Cambridge Judge Business School | People Analytics: Transforming HR Strategy with Data Science’s Post

Bad hires, regrettable attrition, cost overruns, and poor productivity are common challenges faced by HR leaders daily. People analytics is a valuable tool that can help address these issues effectively. Deciding how to tackle these challenges is no easy feat, especially in the realm of human dynamics where things are not always as they appear. People analytics enables HR professionals to move beyond guesswork and make informed, data-driven decisions. (https://lnkd.in/gBeRxt-V) #HR #PeopleAnalytics #DataDrivenDecisions #HumanResources #Analytics #Productivity

Organizations have the opportunity to enhance requirement management and decision-making by utilizing the Business Intelligence platform. Our BI platform offers essential features such as customizable dashboards, report generation, and collaborative tools specifically tailored to support requirement management. #NERP #BI #HCM #AI #DASHBOARD #ANALYTICS #TALENET_MANAGEMENT #RECRUITMENT

If you take nothing else away from this post from Laura Close make note of this key piece of advice! 💡 𝐑𝐞𝐦𝐞𝐦𝐛𝐞𝐫: 𝐓𝐡𝐞 𝐛𝐞𝐬𝐭 𝐦𝐞𝐭𝐫𝐢𝐜𝐬 𝐭𝐞𝐥𝐥 𝐲𝐨𝐮 𝐰𝐡𝐚𝐭 𝐭𝐨 𝐝𝐨 𝐧𝐞𝐱𝐭. • Quick Test: Look at your HR dashboard. Ask: "If this number changes, do I know exactly what action to take?" If no - probably time to replace it.

These HR Metrics don’t deliver. In fact, I've been known to discourage customers from relying on them. At Included we know the struggle of selecting the right metrics! But our AI automates something genius: "significance testing" (a data science term) Meaning: the AI instantly knows WHICH data points are the most important for you & the AI shows you the hot spots! ✨ Our customers roll out of bed and ask Included their metrics questions - and Included delivers precise answers in beautiful visuals and written data stories. IF your company isn't ready to invest in AI for HR, here's a Mega Fast Hack to knowing which HR metrics don't deliver! ➡️ ➡️ 🚫 After years in HR tech, I've seen smart teams waste time on metrics that sound good but don't drive action. Here's your mega fast guide of metrics to skip and examples of what to select instead: • Engagement Survey Scores Without Context ✅ Track instead: Questions tied to specific programs Example: "Do you have the tools to do your job?" vs vague "Are you engaged?" • Overall Turnover Rate ✅ Track instead: Regrettable turnover by team & tenure Example: "Lost 3 high performers in engineering after 2 years" vs "15% turnover" • Training Completion Rates ✅ Track instead: Skill application after 30 days Example: "67% of managers using new feedback methods" vs "98% completed training" • Time to Hire ✅ Track instead: Quality of hire at 6 months Example: "85% of new hires hitting goals" vs "25-day fill time" • General Employee Satisfaction ✅ Track instead: Specific satisfaction drivers Example: "Team collaboration scores" vs "Overall happiness" 💡 Remember: The best metrics tell you what to do next. • Quick Test: Look at your HR dashboard. Ask: "If this number changes, do I know exactly what action to take?" If no - probably time to replace it. What metrics were you surprised to discover were not a value add? Drop your experience below ⬇️ Still reading? We could be friends I read to the bottom too! Having built AI for HR technology and partnered with exceptional HR leaders, I'm passionate about making measurement simple yet powerful. Drop a comment about a metric you'd like to see Mega Fast Hacks for and I'll read your comment and design a post! ------------------------------------------------------------- This week, I'm sharing mega fast hacks to help HR leaders embrace data-driven approaches: 📉 Thursday: You asked for: Metrics to avoid - metrics that simply don’t deliver ✅ Friday: You asked for: Mega fast hack to measure quality of hire 12/23 🎁 Holiday Gift Compilation Post! 🎁 All our best HR data hacks compiled into one simple resource for you to keep & reference #HR #PeopleAnalytics #HRMetrics #DataDrivenHR #AIforHR #CHRO #DataInsights #DataDrivenHR #PeopleOps #PeopleAnalytics

Business Intelligence improves talent management through data analysis, identifying strengths, setting benchmarks, and making informed decisions, leading to a successful workforce. #nerp #AI #BI #analytics #hcm #dashboard #talentmanagement #recuitment #crm #kpi

Across the last year, human resources (HR) leaders were inundated with responding to new trends and challenges, including implications of advanced analytics and artificial intelligence. Deloitte’s Human Capital Forward team predicts how 5 of today’s HR technology trends could innovate across disparate systems, work processes, and workforce experiences in 2024. Read on... #HR #HumarResources #HumanCapital #HRTrends #Recruitment #Staffing #ITHiring #TechnologyRecruitment #ITRecruitment Franz Gilbert Matthew Shannon Erin Spencer

AI-powered HR analytics can help organisations unlock "dead data," transforming it into clear insights that reveal employees' collaboration patterns and contributions. By leveraging this data, organisations can enhance performance reviews, ensure they are more objective, and provide better coaching to support employee growth and development. #HRAnalytics #HRTech

The essence of a successful HR tech infrastructure lies not only in the tools used but also in the culture and values embraced. Transparent communication, trust, and a supportive environment are "musts" in this process. #Technology #ArtificialIntelligence #TheFutureOfWork https://lnkd.in/ggU9iQM8

HR Decisions Grounded in Research "If you’re not practising evidence-based HR, what type of HR are you practising?" In recent editions of the Data Driven HR Monthly, I’ve featured an ensemble of articles by current and recent people analytics leaders. In the June edition - which you can read here: https://lnkd.in/ePEbDzq5 - - those featured are: 1️⃣ David Hodges takes inspiration from Rob Briner’s research to make the case for evidence-based HR. As Dave asks: “If you’re not practising evidence-based HR, what type of HR are you practising?” (see Figure). 2️⃣ Henrik Håkansson applies the popular concept of “fear of missing out” to people analytics in his astute article. 3️⃣ Amit Mohindra provides a handy explanation of the ‘Rule of 72”, which can be used to extract a key parameter from a growth rate. 4️⃣ Louise Baird breaks down the two different types of machine learning – supervised and unsupervised – and how it can be applied to people analytics. 5️⃣ Martha Curioni provides examples of building explainable AI into a range of HR processes including: hiring, predicting attrition, and assessing promotion readiness. 6️⃣ Based on their survey of people analytics practitioners, Nick Jesteadt and Erin Fleming highlight three common yet seemingly elusive themes in the field: productivity, skills and productisation. 7️⃣ Christopher Rosett breaks down the People Analytics Cube in his LinkedIn post with a nod to Alexis Fink. #peopleanalytics #humanresources #workforceplanning #evidencebasedhr #futureofwork #employeeexperience #employeelistening #leadership #learning #culture #recruiting #generativeai

What type of HR are you practicing? Connect with us to find out how we can support you in your evidence based HR journey. #HR #HRIS #HCM