If you run a non-profit, your impact is too important to leave to chance. Social entrepreneurs have a responsibility to quantify the impact they seek, measure results over time and improve. However, collecting and analyzing 'big data' can only help this process when organizations measure the right things and apply what they discover.

Seven years ago, I co-founded Krochet Kids intl., a non-profit lifestyle brand that empowers women to rise above poverty by providing jobs, mentorship and educational programs. We began teaching women in Uganda (and now Peru) how to make apparel and accessories that are sold online and through retailers like Nordstrom, Urban Outfitters, Whole Foods and others. We invest over 85 percent of revenue directly back into empowerment programs.

Within the first year, my co-founders and I ran into several questions: How do we know if we actually creating impact? How do we know if our work is truly "empowering" women? We went through a process that led us to collect 45 data points about each of our participants on a monthly basis. Today, this data guides our mission and provides invaluable feedback on our programs.

If you're trying to use big data to achieve a social good, these three steps will help you make your way:

1. Listen

What do the people you aim to serve actually need? A lot of non-profits in the U.S. want to help, so they make a plan, build out a 5-step program, they implement it somewhere in the developing world and it fails miserably.

Typically, they fail because they didn't involve the beneficiaries in decision making. They never asked, "What do you need? How can we get it or develop it together?" Involve beneficiaries in their life change -- let them take ownership. Conduct field research, build connections with local people and test your ideas before you start trying to help. Big data can't make a difference if you skip this step.

2. Theory of Change

How does a woman in Uganda go from living in poverty to achieving her dreams and supporting her family?

Back in 2008, we wrote a document that explains how this change occurs, and we identified key performance indicators (KPIs) based on our theory. We designated six forms of empowerment: economic, physical, social, intellectual, psychological and spiritual. And within in each bucket, we identified 45 metrics that could speak to empowerment. These include net-worth, supplemental income, self-esteem, nutrition, average meals per day, health expenses and many other measurements. We collect this data from each participant on a monthly basis.

We now have five years of data that validate our theory of change, but also shows us how to make adjustments and prevent breakdowns as we go. When a participant's savings drops, we know to intervene. The KPIs also give us the confidence to communicate our impact to the public.

If you're new to data, spend a lot of time understanding what outcomes you hope to attain. What influences those outcomes? What will tell you if you're achieving them or not? Those are the data points worth tracking.

3. From Collecting to Using Data

It's challenging to get data, and it's even hard to use it. For us, the key is to visualize the data. We're not data scientists, and we want as much revenue as possible going to participants instead of technology, so we rely on a subscription analytics platform from Tableau. We can see the micro and macros trends at the individual, community and overall program scale, and we can look at change over any timespan.

This gives us the power to test new ideas. So, for example, if we host a training session on personal finance, then we can look at each participant's economic empowerment statistics over the next several months to gauge the effects. If it works, we invest in providing that training to more participants. If not, we go back to the drawing board and improve.

Big data and visualization allow you to analyze the impact of specific events, trainings and whole programs so you can take action to improve. 1s and 0s in a spreadsheet won't give you that ability.

There is some (justified) skepticism around non-profits because many can't demonstrate their impact. However, you can eliminate doubt by being powerfully transparent and using data to tell your story. You can't rely on anecdote of one woman or child to build confidence in your programs. Big data can reveal your true impact, and it can serve as an engine of conversation, questioning and growth in your organization.

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