Measuring Employee Engagement in CSR

“Is this statistically significant?” – every stakeholder ever I’ve lost count of how many times I’ve had to answer this. But statistical significance was never designed for qualitative research. We’re not trying to publish academic research We’re not trying to prove universal truths We’re trying to reach theoretical saturation, the point where additional research doesn’t give us new insights Here’s how I handle the question when it comes up: 1. Stop inviting the wrong conversation Numbers like “3 out of 5 users struggled with this” only open the door for debate. Instead, frame findings in a way that’s harder to ignore: ↳ “Users consistently struggled to find this feature.” ↳ “Most participants expected X but got Y.” ↳ “A clear pattern emerged around [pain point].” 2. Reframe the question from stats to risk When stakeholders ask about statistical significance, what they really mean is: “Can we trust this enough to act on it?” My response? “If five people hit the same pothole and wreck their car, how many more do you need before fixing the road?” 3. Shift the focus to theoretical saturation Qualitative research is about reaching a point where more research isn’t adding new insights. ↳ 5 users per segment often surface major issues ↳ 10-15 users per segment usually reach saturation ↳ If you’re still getting new insights after that, your scope is too broad 4. Tie insights to business impact If an insight affects conversion, retention, or revenue, debating sample size is just a distraction ↳ If three enterprise customers say onboarding is confusing, that’s a churn risk ↳ If two usability tests expose a checkout issue, that’s abandoned revenue ↳ If one customer interview reveals a security concern, that’s a crisis waiting to happen 5. Flip the question back on them Next time someone asks if your findings are statistically significant, ask: ↳ How many lost users would be enough to take this seriously? ↳ How much revenue would we need to lose before fixing this? ↳ Would you want us to wait for more data if this were your experience? Research isn’t about proving something is true. It’s about preventing costly mistakes before they happen. How do you handle the statistical significance debate? Drop your best response in the comments

HR doesn’t need more dashboards. It needs better listening. Most people teams measure what’s easy…like engagement scores or turnover. But the best teams? They build feedback loops that help them predict problems, not just react to them. This post gives you 11 of the most useful, often-overlooked loops you can implement across the employee lifecycle: 🟢 Week 2 new hire check-ins (capture early impressions) 🟠 Post-interview surveys (from both sides) 🔵 Onboarding reviews (day 90 is your goldmine) 🟡 Skip-level 1:1s (cross-level truth-telling) 🟣 Quarterly team health check-ins (lightweight, manager-led) …and 7 more. 📌 Save this if: • You’re building a modern HR function • You want fewer “We should’ve seen this coming” moments • You believe listening is strategy Which feedback loop is missing in your company?

Are you measuring what matters in your organization? A comprehensive measure of organizational effectiveness includes much more than profit margins and growth rates. The market and media often celebrate companies that show rapid financial growth or high profitability, leading to a cultural bias towards these metrics as signs of success BUT the tide is slowly turning- more businesses are recognizing the long-term value of a holistic approach to effectiveness and success. Many more businesses are embracing the concept of the "Triple Bottom Line," which measures success not just by financial profit ("Profit"), but also by the company's impact on people ("People") and the planet ("Planet"). HOWEVER 🚨 There is more work to be done! The prioritization of non-financial elements of organizational success can get pushed aside when financial pressures hit or quick results are valued. You have probably heard the phrase "What gets measured gets managed". This is generally true. Quantifying and measuring non-financial aspects of effectiveness, such as employee well-being, social impact, and workplace culture, is hugely important but remains challenging. 💡 Here's some straightforward steps to move you towards a more holistic approach to measuring success: 𝐒𝐭𝐚𝐫𝐭 𝐰𝐢𝐭𝐡 𝐜𝐥𝐞𝐚𝐫 𝐠𝐨𝐚𝐥𝐬: Define what holistic success means for your organization. This could include specific targets related to employee well-being, social impact, and environmental sustainability. 𝐄𝐧𝐠𝐚𝐠𝐞 𝐬𝐭𝐚𝐤𝐞𝐡𝐨𝐥𝐝𝐞𝐫𝐬: Talk to employees, customers, and community members to understand what aspects of your business matter most to them. Their insights can help shape your holistic success framework. 𝐂𝐡𝐨𝐨𝐬𝐞 𝐫𝐞𝐥𝐞𝐯𝐚𝐧𝐭 𝐦𝐞𝐭𝐫𝐢𝐜𝐬: Based on your goals and stakeholder feedback, pick metrics that are meaningful and manageable. For example, employee satisfaction can be measured through regular surveys, while environmental impact can be tracked through energy consumption or waste reduction metrics. 𝐔𝐬𝐞 𝐞𝐱𝐢𝐬𝐭𝐢𝐧𝐠 𝐟𝐫𝐚𝐦𝐞𝐰𝐨𝐫𝐤𝐬: Look into established frameworks (like GRI or B Corp standards for sustainability; Gallups Q12 Engagement Survey for employee engagement or the Denison Organizational Culture Model to measure workplace culture). There are existing frameworks for most known elements of organizational effectiveness so it's just a matter of looking into them. 𝐈𝐧𝐭𝐞𝐠𝐫𝐚𝐭𝐞 𝐢𝐧𝐭𝐨 𝐝𝐞𝐜𝐢𝐬𝐢𝐨𝐧-𝐦𝐚𝐤𝐢𝐧𝐠: Ensure that these holistic metrics are part of regular business reviews and decision-making processes, not just side projects. 𝐑𝐞𝐩𝐨𝐫𝐭 𝐭𝐫𝐚𝐧𝐬𝐩𝐚𝐫𝐞𝐧𝐭𝐥𝐲: Share your progress openly, including both successes and areas for improvement. Transparency builds trust and credibility. 𝐂𝐨𝐧𝐭𝐢𝐧𝐮𝐨𝐮𝐬 𝐥𝐞𝐚𝐫𝐧𝐢𝐧𝐠: Be prepared to adapt and refine your approach as you learn what works and what doesn't. This is a journey, not a one-time task. #organizationaleffectiveness #measurewhatmatters #leaders

If you care about culture, measure it like you would any other part of your business - sales, profits, innovation. In my interview with Kae Kronthaler-Williams, I learned that: Culture Needs Tangible Metrics, Not Just Talk: Organizations must treat culture like a business outcome, measuring it with the same rigor they apply to revenue and profit. This means looking at metrics such as retention rate and understanding that the main drivers of people leaving are burnout, not feeling supported, and lack of career growth. Focus on the "How," Not Just the "What": Performance reviews and rewards must balance the results an employee achieves with how they achieve them. A high performer who creates a toxic work environment will ultimately cost the company more in lost talent than the revenue they generate. Companies should actively reward behaviors like leading with empathy and being a "culture maker". Support and Train Your Managers: Middle managers are essential to the employee experience, but are often stuck without the right tools. Equipping them with skills like giving constructive, behavior-based feedback and knowing how to coach their teams is vital. Furthermore, organizations must audit workloads to prevent burnout and shift non-promotable tasks to avoid over-burdening women and marginalized employees. Read full piece here: https://lnkd.in/gd4rUvkM #culture #leadership #talent

#PeopleAnalytics: Turning #HRMetrics into #Strategic Insights In today’s data-driven organizations, HR is evolving from a support function to a strategic powerhouse. These HR Metrics are more than just numbers; they’re lenses through which we can understand workforce dynamics, organizational health, and business impact. Let’s break it down: 🔹 Absenteeism Rate: A high rate may signal burnout, disengagement, or systemic issues in workplace culture. Tracking it helps identify patterns and intervene early. 🔹 Employee Attrition & Retention: These twin metrics reveal the stability of your workforce. High attrition can be costly and disruptive, while strong retention often reflects good leadership and employee satisfaction. 🔹 Internal Promotion Rate: A key indicator of talent mobility and succession planning. Promoting from within boosts morale and reduces hiring costs. 🔹 Cost Per Hire & Time to Hire: Efficiency metrics that reflect the effectiveness of your recruitment strategy. Long hiring cycles or high costs may point to process inefficiencies or misaligned sourcing channels. 🔹 Offer Acceptance Rate: A direct measure of your employer brand and candidate experience. Low acceptance rates might mean your value proposition isn’t resonating. 🔹 Human Capital ROI: This is the ultimate business case for HR—how much return you’re getting from your investment in people. It’s a powerful metric for aligning HR with financial performance. 🔹 Employee Engagement: Often measured through surveys, this metric captures how emotionally and cognitively invested employees are in their work. High engagement is correlated with productivity, innovation, and employee retention. 💡 Why it matters: These formulas empower HR teams to move from reactive to proactive. They help diagnose problems, forecast trends, and make evidence-based decisions that drive business value. People analytics isn’t just about tracking—it’s about transforming. #PeopleAnalytics #HRStrategy #HumanCapital #WorkforceInsights #EmployeeExperience #DataDrivenHR #Leadership #FutureOfWork #LinkedInHR #HRLeadership

Most teams are just wasting their time watching session replays. Why? Because not all session replays are equally valuable, and many don’t uncover the real insights you need. After 15 years of experience, here’s how to find insights that can transform your product: — 𝗛𝗼𝘄 𝘁𝗼 𝗘𝘅𝘁𝗿𝗮𝗰𝘁 𝗥𝗲𝗮𝗹 𝗜𝗻𝘀𝗶𝗴𝗵𝘁𝘀 𝗳𝗿𝗼𝗺 𝗦𝗲𝘀𝘀𝗶𝗼𝗻 𝗥𝗲𝗽𝗹𝗮𝘆𝘀 𝗧𝗵𝗲 𝗗𝗶𝗹𝗲𝗺𝗺𝗮: Too many teams pick random sessions, watch them from start to finish, and hope for meaningful insights. It’s like searching for a needle in a haystack. The fix? Start with trigger moments — specific user behaviors that reveal critical insights. ➔ The last session before a user churns. ➔ The journey that ended in a support ticket. ➔ The user who refreshed the page multiple times in frustration. Select five sessions with these triggers using powerful tools like @LogRocket. Focusing on a few key sessions will reveal patterns without overwhelming you with data. — 𝗧𝗵𝗲 𝗧𝗵𝗿𝗲𝗲-𝗣𝗮𝘀𝘀 𝗧𝗲𝗰𝗵𝗻𝗶𝗾𝘂𝗲 Think of it like peeling back layers: each pass reveals more details. 𝗣𝗮𝘀𝘀 𝟭: Watch at double speed to capture the overall flow of the session. ➔ Identify key moments based on time spent and notable actions. ➔ Bookmark moments to explore in the next passes. 𝗣𝗮𝘀𝘀 𝟮: Slow down to normal speed, focusing on cursor movement and pauses. ➔ Observe cursor behavior for signs of hesitation or confusion. ➔ Watch for pauses or retracing steps as indicators of friction. 𝗣𝗮𝘀𝘀 𝟯: Zoom in on the bookmarked moments at half speed. ➔ Catch subtle signals of frustration, like extended hovering or near-miss clicks. ➔ These small moments often hold the key to understanding user pain points. — 𝗧𝗵𝗲 𝗤𝘂𝗮𝗻𝘁𝗶𝘁𝗮𝘁𝗶𝘃𝗲 + 𝗤𝘂𝗮𝗹𝗶𝘁𝗮𝘁𝗶𝘃𝗲 𝗙𝗿𝗮𝗺𝗲𝘄𝗼𝗿𝗸 Metrics show the “what,” session replays help explain the “why.” 𝗦𝘁𝗲𝗽 𝟭: 𝗦𝘁𝗮𝗿𝘁 𝘄𝗶𝘁𝗵 𝗗𝗮𝘁𝗮 Gather essential metrics before diving into sessions. ➔ Focus on conversion rates, time on page, bounce rates, and support ticket volume. ➔ Look for spikes, unusual trends, or issues tied to specific devices. 𝗦𝘁𝗲𝗽 𝟮: 𝗖𝗿𝗲𝗮𝘁𝗲 𝗪𝗮𝘁𝗰𝗵 𝗟𝗶𝘀𝘁𝘀 𝗳𝗿𝗼𝗺 𝗗𝗮𝘁𝗮 Organize sessions based on success and failure metrics: ➔ 𝗦𝘂𝗰𝗰𝗲𝘀𝘀 𝗖𝗮𝘀𝗲𝘀: Top 10% of conversions, fastest completions, smoothest navigation. ➔ 𝗙𝗮𝗶𝗹𝘂𝗿𝗲 𝗖𝗮𝘀𝗲𝘀: Bottom 10% of conversions, abandonment points, error encounters. — 𝗕𝘂𝗶𝗹𝗱𝗶𝗻𝗴 𝗮 𝗖𝗼𝗻𝘀𝗶𝘀𝘁𝗲𝗻𝘁 𝗦𝗲𝘀𝘀𝗶𝗼𝗻 𝗥𝗲𝗽𝗹𝗮𝘆 𝗣𝗿𝗮𝗰𝘁𝗶𝗰𝗲 Make session replays a regular part of your team’s workflow and follow these principles: ➔ Focus on one critical flow at first, then expand. ➔ Keep it routine. Fifteen minutes of focused sessions beats hours of unfocused watching. ➔ Keep rotating the responsibiliy and document everything. — Want to go deeper and get more out of your session replays without wasting time? Check the link in the comments!

Improving productivity is a crucial aspect of enhancing company efficiency. Generative AI (GenAI) tools like ChatGPT and tailored LLM models hold great promise in achieving this goal. A recent blog post by Intuit's data team explores their study investigating the impact of these tools on data analyst productivity. The study recruited several internal analysts from different business units, spanning various tenures and levels of analytics experience, to ensure diverse participation. Half of the analysts were given access to an internal GenAI tool and tasked with completing representative work assignments within an hour. The study carefully balanced tasks involving both familiar and unfamiliar domains to account for domain expertise. The results revealed a significant productivity increase among GenAI tool users, with SQL tasks being completed 2.2 times faster, or a 55% reduction in time, compared to the control group. Interestingly, the study found that junior analysts experienced the most substantial productivity gains, as well as those tasks involved handling unfamiliar data. This study sheds light on effective approaches to measuring productivity enhancements in the data analyst domain. Despite potential issues with hallucination and accuracy in GenAI tools, their integration with proper user experience interaction proves highly beneficial for productivity enhancement. As more industrial-customized LLM models emerge, they may herald a forthcoming trend in elevating productivity in the analytical domain. #data #analytics #llm #generativeai #productivity #experiment – – –  Check out the "Snacks Weekly on Data Science" podcast and subscribe, where I explain in more detail the concepts discussed in this and future posts:    -- Apple Podcast: https://lnkd.in/gj6aPBBY    -- Spotify: https://lnkd.in/gKgaMvbh https://lnkd.in/gAxNBbCg

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. 

Abraham Maslow’s hierarchy of needs has been a foundation for understanding human motivation since the mid-20th century. But as a researcher and leadership coach, I began asking: how does this apply to today’s workplace? That question led me to develop a modern framework, building on Maslow’s theory, to measure workplace culture. Our research identified three key categories of workplace needs: basic, psychological, and growth needs. 🔹 Basic Needs This is about how an organization supports its employees. In the post-COVID workplace, employees have more basic needs and higher expectations from their employers. These include: ▫️ Onboarding ▫️ Job Security ▫️ Networking ▫️ Inclusivity ▫️ Creative Workspace ▫️ Clean Workspace ▫️ Safe Workspace ▫️ Consideration ▫️ Wellbeing ▫️ Compensation ▫️ Benefits ▫️ Tools & Technology ▫️ Training 🔹 Psychological Needs Our research shows that relationships at work matter more than ever. The psychological needs focus on how employees connect with their coworkers. We identified three key needs here: ▫️ Positive Interactions ▫️ Belonging ▫️ Camaraderie 🔹 Growth Needs Here’s where leadership comes into play. The most significant finding at this level was that employees' highest growth needs are directly tied to their relationship with their leaders. Employees look for leaders who model values, provide clear goals, and offer ongoing support. The 10 growth needs include: ▫️ Leadership Role Modeling ▫️ Values Role Modeling ▫️ Clear Goal Setting ▫️ Purpose Broadcasting ▫️ Constructive Feedback ▫️ Inclusive Decision Making ▫️ Belief in Potential ▫️ Mentoring ▫️ Coaching ▫️ Cohesiveness The new hierarchy of workplace needs centers around leadership, cohesive teams, and an organization that truly understands the changing priorities of its people. Meeting these needs helps employees bring their best selves to work—what we call Culture-Actualization©. This idea is also the core of my upcoming book, Leading With Culture: Second Edition, coming out in December. I’m excited to share more about how organizations can unlock their full potential by focusing on what their employees truly need. #LeadingWithCulture #FutureofWork #CultureActualization

🔍 Research Snapshot: Why Learning & Development Isn’t Just Nice—It’s Essential Today, I’m digging into evidence that L&D does more than spark growth—it fuels performance, retention, and revenue. 📈 1. L&D drives revenue According to Deloitte, a 1% increase in per-employee L&D spend is associated with a 0.2% increase in business revenue—which translates to ~$4.70 return for every $1 invested. 🔗 Deloitte: The Business Return on Learning & Development https://lnkd.in/eVyqGRYm 🔄 2. It retains talent Companies with strong learning cultures experience 57% higher retention than those without. And 94% of employees say they’d stay longer at a company that invests in their learning. 🔗 LinkedIn Workplace Learning Report - https://lnkd.in/eppTiNG3 Learning access reduces intent to leave, especially among Gen Z and Millennials. 🔗 UK Government Rapid Review on L&D and Retention - https://lnkd.in/e_94_2vz ❤️ 3. Engagement fuels performance & loyalty 92% of employees say professional development positively impacts job engagement. 🔗 Devlin Peck: Employee Training Statistics - https://lnkd.in/ekCTQ_SZ Gallup finds that learning investment strengthens connection, purpose, and intent to stay. 🔗 Gallup: Building a Culture That Retains Employees - https://lnkd.in/eBaY7naH 🧠 What This Means for L&D Teams: Stop calling it a cost. Start calling it what it is: a growth strategy. If you’re advocating for a 1–2% increase in L&D spend, you now have credible ROI benchmarks to reference. Don't just build programs—build a learning culture. That’s what drives outcomes that last. 💬 Over to You: What’s one L&D investment your org made this year that paid off in real impact—on revenue, retention, or performance? Drop it in the comments. I may feature a few in next week’s post (with your permission, of course). #HiddenValue #LND #StrategicLearning #ValueCreation #LearningCulture #BusinessImpact #TalentDevelopment #FutureOfWork #TrustedLearningAdvisor