Story Before Storage
"Story before storage" has become my catchphrase for addressing a big issue with nonprofit data. In my consulting work, I've seen this problem over and over in data collection approaches used by nonprofits. The problem is that nonprofits are collecting and storing data that they have never told as a story or used to connect with stakeholders.
When we say "data-driven decision making," there is an implication that the data tells the story, that all our stakeholders need is access to the complete data and they will be able to see our story. This is as ineffective as imagining that all someone needs to understand how to operate complex machinery is a detailed diagram of the engine, gears, and pedals. At worst, we collect data, maybe make some decisions, and then store it without ever telling the story of why we made those decisions based on that data. When you move from data collection to storage without letting it inform a story that your stakeholders can see and hear, in a form that makes sense to everyday people, you are putting storage before story. The solution is to put story before storage. Putting story before storage means both acknowledging that data does not come with its own story as well as a commitment to making sure that the meaning derived from data collection helps nonprofits make connections.
Sometimes we imagine that we are doing what is "obvious" based on data or, put another way, we hold a fantasy that data can make decisions for us. We think all we have to do is collect it, and then we have the answers. The problem is that this approach completely neglects what makes data meaningful. Data becomes meaningful in direct relationship to the questions we ask to collect it. It becomes effective communication when we craft well-evidenced stories about what it means. Storytelling involves a three-part relationship between the teller, audience, and story. Handing an uninterpreted spreadsheet to our stakeholders-as-audience and expecting them to glean the meaning for themselves is irresponsible, because it abdicates our relationship to the audience as storytellers and leaves them not only confused but also uncertain about whose perspective the data represents. Telling the story also makes it clear who could answer questions--the storyteller.
But there's more than that to the problem, and more to be gained from putting story before storage. Let's say that you work for a nonprofit organization that serves the public. In order to assess how well you are doing, you periodically ask for input from the public--your audience--that you collect and then aggregate as data in order to generate an understanding of how well you are meeting your goals. I advocate putting story before storage because your first obligation is to give back to your audience, to tell the story of the data you have collected. When you tell the data as story to your stakeholders, you acknowledge their input, honoring the relationship that allowed you to collect some of your data from them. Your stakeholders deserve an opportunity to know not only that you are assessing your services, but also how their data was meaningful to your story of that assessment. Fundamentally, most public-facing nonprofit organizations need stakeholders--both clients and supporters, or taxpayers and staff or board members--to understand what you are doing and, hopefully, to remain in support of giving you their data, time, money, and more.
When you ask people for data, you ask them to tell you something. Maybe it's not a story, maybe it's just a series of clicks in response to questions. No matter how big or small, when you collect data from people you have an opportunity to connect with them more deeply, as the audience members and co-creators of your ongoing mutually beneficial story. You can connect by telling them what you learned, partly from them, about the work you are trying to accomplish and how well your services are working.
The impact of data is only as effective as the story you tell about it, so put story before storage. Do it for the relationships it helps to foster, the ongoing community collaborations you need, and for the sake of future opportunities for new stakeholders to connect with your organization. Don't stop with data storage; your job isn't done until you've used data to tell a story. That way, you've stored the meaning that allows those who come after you to understand why you made the decisions you did.
When we say "data-driven decision making," there is an implication that the data tells the story, that all our stakeholders need is access to the complete data and they will be able to see our story. This is as ineffective as imagining that all someone needs to understand how to operate complex machinery is a detailed diagram of the engine, gears, and pedals. At worst, we collect data, maybe make some decisions, and then store it without ever telling the story of why we made those decisions based on that data. When you move from data collection to storage without letting it inform a story that your stakeholders can see and hear, in a form that makes sense to everyday people, you are putting storage before story. The solution is to put story before storage. Putting story before storage means both acknowledging that data does not come with its own story as well as a commitment to making sure that the meaning derived from data collection helps nonprofits make connections.
Sometimes we imagine that we are doing what is "obvious" based on data or, put another way, we hold a fantasy that data can make decisions for us. We think all we have to do is collect it, and then we have the answers. The problem is that this approach completely neglects what makes data meaningful. Data becomes meaningful in direct relationship to the questions we ask to collect it. It becomes effective communication when we craft well-evidenced stories about what it means. Storytelling involves a three-part relationship between the teller, audience, and story. Handing an uninterpreted spreadsheet to our stakeholders-as-audience and expecting them to glean the meaning for themselves is irresponsible, because it abdicates our relationship to the audience as storytellers and leaves them not only confused but also uncertain about whose perspective the data represents. Telling the story also makes it clear who could answer questions--the storyteller.
When you ask people for data, you ask them to tell you something. Maybe it's not a story, maybe it's just a series of clicks in response to questions. No matter how big or small, when you collect data from people you have an opportunity to connect with them more deeply, as the audience members and co-creators of your ongoing mutually beneficial story. You can connect by telling them what you learned, partly from them, about the work you are trying to accomplish and how well your services are working.
The impact of data is only as effective as the story you tell about it, so put story before storage. Do it for the relationships it helps to foster, the ongoing community collaborations you need, and for the sake of future opportunities for new stakeholders to connect with your organization. Don't stop with data storage; your job isn't done until you've used data to tell a story. That way, you've stored the meaning that allows those who come after you to understand why you made the decisions you did.
