Understanding Career Dynamics

HR Beyond Knowing People: Do We Know Work? A century ago, HR was a lot about the nature of work itself. The advent of scientific management, or Taylorism, during the industrial revolution introduced rigorous methods for measuring and optimizing human effort. Early “personnel” departments specialized in analyzing work—timing tasks, standardizing processes, and designing jobs for maximum efficiency. As economies evolved, so did the nature of work. Modern roles demand less repetition and more creativity, adaptability, and cognitive skill. Job design shifted from breaking tasks into isolated parts to empowering people to tackle complexity and change. In 1997, Steven Hankin of McKinsey & Company introduced the concept of the “war for talent,” driving HR departments to focus even more on the people aspect of the equation. Recently, companies have begun to treat skills as the new currency of talent management. The emphasis now extends beyond job titles and résumés to understanding the mix of abilities—both technical and human—that fuel performance and potential. HR leaders recognize that matching people to work requires deep insight into skills, learning agility, and cross-role mobility rather than relying solely on experience or credentials. This skills-based approach has been accelerated by the rise of AI-powered Talent Intelligence Platforms. These systems integrate data on employees and external labor markets to optimize hiring, workforce planning, and talent development—highlighting not just what employees know, but what they can do and where they could grow. The New Challenge: Human-AI Role sort. Today, another transformation is underway. Work is increasingly defined by how humans and AI share and shift activities. As AI and automation rapidly reshape jobs, even the most advanced HR systems struggle to keep pace with the fundamental changes in the content of work. Few tools can thoroughly support the analysis and redesign of work itself. Work content now evolves rapidly, as tasks are redefined, augmented, or automated. Traditional surveys and spreadsheets are no longer adequate. What’s needed is a solution for dynamic analysis of work and work redesign at scale. Organizations need a new generation of tools: Work Intelligence Systems. These AI-native platforms should: - Analyze real work activities and required skills, rather than just job titles or organizational charts. - Track how tasks evolve with emerging technologies such as generative AI. - Reveal where automation is shifting or creating new roles. - Deliver actionable insights for work design, organizational effectiveness, and workforce planning. There are already some pioneers in this space, such as the AI based Impact Assessment solution from TI-People, and likely many other HR technology providers are entering—or will soon enter—this promising new category. At least, I hope they do.

We have spent years measuring activity and outputs. But now we have such an amazing opportunity to do the real work of measuring outcomes/impact... the crown jewel of project management. That’s exactly why we put together this Hacking HR Guide to People Analytics: Definitions, Leading and Lagging Indicators... It is a practical framework to help HR leaders move from reporting numbers to understanding what actually drives performance, culture, and business outcomes. A few key ideas behind the guide: 1️⃣ Not all metrics are equal Lagging indicators (like turnover or cost per hire) tell you what already happened. Leading indicators (like engagement signals, training participation, or early turnover) tell you what is about to happen. Both matter — but only one helps you act before problems explode. 2️⃣ HR metrics are business metrics Turnover, engagement, quality of hire, and revenue per employee aren’t “HR topics.” They influence productivity, innovation, customer satisfaction, and long-term profitability. People analytics is not about HR dashboards. It’s about business performance. 3️⃣ Context matters more than the number itself Every metric in the guide includes common pitfalls. For example: • High retention isn’t always good if it signals stagnation. • High overtime can signal burnout, not dedication. • High salaries alone won’t retain talent without growth and culture. Numbers without interpretation create bad decisions. 4️⃣ Metrics must connect into a system Hiring → onboarding → performance → development → retention → productivity. The power of people analytics comes from connecting these signals, not looking at them in isolation. 5️⃣ The future of HR is evidence-based In the age of AI and increasing organizational complexity, HR leaders will be expected to explain decisions with data, not intuition alone. People analytics is becoming the language of strategic HR. This guide walks through dozens of key indicators, from turnover and engagement to skills gaps, workforce capacity, and human capital ROI, and how they connect to real business outcomes. If you work in HR, leadership, or workforce strategy, one question is worth asking: Are you measuring HR activity… or are you measuring human impact on the business?

Rethinking Performance Measurement in the Hybrid Era Gone are the days when productivity was measured by time clocked in or physical presence in the office. In our new world of hybrid work, it's time for a paradigm shift in how we evaluate employee performance. The key? Focus on outputs and objectives, not inputs. As leaders, we need to ask ourselves: 1️⃣ Are we equipped to effectively evaluate our teams in this new landscape? 2️⃣ How can we ensure fairness and accuracy in performance assessments across different work models? 3️⃣ What tools and metrics truly reflect productivity in a hybrid environment? The challenge lies not just in measurement, but in support.  How can we empower our teams to thrive, regardless of their physical location? Here are a few strategies to consider: ➡️ Set clear, measurable objectives that aren't tied to work hours or location ➡️ Implement regular check-ins focused on progress and roadblocks ➡️ Utilize technology to track project milestones and collaboration ➡️ Prioritize outcomes over activity Remember, the goal isn't just to measure performance, but to foster an environment where high performance is possible whether your team is in the office, at home, or anywhere in between. I'm curious to hear from fellow leaders. How are you adapting your performance management strategies for the hybrid era? What challenges and successes have you encountered?

He delivered perfect metrics. She fumbled through a messy slide deck. He got fired. She got promoted. Because she spoke in dollars. Board meeting. Twelve minutes in. Director of Customer Success presents glowing NPS scores. Zero questions from the executives. Next slide: Engineering shows server uptime at 99.97%. Polite nods around the table. Then Marketing presents one number: Customer acquisition cost dropped 23% to just $3,000. Suddenly everyone's awake. Questions for thirty minutes straight. Additional budget approved on the spot. Here's what I learned watching from the back of that room: Numbers without dollar signs are just statistics. Numbers with dollar signs are how businesses make decisions. Last quarter, somewhere out there in the corporate world, a Head of Support rewrote her quarterly review. Version 1 (what she originally wrote): "Response times improved 15% this quarter. Customer satisfaction jumped to 4.8 stars. Team morale is at an all-time high." Version 2 (what got her promoted): "Faster response times retained $890K in at-risk accounts. Higher satisfaction converted $1.1M in expansion opportunities. Improved team retention saved $200K in recruiting, hiring, and training costs." Same achievements. Completely different reception. Her original presentation got polite applause. Her rewrite received accolades. Operational metrics → Financial impact Team performance → Business outcomes Customer feelings → Revenue protection "We reduced bugs by 60%" becomes "Prevented $400K in churn from technical issues." "Users love the new interface" becomes "UI improvements drove $153k in expansion” "Training improved team skills" becomes "Skills development cut support costs $150K annually." Every metric in your company connects to money. Your job is drawing those lines clearly. Because executives don't fund good feelings. They fund good business.

HR - Emerging Trends & Dynamics 1. AI Integration is No Longer Optional, It's Essential: Widespread Adoption: AI is rapidly moving from experimental to integral in HR. By end of 2025, 70% of employees are expected to interact with AI-powered tools daily. Organizations not adopting AI solutions in the next 2 yrs risk a significant disadvantage. Strategic Impact: AI is transforming talent management, recruitment, performance evaluation, and employee support. It offers predictive analytics to forecast turnover, identifies potential leaders, automates resume screening, and provides real-time feedback. Efficiency & Data-Driven Decisions: AI streamlines repetitive tasks (e.g., payroll, inquiries), reduces time-to-hire by up to 50%, and improves hiring efficiency by 25%. It also enhances data quality and provides insights for better decision-making. Ethical Considerations: HR's role will increasingly involve ensuring AI tools are used ethically, transparently, and without bias. 2. Employee Well-being and Experience Take Center Stage: Holistic Support: Employee well-being remains a top priority, encompassing mental health, work-life balance, and overall physical and financial health. Companies are investing in counseling services, stress management programs, and flexible work arrangements. Burnout & Disengagement: A significant portion of the global workforce is still disengaged Flexibility is Key: Hybrid and remote work model is here to stay. Many employees would take a pay cut or even quit to retain hybrid flexibility, underscoring the importance of accommodating varied work preferences. Employee-Centric Culture: Organizations are focusing on creating positive work cultures, emphasizing trust, purpose, and recognition, to attract and retain talent and improve overall business performance. 3. Upskilling and Reskilling are Imperative: Skills Gap Crisis: The rapid pace of technological advancement means that by end of 2025, approximately 44% of workers' skills will be disrupted. This creates an urgent need for continuous learning and development. Personalized Learning: HR is leveraging AI and learning management systems to tailor educational content to individual employee needs and career aspirations, fostering a growth mindset. 4. Workforce Planning is Becoming More Dynamic and Data-Driven: Scenario-Based Planning: HR is moving away from static headcount planning to dynamic, continuous, and scenario-ready workforce planning. This involves leveraging AI tools for modeling and forecasting future talent needs, skill gaps, and potential turnover. Focus on Skills, Not Just Jobs: With job roles evolving rapidly, the emphasis in workforce planning is shifting from job titles to the underlying skills and capabilities required. Internal Mobility: Given the "Big Stay" trend (employees seeking stability but also growth), HR teams are increasing their focus on internal mobility, creating opportunities for employees to grow and advance within the organization.

Can we apply the analogy of distance, velocity and acceleration to performance reviews? Usually when conducting performance reviews, managers look at what's been accomplished through a given period; 3,6,12 month cycles are normal. We can think about this as the work done or distance travelled. Now how do we incorporate learning and potential into performance reviews? We can look at the "velocity of work": how quickly is someone doing work in shorter amounts of time. This can be valuable to look at in two scenarios, someone joins a new team or starts doing new work. Usually companies look at onboarding speed as a strong signal of a new hire, but in many jobs people take on new work and responsibilities throughout their tenure. Going from a junior to senior developer, you're increasing your scope of work and learning new system design work. You might also be indirectly leading people and this becomes a signal for becoming a manager. It is also a reflection of the role itself, if people do not have the opportunity to increase the speed of their work, usually its harder to learn something new, which might lead to folks leaving. Finally, we can look at work acceleration, or someones potential. How much work will this person accomplish in a few months or years time? This is a hard thing to measure, but recruiting, managing and coaching high potential folks is a key strategy to building a strong team. If someone is continuously improving and this truly compounds it is quite special even though they might lack "traditional indicators" of high potential or credentials for the role. Now, how much should you weigh the "distance", "velocity" and "acceleration" metrics? This would be unique to every role and company, but this should be an open conversation with the team and the needs of the company. Companies with a higher risk profile might aim for a larger focus on velocity and acceleration. Another strategy is to give people more responsibility than usual and measure in short iteration cycles the improvement to validate the work and the potential. And in some roles, measuring the work done is all you need.

🎙️ "Workforce planning is evolving - and in some organizations, being reinvented - to become a key differentiator in a dynamic, artificial intelligence-powered world." Workforce planning needs to evolve because the old model - forecasting headcount and roles based on stable assumptions - no longer holds in a world shaped by rapid AI adoption, skills decay and unpredictable markets. In this environment, workforce planning must anchor the future of work by aligning human, machine and organisational capacity in real time, rather than treating it as a static exercise. In their article for Deloitte, 'Reinventing workforce planning for an AI-powered, uncertain world', Susan Cantrell, Russell Klosk (智能虎), Zac Shaw, Kevin Moss, Christopher Tomke, and Michael Griffiths identify five key shifts to achieve this: 1️⃣ From planning for a single future to planning for multiple futures: 🔎 Build agility by modelling a range of scenarios, embedding resilience and alternative talent paths. 2️⃣ From planning based on jobs to planning based on work: 🔎 Move from fixed roles to tasks, skills and outcomes, including human-machine blends. 3️⃣ From visible capability to unlocking hidden capability and capacity: 🔎 Identify undervalued talent, non-traditional roles and internal mobility, as well as human-machine hybrids. 4️⃣ From static, manual planning to autonomous, dynamic planning: 🔎 Leverage real-time data and AI agents to monitor workforce signals, trigger interventions and continuously adjust. 5️⃣ From silos to synergies (horizontal and vertical): 🔎 Embed workforce planning across business units and levels, democratise data and involve people closest to the work in decision-making. These shifts reposition workforce planning from a support function into a strategic capability - enabling organisations to adapt faster, deploy talent smarter and harness human-machine potential for both business and human outcomes. 🔗 The article is featured in the November edition of the Data Driven HR Monthly, which you can access here: https://lnkd.in/ekVuREn8 🔗

Executive HR Analytics Series | Part 3 After working with HR dashboards and leadership reviews, I noticed something interesting. The metrics HR teams track internally are often very different from the questions C-level leaders actually ask. HR discussions usually focus on things like hiring numbers, engagement scores, or attrition percentages. But when leadership reviews workforce data, the conversation quickly shifts to business impact. Over time, I realized that executive discussions around workforce usually revolve around a few recurring questions. The questions usually sound more like this: 1️⃣ Are we operating within our approved headcount? Executives often want to understand the gap between approved positions and actual manpower. This helps them see whether teams are understaffed, overstaffed, or aligned with workforce planning. 2️⃣ How productive is our workforce? Leaders frequently connect workforce size with productivity. They want to know whether the organization is generating more output as the workforce grows. 3️⃣ Where is our biggest attrition risk? Overall attrition is rarely the main concern. What usually matters is whether critical roles or high-impact employees are leaving. 4️⃣ How efficient is our hiring process? Leadership discussions often focus on how quickly roles are filled and whether recruitment delays are impacting business operations. 5️⃣ Are our recruitment vendors delivering results? When external hiring partners are involved, executives often ask about vendor effectiveness and whether those partnerships are producing quality hires. 6️⃣ How effective are our recruiters internally? Recruiter efficiency is another common topic — how many roles are filled, how quickly, and with what success rate. 7️⃣ What is the cost impact of vacant roles? When positions remain unfilled, productivity drops and projects may slow down. Leadership often wants to understand the real business impact of those vacancies. 8️⃣ Why are employees actually leaving? Understanding the top reasons for termination helps leadership identify whether the root cause lies with management practices, compensation, workload, or internal processes. 9️⃣ Are absenteeism trends telling us something? In some cases absenteeism can signal deeper issues — operational pressure, engagement challenges, or workload imbalance. 🔟 Are our teams structured effectively? Executives often review department span of control and team productivity to understand whether the organization structure supports efficiency. What I’ve realized is that a strong HR dashboard should not just display HR metrics. It should help leadership answer a much bigger question: “How do our workforce decisions impact business performance?” From your experience, what is the one workforce question leadership asks the most in your organization? #HRAnalytics #PeopleAnalytics #WorkforceAnalytics #HRStrategy #HRLeadership #DataDrivenHR #HRInsights #PowerBI

HR metrics are under the microscope at the moment. The last 3-4 reports I have read on the state of HR or the CHRO of the future points to people analytics as being pivotal to the success of the function. What is clear is many of the HR metrics currently used are no longer fit for purpose. Indeed the word "obsolete" was used recently. Can HR leaders put real power behind the function by re-thinking these? The historical “HR academy companies” used HR metrics to help professionalise HR measurement. But much of what we still track today is administrative, not strategic. 🔴 Legacy HR metrics These are familiar and increasingly obsolete: • Time to hire • Cost per hire • Turnover rate (undifferentiated) • Absence rate • Training hours per employee • Engagement survey participation • Grievances / cases logged They’re easy to measure, but they’re lagging indicators, they track activity, not impact, they’re weakly connected to business outcomes and they tell us what happened, not what to do next. 🟢 What HR metrics should be considered now Leading organisations are trying to shift toward value, capability and outcome-based metrics. A lot of these are aspirational rather than in use today. They can be grouped in the following ways: Talent quality & impact • Talent density • Quality of hire (6–12 month performance) • Performance contribution by role / segment Speed to value • Time to effectiveness (not just time to hire) • Ramp-up curves for critical roles • Role readiness Experience, engagement & retention • Employee experience (multi-touch, not annual) • Predictive attrition risk • Internal mobility rate Capability & future readiness • Skill currency / skill gap index • Leadership bench strength • Organisational agility The real shift From: “HR delivered X activities” To: “HR enabled Y outcomes” The question for HR leaders isn’t “what can we measure?” It’s “what actually drives enterprise value and are we brave enough to measure that?” As a function, this is clearly where the direction has to go. I would love to hear of any organisation who are already there, or moving in the right direction? When I have posed questions on HR value creation, I have often seen the smallest response in the replies, I would love to hear where HR leaders are finding success.

Most organizations measure employee experience as a satisfaction exercise. The ones that outperform treat it as a business performance system. That distinction shows up across every stage of the employee lifecycle, and the metrics you choose at each stage tell you exactly which camp you're in. Employee experience is not one moment. It's a chain of decisions, signals, and outcomes that begins before someone accepts your offer and continues through the day they leave. If you're only measuring it at the engagement survey, you're reading the last chapter and ignoring the entire story. The stages that matter and what to measure at each: → Hiring. Candidate NPS, offer acceptance rate, and time to hire are not recruiting metrics. They're your first signal on employer brand strength and market competitiveness. → Onboarding. Time to productivity and new hire satisfaction scores tell you whether your investment in talent acquisition is converting into actual execution capacity, or evaporating in a poor first 90 days. → Performance. 360 feedback data and manager effectiveness metrics reveal whether your leadership layer is developing people or depleting them. → Engagement. Voluntary turnover rate and employee retention ROI quantify the financial cost of the experience you're creating. Engagement isn't soft. It's measurable margin impact. → Recognition and advancement. Internal promotion rate and career path ratio show whether your top talent sees a future inside the organization or is already looking outside it. → Wellbeing. Absenteeism rate and employee wellbeing index are leading indicators of burnout, performance degradation, and the kind of quiet attrition that doesn't show up until it's too late. → Offboarding. Exit interview completion rate and offboarding score close the loop. How people leave determines whether they become advocates or detractors, and whether you learn anything from the loss. Here's the executive framing that matters: Every stage of the employee lifecycle either builds or erodes your organization's execution capacity. Measuring experience without connecting it to business outcomes is just data collection. The metric isn't the point. The decision it enables is.