ProHance

Organizations are measuring AI adoption by licenses issued and tools enabled. But that's not adoption, that's access. Real adoption shows up in how people's work patterns, behaviors, and outputs actually change. And that's exactly where most organizations are flying blind right now. Leaders see dashboards showing AI is "in use." Employees are still figuring out how it fits into their actual day. The gap between the two is where transformation stalls. At ProHance, this is what we've been building toward, giving organizations the visibility to go beyond surface-level adoption metrics and understand what's genuinely shifting on the ground. Arvind Sagar, Senior Advisor at ProHance, breaks this down in detail on nasscom. Worth a read if you're navigating AI rollout in your organization. 🔗https://lnkd.in/gQ_ivpuc #ProHance #FutureOfWork #AITransformation #WorkforceIntelligence #NASSCOM #HumanFirst

Most organizations are not short on people. They are short on visibility. Around 60% of managers say reduced visibility makes performance reviews more challenging in remote and hybrid settings. That challenge does not stay inside the performance review. It flows into headcount decisions, project resourcing, and capacity planning, all made without a clear picture of how work is actually distributed. The result? Organizations hire to solve problems that better allocation would have already fixed. Around 90% of hybrid employees report they are just as productive or more productive than they were in a traditional office setting. And 62% of managers say their teams are actually more productive in hybrid or remote arrangements. Productivity is not the problem. Operational visibility is. The leaders fine-tuning their strategy right now are shifting performance metrics from desk time to deliverables, running regular pulse checks to catch engagement dips early, and investing in the tools that give remote and hybrid employees the same operational standing as their in-office counterparts. That last point matters more than most leadership teams realize. When you cannot see capacity gaps, you make resourcing decisions on assumption. Some teams carry far more than their fair share. Others have capacity that never gets deployed. Both outcomes are expensive, and neither shows up cleanly on a headcount report. This is exactly where ProHance is built to help. Workflow intelligence, work time analytics, and capacity insights, designed to give enterprise leaders the operational clarity to make decisions that are grounded in reality, not assumption. The organizations closing this visibility gap are not spending more. They are spending smarter. See ProHance in action: https://lnkd.in/gaCXhN8y What is one workforce decision in the last quarter that better data would have changed for your organization? #WorkforceAnalytics #CapacityPlanning #OperationalIntelligence #HybridWork #FutureOfWork #EnterpriseProductivity

55% of the U.S. workforce is burned out right now. Not disengaged. Not unmotivated. Burned out. Eagle Hill Consulting's November 2025 survey of over 1,400 employees found that more than half the workforce is experiencing burnout, with direct consequences on efficiency, innovation, customer service, and retention. Here is what makes this data worth pausing on. Burned-out employees are nearly three times more likely to say they plan to leave their employer in the coming year. And yet, only 42% of those employees have told their manager about it. That silence is the real operational risk. The problem does not announce itself. It quietly shows up in declining output, missed handoffs, slower cycle times, and team imbalances that nobody has the data to explain. In 2026, burnout's influence on engagement has grown: 52% of workers now say burnout drags down their engagement, up from 34% just a year earlier. Leaders cannot fix what they cannot see. The organizations getting ahead of this are not running more pulse surveys. They are building operational infrastructure to monitor workload distribution across teams in real time, flag chronically overloaded teams, and act before an exit interview reveals what the data could have surfaced months earlier. That is the business case for workforce intelligence. Not to watch people. To protect them, and the business they sustain. At ProHance, we help enterprises understand where capacity is stretched and where it sits idle, so leaders can make decisions grounded in how work actually flows, not how they hope it does. The cost of not knowing is already showing up in your attrition numbers. 👉 See where your workforce is stretched before it shows up in resignations: https://lnkd.in/grJnnTSz

Great work is built on great relationships. This March, we had the privilege of bringing together some of the most forward-thinking leaders in the US market over dinner in Dallas. These evenings are always a reminder of what really matters, the relationships behind the work. Conversations flowed from the challenges keeping leaders up at night to where the future of workforce productivity is headed and everything in between. To every senior leader who joined us, thank you for your time, your candor, and your trust in ProHance. Here's to more of these 🥂 #ProHance #ClientAppreciation #Leadership #Dallas #WorkforceIntelligence

In 1917, A.K. Erlang solved one of the most elegant problems in operations research. How many telephone operators does a switchboard need? His formula answered it beautifully. It assumed callers would wait patiently, that demand arrived in predictable patterns, and that every operator handled every call the same way. For a 1917 telephone exchange, that was genius. For a 2026 omnichannel contact center managing voice, chat, email, social, and AI-assisted escalations across distributed teams in multiple time zones? It is a very expensive approximation. And most contact center workforce models are still built on it. Here is what that approximation is costing the industry right now. Overstaffing, while ensuring adequate coverage, increases operational costs by 15 to 25%. Understaffing drives agent burnout, longer wait times, and deteriorating service quality. Most organizations swing between both problems in the same week, sometimes in the same day, because their forecasting model was never designed to handle demand that shifts by the hour across five channels simultaneously. Annual agent turnover in contact centers runs between 40 and 45%. The workforce is being replaced nearly in half every single year. That is not a hiring problem. It is a workload distribution problem. Approximately 63% of contact center agents report high levels of burnout, driven by emotional exhaustion, repetitive tasks, and the pressure of unrelenting volume without adequate support. Medium And replacing each one of them costs up to 33% of their annual salary before a single customer call is answered. Compliance fines for SLA breaches average $5 million annually across the industry. Most of those breaches are not random. They are predictable failures at the intersection of bad forecasting and rigid scheduling, the exact conditions Erlang C was never equipped to prevent. The math is not the villain here. The problem is asking 1917 mathematics to carry operational decisions that require real-time, multi-skill, multi-channel, AI-assisted intelligence. That is what ProHanceCX is built to handle. Advanced demand forecasting across every channel, multi-skill agent routing, real-time capacity balancing, and SLA monitoring that flags risk before a breach occurs, not after. Organizations using ProHanceCX are reporting 5 to 10% reductions in average handling time, 4 to 10% year-on-year margin improvement, and measurable ROI within three to six months of deployment. Not because Erlang was wrong for his era. But because your contact center deserves a model built for yours. Are your staffing decisions still running on a century-old formula? See ProHanceCX in action: https://lnkd.in/gaCXhN8y #ContactCenter #WorkforceManagement #ProHanceCX #CX #OperationalExcellence #ContactCenterAI #FutureOfWork #AgentExperience

We talk to a lot of industry leaders. And one story keeps coming up. A leadership team rolls out AI tools across the organization. Months pass. The dashboards say "adoption complete." The reality was very different. Licenses were active. The behavior hadn't changed. And nobody could answer the one question that actually mattered, are our people working differently because of AI, or just working the same way with a new tab open? That's not a technology problem. That's a governance problem. Hi, I'm Nirav Rawell, SVP of Product Management at ProHance - a workforce intelligence platform helping 200+ enterprises across 36 countries improve productivity. This is #MeasuredLeadership, a ProHance original series where leaders get honest about the things that don't make it into conference keynotes. The real lessons. The uncomfortable truths. The decisions that looked wrong before they looked right. I'm starting with the question that matters most right now: why do so many enterprise AI pilots succeed on paper, and fail to scale in practice?  Read the full piece below. 👇 #AIGovernance #EnterpriseAI #WorkforceProductivity #FutureOfWork #MeasuredLeadership 

Your board approved the AI budget. Your teams are using the tools. Your dashboards show adoption rates climbing. Now answer this one honestly: is it actually working? Most enterprise leaders cannot. And that is not a technology problem. It is a measurement problem. Across more than 5,000 businesses surveyed by four central banks in the US, UK, Germany, and Australia, AI is reported to have boosted productivity by just 0.29% over the past three years. Most businesses report AI has not affected their productivity at all. Meanwhile, boardrooms are cutting headcount based on gains they have not yet seen. Gartner found that only 1% of layoffs in H1 2025 were actually the result of AI increasing employee productivity. Leaders are being asked to make cuts on the basis of AI returns that have not yet been realized, and may never be. In some cases, organizations will end up rehiring for roles they cut.  And there is a third problem nobody is talking about loudly enough yet. Gartner calls it "workslop": an abundance of fast but poor-quality work produced by or with AI. Employees are being pressured to adopt AI across as many tasks as possible, with no time or autonomy to check whether the output is actually good. So you have three simultaneous crises running in parallel inside most large enterprises right now. AI adoption is being measured. AI quality is not. AI impact on workforce productivity is not. The organizations pulling ahead are not the ones with the most AI tools. Gartner's data shows that teams redesigning actual workflows with AI are twice as likely to exceed their revenue goals. The difference is not what they are using. It is whether they can see what is changing. That requires workforce intelligence that sits above the tools. Something that connects AI usage patterns to actual output, tracks where productivity is genuinely improving and where it is quietly slipping, and tells you whether AI is reducing workload or simply redistributing it. That is exactly the visibility gap ProHance is built to close. 400,000+ users across 200+ enterprises are already using ProHance to connect effort to outcome, not just log activity. Because the real ROI of AI is not in licenses purchased or tools deployed. It is in outcomes you can actually measure, explain, and act on. How confident are you that your organization can tell the difference between AI adoption and AI impact? Book a demo: https://lnkd.in/gaCXhN8y #AIatWork #WorkforceIntelligence #OperationalExcellence #FutureOfWork #ProHance #GenAI #CHROInsights #EnterpriseProductivity

💸 $400,000 lost. Not to fraud. Not to bad actors. To invisible payroll leakage. That is what one Business Process Management company discovered when they started looking at the gap between what their HRMS said and what was actually happening. 📊 The scale of the problem: According to Deloitte, payroll leakage costs employers an average of 2.5% of total payroll expenses. For large organizations, that translates into hundreds of thousands in unintended spending every year. The challenge is not dishonesty. It is system lag. 🔍 Root causes identified: For this BPM company, the discrepancies came down to three issues: 1. Emergency leave lag: employees took time off, but HRMS systems were not updated in time 2. Deployment gaps: some employees were not consistently deploying the tracking tool, reducing accountability 3. Off-machine activities: physical trainings and meetings without system access went unrecorded 📈 Results after implementing ProHance: ✅ Payroll leakage reduced from 100 man-days to zero ✅ Attendance discrepancies identified within the same pay cycle ✅ $400,000 in verified savings over 2 years ✅ Improved compliance and schedule adherence across operations 💡 This is not about monitoring employees. It is about ensuring that payroll accuracy matches operational reality. Every dollar lost to leakage is a dollar that could have gone toward growth, training, or retention. Same workforce. Accurate visibility. Real savings. 👇 Has your organization ever audited the gap between HRMS data and actual attendance? Find out where your payroll accuracy stands. Book a demo: https://lnkd.in/gaCXhN8y #Payroll #CostOptimization #WorkforceAnalytics #OperationalExcellence #ProHance #BPO

🔎 AI Is Not Lightening the Workday. It Is Compressing It. The assumption was simple: AI tools will reduce work. Shorter days. Lighter loads. More breathing room. The data tells a very different story. 📌 What the research says: > A Feb 2026 study in Harvard Business Review by UC Berkeley researchers found that AI tools do not reduce work. They consistently intensify it. Employees worked faster, took on broader tasks, and extended into more hours, often without being asked. (Source: https://lnkd.in/ewbRpXx9) > Morgan Stanley surveyed 935 executives across the US, Germany, Japan, and Australia. AI delivered an average 11.5% productivity gain, but also a 4% net decline in headcount. (Source: https://lnkd.in/dJFfeMuG) > Gartner's Jan 2026 Future of Work Trends warns that AI pressure is creating "workslop": fast but poor-quality output produced without time to assess quality. (Source: https://lnkd.in/eyjSc7ce) 🔴 The real risk: The question for leaders is no longer "have we adopted AI?" It is: "Do we have visibility into what AI adoption is actually doing to our people?" Without that visibility: • Overload goes undetected • Burnout compounds silently • Productivity gains mask unsustainable patterns • "Workslop" erodes output quality 💡 The ProHance perspective: AI adoption without workforce intelligence is a blind bet. Our platform helps leaders see not just whether AI is being used, but how it is reshaping workload, capacity, and sustainable performance across teams. AI is accelerating work. The question is whether your organization can see what that acceleration is actually costing. 👇 What is your organization doing to measure AI's real impact on workload? Want to see how AI is really impacting your workforce? Book a demo: https://lnkd.in/gaCXhN8y #AI #WorkforceAnalytics #Productivity #FutureOfWork #Burnout #ProHance #AIAdoption #OperationalExcellence

The conversations are shifting from “exploring transformation” to “proving impact.” And that’s exactly where ProHance showed up strong last week in SSOW 2026. As a proud sponsor, our focus was clear: helping GBS and GCC leaders move beyond pilots and into measurable, scalable productivity outcomes. Here’s what that looked like from our end 👇 Booth 212 Four days of engaging with global leaders who are actively building data-led, performance-driven organizations. 🎤 On the stage 17th March | Workshop:  From AI Pilots to Proven Productivity ROI A deep dive into how organizations can measure, scale, and sustain workforce value beyond experimentation. 18th March | Fireside Chat-  Data First Foundations: Building a Unified, Actionable Strategy An insightful conversation between our SVP, Khiv Singh, and Vikram Talwar on why strong data foundations are the backbone of sustainable transformation. What stood out across every interaction: Leaders who are pulling ahead are the ones who can prove impact, not just promise it, and that starts with the right data. If we connected, let’s keep the conversation going. If not, we’d love to show you how ProHance can help you turn productivity into a measurable advantage. 🔗 Book a demo: https://lnkd.in/gaCXhN8y #WorkforceProductivity #DataStrategy #GBS #GCC #ProHance #AI #FutureOfWork