How to Align Technology Delivery With Business Value

I watched a brilliant, but "green" CTO nearly kill his own digital transformation proposal. It was my first day with this advisory client. Thirty minutes into a presentation, he was deep into microservices architectures and API gateways. The CEO finally interrupted: "How will this impact our quarterly earnings?" Silence. Let's do some "executive translation" practice: ❌ **Technology narrative:** "We need to modernize our legacy systems with cloud-native architecture to improve scalability and reduce technical debt” (accurate, but wrong). ✅ **Business narrative:**  "In order to achieve our North Star vision, we need the technological capability to iterate and launch 75% faster while reducing our operational risk from system failures” (still accurate, and right). Here's the framework: 🎯 **Lead with business outcomes** → Revenue acceleration → Cost reduction  → Risk mitigation → Competitive advantage 💡 **Connect technology to improved business capabilities** → "Speed to market" → "Operational resilience" → "Customer experience quality" → "Innovation velocity" 📊 **Quantify in real business terms** → Time to revenue → Market share protection → Customer retention rates → Operational efficiency gains The reframe that changes everything: ❌: "We're implementing DevSecOps" ✅: "We're building the capability to deliver customer value continuously while reducing our risk" Whatever your role or level today, if you can master this translation, you will become a strategic partner, not a service provider. Even if you're not a CTO yet, you could become his/her best friend tomorrow. The board doesn't care about your RAG pattern, micro services architecture or your DevSecOps. They care about what it enables for their business. #TechnologyStrategy #ExecutiveCommunication #BusinessValue #CTO #BoardReadiness

Stop being the IT department’s repair shop—start leading strategic change. You’re more than just tech support—here’s how to prove it. Tech leaders, it's time to rewrite your role. You're not just the person who keeps the lights on - you're the visionary who illuminates new paths forward. Here's how to make that shift: 𝟭. 𝗔𝗹𝗶𝗴𝗻 𝗧𝗲𝗰𝗵 𝘄𝗶𝘁𝗵 𝗕𝘂𝘀𝗶𝗻𝗲𝘀𝘀 𝗚𝗼𝗮𝗹𝘀 Every project should answer: "How does this drive our strategy?" When you present, lead with outcomes, not gigabytes. Show how IT propels the company forward. 𝟮. 𝗕𝘂𝗶𝗹𝗱 𝗕𝗿𝗶𝗱𝗴𝗲𝘀 𝗔𝗰𝗿𝗼𝘀𝘀 𝗗𝗲𝗽𝗮𝗿𝘁𝗺𝗲𝗻𝘁𝘀 Be curious. Learn what keeps other leaders up at night. Then, offer solutions they haven't even dreamed of yet. Your value skyrockets when you solve problems beyond the server room. 𝟯. 𝗖𝗵𝗮𝗺𝗽𝗶𝗼𝗻 𝗜𝗻𝗻𝗼𝘃𝗮𝘁𝗶𝗼𝗻 Don't wait for permission to innovate. Pilot new ideas that could transform the business. Be the catalyst for "what if" conversations that open new possibilities. 𝟰. 𝗠𝗲𝗮𝘀𝘂𝗿𝗲 𝗪𝗵𝗮𝘁 𝗠𝗮𝘁𝘁𝗲𝗿𝘀 Capture the impact of your work in terms the C-suite cares about. Revenue generated. Costs saved. Customer satisfaction improved. Let the numbers tell your story. 𝟱. 𝗖𝗹𝗮𝗶𝗺 𝗬𝗼𝘂𝗿 𝗦𝗲𝗮𝘁 𝗮𝘁 𝘁𝗵𝗲 𝗦𝘁𝗿𝗮𝘁𝗲𝗴𝘆 𝗧𝗮𝗯𝗹𝗲 Inject tech insights into high-level planning. Show how IT isn't just a support function - it's a cornerstone of future success. Your perspective is essential. 𝙏𝙝𝙚 𝙎𝙩𝙖𝙩𝙨 𝘿𝙤𝙣'𝙩 𝙇𝙞𝙚: - 32% of IT pros feel they lack leadership skills to advance. It's time to invest in yourself. (Global Knowledge) - 70% want leadership roles, but only 40% get needed development. Seek mentors and training. (Gartner) - IT leaders with business savvy are 2.5x more likely to reach the C-suite. Master the big picture. (Deloitte) The shift from "fix it" to "future it" won't happen overnight. But with persistence and vision, you'll transform not just your role, but your entire organization's relationship with technology. Pick one of these steps. Implement it this week. Share your results. Let's change the narrative together.

You might as well be speaking “Klingon” Just dropped from a meeting where the IT Director provided his update to the leadership team. The c-level folks and non-technical leaders had no clue what he was talking about… From my experience this is the #1 mistake technical professionals make when meeting with business stakeholders I'll be blunt… business stakeholders don’t care about your technical architecture diagrams, your configuration details, or how cutting-edge your solution is. They care about outcomes. They care about results. They care about impact. BUT most technical professionals go into meetings armed with technical jargon & acronyms and leave the room wondering why no one bought in. If you’re presenting to business leaders, here’s the reality check… you are selling and you’re not selling technology - you’re selling business value. I don’t like to present a problem without a solution – so let’s try this… Step 1 Start every conversation by answering this “How does this solve a business problem?” If you have a technical solution that reduces costs, increases revenue, mitigates risk, or makes life easier for users, lead with that. Everything else is just details that nobody cares about. Step 2 Translate technical features into business benefits. Instead of saying, “We’re implementing zero trust,” say, “We’re reducing critical risks to our top revenue producing critical business functions.” Step 3 Stakeholders want to hear about how your solution will reduce downtime, increase productivity, save $$$, or improve client satisfaction. Make your impact measurable and relatable. Step 4 Can you reframe your message using an analogy or better yet a story. Numbers are great, but stories are sticky and resonate. Frame your solution in the context of a real-world scenario, like something stakeholders can visualize and connect with. Step 5 No one likes a squeaky wishy washy technical expert. Take a position, back it with evidence, and be clear about the path forward. Confidence inspires trust. Stop talking about the “how.” Start owning the “why.” And STOP speaking “Klingon” When you shift your focus to business value, you’ll see interest, buy-in, alignment, and support. #ciso #dpo #msp #leadership

I got this line from a CIO in 2019. He meant that they had bought a new server—one server—and it was sitting in a mostly empty rack in a data science manager’s office. It was on a closed network (consumer grade router wired into each team member’s office) that couldn’t be accessed remotely “for security reasons.” Punchline: There was no data on it yet and they hadn’t gotten approval to migrate any datasets. It was a basic install of Redhat with empty MySQL and MongoDB instances. 1% of businesses are ready for AI, while 99%, including some of the biggest companies in the world, are still trying to understand data and the cloud. What should we do? Start with business value. Each technical transformation must have a value-centric justification. Connect infrastructure to the data and AI product roadmap. Develop infrastructure while building and delivering products. Each phase must deliver value, and the product roadmap has initiatives that turn each technology investment into business impacts. It makes the connection clear. If the business wants this revenue and these cost savings, we must invest in these tools. If you’re told, “No, just make do with what we have,” show which initiatives are no longer feasible, either because they cost too much or take too long to be delivered without the infrastructure to support them. Connect investments with the high returns data and AI initiatives can deliver, and you’ll be able to justify a G-650 instead of working on a Dell Ductapeon server. #DataEngineering #DataScience #ProductManagement

𝑵𝒆𝒘 𝒑𝒐𝒔𝒕 𝒔𝒆𝒓𝒊𝒆𝒔 -- 𝑮𝒆𝒏 𝑨𝑰 𝒇𝒐𝒓 𝑵𝒆𝒕𝒘𝒐𝒓𝒌𝒔. 𝑷𝒐𝒔𝒕 6/7 Setting Clear Objectives for AI Integration = Measuring ROI When implementing AI initiatives, it's crucial to ➡ establish clear, measurable objectives, ➡seamlessly integrate AI into existing processes, ➡ continuously measure ROI to ensure alignment with business goals. 𝐂𝐥𝐞𝐚𝐫 𝐃𝐞𝐟𝐢𝐧𝐢𝐭𝐢𝐨𝐧 𝐨𝐟 𝐎𝐛𝐣𝐞𝐜𝐭𝐢𝐯𝐞𝐬 To ensure that AI initiatives are successful, start by setting clear, measurable objectives that align with your overall business goals: ✅ Setting targets for cost reduction through automation and optimization. For instance, a McKinsey report indicates that AI-driven predictive maintenance can reduce maintenance costs by up to 20% and cut unplanned downtime by 50%. ✅Enhancing customer experience by leveraging AI for personalized recommendations, chatbots, and 24/7 support. Gartner predicts that by 2025, 80% of customer service interactions will be handled by AI, leading to faster response times and higher customer satisfaction. ✅Generating new revenue streams by using AI to identify market opportunities and develop innovative products. PwC studies show that AI could contribute up to $15.7 trillion to the global economy by 2030, highlighting its potential for creating new business opportunities. 𝐏𝐫𝐨𝐜𝐞𝐬𝐬 𝐈𝐧𝐭𝐞𝐠𝐫𝐚𝐭𝐢𝐨𝐧 For AI to deliver its maximum value, it needs to be seamlessly integrated into existing business processes: ✅Mapping out existing workflows to identify areas where AI can be most beneficial, such as repetitive, time-consuming tasks that can be automated. ✅Designing a strategic integration plan that minimizes disruptions while maximizing the benefits of AI technologies. Start with pilot projects to test the integration process and refine your approach based on feedback and initial results. 𝐌𝐞𝐚𝐬𝐮𝐫𝐞𝐦𝐞𝐧𝐭 𝐨𝐟 𝐑𝐎𝐈 To justify AI investments, it's essential to establish and continuously monitor metrics that measure the return on investment: ✅Tracking direct financial gains, such as cost savings from automation, increased sales from personalized marketing, or new revenue streams from AI-driven products. ✅Measuring indirect benefits like improvements in customer satisfaction, operational efficiency, and employee productivity. For example, AI can streamline customer service operations, leading to faster response times and higher customer satisfaction ratings. ✅Implementing a robust monitoring system to continuously track these metrics, regularly evaluating the success of AI implementations, and making necessary adjustments to optimize performance and outcomes. This structured methodology helps organizations harness the full potential of AI, driving both innovation and efficiency. What would you add?

Our $2M project went flawlessly, 𝗯𝘂𝘁, 𝗼𝗻𝗹𝘆 𝟮𝟬% 𝗼𝗳 𝘁𝗵𝗲 𝗯𝘂𝘀𝗶𝗻𝗲𝘀𝘀 𝗶𝘀 𝘂𝘀𝗶𝗻𝗴 𝗶𝘁. 🫨 Sound familiar? As IT leaders, we've all felt that pain. The perfect execution that somehow missed the mark on delivering real business value. Here's what 20 years of working with all kinds of companies has taught me: 𝗧𝗵𝗲 𝘁𝗿𝘂𝗲 𝗺𝗲𝗮𝘀𝘂𝗿𝗲 𝗼𝗳 𝗜𝗧 𝘃𝗮𝗹𝘂𝗲 𝗶𝘀𝗻'𝘁 𝘄𝗵𝗲𝗻 𝘁𝗲𝗰𝗵𝗻𝗼𝗹𝗼𝗴𝘆 𝗶𝘀 𝗱𝗲𝗹𝗶𝘃𝗲𝗿𝗲𝗱 - 𝗶𝘁'𝘀 𝘄𝗵𝗲𝗻 𝘁𝗵𝗲 𝗯𝘂𝘀𝗶𝗻𝗲𝘀𝘀 𝗮𝗰𝘁𝗶𝘃𝗲𝗹𝘆 𝘂𝘀𝗲𝘀 𝗶𝘁 𝘁𝗼 𝗱𝗿𝗶𝘃𝗲 𝗼𝘂𝘁𝗰𝗼𝗺𝗲𝘀. Consider this: 𝗖𝗜𝗢𝘀 𝘄𝗵𝗼 𝗲𝗳𝗳𝗲𝗰𝘁𝗶𝘃𝗲𝗹𝘆 𝗰𝗼𝗺𝗺𝘂𝗻𝗶𝗰𝗮𝘁𝗲 𝗯𝘂𝘀𝗶𝗻𝗲𝘀𝘀 𝘃𝗮𝗹𝘂𝗲 𝗺𝗮𝗶𝗻𝘁𝗮𝗶𝗻 𝟲𝟬% 𝗵𝗶𝗴𝗵𝗲𝗿 𝗳𝘂𝗻𝗱𝗶𝗻𝗴 𝗹𝗲𝘃𝗲𝗹𝘀 𝘁𝗵𝗮𝗻 𝘁𝗵𝗲𝗶𝗿 𝗽𝗲𝗲𝗿𝘀 𝗮𝗰𝗰𝗼𝗿𝗱𝗶𝗻𝗴 𝘁𝗼 𝗚𝗮𝗿𝘁𝗻𝗲𝗿. But that communication must go beyond uptime statistics and deployment metrics. Three key principles I've learned about maximizing and communicating IT value: 1️⃣ 𝗩𝗮𝗹𝘂𝗲 𝗶𝘀 𝗱𝗲𝗳𝗶𝗻𝗲𝗱 𝗯𝘆 𝘁𝗵𝗲 𝗯𝘂𝘀𝗶𝗻𝗲𝘀𝘀 𝘀𝘁𝗮𝗸𝗲𝗵𝗼𝗹𝗱𝗲𝗿, 𝗻𝗼𝘁 𝗜𝗧. Revenue growth, cost optimization, and risk management are universal languages. Speak them fluently. 2️⃣ 𝗧𝗲𝗰𝗵𝗻𝗼𝗹𝗼𝗴𝘆 𝗮𝗱𝗼𝗽𝘁𝗶𝗼𝗻 𝗶𝘀 𝘁𝗵𝗲 𝗯𝗿𝗶𝗱𝗴𝗲 𝗯𝗲𝘁𝘄𝗲𝗲𝗻 𝗱𝗲𝗹𝗶𝘃𝗲𝗿𝘆 𝗮𝗻𝗱 𝘃𝗮𝗹𝘂𝗲. The most elegant solution delivers zero value if users aren't prepared or willing to embrace it. Build adoption strategies into every initiative. 3️⃣ 𝗧𝗲𝗹𝗹 𝗯𝗼𝘁𝗵 "𝗿𝘂𝗻" 𝗮𝗻𝗱 "𝗰𝗵𝗮𝗻𝗴𝗲" 𝘃𝗮𝗹𝘂𝗲 𝘀𝘁𝗼𝗿𝗶𝗲𝘀. While transformation projects are exciting, 70% of IT budgets support daily operations. Both narratives matter. 𝗧𝗵𝗲 𝗯𝗼𝘁𝘁𝗼𝗺 𝗹𝗶𝗻𝗲: 𝗧𝗲𝗰𝗵𝗻𝗶𝗰𝗮𝗹 𝗲𝘅𝗰𝗲𝗹𝗹𝗲𝗻𝗰𝗲 𝗮𝗹𝗼𝗻𝗲 𝗱𝗼𝗲𝘀𝗻'𝘁 𝗴𝘂𝗮𝗿𝗮𝗻𝘁𝗲𝗲 𝗯𝘂𝘀𝗶𝗻𝗲𝘀𝘀 𝘃𝗮𝗹𝘂𝗲. Success lies at the intersection of robust technology, meaningful metrics, and accelerated adoption. What's your experience with technology adoption's impact on value realization? SIM South Florida 🔵 #CIO #ITLeadership #BusinessValue #DigitalTransformation

✴ ISO42001 as the New Blueprint for Creating Business Value with AI Governance✴ Your organizations have embraced AI. In doing so, you’ve matured to approach #AIgovernance from a perspective other than just compliance; you now need to ensure your AI systems are creating business value by ensuring they deliver desired outcomes while optimizing both risk and cost. #ISO42001 reframes and positions governance as a framework for value creation, integrating risk management, bias reduction, ethical oversight, and stakeholder engagement to optimize AI’s impact. ➡1. Comprehensive Risk Management: Protecting Value Through Resilience AI introduces dynamic risks, from security threats to operational failures, which can impact business value. ISO42001 provides a structured approach to managing these risks, enabling organizations to protect and enhance AI’s value by building resilience. ☑Supporting Standards: #ISO23894 complements ISO42001 with lifecycle risk management, guiding proactive mitigation to prevent costly issues. ✅Value Creation: By reducing disruptions and unforeseen costs, risk management ensures AI reliability and aligns performance with strategic goals. ➡2. Bias Management at Every Stage: Achieving Desired Outcomes and Reducing Reputational Risk Bias can undermine AI’s ability to deliver fair outcomes, impacting brand trust. ISO42001 emphasizes bias management across the lifecycle, ensuring AI systems meet ethical standards and public expectations. ☑Supporting Standards: #ISO12791 provides practical guidance on reducing bias in data collection, model training, and deployment. ✅Value Creation: By minimizing bias, organizations achieve reliable outputs that meet desired outcomes, reducing reputational risk and enhancing long-term value. ➡3. Ethical Oversight and Stakeholder Engagement: Aligning AI with Organizational Values and User Trust ISO42001 includes ethical oversight and stakeholder engagement to align AI with organizational values and user needs, crucial for value realization. ☑Supporting Standards: #ISO5339 adds depth by focusing on societal impacts and stakeholder expectations, ensuring AI operates responsibly and transparently. ✅Value Creation: Engaging stakeholders and embedding ethics builds trust and aligns AI with societal expectations, enhancing brand reputation and customer loyalty—key drivers of long-term value. ➡4. Continuous Monitoring for Adaptability: Sustaining Value by Optimizing Performance AI requires ongoing adaptation to stay aligned with business goals. ISO42001 emphasizes continuous monitoring, helping organizations sustain and optimize AI performance over time. ☑Supporting Standards: #ISO5338 structures lifecycle processes for iterative improvement, while ISO23894 provides ongoing risk monitoring. ✅Value Creation: Ongoing optimization keeps AI aligned with desired outcomes, minimizing costs from outdated models and maximizing efficiency. A-LIGN #TheBusinessofCompliance #ComplianceAlignedtoYou

🚨 𝐈𝐟 𝐲𝐨𝐮𝐫 𝐭𝐞𝐜𝐡 𝐫𝐨𝐚𝐝𝐦𝐚𝐩 𝐢𝐬𝐧’𝐭 𝐭𝐢𝐞𝐝 𝐭𝐨 𝐛𝐮𝐬𝐢𝐧𝐞𝐬𝐬 𝐜𝐚𝐩𝐚𝐛𝐢𝐥𝐢𝐭𝐢𝐞𝐬, 𝐢𝐭’𝐬 𝐣𝐮𝐬𝐭 𝐚 𝐰𝐢𝐬𝐡𝐥𝐢𝐬𝐭. Everyone’s launching AI pilots, buying new tools, moving to cloud. But ask this first: 👉 𝑊ℎ𝑎𝑡 𝑐𝑎𝑝𝑎𝑏𝑖𝑙𝑖𝑡𝑦 𝑎𝑟𝑒 𝑤𝑒 𝑒𝑛𝑎𝑏𝑙𝑖𝑛𝑔? 👉 𝐼𝑠 𝑖𝑡 𝑐𝑜𝑟𝑒 𝑡𝑜 ℎ𝑜𝑤 𝑤𝑒 𝑐𝑜𝑚𝑝𝑒𝑡𝑒 — 𝑜𝑟 𝑗𝑢𝑠𝑡 𝑐𝑜𝑛𝑣𝑒𝑛𝑖𝑒𝑛𝑡? Too many roadmaps look impressive. But don’t move the business forward. Why? Because we’re prioritizing 𝐭𝐞𝐜𝐡𝐧𝐨𝐥𝐨𝐠𝐲 without prioritizing 𝐯𝐚𝐥𝐮𝐞. 💡 The bridge between strategy and execution isn’t more tools. It’s 𝐄𝐧𝐭𝐞𝐫𝐩𝐫𝐢𝐬𝐞 𝐀𝐫𝐜𝐡𝐢𝐭𝐞𝐜𝐭𝐮𝐫𝐞. Not as governance. But as 𝑐𝑙𝑎𝑟𝑖𝑡𝑦: ✅ Define which capabilities matter ✅ Align initiatives to those capabilities ✅ Build tech that actually delivers outcomes 🎯 𝐖𝐡𝐚𝐭 𝐦𝐚𝐤𝐞𝐬 𝐚𝐧 𝐞𝐟𝐟𝐞𝐜𝐭𝐢𝐯𝐞 𝐫𝐨𝐚𝐝𝐦𝐚𝐩 𝐭𝐨𝐝𝐚𝐲? ➡ Clear connection to business priorities ➡ Ruthless focus on core capabilities ➡ AI + automation that frees up resources — not adds noise 👑 𝐋𝐞𝐚𝐝𝐞𝐫𝐬𝐡𝐢𝐩 𝐥𝐞𝐬𝐬𝐨𝐧: Don’t measure how much you’re building. Measure whether you’re building what 𝑚𝑎𝑡𝑡𝑒𝑟𝑠. 💬 What’s one capability your roadmap has helped unlock — or one you wish had been prioritized earlier? 👇 Let’s share and learn — because real strategy lives in what we 𝑏𝑢𝑖𝑙𝑑 𝑛𝑒𝑥𝑡. #EnterpriseArchitecture #AI #TechStrategy #Leadership

🚨 Shipping fast isn't enough. If your AI roadmap doesn’t reflect enterprise value, you add technical debt. In my latest article, I share the moment that reshaped how I lead: A boardroom question that exposed the gap between technical excellence and business alignment. Inside the post: ✅ Why trust architecture, not just tech stack, wins enterprise deals 📈 How we linked GenAI features to NRR, OpEx reduction, and CAC payback 🛡️ How we made ethics, FinOps, and observability part of every deployment 💬 What boards want from technology leaders today This isn’t just about delivering, it’s about delivering what matters. Would love to hear how you're connecting tech to revenue and risk in your organization. #AILeadership #TechStrategy #DigitalExecution #EnterpriseValue #FinOps #TrustByDesign #ProductLeadership