After joining Bullpen Capital in 2020, Ann Lai quickly rose through the ranks to general partner, where she has invested in and advised over 30 companies at various stages.

A startup’s pitch to investors or marketing materials will often feature the phrase “data-driven,” which is among the most overused phrases in the business world. However, what does it actually entail to be data-driven?

Venture capitalists are becoming more stingy with their investments as a result. Once-popular tech startups in BNPL, cryptocurrency, and the delivery market are now struggling to deliver on the growth and returns they promised during their initial funding rounds.

Investors in search of safer, smaller deals may be attracted to startups with more modest goals, but taking a data-driven approach to an early-stage venture is often unfair to the company.

Give up using raw data

Many new businesses make the mistake of using unprocessed data because they lack the resources to properly filter it.

You shouldn’t, for instance, boast to investors about your website’s traffic volume without also disclosing the average time spent on each page.

Inaccurate or biassed information can do more harm than good if it goes unchecked. Unfortunately, many rapidly developing AI programmes have developed racial or gender biases as a result of the unfiltered data fed to them. Understanding where a company excels and where it can be improved requires skill in data filtering.

This can be avoided by dividing the data into subsets and making use of anomalies.

The ability to compare like with like relies on data being filtered to accurately depict operations and performance. Unfiltered data leads to flawed comparisons, overemphasis on the wrong aspects of the business, and obscuring of crucial outliers that venture capitalists seek.