric. 

They can justify it using two approaches: first, by leveraging past experience and historical examples, providing investors with faith or skepticism. Second, by acknowledging their lack of experience but presenting a set of hypotheses to test and identify the tools necessary to attract the desired leads.

In both cases, the team assumes responsibility for what it can influence. Mistakes are possible, but they are inherent risks that arise when teams speculate on parameters they cannot control, such as competitors, using drivers beyond their influence.