How to kick off any big project: Ask lots of questions

Before diving into a big project, it’s common to have a kick-off meeting with team members and stakeholders to discuss hopes, dreams and ideas. With our Journalism 360 Challenge project, we tried a new structure for kick-off meetings, with the hope of setting more specific expectations and avoiding common pitfalls like “I really wish we’d thought of X.”

Based on A List Apart’s “Kick Ass Kickoff Meetings,” Seth Blanchard wrote a series of questions to ensure everyone was on the same page at the beginning and everyone is involved who should be involved. After answering as many questions as we could, we reviewed the list with our editors and filled in the blanks.

To help you understand our answers, I’ll explain a bit about our project. We’re researching if bias is detectable in readers’ facial expressions as they read news-related statements. Our end goal is to help readers understand the bias they bring to the news they consume, by incorporating each reader’s own facial expressions in the analysis.

To do this, we partnered with researchers from Ohio State University and the University of California, Irvine, who specialize in computer vision, facial expression analysis and bias. We worked together to design an activity where participants’ facial expressions are recorded as they read a series of news-related statements and answer whether they think those statements are true or false. We’ll run the data through an algorithm to determine if there is a facial expression that corresponds to bias. After the data collection phase, we’ll be working on further reporting, design and development to present this information to our readers.

Now, back to the outline. You don’t need to answer every question before you start, but I recommend answering the big picture, organization and scheduling questions before moving forward. The story, design and technical questions are pretty specific to our project, so remember to brainstorm your own. I’ve included our original answers to the big picture questions to get you started.

What are your tips and must-dos before starting a big project? Let us know in the comments!

Big Picture Questions

  1. What is the one thing we must get right to make this project worthwhile?
  • Base experience on reliable research.
  • Accurately analyze readers’ facial expressions.

2. What is success for this project?

  • Readers complete the experience and learn something about how their mind processes information.
  • We learn how to work with facial expression recognition software and the front-facing camera.
  • Journalists learn from and repurpose our open source documentation.

3. What could put this project at risk?

  • Not making time for usability testing.
  • Not finding the right researchers to collaborate with.
  • Stakeholders not involved early or often enough. Not enough demos.

Specific Questions


  1. Who is the decider?
  2. Whom do we need final sign-off from?
  3. What teams are working on this?
  4. What stakeholders do we need to interview?
  5. Do we want to do a sprint week?
  6. How are we tracking tasks?


  1. How frequently do we want to demo for editorial?
  2. How frequently do we want scope check-ins?
  3. What is our meeting cadence? How soon do we start daily scrums?
  4. When are we doing user testing and what is it focused on?
  5. What is our deadline?


  1. What are the formal grant requirements?
  2. What else do we want to do to build community?
  3. How do we want to structure our documentation?
  4. How frequently should we document our process?


  1. What scientists are we working with?
  2. What topics work for measuring bias?
  3. What studies can we use as a starter for this work?
  4. How do we use emotion as a measure of bias?
  5. What source material will the reader look at?
  6. Do we need a written component as the entry point? If yes, who will write it?
  7. Should we be focusing on a particular type of bias? (Confirmation, availability, anchor, rush to solve, asymmetrical attention?)


  1. How do we illustrate what we are measuring?
  2. How are we going to make onboarding better?
  3. How are we going to explain the technology to readers/editorial?
  4. What does sharing look like?
  5. How do we make people care?


  1. What platforms can we do this on? Can we do it on the web?
  2. How do we do face tracking on native?
  3. Is the emotion measuring fast enough for this?
  4. What emotion recognition API is the best? How much does it cost?
  5. How are we going to make onboarding better?
  6. If we’re working in native, what is our process for updating and testing builds?
  7. What is the server side setup for this? Can we get enough throughput? Does the cost of this bother us at all? What about the long tail?