Using Analytics to Measure Productivity

She was one of our brightest talents Smart. Committed. A quiet force that lifted the whole team And then... she resigned No warning. No second thoughts. Just… gone. We were stunned. She had everything: a promising future, fair pay, great feedback. So we asked her why. Her words hit like a punch: "I didn’t feel seen. I didn’t feel like we mattered." That moment changed everything. Because the truth is, we missed the signs: - Her engagement score had dropped - Her internal applications went nowhere - She kept going the extra mile with no recognition We had the data. We just didn’t use it wisely. Today, we have no excuse. AI and predictive analytics give us a head start. They help us spot patterns before they become problems: - Who might be silently disengaging? - Where are we overlooking skills and potential? - Are we creating an inclusive space where everyone feels they belong? This isn’t about replacing human connection, it’s about deepening it. When we pair data with empathy, we lead smarter, faster, and more human. Because great HR doesn’t just prevent risks. It unlocks possibility. If we reinforce our data and tools, we can spend even more time on what matters most: making sure people remain at the heart of our organizations. #Talents #PredictiveHR #DataDrivenLeadership #EmployeeExperience #humanresources

Happy employees create successful organizations. People Analytics is the key to building a thriving workforce. This innovative and evolving field that allows organizations to move beyond assumptions and get to data-driven insights about the employee experience. Forward-thinking companies prioritize these essential metrics to measure intangible factors like engagement, loyalty, and job satisfaction that greatly impact its culture: - Employee Net Promoter Score (eNPS): This simple question, "Would you recommend this company as a place to work?", helps assess loyalty and track changes in morale over time. - Leading Indicators of Engagement: While retention and turnover rates are important, they only provide a retrospective view. Organizations now focus on real-time metrics such as attendance and absenteeism to identify early signs of disengagement and take proactive action. - Performance & Productivity Metrics: In addition to measuring raw output, these metrics offer a holistic understanding of employee contribution and potential, providing insights into engagement and well-being. - Time to Hire: It's not just about how quickly a position gets filled. A well-managed Time to Hire indicates strong appeal as an employer and effective recruitment practices - both crucial elements of a positive employee experience. Advanced analytics tools and AI are making it possible to predict turnover risks and engagement trends before they impact the business. And while data alone can’t create a happy workforce, it can tell a story that guides action when it starts with ethical data collection and clear communication to build trust. People Analytics has the power to shape work cultures where employees feel seen, valued, and empowered to grow. 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

Most companies can tell you exactly why a customer abandoned a cart. They have journey maps, behavioral segments, predictive models. They know what triggered the purchase, what almost didn't, and what would bring the customer back. Then ask them why their best employees left last quarter, and most will give you a wild guess. When researchers applied customer-style analytics to frontline retail employees (segmentation, behavioral correlation, task-by-task enjoyment mapping), they found that 𝗵𝗶𝗴𝗵-𝗷𝗼𝘆 𝗲𝗺𝗽𝗹𝗼𝘆𝗲𝗲𝘀 𝗴𝗲𝗻𝗲𝗿𝗮𝘁𝗲𝗱 𝟮𝟱% 𝗺𝗼𝗿𝗲 𝗿𝗲𝘃𝗲𝗻𝘂𝗲 𝗽𝗲𝗿 𝗵𝗼𝘂𝗿 𝘁𝗵𝗮𝗻 𝗹𝗼𝘄-𝗷𝗼𝘆 𝗲𝗺𝗽𝗹𝗼𝘆𝗲𝗲𝘀. A one-percentage-point shift in the share of high-joy workers translated to roughly 0.25% of total annual revenue. The upside of getting the mix right: 5–15% annual sales lift. None of that was visible through a standard engagement survey. The insight that surprised leadership most: the highest-performing segment was later-career, part-time workers who loved the brand, loved customers, and wanted respect, community, and purposeful work. They weren't asking for promotions. They were asking to be understood. Most organizations are still guessing at that. The question is whether you're learning about your people with the same precision you apply to the people who pay you. What would change if you did? Source: Lovich, Joly & Taylor — "Leaders Underestimate the Value of Employee Joy," HBR, March 2026. https://lnkd.in/gRu9H9UD

People Analytics Case: When Performance Is Fine, but Motivation Is Fading The Problem: - Teams are hitting metrics, but energy is low. - Initiative is slipping, collaboration is down, and work feels routine. - You are seeing compliance, not commitment. Key Data Points: - 44 percent of employees say they are doing what is expected but not more. - Peer recognition is down 30 percent from six months ago. - Cross-functional project participation dropped 22 percent last quarter. - Engagement survey comments mention lack of visibility and unclear impact. Applying #NOISEanalysis Needs - Employees want to know their work matters. They need clarity, recognition, and connection to shared goals. Opportunities - Boost motivation without new programs. Use meetings for peer recognition, share team impact stories, and let teams choose how they meet goals. Improvements - Use check-ins to focus on progress made. Help managers connect tasks to broader goals. Track progress, not just end results. Strengths - Teams that reflect weekly on small wins report 18 percent higher motivation. Departments that share peer recognition weekly maintain stronger morale. Exceptions - Motivation stays high where teams link their work to customer results and regularly celebrate progress with peers. Quick Win: Add a short weekly ritual. Ask what progress mattered this week. Use it to spotlight wins, encourage teamwork, and reconnect people to purpose. Why This Works: This is not a performance issue. It is a meaning issue. When people see impact and feel seen, energy returns. NOISE reveals where motivation is fading and where small changes can reignite it. Perfect for team sessions or manager development work.

Annual surveys are dead and ABN AMRO realized it the hard way —by watching engagement data arrive months too late, after the damage was already done. ABN AMRO replaced their once-a-year surveys with a 𝐜𝐨𝐧𝐭𝐢𝐧𝐮𝐨𝐮𝐬 𝐥𝐢𝐬𝐭𝐞𝐧𝐢𝐧𝐠 𝐦𝐨𝐝𝐞𝐥.  Every month, they ask a representative group of employees one core question: Would you recommend this place to work? Plus—open-ended feedback on what’s working and what’s not. Over 𝟏,𝟎𝟎𝟎 𝐜𝐨𝐦𝐦𝐞𝐧𝐭𝐬 𝐩𝐞𝐫 𝐦𝐨𝐧𝐭𝐡 are analyzed using NLP models like TF-IDF, Word2Vec, and SVM. That means 150+ themes clustered and tracked—𝐢𝐧 𝐫𝐞𝐚𝐥 𝐭𝐢𝐦𝐞. And the impact: 1. Spot issues before they spiral 2. Build trust through transparency 3. Align HR insights with quarterly leadership decisions They didn’t just collect data. They turned feedback into fuel—for culture, strategy, and trust. 𝐓𝐡𝐢𝐬 𝐢𝐬 𝐰𝐡𝐚𝐭 𝐩𝐞𝐨𝐩𝐥𝐞 𝐚𝐧𝐚𝐥𝐲𝐭𝐢𝐜𝐬 𝐬𝐡𝐨𝐮𝐥𝐝 𝐥𝐨𝐨𝐤 𝐥𝐢𝐤𝐞. Fast, actionable, employee-led. Not a dashboard no one opens, 10 months too late. When employees feel heard and see change—HR becomes a driver of transformation, not just measurement. #PeopleAnalytics #EmployeeEngagement #HRTech #Leadership #ContinuousListening #FutureOfWork

In today's rapidly changing workplace, understanding your team's emotions has never been more crucial. Enter sentiment analysis—an innovative tool that can transform your workplace culture. Sentiment analysis uses AI to gauge employee feelings from various communication channels, such as emails, chats, and surveys. It provides insights into morale, engagement, and potential pain points, allowing leaders to address issues before they escalate. Here’s how to implement it effectively: 1. Gather Data: Start by collecting feedback regularly, not just during annual reviews. Opt for real-time pulse surveys to get a continuous read on employee sentiment. 2. Analyze Trends: Use sentiment analysis tools to identify patterns in feedback. Is there a recurring theme of dissatisfaction or enthusiasm? Understand the why behind the numbers. 3. Take Action: The real power lies in translating insights into action. If sentiment dips, engage your teams to collaboratively address the root causes. 4. Communicate Openly: Keep lines of communication transparent. Share what you’ve learned and the steps you plan to take. This builds trust and shows your team that their opinions matter. Remember, it’s not just about collecting data; it’s about creating a culture where employees feel seen and heard. What steps are you taking to understand employee sentiment in your organization?

🌐 𝗟𝗲𝘃𝗲𝗿𝗮𝗴𝗶𝗻𝗴 𝗔𝗜 𝗳𝗼𝗿 𝗢𝗗: 𝗧𝗿𝗮𝗻𝘀𝗳𝗼𝗿𝗺𝗶𝗻𝗴 𝗢𝗿𝗴𝗮𝗻𝗶𝘇𝗮𝘁𝗶𝗼𝗻𝗮𝗹 𝗗𝗲𝘃𝗲𝗹𝗼𝗽𝗺𝗲𝗻𝘁 𝘄𝗶𝘁𝗵 𝗗𝗮𝘁𝗮-𝗗𝗿𝗶𝘃𝗲𝗻 𝗜𝗻𝘀𝗶𝗴𝗵𝘁𝘀 Artificial Intelligence (AI) is revolutionizing Organizational Development (OD) by offering powerful, data-driven tools that drive engagement, optimize performance, and enhance decision-making. The impact of AI in OD is backed by compelling research and statistics: ▪ 25% Increase in Employee Engagement: AI-driven tools help organizations monitor engagement levels in real-time, enabling timely interventions that boost productivity and morale. ▪ 30% Reduction in Turnover Rates: Predictive analytics powered by AI can identify employees at risk of leaving, leading to targeted retention strategies that significantly reduce turnover. ▪ 50% Faster Onboarding: AI streamlines the onboarding process by automating training and integrating personalized learning paths, helping new hires become productive more quickly. ▪ 40% Improvement in Diversity & Inclusion (D&I) Initiatives: AI-powered recruitment tools help eliminate unconscious bias, leading to more diverse hiring outcomes and inclusive workplace cultures. ▪ 20% Boost in Productivity: AI’s ability to analyze workflow patterns and employee performance data allows organizations to optimize tasks and resource allocation, resulting in measurable productivity gains. Here's how AI is driving these impressive outcomes: ✅ Predictive Analytics: Analyze vast datasets to predict potential challenges and opportunities. Companies using AI-driven analytics report up to a 60% improvement in the accuracy of workforce planning by anticipating shifts in engagement and productivity. ✅ Personalized Development Plans: Assess individual skills, performance metrics, and career aspirations to craft highly customized development plans. These tailored approaches can lead to a 25% increase in employee retention, as employees feel more supported and aligned with their career goals. ✅ Enhanced D&I: Audit and optimize recruitment processes, identifying and mitigating biases in hiring and promotions. Companies using AI in their diversity efforts have seen a 30% increase in diverse candidates reaching the final interview stages and a 15% improvement in promotion rates for underrepresented groups. ✅ Continuous Feedback Loops: Facilitate real-time, continuous feedback mechanisms, helping organizations stay attuned to employee sentiment and needs. Organizations that implement AI-driven feedback systems experience a 20% increase in employee satisfaction and a rise in engagement. ✅ Optimized Workforce: Analyze workflow and project data to recommend optimal team compositions and task assignments, leading to 20-30% increases in project efficiency and significant reductions in time-to-market for new initiatives. #OrganizationalDevelopment #OD #AI #DataDrivenInsights #EmployeeEngagement #Leadership #Innovation #FutureOfWork #DiversityAndInclusion

Most HR analytics focus on the past when they should be predicting the future. Predictive culture analytics combines traditional engagement data with operational metrics, external benchmarks, and unstructured data sources to forecast potential issues before they manifest. The key components of an effective predictive system include: • Multi-source data integration (HR metrics + operational data + communication patterns) • Pattern recognition algorithms (identifying correlations between culture and outcomes) • Threshold-based alerting (signaling potential issues requiring intervention) • Scenario modeling (simulating how cultural changes might impact performance) • Continuous learning mechanisms (refining models based on actual outcomes) This isn't just better measurement—it's competitive intelligence. When you can predict which teams are likely to experience performance issues 4-6 weeks before traditional metrics show problems, you've moved from reactive to proactive management. The future of HR isn't better reporting. It's predictive intelligence. ♻ Repost if you found this insightful 📣 Follow me, Anthony Calleo, for EX insights 🌐 Contact Calleo EX for a free consultation #EmployeeExperience #EX #CalleoEX #WorkplaceCulture #HumanResources #EmployeeEngagement #DataDrivenCulture

"We had to manage out people days after they got promoted." That's what a well-known, 2,000-person company told us in our early days of building Confirm. A company praised for its great culture. After the promotion cycle, a flood of feedback emerged about how problematic some of the promoted people were—serious enough that they had to be fired. That’s what happens when you rely on poor and biased data to assess talent performance. Most promotion decisions rely on a manager’s limited view. But in today’s world of work—where collaboration happens across teams, often remotely—managers don’t see everything. They miss impact that happens outside of one-on-ones or team meetings. Active Organizational Network Analysis (ONA) surveys fix this. ONA analyzes real workplace interactions to identify key influencers, quiet contributors, and hidden problems — things like who employees turn to for advice, problem-solving, and execution, and who is toxic but good at managing up. It gives leaders a clear view of impact beyond titles, tenure, or office politics. When companies use ONA in performance reviews, they: 1) Identify quiet contributor high performers—not just those who are visible to leadership. 2) Reduce bias by making promotion decisions informed by data beyond selection-biased, cherry-picked peers. 3) Retain mission-critical employees by recognizing their contributions early. 4) Improve employee engagement by ensuring talent is evaluated fairly. The old way of evaluating talent is broken. Performance reviews based on manager opinions leave too much room for bias and blind spots. People deserve better. And we are going to keep pushing until fair, data-driven promotions become the norm—not the exception.