A data-driven approach to scale your business

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There is no foolproof plan when it comes to scaling; problems will arise, hinges may be needed and different industries and social dynamics require different solutions. Only half of startups survive the first five years and one in 200 (or 0.5%) become scale-ups.

Still, there are also early-stage decisions startups can make, especially around data, that can increase their chances of scaling up and make the journey at least a little more predictable. My advice is to embrace a data-driven scaling process. I’ve found that founders who overlook a data-driven process early on often fail in the long run. By implementing data-driven processes, you can base decisions on facts from the start and support pivot points that are often needed.

Here are three tips to future-proof your startup by embracing data:

1. Consider Hiring a Chief Data Scientist

While data scientists are seasoned professionals, many organizations should consider hiring a Chief Data Scientist (CDS) early on. About 92% of companies report that the pace of their investments in data and AI projects is accelerating, and it’s no wonder that data-driven companies are 23 times more likely to acquire customers and 19 times more likely to be profitable. But the transformation to a data-driven company requires sound judgment about the right tools and strategies and ongoing expertise in implementation and maintenance. Taking it to the highest level of a company’s decision-making process at an early stage will most likely prove to be a significant benefit. It ensures that when data teams need to be built and monitored, there is an expert decision maker at the helm with the ear of the other executives.

In the area of my business – approving loans for foreign buyers – shortening underwriting cycles is paramount. We can take out a loan quickly, easily and efficiently, while traditional methods are time-consuming and require a lot of manual work. Our data-driven process is only possible with dedicated guidance and the kind of strong field expertise a CDS can provide.

2. Let CTOs and CDSs focus on their respective expertise

In a data-driven business, the role of the CDS is to bridge the gap between business managers and data teams and guide both parties toward a mutual understanding of what can be accomplished with data. The CTO, on the other hand, is more focused on product development and the resources needed to achieve product-specific goals. Each role requires a separate, distinct set of tools, a fact that is often overlooked. Treating the CDS as a “sidekick” role or placing the data scientists under the purview of the CTO promotes shortcomings in data-driven decisions and deep AI and ML expertise. However, when both roles are clearly defined, a solid data infrastructure is created with accessible tools to extract meaningful insights and business intelligence results. By decoupling the data and ML pipelines from customer-centric research and development, our company has developed a collaborative partnership between the two departments, allowing the teams to focus their expertise and sharpen their strategies, working together rather than with each other come into conflict.

3. Invest in data infrastructure or pay for it later

Having a rockstar CTO and an incredibly bright Chief Data Scientist is an important starting point, but the right people and strategy should always be accompanied by action. One of the biggest steps companies can take to become scalable is investing in data infrastructure. Data warehousing is especially critical because it eliminates the constant back and forth between DevOps and backend engineering departments by incorporating data from multiple sources into a single source of truth that can be easily extracted. The next investment should be to extend that accessibility beyond the data team by embracing a data mesh approach and purchasing software that empowers marketing, customer success, and other groups to make effective use of data themselves.

Applying these three tips may seem simple, but the implementation comes with quite a few challenges. Entrepreneurs who remain fearless and work hard to achieve them will lay the foundation for a thriving business well into the future.

Tim Mironov is Chief Data Scientist at Lendai.

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