StoryEngine is way to listen to and learn from the people who matter most to an organization or a cause. It can be used to do research, monitor or evaluate a program, generate learning, or facilitate grant reporting. StoryEngine is based in-depth interviews that get transformed into stories. These stories are data points as well as assets — for communications, advocacy, and more. Story collections form a dataset that can analyzed to surface insights and inform strategy and design decisions.
What is StoryEngine?
StoryEngine is an easy way for organizations to listen to and learn from the people they serve. We call it an “engine” because it generates narratives that can be used to power both communications and decision-making.
StoryEngine is unique because it sets up a system to serve multiple organizational functions: communications, learning, research, grant management, monitoring and evaluation. Typically, these different functions have their own ways of collecting and processing data — and they often work independently from one another, which can lead to inefficiencies and problems. By setting up one intake system, each of these departments can build on each other’s work and better manage relationships with participants. One process also means that staff are co-learning as they engage with the stories — it’s like an ongoing, default workshop about your most important users. And a shared knowledge base.
From the participant’s perspective, StoryEngine is different because we focus on the experience of the interview. We strive to create a transformational experience — we recognize that an interview is a key touchpoint with an organization or a brand — and we’re always looking for ways to give back to people who take the time to share their story. We conduct our interviews via video or in person and practice deep listening, which means we’re fully present and use paraphrasing and follow-up questions to reflect back and check what we’re hearing.
The way we interview provides opportunities for new perspectives and insights to emerge. We surface moments when people felt a sense of success, had a breakthrough, or faced a challenge. We dig into the “why” of those moments to get at purpose, underlying values, and needs. On a more practical level, we work with participants to edit their words — so by the end of the process they have some solid language they can use to promote their work or help others better understand what they do. Stories become tweets and blogs, get embedded into proposals, and are even used to find collaborators.
We say that StoryEngine is easy because there’s nothing fancy or complex about it: We come up with a set of questions, interview people, and transform transcripts into published stories. We then use those stories as raw material to create a bunch of different communication assets, and we analyze story collections, looking for patterns or gaps so that organizations can make better decisions. The magic is in the way we listen and in or commitment to bringing empathy and respect to each step of the process — for individual participants as well as for the organizations who hire us.
StoryEngine might look like just another way to collect “success stories” or “impact narratives” but for us it has evolved into something more profound: a way create moments where people feel heard and understood. Affirmed. For the CEOs or Executive Directors we interview this may not matter. But for people not in positions of power, it can be transformative to have your experiences documented, elevated, and shared with the world.
Dave Isay — the founder of StoryCorps — gets at some of these ideas in his TED Talk, part of a TED Radio Hour episode on “The Act of Listening”. We were blown away by this show because it resonated so deeply with us.
Why did you start working on StoryEngine?
StoryEngine emerged out of a need to design a qualitative data / story intake process for the emerging Mozilla Leadership Network, which was part of Mozilla’s 2020 strategy. The Network was envisioned as a “virtual, year-round MozFest” that would attract and connect leaders and serve as a training ground and a lab. (The Mozilla Open Leaders cohorts / training that we’re a part of now is an evolution of that thinking.)
Chris Lawrence, who was the VP for Learning at the Mozilla Foundation at the time, wanted to better tell the story of the diversity of people and organizations who work to ensure the web remains a public resource. There was a sense that Mozilla needed more human impact stories to bring the numbers to life. Stories that would spark empathy and understanding and tell a clearer story about the Foundation’s work and its impact. From the outset, Chris was envisioning a system that would serve existing projects, initiatives, and teams — network survey and mapping efforts, curriculum being developed around open leadership, and Mozilla staff working on research, advocacy, fundraising, and the “State of the Web”, which is now the Internet Health Report. The idea was to produce a steady stream of content that could also be analyzed to identify emerging trends and themes and that could be curated and used across diverse media to illuminate core Internet health issues.
We got started in May 2016 and by 2017 we realized that we had created a methodology that could be helpful to other organizations, so we started the processes of documenting StoryEngine as an open project, and spun it off from Mozilla with Loup as its steward.
How does StoryEngine help an organization or individual make discoveries about their practices?
StoryEngine helps individuals learn about their own practice by creating space for reflection with the interviewer acting as a facilitator, asking follow-up questions and re-stating what they’ve heard to check understanding. When people give us vague answers, we push them gently for answers that are grounded in specific moments in time.
We’ve since been working with a learning expert, Joy Amulya, and through her we learned that reflecting on grounded, lived experiences is at the core of practitioner learning. That’s learning that comes from your own work — not from some outside source or “expert”. We believe that recognizing and elevating this type of learning is important because it is linked to boosting a sense of agency and self-efficacy, which is just a fancy way of saying it makes people stronger. More powerful.
Discovery also happens during the editing process. The time lapse between the interview and editing the final story allows individuals to consider what they said with a fresh perspective — to interrogate their own thinking. The editor facilitates this process by asking clarifying questions during the editing process. We knew we were on to something when participants started thanking us and saying things like “Wow, this was like therapy!” Recently, a participant wrote to tell us that they’re using their interview as part of their “auto-ethnography” into open practices.
Organizations can make discoveries about their practices by analyzing the corpus — the collection of StoryEngine narratives related to their work — to look for patterns and insights, as well as to test assumptions, especially around their theory of change and the impacts their work is generating (or not). This analysis can be done by a few coders, using qualitative research methods, or it can be done by a group of people in a face-to-face workshop or asynchronously over the web. The discoveries that emerge can feed into existing planning or design processes.
Of course, this listening and learning process is more powerful when it is regular and ongoing. And it’s important to flag that collecting the stories doesn’t automatically lead to insights — organizations need to engage with a set of stories and be able to take in and use what they’re hearing. Organizational dynamics and politics can get in the way, so engaging an outside facilitator and committing to the learning process matters. A lot.
We’ve also learned that people or teams within an organization can benefit by reading some stories. StoryEngine helps them develop a clearer understand of who the work is for — and what those people actually want. When you bring staff closer to the experience of real stakeholders on the ground, it boosts their understanding, empathy, and ideas for improvement. In one of the StoryEngine use cases, Stephanie Wright, Mozilla’s Open Science Program Lead, told us that what she learned from the stories ended up changing the program’s design. They were about to cut a part of the program that their participants reported as super powerful; instead, they doubled down on that investment. Tais Lessa, a User Experience Designer, used her reading of 30 stories to create personas to inform the design of Mozilla Pulse, which gathers and highlights projects from across the Mozilla ecosystem. What helped her most was building those personas with her team. So it was a shared process — together they created a common understanding of the humans they were designing for. She told us that StortEngine was essential to designing for such a diverse group of people.
Can you describe deep listening and how it makes StoryEngine different from other research or consultancy models?
Deep listening is defined by what the interviewer brings to the interaction: presence, patience, curiosity, preparation, and empathy.
Presence is about focus. It’s normal for our thoughts to wander while speaking with others; we’re mindful of that and keep bringing ourselves back to the moment, back into the interview. Presence allows us to take in non-verbal cues, to paraphrase what we’re hearing, and to ask follow-up questions that spark thinking and responses that go beyond the surface or the obvious.
Patience is important because people can find it difficult or scary to express their thoughts. We let folks know that silence, stopping and shifting to another line of thought, and contradictions are okay. We stay with them and help them get at what they want to say. Patience is also needed when people give us vague answers. Sometimes we need to ask the same question using different words to help someone remember a moment from their direct, lived experience.
Curiosity is about a mindset of openness — coming to the interaction without preconceived ideas, or naming for ourselves what those preconceptions might be in order to mitigate against them. We’re usually happy when we’re surprised — because that means we created space for something unexpected.
Preparation means that we’ve taken the time, when possible, before the interview to learn about a person or the field they’re working in. An understanding of the context allows us to go deeper with follow-up questions.
Empathy is about an awareness of the participant’s emotional world and how the interview might feel for them. Of course, empathy is not possible without presence — they work together. Listening with empathy means we may ask a participant if they need to take a break, or we may ask a follow-up question based on the tone of a response, rather than just reacting to the actual words.
We think it’s important to flag that you can’t — and wouldn’t want to — do deep listening all of the time. It’s too much. It’s completely exhausting. Surface-level listening is important because it allows us to multitask, coordinate, and save our energy — so we can make it through the day.
So, how is deep listening different from other research and consulting approaches? Well, although it can be used to do “market research”, it draws on practices from facilitation, coaching, and psychotherapy, as well as ideas and values from education and community development. Instead of seeking to extract insights from the people we interview, we’re intentional about how we can give back to the person sharing their thoughts — during the interview as well as afterwards — in the way that their story is amplified, in how we share what we’re learning, and in how we help clients act on what we’ve heard. That’s the consulting side. StoryEngine — and the consulting work that follows — is especially powerful in contexts where building relationships and connections is important. So for organizations working to build movements or strengthen networks, associations, employees, and affiliates. Our ethos and approach is super different from the “Hey! Tell us what you think and we’ll give you a $25 Amazon gift card!” approach.
What challenges have you faced working on this project?
Our main challenges have been related to costs, follow through, and consent.
It’s an investment to process interviews into stories, and then to analyze a collection of stories. Because StoryEngine serves multiple departments — senior leadership, program teams, and others — organizations gain the greatest returns on that investment if they take the time up front to create a shared understanding of how the content and the data will be used, and how the StoryEngine process and outputs will support existing initiatives.
Follow-through challenges relate to interviewees dropping out after we’ve processed their interview and before we’ve published it. Thankfully, dropping out is rare, but given that we’re trying to minimize costs, our clients take a hit when resources invested into transcription and editing don’t result in a story. We’ve observed this most among higher-profile interviewees. To avoid this, we started emphasizing more what’s involved — being clearer around expectations and commitments. That’s helped a lot. That ways, people can decide up front if they want to participate.
Consent is not so much of a challenge, but rather something that we’re very mindful of. Actually, most of our learning around consent comes from an interview we did! We love that. We’re now thinking through how to make it easy for participants to revoke consent, and what that means in practical terms. Given that StoryEngine stories belong to our clients and are distributed under open licenses, we have to be super careful about informing participants about their rights and the risks. We’ve worked with several lawyers and GDPR experts who have helped us think through different scenarios and their implications. We’re really appreciative of their time. Our approach is to design consent processes for the edge cases — for those most at risk. If we get it right for them, we do right by everyone.
What kind of skills do I need to help you?
All different skills welcome! We’d love feedback on documentation and help with communication design — especially visualizing the process. We also need advice on reducing the cost per interview and on developing deep listening learning curricula and participatory analysis workshops. We’d also love folks to test-drive the methodology and work with us to make it better. Help with community engagement and facilitation will also be important as the StoryEngine user community grows. A more detailed list can be found in our contributor’s guide.
How can others join your project at #mozsprint 2018?
First of all, thank you for considering contributing to StoryEngine during #mozsprint! We’re super grateful. For those of you who want to join us, we’ve created a contributor’s guide. And you can go to https://github.com/LoupDesign/StoryEngine/labels/mozsprint for a list of issues ready to be tackled during #mozsprint 2018!
What meme or gif best represents your project?
This doesn’t really represent our project. At all. But it sure made us laugh when we first saw it. We’re actually big fans of mixed-methods research… but sometimes this obsession over big data is too much. And worrisome.
Join us wherever you are May 10–11 at Mozilla’s Global Sprint to work on many amazing open projects! Join a diverse network of scientists, educators, artists, engineers and others in person and online to hack and build projects for a health Internet. Register today
This post by Chad Sansing is licensed under a Creative Commons Attribution 4.0 International License.