Intelligent Workforce Scheduling Solutions

10^30000 scheduling combinations. 50 hours per week in Excel. If you've lived inside traditional WFM tools, you know this headache. Assembled's new AI-powered Schedule Generation does it in minutes. Here's the breakdown: 1,000 agents. 5 shifts each. 8 hours per shift. That's 5,000 shifts to schedule. Each shift needs: One productive event (chat, email, or phone). Two breaks. One lunch. One meeting. Discretize 8 hours into 15-minute blocks and you get 32 options. For non-productive events alone: 32 × 31 × 30 × 29 / 2 = 431,520 combinations per shift. Multiply by 3 productive event options. 1,294,560 combinations per shift. Now do that for 5,000 shifts. (10^6)^5000 = 10^30000. That's a number with 30,000 digits. At 2,000 digits per page, it takes 15 pages just to write it out. The “nurse scheduling” problem is a classic NP-hard problem. This is what workforce managers are solving with spreadsheets. Assembled's AI-powered Schedule Generation feature handles this in minutes. Agent needs Thursday off for a doctor's appointment? Old way: Submit request. Wait for approval. Hope it doesn't conflict. Assembled's way: Integer linear programming for coverage optimization. Constraint programming for breaks, lunches, and labor law compliance. Decomposition to break 34,000 weekly shifts into 50 parallel subproblems. 2 hours becomes 10 minutes. Agents can also browse available swaps directly in the system. AI ensures swaps follow your rules: Matching skills Queue compatibility Channel requirements. Our schedule Layers prevent coverage gaps entirely. It has three intelligent layers: Productive work Meetings/breaks Time off. When a training cancels, productive work surfaces automatically underneath. One global payments company told us: "This replaces our hideous spreadsheet where we export schedules just to flag compliance issues. Programming rules directly in is chef's kiss." AI handles 10^30000 combinations. Managers can now handle strategy. Kudos to the team on this big, NP-hard launch. Antony Phillips, Claire D., Jack Gleeson, Malfy Das, Nicole Pan, Zach Clark, Chancie(Qianshi) Zheng, Charlie Rotholtz, David Patou, Devon Berger, Todd Bergman, Dan Hertz

Workforce Management (WFM) is poised for significant advancements, leveraging technological innovations to revolutionize the workplace. In the near future, several key developments are expected to reshape WFM strategies: 1. **AI-Driven Forecasting and Scheduling:** Artificial Intelligence (AI) will play a pivotal role in refining forecasting accuracy. Machine learning algorithms will analyze historical data, market trends, and various parameters to predict staffing needs more accurately. Dynamic scheduling, empowered by AI, will adapt in real-time to meet demand fluctuations, ensuring optimal resource allocation. 2. **Enhanced Remote Work Capabilities:** With the rising prominence of remote work, WFM tools will prioritize features tailored to distributed teams. This includes virtual collaboration platforms integrated into WFM systems, advanced remote monitoring capabilities, and algorithms to equitably distribute workloads between on-site and remote employees while ensuring seamless communication. 3. **Predictive Analytics for Employee Engagement:** WFM will delve deeper into predictive analytics to anticipate employee engagement levels. By analyzing performance metrics, sentiment analysis, and other indicators, these systems will help managers identify potential issues affecting morale, allowing proactive interventions to boost engagement and retention. 4. **Personalized Employee Experience:** Future WFM systems will focus on delivering tailored experiences to individual employees. Customized scheduling preferences, career development plans, and targeted feedback mechanisms will enhance employee satisfaction and productivity by catering to their unique needs and work styles. 5. **Integration of Internet of Things (IoT):** IoT devices will be integrated into WFM to provide real-time data on employee activities and environmental factors impacting productivity. Smart sensors and wearables will offer insights into employee well-being, optimizing work conditions and schedules accordingly. 6. **Adaptive Learning and Development:** WFM platforms will incorporate adaptive learning algorithms to identify skill gaps and recommend personalized training programs. Continuous learning approaches will ensure employees remain equipped with the necessary skills for evolving job roles. 7. **Ethical AI and Bias Mitigation:** There will be a heightened emphasis on developing ethical AI models within WFM to mitigate biases. Ensuring fairness and equity in decision-making processes and opportunities for all employees will be a significant focus. These innovations collectively represent a shift towards more intelligent, adaptive, and employee-centric WFM systems, empowering organizations to optimize their workforce strategies and navigate the complexities of the modern workplace efficiently. #wfm #innovation #efficiency

𝗖𝗮𝗻 𝗮 𝗦𝗰𝗵𝗲𝗱𝘂𝗹𝗶𝗻𝗴 𝗧𝗼𝗼𝗹 𝗥𝗲𝗱𝘂𝗰𝗲 𝗕𝘂𝗿𝗻𝗼𝘂𝘁 𝗮𝗻𝗱 𝗪𝗮𝗶𝘁 𝗧𝗶𝗺𝗲𝘀 𝗮𝘁 𝗢𝗻𝗰𝗲? Orlando Health thought their infusion clinics were running at full capacity. Turns out, they were just poorly scheduled. After implementing Epic’s infusion scheduling template generator, everything changed. 𝗧𝗵𝗲 𝗕𝗲𝗳𝗼𝗿𝗲 → Patients waited up to a week for an appointment → Nurses overwhelmed during midday peaks → 6-minute average scheduling calls → High turnover, overbooked chairs 𝗧𝗵𝗲 𝗔𝗳𝘁𝗲𝗿 → 32% drop in patient wait times → 50% increase in nurse satisfaction → 200 monthly care hours recovered → Appointments offered within 24 hours The difference? Smarter scheduling built around actual staffing, capacity, and patient needs not guesswork. 𝗪𝗵𝗮𝘁 𝗧𝗵𝗲𝘆 𝗗𝗶𝗱? → Used Epic’s system to auto-build templates based on data → Shifted scheduling conversations to system-recommended slots → Consolidated appointment info onto one screen → Automatically rebalanced unclaimed appointments overnight 𝗧𝗵𝗲 𝗥𝗲𝗮𝗹 𝗦𝗵𝗶𝗳𝘁? This wasn’t about more chairs or overtime. It was about reducing chaos through system logic and giving nurses and patients a better experience. 𝗬𝗢𝗨𝗥 𝗧𝗔𝗞𝗘? → Is your clinic really full or just misaligned? → Would automated scheduling free up care hours in your workflow? → Could smarter workflows reduce nurse turnover without increasing cost? #EpicSystems #DigitalHealth #InfusionCare #PatientExperience #ClinicalWorkflows #NurseRetention #SmartScheduling #OrlandoHealth #HealthTech #OncologyCare #EpicShare #TechlingHealthcare

𝗧𝗵𝗲 𝘀𝗲𝗰𝘂𝗿𝗶𝘁𝘆 𝘀𝘂𝗽𝗲𝗿𝘃𝗶𝘀𝗼𝗿 𝗶𝘀 𝘀𝘁𝗶𝗹𝗹 𝗯𝘂𝗶𝗹𝗱𝗶𝗻𝗴 𝗻𝗲𝘅𝘁 𝘄𝗲𝗲𝗸'𝘀 𝗿𝗼𝘀𝘁𝗲𝗿 𝗼𝗻 𝗮 𝘀𝗽𝗿𝗲𝗮𝗱𝘀𝗵𝗲𝗲𝘁. Airport security is one of the most operationally complex staffing challenges in any industry. Certification requirements, gender ratios, lane configurations, peak passenger flows, regulatory minimums, last-minute absences — all of it managed manually by a supervisor who also has a live operation to run. The consequence is visible to every passenger. Airports such as Miami, Los Angeles and JFK recorded average security wait times exceeding 54 minutes during peak periods in 2024. One in seven passengers globally reported missing a flight due to security queues in the period before the pandemic. These are not capacity failures. In most cases they are allocation failures — the wrong number of staff, in the wrong lanes, at the wrong time, because the scheduling tool could not see what was coming. AI workforce scheduling optimisation changes the equation. It ingests historical flow data, live flight schedules, seasonal patterns and real-time absence information, then outputs optimised lane staffing plans — prescribing when to open or close checkpoints, where certified staff must be positioned, and when to trigger overtime before the queue builds rather than after. The TSA is already building this. Their "Plan of Day" programme is actively developing AI to automate screening staff optimisation across the US national network. Manchester Airports Group deployed AI-powered absence management across thousands of operational staff using large language models, achieving over 90% accuracy in processing workforce interactions. 𝗠𝘆 𝗩𝗶𝗲𝘄 💡 The security supervisor's spreadsheet is not a planning tool. It is a record of decisions already made under pressure, with incomplete information, by someone who had twelve other things to manage. AI scheduling optimisation does not replace the supervisor's judgement — it gives them the data to exercise it before the problem arrives rather than after. The barrier is not technology. It is the organisational willingness to connect scheduling systems to live operational data and trust the output. When did your security operation last allocate staffing based on what was predicted rather than what was planned?

Most waited feature: SAP brings shift scheduling home — no integration, no sync, no guesswork. The latest SAP SuccessFactors Workforce Scheduling capability marks a major milestone in time management transformation. For the first time, HR leaders can: 1) Create weekly and monthly shift plans within SuccessFactors 2) Align staffing with real-time production demand 3) Auto-match employees based on skills, certifications, and availability 4) Sync shifts seamlessly with Time Tracking and Payroll No more juggling third-party tools. No more data sync delays. Also roadmap defined, SAP announced upcoming extensions: 1) Smart Shift Proposals: AI-generated schedules (based on demand, skills, holidays). 2) Joule Integration: Conversational “Create next week’s schedule for Plant 01” capability. 3) Integration to Payroll Costs in Business Data Cloud. Everything — from demand to shift to pay — now flows within one intelligent platform. It’s efficient, compliant, and AI-ready. This is how HR and Operations finally converge under a single source of truth: SAP SuccessFactors. #SAP #SuccessFactors #WorkforceScheduling #AIinHR #SAPTimeTracking #DigitalHR #ShiftPlanning #HXM #RetailWorkforce #ManufacturingWorkforce #LogisticsWorkforce #healthcareWorkforce

Intraday used to mean firefighting. We watched the dashboards, waited for something to break, and then reacted. But with AI, intraday management is becoming proactive instead of reactive: ⚡ Volume → AI predicts spikes earlier. ⚡ Staffing → AI suggests best-fit coverage in real time. ⚡ Breaks → schedules re-balance instantly when demand shifts. ⚡ Adherence → AI alerts us the moment risk appears. 👉 For WFM professionals, this means moving from chasing problems to guiding strategy. Less manual juggling. More confidence in decisions. And ultimately, a smoother day for both agents and customers. Question for you: 👉 Do you think AI can truly replace the human judgment in intraday, or will we always need the “human touch”? #WorkforceManagement #WFM #AI #ContactCenter #FutureOfWork #CustomerExperience #Leadership

How I cut 80% of scheduling headaches with one AI Agent. (in 4 simple steps) If your inbox is messy, your calendar is worse. → Double-bookings you missed. → Meetings scattered across time zones. → A hundred emails to schedule a 30-minute call. Sound familiar? Here’s the good news: scheduling is one of the easiest things to hand off to an AI Agent. Here’s the 4-step framework we use inside the Lab: Step 1: Define your rules. Before you touch tools, decide how you want your calendar to run. Examples: → Only book new prospects on Tue/Thu mornings. → Leave Fri afternoons blocked for deep work. → Auto-accept calls from existing clients. These rules become the instructions your agent follows, so it acts like a personal assistant. Not a guessing machine. Step 2: Choose your calendar + comms stack. Where does scheduling happen now? → Zoom. → Calendly. → Google Calendar. → Outlook. → Slack. Pick the platforms that matter, then let your agent connect the dots. Step 3: Pick an agent builder. Tools like Lindy, Make, or Relay let you build flows that apply your rules automatically. The key? It's matching complexity to your needs. Don’t overbuild. Step 4: Connect and deploy. Sync your rules, connect your stack, then run it live. Monitor the agent like a new hire for a week to make sure it handles the edge cases. That’s it. You now have an AI scheduling assistant that: → Manages requests. → Protects your focus time. → Cuts out 80% of the headaches. We build agents like this live every Friday inside the Mighty AI Lab. Take a peek inside our community: https://lnkd.in/gjah4Yen

Service worker churn isn’t a mystery; it’s a design problem. A recent Harvard Business Review piece examining retail and service environments reinforces something we see clearly in the data: employees don’t leave because they don’t care — they leave because the system around them makes it too hard to succeed. Unpredictable schedules. Last-minute changes. Limited control over hours. Little visibility into pay. At UKG, we believe scheduling is one of the most powerful and underleveraged drivers of retention. And we don’t say that lightly. UKG is built on the world’s largest collection of real-world work and people data — millions of employees across industries and geographies. That scale gives us a unique lens into what actually drives engagement, absenteeism, productivity, and churn, especially in frontline-heavy industries. With Bryte AI embedded across our workforce operating platform, we’re helping managers turn that data into action. Bryte surfaces insights in the flow of work, identifying coverage gaps, flagging overtime risk, recommending optimized schedules, and helping managers make smarter, faster, more equitable decisions. Not based on instinct, but based on data. What we consistently see: - Real-time schedule visibility builds trust - AI-powered recommendations improve efficiency and fairness - Easy shift swaps increase flexibility without sacrificing coverage - Transparency into hours and pay strengthens commitment When managers are equipped with intelligent tools and employees have autonomy and clarity, scheduling becomes more than an operational task; it becomes a strategic lever for retention. In industries where churn is highest, stability and flexibility aren’t perks. They’re competitive advantages. https://lnkd.in/eqJCVs6x