The irony is not lost on me that the girl who had to take Algebra four times has now become a go-to data person.
To delve into the redundancy of my math education would require a detailed account of the shortcomings of my educational upbringing - perhaps a tale for another day - but it does give me a chuckle that, as much as I struggled with math growing up, it has now become part of the way I make my living.
I have become a data advocate, a data activist even. Fighting to insist that data must be recognized, collected, sorted, and analyzed if we want change to occur.
A social worker who once conducted group therapy at the Olive View psychiatric emergency center now crunches numbers to find the value of x, standard deviation, outliers, and correlation coefficients.
How did I get here?
Well, the truth is that it was not planned.
I fell into data analysis 10 years ago, when I was tasked with bringing more people in to attend information sessions on how to advocate for foster youth. At the time, sessions were meagerly attended, but in order to understand why, and how to change it, I needed to get a better picture of the problem. Data became my solution.
By surveying attendees to find out how they heard about these sessions; analyzing which platforms brought in most attendees; and identifying the show rate of attendees compared with sign-ups, I was able to determine what the most successful and least successful approaches were. With this data in hand, I developed and then implemented a series of action steps that eventually increased the number of information session attendees by 75%.
I took these "lessons learned" to my next role, working in victims’ advocacy. By measuring the frequency of emergency calls and the types of services requested on these calls, I was able to campaign for more staffing in certain program areas over others.
As recently as last week, I was arguing for the collection of certain data points to help assist a client in determining a future course of action.
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What seems exponentially better understood in the business world than the nonprofit world is how data analytics can drive decision-making.
In the nonprofit world, the most persuasive argument for measuring data seems to be focused on grant reporting. When we say “we need these numbers for our grant,” it takes little convincing to help a partner design an effective tracking method.
But I find myself, more often than feels reasonable, explaining why data must be used to inform future planning.
Data is not just a snapshot of what has happened in the past; it is a predictor of what is likely to happen.
Just as a retail company uses historical sales data to determine appropriate levels for their inventory, nonprofits can use historical data to predict where service demands will be their highest or the best interventions for desired outcomes.
Put simply, data tells the story of where we are putting our energy, whether that effort is working, the loci of where our inputs are not working, and where our input could yield better results.
But when we ignore data, our informed decision-making is replaced by instinct, hunches, mood, and “seeing what sticks.”
When we ignore data, we increase the likelihood of repeating old mistakes and making new ones.
And maybe even more perilously, if we ignore data, we increase our potential for personal bias decision-making.
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As a data activist, I wish I could say this challenge is only seen in the small nonprofit space where bandwidth is limited and data analysis may be deemed a luxury. But I’ve seen government departments sitting on a trove of data only to ignore what the data was saying because it wasn’t a politically popular direction to take.
I’m not saying that data is the cure-all for how we should make decisions, but I am saying it must be a key component to the decision-making process. Otherwise, you will likely be spinning your wheels and not getting anywhere.
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