Using Technology to Enhance Productivity During Change

In a fast-moving digital landscape, I’ve found that staying hands-on with emerging technologies is key—not to master every tool, but to understand how they can drive meaningful value across the organization. It’s about connecting innovation to strategy and making sure the right technologies are in place to support teams, streamline operations, and deliver better outcomes. This past weekend, I spent time exploring how these tools can be applied in practical ways. I used CursorAI for some vibecoding—building API-driven dashboards to transform financial and system data into meaningful, actionable reports. I then designed agentic agent workflows in N8N to automate repetitive tasks and enhance operational efficiency. To build on that, I created logic in Azure Logic Apps and integrated it with Microsoft Sentinel to monitor security alerts. Those alerts were sent to ChatGPT for contextual analysis, with the results published back into Sentinel—helping surface insights faster and enabling more informed responses. It’s not about becoming an expert in every platform. It’s about staying close enough to the technology to guide strategy, ask better questions, and empower teams to apply innovation where it matters most. What are you exploring, building, or learning to stay sharp and future-ready? #TechLeadership #AI #Automation #CursorAI #N8N #LogicApps #MicrosoftSentinel #DigitalStrategy #Innovation #ContinuousLearning

Recommended 👓 Navigating the Jagged Technological Frontier: Field Experimental Evidence of the Effects of AI on Knowledge Worker Productivity and Quality by Harvard University This study investigates the impact of generative AI on productivity and quality in knowledge work. It explores how AI tools like GPT-4 influence consultants' efficiency and effectiveness, the differential impacts on various skill levels, and effective integration strategies. Conducted with 758 consultants from Boston Consulting Group, the study used a controlled experiment to measure productivity and quality outcomes. The findings reveal that AI significantly enhances both productivity and quality, with notable improvements across all skill levels, particularly for below-average performers. Successful integration requires discerning suitable tasks for AI and adopting either "Centaur" or "Cyborg" approaches. Continuous learning and adaptation are essential as AI capabilities evolve. Takeaways and Recommendations 1. Enhanced Productivity and Quality with AI: - Takeaway: AI significantly boosts productivity and quality in knowledge work. Consultants using AI completed 12.2% more tasks and did so 25.1% faster, with a 40% improvement in quality compared to the control group. - Recommendation: Integrate AI tools like GPT-4 into daily workflows for tasks within AI’s current capabilities to enhance efficiency and output quality. 2. Varied Impact on Different Skill Levels: - Takeaway: AI benefits consultants across all skill levels, with below-average performers improving by 43% and above-average performers by 17%. - Recommendation: Provide AI training and access to all employees, focusing on upskilling lower-performing individuals to maximize productivity gains. 3. Navigating the Jagged Technological Frontier: - Takeaway: The AI frontier is uneven, excelling in some tasks while failing in others. - Recommendation: Carefully assess which tasks are suitable for AI assistance. Implement guidelines to identify tasks where AI can be beneficial and where human expertise is crucial. 4. Patterns of Successful AI Integration: - Takeaway: Successful AI users fall into two categories: “Centaurs,” who divide tasks between themselves and AI, and “Cyborgs,” who fully integrate AI into their workflow. - Recommendation: Encourage employees to adopt either the Centaur or Cyborg approach based on task requirements and personal working styles. Provide training on effective AI collaboration techniques. 5. Continuous Learning and Adaptation: - Takeaway: The capabilities and failure points of AI are constantly evolving, making ongoing learning and adaptation essential. - Recommendation: Establish continuous learning programs and feedback loops for employees to stay updated on AI advancements and best practices. https://lnkd.in/emfK2MtK

Technology is changing. So should your approach to continuous improvement. Lean was born in the mid-20th century as a response to manufacturing inefficiencies. There’s been a technological revolution since then. Back then: - time studies were done with stopwatches, pen and paper - charts were drawn by hand - data collection was done manually The old methods are tried and true, but we can do better. Continuous Improvement leaders cannot afford to be Luddites. Here are 4 ways to embrace 21st-century technology in your CI strategy: ✅ Robotic Process Automation (RPA) → Extremely useful for computer-based admin tasks. → Automate repetitive tasks to free up time for value-added activities. → RPA enhances efficiency, reduces human error, and accelerates process cycles. ✅ Agile Framework + Project Management Software → Helps adapt quickly to change. → The best practice for most projects. → Track progress, collaborate seamlessly, and deliver improvements faster. ✅ Real-Time Process Monitoring → provides immediate feedback → allows for faster decision-making and quicker issue resolution. → Use sensors, IoT devices, and data analytics to monitor processes in real-time. ✅Vision Systems → AI-driven vision systems for enhanced quality control and defect detection. → analyze production lines in real-time, improving consistency and reducing waste. Technology is not a threat to CI — it’s the key to unlocking its full potential. How are you embracing 21st-century technology in your Continuous Improvement initiatives? #ContinuousImprovement #Lean #Technology #Innovation #ProcessImprovement #Automation #Agile #RPA #QualityControl #Manufacturing *** 👋 Hi, I'm Michael! 🙏 Thanks for reading my post 📣 Please like, comment, and share 🔔 Turn on notifications & follow so you don't miss a post