Workforce Planning Strategies Using Technology

𝐀𝐈 𝐢𝐧 𝐇𝐑: I’ve seen firsthand how organizations I partner with are moving from exploration to execution and how AI, when used well, becomes a force multiplier for people strategy. That’s why I was excited to contribute to Emma Stenhouse'𝐬 Lattice article “𝟒𝟐 𝐀𝐈 𝐏𝐫𝐨𝐦𝐩𝐭𝐬 𝐇𝐑 𝐂𝐚𝐧 𝐒𝐭𝐚𝐫𝐭 𝐔𝐬𝐢𝐧𝐠 𝐓𝐨𝐝𝐚𝐲." 𝐇𝐞𝐫𝐞 𝐚𝐫𝐞 𝐚 𝐟𝐞𝐰 𝐚𝐫𝐞𝐚𝐬 𝐰𝐡𝐞𝐫𝐞 𝐈’𝐯𝐞 𝐡𝐞𝐥𝐩𝐞𝐝 𝐨𝐫𝐠𝐚𝐧𝐢𝐳𝐚𝐭𝐢𝐨𝐧𝐬 𝐥𝐞𝐯𝐞𝐫𝐚𝐠𝐞 𝐀𝐈 𝐭𝐨 𝐛𝐨𝐨𝐬𝐭 𝐛𝐨𝐭𝐡 𝐞𝐦𝐩𝐥𝐨𝐲𝐞𝐞 𝐞𝐱𝐩𝐞𝐫𝐢𝐞𝐧𝐜𝐞 𝐚𝐧𝐝 𝐛𝐮𝐬𝐢𝐧𝐞𝐬𝐬 𝐨𝐮𝐭𝐜𝐨𝐦𝐞𝐬: 🔹 𝐑𝐞𝐜𝐫𝐮𝐢𝐭𝐦𝐞𝐧𝐭 & 𝐇𝐢𝐫𝐢𝐧𝐠 AI can quickly scan resumes, match candidates to job profiles, and automate interview scheduling. It speeds up the process and supports more consistent, fair assessments. 🔹 𝐎𝐧𝐛𝐨𝐚𝐫𝐝𝐢𝐧𝐠 & 𝐎𝐟𝐟𝐛𝐨𝐚𝐫𝐝𝐢𝐧𝐠 AI platforms help ensure everything from paperwork to training is seamless. Virtual assistants guide new hires step-by-step, which boosts clarity and connection from day one. 🔹 𝐄𝐦𝐩𝐥𝐨𝐲𝐞𝐞 𝐄𝐱𝐩𝐞𝐫𝐢𝐞𝐧𝐜𝐞 Think 24/7 chatbots for HR questions, or platforms that track engagement and sentiment so teams can act in real time—not react after the fact. 🔹 𝐖𝐨𝐫𝐤𝐟𝐨𝐫𝐜𝐞 𝐏𝐥𝐚𝐧𝐧𝐢𝐧𝐠 AI can flag potential turnover risks, highlight skill gaps, and give insights to make smarter resourcing decisions. 🔹 𝐏𝐞𝐫𝐟𝐨𝐫𝐦𝐚𝐧𝐜𝐞 & 𝐃𝐞𝐯𝐞𝐥𝐨𝐩𝐦𝐞𝐧𝐭 AI tools support 360 reviews, track performance trends, and suggest personalized coaching and growth opportunities. 𝐇𝐞𝐫𝐞 𝐚𝐫𝐞 𝐬𝐨𝐦𝐞 𝐨𝐟 𝐦𝐲 𝐟𝐚𝐯𝐨𝐫𝐢𝐭𝐞 𝐀𝐈 𝐇𝐑 𝐩𝐫𝐨𝐦𝐩𝐭𝐬 𝐈'𝐯𝐞 𝐮𝐬𝐞𝐝: 1️⃣ "Generate 10 LinkedIn post options for our [job] opening, targeting candidates who align with [company values and required experience]." 2️⃣ "Create a personalized 90-day onboarding plan for a [job], focusing on integration, technical goals, and internal tools." 3️⃣ "Generate a training module outline for [specific skill] for [employee group/team], aligned with [learning objectives]." 4️⃣ "Share compliance requirements for [labor law] in [region] and where to find more information." (You always want to verify accuracy.) 5️⃣ What are three tips for having a difficult conversation with an underperforming employee on [topic]? Provide sample conversation openers and closers and an action plan template. 𝐇𝐞𝐫𝐞’𝐬 𝐭𝐡𝐞 𝐟𝐮𝐥𝐥 𝐚𝐫𝐭𝐢𝐜𝐥𝐞: https://lnkd.in/gifjf8ff 💬 Where have you seen AI free up time for deeper work, better decisions, or stronger connection—in your team or your own role?

AI in Human Resources: Revolutionizing Workforce Management The field of human resources is undergoing a seismic shift as #artificialintelligence (AI) revolutionizes how organizations attract, manage, and retain top talent. From intelligent recruiting and enhanced employee experience to data-driven workforce planning and bias reduction, #AI is transforming #HR functions at an unprecedented pace. AI in HR Market Primed to Surpass USD 26.5 billion by 2033. Gartner predicts that by 2025, 50% of HR leaders will have moved toward algorithmic management to better organize and optimize their workforce. Unilever has implemented AI solutions from Pymetrics to reduce bias in hiring and improve diversity and inclusion efforts. Here I have written three applications in #humanresources leveraging AI with case study, action and tools. 1. Recruitment and Hiring: Case Study: Hilton Situation: Hilton implemented AI-driven tools to enhance their recruitment processes, specifically in screening and evaluating a large volume of applicants efficiently. Action: They employed an AI system that automates the initial stages of screening by assessing candidates' responses in video interviews. The AI analyzes verbal and non-verbal cues to determine suitability for the role. Result: This led to a more efficient recruitment process, reducing the time spent on each hire and improving candidate quality. The system helps in identifying the best candidates based on consistent criteria, reducing human biases. Tools: HireVue Pymetrics 2. Employee Engagement and Development: Case Study: IBM Situation: IBM sought to improve employee development and retention through personalized learning and career pathing. Action: They developed an AI-powered personal development platform that provides employees with tailored learning recommendations based on their current skills, job role, and career aspirations. Result: The platform has led to increased employee engagement and satisfaction as it actively aids in personal and professional growth, making learning opportunities more relevant and accessible. Tools: IBM Watson Career Coach Degreed 3. Performance Management: Case Study: Accenture Situation: Accenture aimed to revamp its traditional performance reviews with a more continuous and real-time feedback system. Action: They implemented an AI-driven platform that collects continuous feedback from various sources, providing employees and managers with more timely and frequent performance insights. Result: This approach has not only improved the accuracy and relevance of performance data but also enhanced the overall experience of performance management, making it more dynamic and aligned with individual goals and company objectives. Tools: Workday Reflektive As organizations grapple with the evolving workforce landscape, those that strategically leverage AI will be well-positioned to attract, nurture, and retain the talent essential for long-term success. #management

After participating in a series of Gen AI events, we've compiled a summary of our insights regarding the implications that workforce planners should take into account. 1. Leveraging Gen AI, we can enhance productivity with early career talent. As a result, we can do more with early career talent 2. It's essential to reconsider the experience requirements outlined in job descriptions as due to automation, this may change 3. Particular roles, such as Data Engineering, Prompt Engineering could become pivotal and potential bottlenecks without careful planning. 4. AI integration will not merely augment tasks but will be fully integrated into job functions. 5. The Analysts' talent pool must receive training in newer generative AI skills. 6. Initiating projects sooner may be advantageous in some cases, while in others, a different approach may be preferable. 7. Developing comprehensive cost models for Gen AI, including setup, deployment, and yearly operational expenses, will be a critical aspect of Workforce Planning. 8. Proficiency in interpreting and understanding data limitations will become a vital power skill. 9. Smaller talent pool ecosystems will gain prominence, shifting the focus towards the quality of available talent. 10. Collaboration and connectivity between enterprises, universities, research institutions, and professors will significantly expand as enterprises explore advanced AI applications. Draup #workforceplanning

Founding a Workforce Management (WFM) team from scratch? Here's a structured approach I’ve used to build high-impact WFM functions that scale. Phase 1: Foundation Executive Alignment • Clarify WFM’s purpose: SLA protection, cost control, service reliability • Define scope: forecasting, scheduling, intraday, reporting • Secure senior sponsorship Assessment • Map current gaps in data, tools, and processes • Identify pain points like adherence issues, shrinkage, or coverage volatility Charter • Define KPIs: forecast accuracy, SLA attainment, schedule efficiency • Clarify supported functions such as voice, chat, and back office Phase 2: Function Design Core Functions • Forecasting: volume prediction based on trends and drivers • Capacity Planning: converts workload into staffing needs • Scheduling: aligns staff supply to forecasted demand • Intraday: monitors queues and initiates recovery actions • Reporting: provides performance visibility • Governance: creates process standards and planning cadence Technology • Select a WFM platform (i.e. NiCE) • Plan for integrations: ACD, HRIS, CRM, BI • Fill any gaps with reporting tools, Excel, or automation Phase 3: Build the Team Team Roles • WFM Lead: owns strategy and alignment • Forecasters: build short- and long-term models • Schedulers: create and maintain shifts • RTAs: monitor queues and agent states • Reporting Analysts: track KPIs and trends • System Admins: configure and support tools Skills and Training • Prioritize analytical thinking, communication, and tool fluency • Train on concepts like occupancy, shrinkage, adherence, and intraday control Phase 4: Execution Cadence • Set up cycles: annual plans, monthly forecasts, weekly schedules, daily huddles • Deliver standardized outputs like forecast decks, staffing plans, and recovery updates Governance • Define SLAs, shrinkage categories, adherence logic • Document escalation paths and playbooks Stakeholder Engagement • Embed WFM in hiring, policy changes, and new programs • Partner closely with Ops, QA, Training, HR, and Finance Phase 5: Scale and Refine Enhance Efficiency • Automate tasks like shrinkage tracking and exception handling • Enable agent self-service for availability and shift bidding Mature the Function • Add scenario modeling, risk-based staffing, and budget alignment • Position WFM as a trusted planning partner across the org #workforcemanagement #contactcenterstrategy #wfm #forecasting #scheduling #realtimemanagement #cxleadership #operationalexcellence #teamdesign