Securing funding for a startup has never been easy, and the current economic volatility has made it even more demanding. According to PitchBook's 2023 report, demand for capital exceeds supply by an overwhelming 50,5% for early-stage companies and 67,1% for growth-stage companies. Startups cannot rely on impressing with metrics alone to attract investors. Investors want more. They want to understand the “why” behind a startup's success, delving into the long-term growth trajectory.
At a time when investors are acting more cautiously, a strong data culture is invaluable. When you have a solid data culture, investors can better understand the “reasons” for success. They understand how the data team solves problems, optimizes funding allocation, and identifies revenue-generating insights.
A data-centric approach indicates a company's ability to manage its business efficiently. Leaders need to know the drivers of their business, what motivates their customers, what is important to their growth, what helps or hinders their growth, and then work backwards through the data they need to gain insight into these aspects.”
Data culture can help align metrics with objectives, manage risks, streamline Due Diligence, optimize data recovery and ensure control and transparency.
Building this culture allows founders to convincingly articulate their journey to potential investors. It signals a commitment to data-driven decisions over instincts, a trait that gives confidence to cautious investors.
Below are some points on how startups and growth companies can build a strong and adaptable data culture that can help them drive this initiative.
Empower data-driven leadership
While strategies are not necessarily a step-by-step sequence, data culture starts at the top.
Every decision leaders make must carry an accurate expectation of its business impact, aligned with the company's broader goals.
Leadership is the engine that drives a strong data culture in an organization. The essence of establishing a thriving data culture in these environments depends on leaders making decisions based on data-driven insights.
Many startups start with gut-based decision making. However, as they evolve and grow, relying solely on hunches becomes limiting. It is crucial to differentiate between hunches and structured hypotheses. Hunches are often based on intuition without hard data, while hypotheses involve making specific statements based on existing data and logic. This transition can set them on a path of rigorous experimentation and data analysis, resulting in more informed, data-driven decisions.
Deepening understanding of the complex cause and effect dynamics within operations cultivates a culture of data-driven excellence.
OKRs go north to guide efforts
Let's talk about objectives and key results (OKR)– A robust framework that guides businesses in making data-driven decisions. It's about accountability, paving the way for a culture focused on results and rooted in clear assumptions. Every decision leaders make must carry an accurate expectation of its business impact, aligned with the company's broader goals.
On the other hand, the strategy of adopting a net-zero budget urges executives to dig deeper into spending, ensuring that resources are allocated efficiently. By systematically implementing OKRs and net zero budgeting, any startup can navigate data-driven decision making while optimizing resource utilization, ultimately driving growth and success.
Hire a chief data officer and centralize the function
Startups should view their data team as a revenue center rather than a cost center. This means giving the chief data officer a seat at the table, reporting directly to the CEO or a CXO with significant P&L experience.
By having an internal leader actively driving the data agenda, a growing company can ensure that good data science is always an active part of its growth strategy. Investors agree that data equipment is an investment, not a cost that should be deferred.
Additionally, having a chief data officer and a data team will centralize the data function. Instead of having multiple data processes scattered across departments, having a chief data officer integrates them into a more coordinated system. Whether creating the data strategy that will drive decision-making, maintaining data integrity and security, providing insights through intelligent analytics, or managing a scalable data infrastructure, the chief data officer is indispensable to the company's data culture. any startup.
Guide data efforts toward key business use cases.
Unlike larger corporations, startups and growth companies don't have the luxury of unlimited resources to drive multiple initiatives. Instead, they should focus on the key performance indicators (KPIs) that matter most to business success.
A proposed approach is the exercise DuPont KPI, a visual method that helps companies better understand their KPIs and the metrics that drive them. The process is most effective when the entire executive leadership team (ELT) is involved and, with the support of the chief data officer, typically takes four to six weeks to complete. With the DuPont KPI finalized, leadership can now identify the initiatives (use cases) that have the greatest impact on the driver metrics and, consequently, their KPIs. This alignment between use cases and business outcomes ensures that outcomes are directly linked to key DuPont KPI driver metrics.
The DuPont KPI exercise creates a visual tree that links each KPI to its immediate driving metrics, allowing for up to five to 10 levels of metrics. This structure often reflects the hierarchy of the actual organization. For example, if a company is divided into geographic regions and segmented into different product lines, the DuPont KPI will accurately reflect this hierarchical structure.
This exercise does more than simply align the leadership team's approach to measuring success; reveals important opportunities to rapidly improve KPIs. For example, if the KPI is revenue growth and a metric four levels below it is customer retention, which is currently, say, 60% below industry standards. Then, improving it by 5% could result in a substantial 3% increase in revenue growth, which can be equivalent to significant incremental revenue (these figures are for example purposes only). These opportunities, revealed during the financial year, can be evaluated and prioritized in the top three to five, resulting in a substantial boost to revenue growth.
By ensuring initiatives align with the most impactful KPIs, startups and growth companies can also easily demonstrate to investors how their efforts directly contribute to the bottom line.
Invest in a single source of truth and KPI charts
As startups experience rapid growth, it is a mixed blessing as it brings with it a host of opportunities and a set of challenges. On the one hand, it opens the doors to improved insights, greater efficiency, and better decision-making. On the other hand, it introduces complexities such as the volume, organization and accessibility of data.
Maintaining a clear focus becomes critical as businesses expand. Every startup, at some point in its journey, faces a common challenge: data inconsistencies, with vital metrics like subscriber count and revenue often refusing to work well together. It is important to remember that there is no such thing as “perfect data.” So what is the solution? Identifying the 300 to 500 crucial metrics for the business is the way to go. But it is not enough to identify them; It's about ensuring that everyone in the organization has access to accurate versions of these metrics, and that's where single source of truth (SSOT) driven by KPI charts comes into play.
The charts provide a visual representation of DuPont KPIs, enabling quick and informed decision-making. The key is to make these dashboards easy to use and easy to access so that all team members get used to using them.
While KPI dashboards serve CXOs, supporting metrics are necessary for detailed business insights, which extend to frontline roles. These 300 to 500 metrics should also be consolidated into an SSOT, allowing access to data, information and insights from a single repository. This avoids data silos and keeps everyone on the same page when it comes to each specific KPI.
Additionally, KPI dashboards, supported by SSOT, simplify accurate presentations of the company's health to potential investors.
How a data culture overhaul transformed a payments orchestration startup
This startup was dealing with issues around conversion rates, pricing, and cost optimization. Additionally, they faced inconsistencies in data, which eroded trust in them and hampered their progress.
To address these challenges, they started by creating a DuPont KPI with their leadership team, drilling down to level 6 to identify key metrics and their drivers. They then aligned their OKRs with the relevant metrics identified in the DuPont KPI.
This eye-opening process shed light on the different perspectives of company leaders regarding what is essential to drive the business. This exercise served as the basis for a unified vision and guidelines, represented by the DuPont KPI and, eventually, KPI charts.
At the same time, key business use cases with potential to significantly impact key KPI drivers were identified. In parallel, the evaluation of the technological infrastructure was carried out to identify gaps in the SSOT and technical skills. Using these business use cases as a blueprint, they laid out a roadmap to generate tangible business results.
Key initiatives included:
- Implement a democratized SSOT with more than 300 key metrics.
- Creation of KPI dashboards to monitor performance.
- Enhance analysis capabilities to obtain valuable information.
By completing this transformation in just nine months, the startup achieved a revenue increase of $8,4 million and a loss reduction of $1,7 million. The CTO praised this process as a “game changer,” underscoring the monetary value placed on fostering a data culture. He enabled teams to solve problems, optimize fund allocation, and identify revenue-generating ideas, and this is the kind of data-driven approach investors want to see.
Data culture is not just a buzzword; It is a strategic necessity that forms the basis of intelligent decision making, rooted in facts and results of experimentation. It provides emerging and growing businesses with the confidence they need for a successful journey.
Developing a strong data culture doesn't happen overnight; It requires sustained effort and commitment, particularly on the part of leaders. When implemented effectively, a strong data culture is not an abstract notion: it is quantifiable and directly influences profitability.
It is crucial for startups and growing companies to change their perspective on data. Unlike larger companies, they operate under different restrictions. They must be resourceful and insightful to extend their lead to the next round of funding. While fundraising is a priority for startups, fostering a strong data culture can significantly contribute to your overall success.
