John Lepore

At HealthEdge®, we believe true transformation happens when people across the organization don’t just understand what AI can do, but apply it to elevate their day-to-day work. To drive this, we’ve built a learning ecosystem that meets our teams where they are. The Results of Our Strategy: -Centralization: Our "AI Hub" serves as a single source of truth for curated content and learning paths, eliminating the friction of scattered resources. -Engagement: 30% of our global workforce has attended at least one AI-specific "Power Hour." Our January session on "AI Innovation in Action" saw a peak of 380 participants. -Skill Development: Our LinkedIn Learning consumption includes 122 employees who have started structured AI learning paths. -The Impact: Our latest quarterly pulse survey shows measurable progress across the board. The number of employees who feel empowered to recommend AI solutions grew from 66% to 76%, and overall AI familiarity rose to 81%. Successful AI adoption requires more than technology implementation. It demands a multi-channel approach that respects how different roles learn—unifying the organization around smarter decisions and better outcomes. See how Anshuman Dewangan, Lead Machine Learning Engineer at HealthEdge, and his team are helping drive AI transformation: http://spr.ly/6049h2eK5

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What he's describing is good capture and solutioning practice. This is how you build relationships and confidence pre-RFP. If you're familiar enough with the problem to describe it to the customer? Don't. Instead, leverage that understanding and be prepared to: 1. Ask clarifying questions AND 2. Discuss a potential solution Prepare before you step foot into a meeting with government stakeholders, and you will start to see real progress.

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Across Massachusetts, community colleges are navigating rising enrollment, evolving student expectations, and increasing operational demands—making digital modernization more critical than ever. Bristol Community College is meeting this moment by expanding our partnership and moving to our SaaS platform. This modernization equips Bristol with faster workflows, stronger reporting, seamless integrations, and more personalized experiences for students, faculty, and staff. We’re excited to support Bristol as it embraces a more agile, scalable, and future-ready system!

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Dive into a powerful conversation unpacking Pega’s latest research on the staggering $370M in annual waste caused by technical debt at the average global enterprise. Read the full report: https://lnkd.in/e7TQhpNU

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A huge thank you to Michael Altman , VP of E2E Self Care SCM at Kenvue, for visiting our Rutgers Business School EMBA cohort as a guest speaker. Mike provided us with deep insights into Integrated Business Planning (IBP). The key focus of our session yesterday was to understand the core pillars of IBP: ✅ Portfolio Management Review: Tracks innovation performance and aligns resources with strategy. Takeaway: Stage Gate Management is essential for project progression and clear go/no-go decisions.  ✅ Demand Planning: Reaches consensus on an unconstrained, assumption-based view of sales. Takeaway: Prioritize the top 20% of products that generate 80% of sales and gross profit.  ✅ Supply Planning: Synchronizes manufacturing and procurement to support demand based on demonstrated capacity. Takeaway: Monitor key asset capacity; underutilization is as detrimental to costs as overutilization.  ✅ Integrated Reconciliation (IRR): Consolidates the financial outlook and vets gap-closing proposals.  ✅ Management Business Review (MBR): Final leadership alignment on a 24-month outlook to decide on trade-offs and investments. The highlight was a group exercise Mike facilitated where we represented different functional areas: Commercial Sales & Marketing, Distribution & Logistics, and Manufacturing & Procurement. We simulated a real-world crisis—a massive 4x demand spike for Listerine during a global pandemic. The exercise helped demonstrate how these departments must pivot in unison to manage raw material shortages, optimize capacity, and ensure product reaches customers when they need it most. ✨ Key takeaways from the Session • Variable Horizons: Planning windows (typically 4–24 months) vary based on industry, product, and organizational size.  • Data-Driven: IBP leverages industry-standard metrics to eliminate bias and ensure objective decision-making.  • Cross-Functional Collaboration: Success depends on continuous partnership between Sales, Marketing, Supply Chain, and Finance.  • Execution vs. Planning: Organizations must bridge short-term execution (S&OE) with the long-term IBP window to navigate disruptions.  • Modern Tech & Data Quality: With AI integration, data harmonization and quality are now critical for reliable planning Thank you, Mike, for sharing your expertise and helping the Rutgers EMBA Class of 2027 bridge the gap between classroom theory and world-class strategic leadership! 🎓 Special thanks to Professor Joe Agresta for inviting Mike and continuously helping our cohort connect with distinguished industry leaders. This bridge between academic theory and real-world leadership is invaluable to our growth. #RutgersEMBA #SupplyChain #IntegratedBusinessPlanning #Leadership #EMBAClassOf2027

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The VA is piloting new AI tools to support its mission, from clinical decision support to streamlining benefits access. USA TODAY’s latest coverage includes insights from Slalom’s Marcus Forman, whose veteran experience underscores the potential impact of this work.

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CNA Insurance moved from static spreadsheets to agile, connected planning with Atlassian’s Strategy Collection. See how this 100-year-old leader transformed its strategy: https://oal.lu/nmrGi

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I completely agree — shifting from static systems of record to event-driven, intelligent, and proactive platforms is critical for the life sciences industry. But this evolution isn’t about AI. It’s about how these platforms were originally engineered. Most were built as systems of record, not as event-driven systems designed to accommodate real-time intelligence, automation, and the power of AI — often requiring massive development teams to adapt. A major challenge across the industry remains adaptability. True innovation won’t come from adding more code, but from No-Code Platforms that make it easy to configure and tailor solutions across studies, sites, sponsors, and brands — while quickly responding to inevitable protocol amendments, regulatory updates, or program changes without needing an army of developers to build bespoke solutions each time. Platforms that were engineered this way from the start can quickly “plug AI Agents inside” — amplifying their capabilities to become intelligent, proactive, and self-optimizing without an army of developers. I believe, this is the real shift that's needed: from record-keeping systems to adaptive, event-oriented intelligence built for the future of life sciences, now with the power of AI inside.

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