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Written by Michael Li, CEO of The Data Incubator. The Data Incubator is an 8 week fellowship training PhDs to learn to be a data scientist based in NYC, DC, and SF.

As an entrepreneur, one of your goals may be to find ways to do your job smarter, faster and better. You may seek this for your employees too: finding ways to lighten their load while increasing output. In this pursuit, our friends over at The Data Incubator have figured out that using a “data scientist mindset” can increase efficiency and assist in solving the biggest problems facing organizations or businesses. Here, they share some of their thoughts and tips on how to implement this paradigm.

The goal of using business as a tool to drive positive change is a noble endeavor that can help make the world a better place, while generating profit. To be the standard for purpose-based enterprises, leaders have to adapt to changing demands and incorporate creative ways to stay ahead. The field of data science allows social enterprises to leverage the vast amounts of data they’re collecting to identify waste, make better decisions, and help achieve their mission.

A data scientist extracts knowledge or insights from data in various forms, like statistics, machine learning, data mining and predictive analytics.  At The Data Incubator, a data science training company, we help companies train and hire top data science and analytical talent. We’re also seeing an increasing demand for data science training for non-technical employees too.  Data science isn’t just a technical discipline — it’s a whole mindset and cultural shift that the entire company needs to embrace. Here are my top tips on how the data science mindset can help your social enterprise:


The data science mindset can be boiled down to a single word: why. We look at diverse and broad ranges of data, always asking, “Why?”. This is also crucial in business. Constantly asking questions like these can help focus your capital, “Why does my company exist? Why are we having those meetings? Why are those transactions happening that way? Why are those the right outcomes to strive toward? Why is this the best strategy?” Taking a moment to step back and reflect on why is essential as it connects you with your big vision of why you are building your business in the first place.


It’s very important to pick the right problem in data science, and understand it deeply. This is the same for having a successful enterprise. Ask your self, “Am I working on a solution for the right problem? Is my solution working in the right context?” Picking the right problem can be applied to day-to-day tasks also; by asking if you are solving the right issue, or are you improving the right process, or is it possible the cause of the problem has been misunderstood?


If you are not measuring your outputs, you have no way of knowing if you are improving or going backwards, no clue if your strategy is hitting the mark, and no idea what needs to be improved. Measure all data and track your feedback so you can make informed adjustments. Nothing is more crucial to continuous improvement.


Data scientists by their nature are problem solvers – as are entrepreneurs. And social enterprises aren’t just looking to solve practical problems, they’re looking to better society. But sometimes it can be exhausting, overcoming hurdle after hurdle. In Richard Branson’s own words, “A business means successfully solving problems.” So, take a deep breath and fall in love again with problem-solving. Welcome it with enthusiasm, curiosity, and perseverance.