Happy 2016! I hope you are ringing in the new year with a good ol’ hangover or some traditional New Year’s food – collard greens, black eyed peas, champagne, or in my culture mochi. A quick side story: every year on New Year’s Day my mom and dad would serve me Japanese mochi. Not the sweet stuff filled with red azuki beans. This is the gelatinous white rice flour pounded until it is smooth and sticky. Growing up I hated eating it, I now only eat it out of obligation to some tradition I can’t name. Tomorrow, New Year’s Day, I pass on this tradition to my first born. I am anticipating a lot of whining and protesting, but damn it he will eat mochi – if only because I had to as a kid.

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There is a tension between focusing on data and remembering that real people are behind the numbers and statistics. Too often when we do our work, we are encouraged and taught to focus on data. This past Sunday the Seattle Times featured a story about how millennials are more data-driven in their approach to giving. The millennial-philanthropist ask organizations to show how they are using data to ensure that their interventions work and how organizations re-calibrate to get even better results; in other words they want to make sure their funding is making a difference. I agree with the focus on data, in fact I’ve previously written that data should define the gaps and the problems which helps to frame equitable outcomes.

Where we go wrong, is forgetting that stories are a form of data, and people’s experiences and stories are equally important. We need to humanize problems. Charts, graphs, and reports do not create urgency, they don’t build relationships, and in Simon Sinek’s TED Talk he points out Martin Luther King didn’t preach: “I have a plan,” he said “I have a dream.” People are more likely to want to follow a dream they can see themselves in than following someone who says “Follow me I have a strategic plan with data points.” There is power in stories and there is important data in stories and experiences. Human experiences are behind the stories, charts, and graphs.

We cannot forget that every problem has a lived experience behind it. When we fail to recognize the human connection, we have a harder time empathizing. Empathy is essential to understanding another person’s experiences so we can work towards more equitable outcomes.

Why Data isn’t Enough

Data is necessary to understanding a problem and ensuring that we are tackling the ‘right’ problem. Data gives us empirical evidence and helps to shape and frame a problem. Good data also focuses us on what we should be looking at—such as where racial gaps occur, are there clusters of disparity, are there pockets of achievement, etc. Data also helps to ensure an intervention is working and how to get better results, including testing new methods to see if a small adjustment will yield improvements.

However, when we only look at empirical data – i.e. test scores, homelessness rates, crime data, deaths, etc. we lose an essential element of understanding a problem. We lose the relationships and the human context which are necessary to understanding the problem and the connections needed to solve problems.

As an example police departments across the country rely upon data to tell them where to respond. In the 2000s TV The District, the police chief of the D.C. police force uses CompStat (comparative statistics) to focus his police department. The show is what you would imagine from a TV drama— a ruggedly tall and dapper police chief, with self-depreciating humor, but still tough as nails police chief uses data to solve crimes. In this show the police chief has a big room where he brings all of his people and projects crime data onto big screens, then gives them speeches with punch lines that motivate them to solve crimes. One of the problems with the CompStat approach displayed on TV was relying upon past data, i.e. crimes already committed, and not using community level data to understand what is happening and what isn’t being shared. There is also an absence of talking about the human impact and the role of what communities are experiencing. For every data point we also have to ask who isn’t represented in the data point. In a CompStat review could there be under reporting, or an over intervention? We need to ask these questions.

When we focus only on data we fail to recognize the power of a human experience. Raw data makes it too easy for us to think of a statistic exactly for what it is, a number, a percentage, or a risk. Yet, when we humanize our work we see what is behind it. For every CompStat crime statistic there is a human face behind it.

People Behind the Stats and a Little about Weaponizing Data
On a local Facebook group there is a neighbor, we’ll call him Fox Mulder, who constantly posts crime stats. They look like this:
11/30/2015 2:45:26 PM
HARASSMENT, THREATS (to kill)
10XX BLOCK OF S Moo ST
Final Call Type Category: THREATS, HARASSMENT

Several of the Facebook group members have asked Fox Mulder to stop posting every police call, saying it is negativity and they don’t want to see it. Fox writes back that he wants to daylight the information to motivate people to press city government for more police, arguing crime should be equally low across the city, not in isolated pockets (we are in the higher crime neighborhoods). Because all of this is over Facebook there aren’t a lot of strong relationships in place between Fox and others.

What Fox Mulder fails to remember is within that data and how it is presented are people. His presentation of the data dehumanizes the process; he presents facts but doesn’t give the whole story. The way the information is presented is straightforward and without context. It is factual and important information, but for a local neighborhood group the context and human experience are equally important. Because the group is neighborhood based he fails to remember the person behind the posting may be a neighbor experiencing a low moment in their life. My colleague Dr. Jondou has a term for this, weaponizing data. Data can be used for good, or it can be used against people and communities. Many in the Facebook group feel like the constant stream of crime data is used as a weapon to highlight the crap of the neighborhood without presenting solutions. We need to use data for good and to help build relationships.

Empathy and Data Must Mix
No matter what the data is we shouldn’t use it in isolation. We have to put a human story to the facts, otherwise we fail to remember the importance of the experience. A fact without a story also allows us to dehumanize and doesn’t promote empathy. Empathy is a key part of working towards undoing institutional and systemic racism. If we don’t have empathy or relationships with people who are the most affected by negative outcomes the policies we build and the practices that take place won’t be effective.

Humanizing our work means we see people, learn and understand lived experiences—including in data sets and other forms of empirical data, only then do we begin to get the work right.
The next time a stat is shared with you, challenge yourself and others in asking questions:

• What is the human story behind this data? Who’s life is represented in it?
• Has this data been shared with the community? How did they receive it?
• What is missing from the data? What story is the data saying and does it match what the community wants to hear and talk about?
• Do you have relationships with the people from those impacted by the data?
• Are we using data for good or are we using it to dehumanize an experience?

These answers will help you frame what to do with your data and how to build a human connection around it.

It is a new year, and in this year let’s end fake data and emphasis real people with real, whole-life stories.

Posted by Erin, photo credits mochi — Wikipedia entry on mochi, Craig T. Nelson on CBS’s The District