Implementing Employee Surveys

Stop pasting interview transcripts into ChatGPT and asking for a summary. You’re not getting insights—you’re getting blabla. Here’s how to actually extract signal from qualitative data with AI. A lot of product teams are experimenting with AI for user research. But most are doing it wrong. They dump all their interviews into ChatGPT and ask: “Summarize these for me.” And what do they get back? Walls of text. Generic fluff. A lot of words that say… nothing. This is the classic trap of horizontal analysis: → “Read all 60 survey responses and give me 3 takeaways.” → Sounds smart. Looks clean. → But it washes out the nuance. Here’s a better way: Go vertical. Use AI for vertical analysis, not horizontal. What does that mean? Instead of compressing across all your data… Zoom into each individual response—deeper than you usually could afford to. One by one. Yes, really. Here’s a tactical playbook: Take each interview transcript or survey response, and feed it into AI with a structured template. Example: “Analyze this response using the following dimensions: • Sentiment (1–5) • Pain level (1–5) • Excitement about solution (1–5) • Provide 3 direct quotes that justify each score.” Now repeat for each data point. You’ll end up with a stack of structured insights you can actually compare. And best of all—those quotes let you go straight back to the raw user voice when needed. AI becomes your assistant, not your editor. The real value of AI in discovery isn’t in writing summaries. It’s in enabling depth at scale. With this vertical approach, you get: ✅ Faster analysis ✅ Clearer signals ✅ Richer context ✅ Traceable quotes back to the user You’re not guessing. You’re pattern matching across structured, consistent reads. ⸻ Are you still using AI for summaries? Try this vertical method on your next batch of interviews—and tell me how it goes. 👇 Drop your favorite prompt so we can learn from each othr.

I tried to compete with AI on data analysis 🤖 Shocker, I lost. Here's what happened... Out of habit, I started analyzing hundreds of detailed responses to an annual survey we send the team after our company retreats. Halfway through, I realized I should have leaned on AI to assist with this 🤦🏻♂️ so I decided to use this as an opportunity to measure the time saved on this routine task. After 7 hours of meticulous manual analysis, I asked Claude (Anthropic's AI) to do the same task. It took 15 minutes to get the same results 😅 Even more impressive, I compared the quality of both analyses, and Claude's was better! It caught the exact same major themes but also spotted patterns I'd missed, probably because I had my own biases about what worked/didn't work. This is probably common sense for many of you now, but just in case, here's how to replicate this process: - Send a feedback form to your team (Google Forms, Typeform, etc) - Export the responses (CSV works best for me) - Upload the file to your AI tool of choice (I use Claude) - Ask it to: Summarize the common themes, list top things that worked well, list areas for improvement, identify data trends, create a TLDR, etc - Share insights with your team The key takeaway for me... Many of us are still adapting to the power of the tools we have at our disposal, and I often find it easy to fall back into doing manual work out of habit or perhaps a bias toward my capabilities. But the use of AI in the modern workplace isn't about replacing human work - it's about complementing it. And it's tasks like these that provide the perfect opportunity to leverage the power of AI so we can focus our energy on implementing the conclusions it helps us create. This was a good reminder for me, hope it's helpful for some of you as well! **Photo below from this retreat in Ireland - stay tuned for another post with more details from the survey and what we learned from this retreat.

Your engagement survey isn't failing to detect the problem. It has quietly become part of it. That's the argument a work psychologist made in People Management recently: employee surveys are now actively hiding a widening wellbeing gap, because the people with the most to say have learned that saying it changes nothing, so they've stopped saying it, and response rates decline in exactly the places leaders most need to hear from. Organisations have built sophisticated listening infrastructure, pulse surveys, sentiment analysis, while the acting infrastructure, the bit that turns what was heard into a decision someone owns, has barely moved since the annual survey came in a PDF. The result is a machine that measures disappointment with ever-increasing precision. Employees don't suffer from survey fatigue; they suffer from inaction fatigue, and the tenth questionnaire simply arrives as confirmation. The fix isn't fewer surveys or shinier dashboards. It's response architecture: before you ask, decide who will act on what you hear, by when, with what authority, and tell people that up front. Ask less, answer more. The better the listening tools get, the more listening substitutes for responding, because it feels like action and photographs like it too. What's the best response architecture you've actually seen attached to a listening exercise, the mechanism that made acting non-optional? Specifics welcome, I'm building a repository of these. #participation #facilitation #organisationalchange #employeevoice #futureofwork

Recently, I was giving a talk on people analytics and employee listening when someone asked, “How do you overcome survey fatigue?” Here’s my hot take: survey fatigue is a myth. Think about it — if you approach someone with genuine curiosity and ask them about their experiences or opinions, how often do they say, “No thanks, I’m tired of sharing my thoughts”? Probably never. People love to be heard. What they don’t love is wasting their time. Or as Morgan Williams put it: It’s not survey fatigue, it’s "inaction fatigue." Employees don’t get tired of surveys; they get tired of giving feedback that goes nowhere. So, if you’re seeing low participation, ask yourself:  📊 Have we shared the results? (Yes, even when scores are low!)  ➡️ Have we shown employees ways their feedback led to real change? The best way to increase survey participation isn’t to send fewer surveys — it’s to *close the loop*. Share what you’ve learned. Take action. Make it clear that feedback actually matters.

Remember that bad survey you wrote? The one that resulted in responses filled with blatant bias and caused you to doubt whether your respondents even understood the questions? Creating a survey may seem like a simple task, but even minor errors can result in biased results and unreliable data. If this has happened to you before, it's likely due to one or more of these common mistakes in your survey design: 1. Ambiguous Questions: Vague wording like “often” or “regularly” leads to varied interpretations among respondents. Be specific—use clear options like “daily,” “weekly,” or “monthly” to ensure consistent and accurate responses. 2. Double-Barreled Questions: Combining two questions into one, such as “Do you find our website attractive and easy to navigate?” can confuse respondents and lead to unclear answers. Break these into separate questions to get precise, actionable feedback. 3. Leading/Loaded Questions: Questions that push respondents toward a specific answer, like “Do you agree that responsible citizens should support local businesses?” can introduce bias. Keep your questions neutral to gather unbiased, genuine opinions. 4. Assumptions: Assuming respondents have certain knowledge or opinions can skew results. For example, “Are you in favor of a balanced budget?” assumes understanding of its implications. Provide necessary context to ensure respondents fully grasp the question. 5. Burdensome Questions: Asking complex or detail-heavy questions, such as “How many times have you dined out in the last six months?” can overwhelm respondents and lead to inaccurate answers. Simplify these questions or offer multiple-choice options to make them easier to answer. 6. Handling Sensitive Topics: Sensitive questions, like those about personal habits or finances, need to be phrased carefully to avoid discomfort. Use neutral language, provide options to skip or anonymize answers, or employ tactics like Randomized Response Survey (RRS) to encourage honest, accurate responses. By being aware of and avoiding these potential mistakes, you can create surveys that produce precise, dependable, and useful information. Art+Science Analytics Institute | University of Notre Dame | University of Notre Dame - Mendoza College of Business | University of Illinois Urbana-Champaign | University of Chicago | D'Amore-McKim School of Business at Northeastern University | ELVTR | Grow with Google - Data Analytics #Analytics #DataStorytelling

PSA: Your engagement survey is a clue NOT a conclusion. And like any good mystery, one clue doesn’t solve the case. Yet I still see teams using it as their source of truth. But that "truth" is in fact a teeny tiny window into the real problem. If you're a team wanting to design people experiences that actually change things for your teams AND your business you must have the full picture. That means triangulating your data and validating assumptions by spotting patterns across different types of data, including: 🔢 Quantitative → e.g. survey scores, time-to-productivity, delivery metrics 💬 Qualitative → e.g. onboarding, stay and exit interviews, Glassdoor reviews 📈 Behavioural & Operational → e.g. Slack usage, LMS completion, 1:1s And here's why... 💬 Survey says: “I feel connected to my team during onboarding.” (High score) Oooh fab, job done. We're nailing it... But, woah hold up a minute... 🎙️ Interviews reveal: “I only spoke to my manager, I didn’t really meet anyone outside my team until week 3.” Erm... 📊 Behavioural data shows: Only 20% of new hires joined the ‘Meet the Team’ virtual social. So what’s really going on? The data now tells us that new starters feel some connection (likely with their immediate team), but broader belonging is delayed. That high score is masking a deeper gap in weak cross-functional connection and slow social integration. ↑ And this is your problem to solve. Because sure, we can all ride the survey score high for a day or two… But give it a few weeks, and suddenly, we’re wondering why things still feel off. That’s what happens when we hang our hats on one shiny data point. So this is your friendly reminder to go beyond the survey and build the full story. Because when you define the right problem to solve, that's when you design people experiences that deliver. How do you make sure you're focusing on the right problem to solve? Would love to hear your thoughts in the comments 👇 #EmployeeEngagement #EmployeeExperience #DesignThinking ------ Hi 👋 I'm Alicia, co-founder of The Future Kind. We collaborate with founders, C-suite and People Ops leaders to design company operating systems that scale. Want to know more? Follow along or DM me, I love to hear form you. 💌

Why your company's engagement data isn’t telling you the full story.⬇️ Several times a year, I’m called in to help a company disappointed by their engagement data. They show me survey results—averages, percentages, and question breakdowns. And every single time, I see the same mistake: They focus on averages. But averages tell you nothing about what’s really happening. Engagement isn’t a company-wide metric. It’s the sum of individual team experiences. So, here’s what I do instead:  1️⃣ Break the data down by region, office, or team leader.  2️⃣ Focus on leaders—they drive engagement. 3️⃣ Look for patterns—who lifts, who lags? For example, I recently worked with a company to raise engagement across their teams. We identified what the best leaders were doing differently:  - Making time for meaningful, consistent conversations.  - Focusing on simple habits that extend beyond work.  - Building trust and creating psychological safety. Then, we brought those habits to leaders who were struggling—not to criticize, but to equip them with the tools that top-performing leaders already use. 9 months later, the company ran the survey again. Engagement scores had soared. Not because of sweeping company-wide initiatives. But because small, consistent changes at the team level made the difference. Here’s the lesson for you: If you’re disappointed by your engagement data, don’t just focus on the averages. Look at the leaders driving them—and give them the tools they need to succeed. Because engagement doesn’t live in a survey. It lives in the actions of every team leader, every single day. 

Employee engagement surveys are broken.   There, I said it.   Companies spend thousands each year on surveys. Promising insights into how their people feel.   Yet the results are often inaccurate, incomplete, and unreliable.   And why is this?   1. Mistrust of anonymity Employees open up when surveys feel safe. But 45% think HR can track their answers, so they hold back. Reframe surveys as confidential and explain how the data is used.   2. Outdated survey design Generic surveys miss the mark. Every company is different, so should its questions be. Tailor surveys to your culture and goals to get useful insights.   3. Timing matters Annual surveys? Outdated. Engagement shifts all year. Regular pulse checks give a clearer picture.   4. The trust gap Nothing kills engagement like ignored feedback. If employees don’t see change, they stop caring. Share results, communicate next steps, and follow through.   How do we fix it?   - Run shorter, more frequent pulse surveys. - Focus on patterns, not individual responses. - Follow up with action and communicate results.   Employee engagement builds trust. Not simply collecting data.   Are your surveys doing that?

Nonprofit friends, planning to collect data soon? Remember: Your questions shape your data—but they don’t always get you what you need. Imagine this: You are filling out a border form, and it asks: "Do you exceed duty-free allowances per person?" The only answers are Yes or No. For someone who didn't bring any goods, selecting No implies they did get something but stayed within the limit. The question doesn't account for people for whom the question is irrelevant, forcing them to provide inaccurate information. Now think about your data collection tools (say, your last survey): ● Are your questions boxing people into answers that don't reflect their reality? ● Are you assuming experiences that don't apply to everyone? ● Are you unintentionally excluding voices by limiting response options? Poorly worded questions = bad data = flawed decisions = a loss of trust. Here are three examples of common pitfalls: ● Assumptions baked into questions Example: “What barriers prevent you from attending our events?” assumes the respondent knows about your events and faces barriers. A better question: “Have you heard of our events?” followed by, “What barriers, if any, prevent you from attending?” ● Excluding relevant options Example: “Which of these programs have you used?” but leaving out “I haven’t used any.” Guess what happens? People pick a random answer or leave it blank, and now your data is a mess. ● Vague questions Example: “On a scale of 1-5, how satisfied are you with our communication?” Without specifying—emails? Social media? In-person?—responses will be all over the place. Your questions are your bridge to listening and understanding. Two things to remember here (and by no means this is the complete list): ● Plan your survey – the why, what, how, when, what-next… before jumping to design ● Use inclusive language, providing options like "Does not apply.", wherever relevant. Ensuring people responding to it can see themselves in the questions and responses is the only way to give them the true choice of what and how much they want to share with us. Please reach out if you want to plan a Survey Kaleidoscope workshop with your team on your upcoming survey (for context, it's a workshop where we solely plan the survey collectively - every single element of how to ensure a successful survey happens) #nonprofits #nonprofitleadership #community

A few years ago, I tried to convince a CEO we should run an employee survey. He looked at me and said, “Why? So we can create a colorful PowerPoint about feelings and then do absolutely nothing with it?” Honestly… fair. He’d seen the movie before: -100+ questions -Good participation -Beautiful charts -Zero change -Collective employee eye-roll At the time, I was determined to prove a survey could be more than a corporate ritual we perform between budgeting season and the holiday party. Here’s what I learned: An employee survey isn’t about asking questions. It’s about deciding what you’re actually willing to hear. And what you’re willing to do about it. Our first draft survey was… ambitious. We asked everything. Engagement. Benefits. Leadership trust. Office snacks. Probably the emotional impact of the expense policy. It was thoughtful. It was thorough. It was also completely unfocused. The CEO asked me one question that changed everything: “What decision will this data help us make?” Silence. We weren’t clear on what we really wanted to learn. We were going through the motions because “good companies run surveys.” So we scrapped it and started over. Instead of starting with questions, we started with intent: -Where are we guessing instead of knowing? -What’s getting in the way of great work? -What are we actually prepared to fix? -What might surprise us? We cut the survey nearly in half. We removed vague questions like, “Do you feel valued?” (valued… by whom? For what?) We replaced them with sharper ones: -What’s one process that makes your job harder than it needs to be? -What does leadership think is working well - but isn’t? -If you could change one thing in the next 90 days, what would it be? The difference was immediate. Participation went up. Comments got specific. Patterns were clear. Within 60 days, we eliminated a clunky approval process, clarified decision rights, and fixed a communication gap that had been frustrating half the company. Nothing revolutionary. Just listening - and acting. And that’s what changed the CEO’s mind. Employees don’t expect perfection. They expect evidence that their input matters. What I took away from that experience: -Don’t ask a question you’re not prepared to act on. -Fewer, sharper questions beat longer, safer surveys. -Specific beats sentimental. -The real work starts after the results come in. -Over-surveying is annoying. Under-listening is fatal. Now, whenever someone says, “We should run a survey,” my first question is: “To learn what?” Because the power isn’t in the form. It’s in the intention behind it. Sometimes tweaking just a few questions doesn’t just change the data. It changes the conversation.