To succeed in today’s data-driven economy, entrepreneurs need data skills to unlock opportunity, stay competitive, and grow robust businesses.
Pictured: DS4A / Colombia Alumni and Guai founders Daniel Gil-Sánchez, Alejandro Sánchez, and Cristian Torres-Montenegro
This article was produced in collaboration with Iris González.
"If you look at the top 10 market cap companies in the stock market in the United States, nine are great at AI — and the tenth is Berkshire Hathaway. And they've got Warren Buffet, so that speaks for itself ... It's not like I took AI in college ... You don't have to be some advanced data scientist or programmer to learn these things. It's actually more ... basic math and common sense than anything else. So, if you put in the time, you can learn [about AI and data] and give yourself a competitive advantage."
Yes, as with other types of business leaders, entrepreneurs with basic data analytics knowledge and skills have unique advantages when it comes to leveraging data while growing their businesses, regardless of their respective industries.
To unpack the “why” of that reality, below we’re highlighting six reasons why entrepreneurs benefit from having data skills.
Along the way, we’re also sharing a few insights into the topic from within the Correlation One community. Daniel Gil-Sánchez, Cristian Torres Montenegro, and Alejandro Sánchez are graduates of our Data Science for All (DS4A) / Colombia, a program sponsored by the country’s Ministry for the Information and Communications Technologies (MinTIC) and the Colombian government.
After meeting in class, the trio launched a data analytics and artificial intelligence (AI) consulting group, GuAI, which they run from Colombia and Texas. We appreciate their input.
Data professionals can help analyze the health of their businesses by collecting, cleaning, and working with raw data. Their insights can help leaders assess specific business strategies.
And this information can prove to be invaluable to entrepreneurs, especially when data reveals insights into, say, customer behavior.
Still, as Gil-Sánchez noted, many company leaders struggle to understand the fundamental of data, including the various professional roles and corresponding skill sets.
"Our consulting company specializes in data analytics and big data to help businesses understand how they can solve problems by working with their data," Montenegro added. "What we've discovered is that many companies lack a basic understanding of data science, how it works, and what different data professionals do."
In an increasingly data-dependent world, however, a significant data knowledge gap can potentially hamstring short-term progress and long-term success.
(Plus, with more venture capitalists (VCs) turning to AI and data to assess which companies are worthy of investment, it can’t hurt for startup founders to brush up their data skills and finely tune their data collection.)
Alas, since data professionals are often regarded as interchangeable knowledge workers, inexperienced senior managers may misassign data-centered roles and responsibilities.
At best, this can confuse and frustrate seasoned data talent. At worst? It can create a range of problems for the C-suite, from costly high turnover on a company’s data team to poor overall business strategy and execution.
If a founder is already data literate, however, then they can draw upon their knowledge to construct a data-driven workforce primed to scale.
Yes, “trusting one’s gut” sounds brave in business, but sooner or later one needs to evaluate well whether a company’s processes or procedures are hitting the mark.
That’s another example of when data knowledge can be valuable.
Entrepreneurs with basic analytics knowledge are better prepared to leverage the right data when, say, assessing strategy or determining which business problem to address next.
“Experimentation is a requirement for founders and data scientists alike," Montenegro said. "Founders and data scientists take what they've learned in theory to discover what works in practice.”
At the same time, successful entrepreneurs — again, much like good data professionals — know the value of pursuing innovation, even when they knowingly risk failure.
"When there's no way to ensure a project's success before its undertaking, having a founder aware of the risks is extremely important," Gil-Sánchez said.
For entrepreneurs who embrace calculated risk taking, competence with predictive analytics may prove useful.
"In many cases, entrepreneurs don't need complicated algorithms per se to answer questions," Sánchez said. "It's more about understanding the business problem and recognizing how basic analytical skills can provide strategic insights."
Meanwhile, some entrepreneurs discover that data knowledge is helpful for nurturing a competitive edge through innovation and benchmarking — provided they’ve guided their team well in collecting and analyzing the data itself.
"Many businesses think that data science and AI is a 'magic black box' that you can query to get answers to all your data questions," Sánchez said. "That's not how it works because it all depends on the quality of your data and your understanding of the problem."
It takes nerve to become an entrepreneur. And the right data skills, strategies, and techniques can help power bold, innovative moves as your company grows.
For instance, data-savvy founders may be more likely to invest in data collection at the outset of a new product’s life cycle, continuing to harvest information throughout subsequent development and go-to-market phases. Relying upon good data throughout a product life cycle, leaders are better prepared to make proactive decisions rather than reactive ones.
After all, with better quality data comes better inputs for strategic decision-making.
Furthermore, founders who are comfortable analyzing multiple data streams may be more likely to identify new opportunities for their product, sales, and marketing teams.
"You can be more proactive — and your company more effective — if you know what the data is trying to tell you," Montenegro said.
With big data and analytics driving change in how businesses create meaningful customer experiences, manage risks, and accelerate innovation, it's no wonder companies are looking to diversify their talent pool by hiring (and training) more data professionals.
"Skill diversity is important in every business," Gil-Sánchez said. "Real-world problems often are messy and interdisciplinary."
By hiring the right data talent, fusing data from multiple related sources, and incorporating data insights across a company’s business areas, data-savvy entrepreneurs can create more innovative workplaces.
(Remember: As your company grows, the creation of good company-wide data governance plan can signal to employees, potential employees, and even prospective VCs that the founders know how to make the most of data analytics and AI.)
In a global, data-infused economy where talent and workplace competition are high, entrepreneurs are smart to seek out every advantage available.
So, yes, this includes data analytics skills.
After all, with data shaping strategy within every industry and organizational unit, entrepreneurs will likely use data skills while developing and improving products, creating go-to market strategies, nurturing customer delight, and growing a workforce fit to scale.
Learn more about how Correlation One has helped governments and government offices — in places such as Colombia and San Jose, California — prepare for the expanding global data economy.