Challenges of predicting future cash flows for startups

Predicting future cash flows of startups is an important aspect of financial planning, ensuring long enough runways, and investment decision making. After all, 82% of business failures are due to poor cash flow management.

However, it is extremely challenging to predict a startup’s future cash flows. This is mainly because of incomplete data, difficulty in making accurate growth assumptions, lack of established pricing strategies, and the unpredictable costs of scaling.

In this article, we will explore seven such key reasons as to why accurately forecasting startup cash flows is troublesome. These insights can help founders improve their financial forecasts, augment strategic decision-making, and improve transparency for investors and other stakeholders.

Predicting future cash flows of startups

Predicting future cash flows is crucial for startup survival and strategic growth. It requires a structured approach to forecasting cash inflows/outflows and scenario planning. Startups must balance realistic revenue assumptions with conservative expense estimates while accounting for market uncertainties and operational challenges.

Some common factors that make predicting future cash flows of startups more challenging than it is for established businesses are as follows.

Inaccuracies from Manual Data Entry

Inaccuracies from manual data entry are one of the major challenges for businesses as they make efforts to predict future cash flows accurately. Manual data entry leads to inaccurate financial records and forecasts. Also, it is labor-intensive and time-consuming, diverting valuable employee hours from strategic tasks.

Using automation tools can reduce errors and enhance data accuracy. Providing clear guidelines and conducting training programs can also help improve data entry proficiency.

Challenges of Insufficient Revenue Forecasting

Like established businesses, startups may not have a steady income stream, making revenue forecasting challenging. Startups often overestimate their growth prospects, leading to unrealistic financial projections. This can result in commitments based on expected revenue that never happen, causing cash flow crises.

To improve revenue forecasting, startups can use a data-driven approach with KPI tracking and industry analysis, complemented by scenario planning for risk management. Leveraging AI tools enhances accuracy, while industry benchmarks and market research help fill data gaps, ensuring informed financial decisions.

Incorporating regulatory risk

Often startups operate in uncharted territories with novel business models, because of which regulating them is a challenge for most governments. A popular business model that probably has the most recent origins and has been drawing the attention of regulators of late would be the subscription model pioneered by software-as-a-service (SaaS) companies.

In 1999, in order to deliver its product while eliminating the need for on-site installations, Salesforce launched its customer relationship management (CRM) product in a subscription-based model. However, as subscription models are replacing ownership in various industries, including automobiles, there is severe push back against them which increases the regulatory risk for such businesses. For instance, BMW had to roll back the subscription model for seat heating in its cars.

Unfixed pricing strategy

Estimating a startup’s revenue streams is challenging since many startups may offer different versions of the same product with laddered pricing. However, maximizing the gains in such a scenario requires an astute understanding of one’s users. Many startups do not know how much their users are willing to pay.

Even if a founder knows exactly how much value their product is creating for the users, if the founder does not understand the users’ cash flow challenges and ability to pay, they cannot craft a pricing strategy that fully extracts a customer’s lifetime value.

Hence, startups must experiment quite a bit to perfect their pricing strategy. Consequently, predicting future cash flows of startups becomes challenging due to uncertainties in pricing strategies.

Difficulties in estimating the cost and benefits of scaling

Scaling production is not always as straightforward as just upgrading the machinery; it may require internalization of various functions, expansion into new territories, and forming partnerships. Due to differences in living costs and labor market conditions for different services, the employee compensation cost of scaling can be difficult to predict.

This challenge is further escalated if scaling is planned for the future rather than immediately. As these factors affecting compensation costs tend to fluctuate more unpredictably making cash flow forecasting even more uncertain.

For instance, when Slack was launched as a tool for internal communication, emails had been the long-preferred mode of official communication. Due to the network benefits enjoyed by email, many would have written off Slack and miscalculated its Serviceable Obtainable Market (SOM). However, Slack overcame this disadvantage and became a globally-dominant player in internal communication.

Lack of customer retention

Startups may experience initial traction due to their target audience being frustrated with existing products or out of curiosity regarding the new offering. However, unless a startup is able to demonstrate that its product provides more value than its competitors, it may not be able to retain customers.

As a result, the startup may need to reconfigure the product to align with the market’s needs.

Thus, lack of customer retention creates two major problems. Firstly, with startups, there’s a higher chance of nose dives in revenue. Secondly, depending on the market feedback, a startup might face unexpected expenditure on research and development (R&D).

Dependence on key partnerships

In order to scale operations in a cost-efficient manner, startups often partner with established players in their value chain. Some of the benefits of such partnerships are enhanced market access, reduced risk, and access to the expertise, credibility, and reputation of an established player.

However, benevolence is seldom the sole reason for established players to support startups through partnerships. Let us understand the fragility of these relationships by looking at them from the perspective of the partners.

By collaborating early, these established firms expect to gain access to innovation. The advantages of these innovations could be faster production, lower costs, development of new products, entry into new markets, or increase in market shares.

However, if another startup is more likely to provide these benefits, it is in the best interest of the established players to switch to the new startup. As a result, startups may experience unexpected rises in production costs or drops in reach, making startup cash flow unstable and complicating reliable cash flow forecasts.

Eqvista – Empowering growth by deciphering value!

While there are plenty of challenges in predicting future cash flows for startups, they can be overcome by using surrogates, conducting in-depth research, and advanced analytical techniques. It is essential for startups to overcome these challenges to enable effective financial planning and strategic decision-making.

Eqvista, a leading valuation service provider assessing over $2 billion in client assets every month, has considerable experience in using these alternatives to derive accurate cash flow predictions that aid fundraising activities as well as strategic planning. Eqvista’s tools help startups create more accurate and realistic financial projections by automating complex calculations, facilitating scenario planning, and enhancing transparency in financial modeling. Contact us to learn more!