How to Adapt Strategies for Technology Investments

Most enterprises waste millions on tech without seeing real impact. I learned this the hard way. Early in my career, I saw companies invest in cutting edge tools only to struggle with adoption, integration, and ROI. That’s when I developed a smarter, outcome-driven approach. Here’s the exact method I use to maximize ROI from technology investments:  Start with Business Outcomes, Not Features ↳ Define the measurable impact before picking the tech. What problem are you solving? What KPIs will prove success?  Ensure Alignment Across Teams ↳ IT, finance, and business leaders must be on the same page. Misalignment leads to wasted budgets and underutilized tools.  Adopt in Phases, Not All at Once ↳ Test, refine, and scale. A phased rollout prevents disruptions and maximizes adoption.  Measure, Optimize, Repeat ↳ Regularly assess ROI. What’s working? What needs adjustment? Continuous refinement drives long-term value. Tech alone doesn’t drive transformation—strategy does. How do you ensure your technology investments deliver real business impact? Let’s discuss. 👇 🔹 Follow me for more insights on digital transformation. 🔹 Connect with me to explore strategies that drive real impact. ♻️ Repost this to help your network. P.S.: Thinking about how to maximize your tech investments? Let’s chat. I’m happy to share insights on what works (and what to avoid).

I thought my first tech strategy would be flawless—until reality hit. Six months in, half our initiatives were off-track, and stakeholder buy-in was crumbling. Sound familiar? Let's face it: most first-time tech strategies crash and burn. But what if you could flip the script? I've seen it all in my years as a tech leader. The good, the bad, and the "oh no, what have we done?" I've developed some unconventional approaches that actually work. Here are 5 game-changers to make your tech strategy stick: 𝟭. 𝗣𝗹𝗮𝘆 "𝗪𝗵𝗮𝘁'𝘀 𝘁𝗵𝗲 𝗪𝗼𝗿𝘀𝘁 𝗧𝗵𝗮𝘁 𝗖𝗼𝘂𝗹𝗱 𝗛𝗮𝗽𝗽𝗲𝗻?" Imagine your strategy failed spectacularly. Why? By identifying weak spots now, you can fix them before they become real problems. Don't just plan for success – plan for setbacks too. 𝟮. 𝗖𝗼-𝗰𝗿𝗲𝗮𝘁𝗲 𝘄𝗶𝘁𝗵 𝗦𝘁𝗮𝗸𝗲𝗵𝗼𝗹𝗱𝗲𝗿𝘀 Get everyone involved, from junior devs to C-suite execs. In my last project, involving customer service reps early led to UX changes we'd never have considered. More diverse brains = better aligned ideas. 𝟯. 𝗠𝗮𝘀𝘁𝗲𝗿 𝗦𝗰𝗲𝗻𝗮𝗿𝗶𝗼 𝗣𝗹𝗮𝗻𝗻𝗶𝗻𝗴 Prepare for multiple futures. When COVID hit, companies with flexible tech strategies adapted quickly. Make your plan resilient enough to thrive in various scenarios. Adaptability is essential. 𝟰. 𝗪𝗼𝗿𝗸 𝗕𝗮𝗰𝗸𝘄𝗮𝗿𝗱𝘀 Start with your end goal, then map the steps to get there. This Reverse Roadmap approach helped us trim 3 months off a recent project timeline by eliminating unnecessary detours. 𝟱. 𝗧𝗵𝗶𝗻𝗸 𝗟𝗶𝗸𝗲 𝗮 𝟰-𝗬𝗲𝗮𝗿-𝗢𝗹𝗱 Channel your inner curious kid. Ask "Why?" about everything, repeatedly. Break big problems into tiny pieces. These first principles thinking can build a resilient and revolutionary strategic foundation. 𝙒𝙝𝙮 𝙗𝙤𝙩𝙝𝙚𝙧 𝙬𝙞𝙩𝙝 𝙩𝙝𝙚𝙨𝙚 𝙪𝙣𝙘𝙤𝙣𝙫𝙚𝙣𝙩𝙞𝙤𝙣𝙖𝙡 𝙢𝙚𝙩𝙝𝙤𝙙𝙨? Because they force you to think differently, challenge assumptions, and create more robust strategies. Plus, the stats are scary: - 70% of digital transformations fail (McKinsey) - But nail it, and you could see 1.8x more growth (MIT Sloan) - 90% of startups sink due to bad tech choices (CB Insights) Don't be another statistic. These approaches have saved me more times than I can count, turning potential disasters into success stories. Ready to level up your tech game? Let's talk about it! What's your uncommon (but most effective) strategy tactic? Share your experiences in the comments!

In the US, enterprise tech spending has grown 8% annually while labor productivity has grown less than 2%. The tech spend to productivity relationship is showing up in mid-year budget discussions currently underway at most companies. The economics of IT/tech/digital/AI are (again) under a microscope. It was the same last year, and the year before that and every year prior for as long as I have been a professional adviser to CEOs, CFOs, and CIOs.  Tired of this Groundhog Day moment every year, we decided to dig into the economics of enterprise tech. There is some “new news” and some new insights on “old news”. The “new news” – what’s driving up costs: 1. Cyberattacks increased over 25% last year, resulting in a 15% increase in cybersecurity spend this year. While much of this is necessary, it doesn't correlate with an ROI a company can point to. 2. Increase in AI and geopolitical-related spending. On AI, most companies haven't seen value from their investments (only 1% describe themselves as “mature” in their AI deployments).     The new insights on “old news” are: 1. Indirect costs of product development (cloud/security services/tool licenses) can account for 80% of a product’s lifetime costs.   2. Incentive misalignment leads to poor decisions on enterprise tech spend and results in a 20-30% loss of value.  3. Companies pay an additional 10-20% to address tech debt on top of the costs of any project, creating a significant drag on productivity.  4. 5-10% of IT productivity improvements can be lost to vendors (for example, when providers don't pass along reduction in hardware costs).     Clearly, there's a need for deeper understanding and transparency into the economics of enterprise tech. In this new analysis with my colleagues Pablo Prieto, Ph.D., Jeffrey Lewis, James Kaplan, we lay out 4 ways to optimize these investments.  1️⃣Meter and measure: Track tech usage cost at a granular level to foster accountability and minimize tech debt, use models like FinOps. 2️⃣Treat everything as a product: Manage all technology initiatives as products with autonomous, accountable, and incentivized cross-functional teams (led by product managers) to ensure cost responsibility and value capture. 3️⃣Go big: Prioritize domains (end-to-end processes) over single use cases, leverage analytics to pinpoint and amplify initiatives with the most impact. 4️⃣Embrace and accelerate: Optimize agentic AI to modernize and rethink talent models with more flexible systems. In this season and beyond, the choices CEOs, CFOs and CIOs make now will be the cornerstone of success in an AI-driven future.  Looking forward to discussing this more with clients over the rest of the year to ensure 2026 decisions and priorities are better planned, executed, and value is fully realized. #NeverJustTech #McKinseyTechnology #TechEconomics #CIO #CFO https://lnkd.in/grFUuQks

Many companies express frustration with their software solutions, but the root cause isn't always the software itself. In my experience as CIO and Chief Strategy Officer at Bed Bath & Beyond, and now at cda Ventures LLC, I've observed that the issue often lies in a lack of understanding of the software's full capabilities and inadequate processes surrounding its use. This disconnect can lead to underutilization of powerful tools and a perception that the software is failing to meet business needs. To address this challenge, companies should first conduct a thorough assessment of their current software usage. This includes defining and/or documenting existing processes, comparing utilized features against the software's full capability set, and evaluating employee training programs. Next, organizations should invest in comprehensive training and create clear, standardized processes that align with the software's functionalities. Engaging with software vendors for advanced training or bringing in external consultants can provide fresh perspectives on optimization. Finally, establishing a feedback loop for continuous improvement and regularly reviewing software utilization can ensure that teams are maximizing their technology investments. Are you effectively leveraging your investment in your software solutions? #SoftwareOptimization #BusinessEfficiency #TechnologyAdoption #ChangeManagement #DigitalTransformation #ProcessImprovement #SoftwareImplementation #CIOInsights #BusinessStrategy

Your PortCo’s have invested in AI, IoT, maybe even Blockchain, but the ROI isn’t showing up. The problem usually isn’t the technology; it’s the operating blueprint underneath it. A 2025 study in ACCESS Journal finds that one of the biggest failure points in digital transformation is trying to force dynamic, flexible technologies into rigid Enterprise Architecture (EA) frameworks. These frameworks — TOGAF, Zachman, and others — were designed for stability, not speed. When today’s tech meets yesterday’s architecture: 🔹Strategic goals and IT execution drift apart 🔹Change slows down 🔹Investments underdeliver To close the gap, companies must evolve EA from a static map into a living, dynamic system that flexes with the business and unlocks value. The research suggests the following actions to turn your EA from an anchor into an enabler: 🔹 Go from Blueprint to GPS: Modern EA must become a translation layer between business strategy and tech capability, not a rigid schematic. → Start by auditing where your EA slows decision velocity. 🔹Rebuild Around Data: AI and IoT require your system to deal with large amounts of real-time data. If your EA can't process and act on it, you're leaving value on the table. → Invest in governance, real-time integration, and feedback loops. 🔹Fix the Culture Constraint: Technology doesn’t fail. People resist. → Shift your culture from "protect the old" to "learn the new." Build adaptability into your org design. 🔹Design for Sustainable Scale: Short-term wins without architectural discipline create long-term complexity. → Pressure-test every tech decision against long-range scalability and strategic alignment. Key Take Away for Executives: Companies who want to become digital transformation champions need to elevate these discussions from being “an IT topic” to a strategic level.  Done right, architecture unlocks the efficiency, agility, and innovation promised by new technology and is a key value driver.   What has been your bigger challenge when implementing new tech and how have you adapted? Link to full study: https://lnkd.in/e-FFsnUH #DigitalTransformation #SciencemeetsStrategy

Continuing the Countdown Series with #7 Challenge for CFOs in 2024: Making the most of Technology Investments. This is a topic I am really passionate about as a CFO for a company that serves the Office of the CFO. But, for CFOs, it goes wider than our own tech stack to include the technology investments being made across the organization and helping to size the value and impact of these tools. Some thoughts on this. 1️⃣ What are the requirements for the next 24 months: Your tech needs are not stagnant and the tools that will support the business today may not meet the needs 2+ years from now. On the one hand, buying an enterprise grade solution as a small 10 person startup is not the right answer, but for larger companies, if you have visibility into where the business is going, predicting those requirements and building them into the decision set will save you a painful transition in the future. 2️⃣ Prioritize, Prioritize, Prioritize: There are a finite number of tools that can be implemented well in a given time period - be it in your finance organization or in other parts of your business. And mostly, it's not about the technology itself. It's the crucial step of change management and process design that allow those tools to be effectively utilized across the organization. If you don't change hearts and minds to use the new tools effectively they won't work. This is especially true if the new tools and processes will impact employees across many areas of the business versus being part of a single department's tech stack. 3️⃣ AI in your existing or new tech stack: Talking with my peers the question that comes up all the time is when will the promises of new AI functionality in our existing and new tech stack result in the outcomes of efficiencies in a more predictable way. I am loving what I am seeing in some functional areas but it's not across the board. Piloting and testing is important to drive learning and choose where to focus the companies resources. But eventually, the outcome needs to be quantifiable in lower cost, faster speed, or higher output depending on the technology. If 2023 was the year to test, then 2024 needs to be about real outcomes. Finance leaders - How are you ensuring effective allocations of resources in your technology decisions? - 📈 Hi, I'm Sarah, CFO at Tipalti 🔔 Connecting with other Finance leaders is a passion of mine.  Follow me here: Sarah Spoja

Let’s say your support center is getting hammered with repeat calls about a new product feature. Historically, the team would escalate, create a task force, and maybe update a knowledge base weeks later. With the tech available today, you should be able to unify signals from tickets, chat logs, and social mentions instead. This helps you quickly interpret the root cause. Perhaps in this case it's a confusing update screen that’s triggering the same questions. Instead of just sharing the feedback with the task force that'll take weeks to deliver something, galvanize leaders and use your tech stack to orchestrate a fix in real time. Don't have orchestration in that stack? Start looking into this asap. An orchestration engine canauto-suggest a targeted in-app message for affected users, trigger a proactive email campaign with step-by-step guidance, and update your chatbot’s responses that same day. Reps get nudges on how to resolve the issue faster, and managers can watch repeat contacts drop by a measurable percentage in real time. But the impact isn’t limited to operations. You energize the business by sharing these results in a company-wide standup and spotlighting how different teams contributed to the OUTCOME. Marketing sees reduced churn, operations sees lower cost-to-serve, and leadership sees a team aligned around outcomes instead of activities. If you want your AI investments to move the needle, focus on unified signals, real-time orchestration, and getting the whole business excited about customer outcomes....not just actions. Remember: Outcomes > Actions #customerexperience #ai #cxleaders #outcomesoveraction

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

Today’s emerging technologies, especially those driven by AI, provide far more than efficiency—they enhance human capabilities to encourage greater innovation, creativity, collaboration, and beyond.      For these investments, the traditional ROI approach may not fully capture their value. Nearly three-quarters of leaders indicate defining metrics is a key challenge in valuation. That’s where a new math is needed.      Leaders who adapt their approach to technology investments are more likely to achieve long-term value and benefit from a stronger, faster, and better workforce. In Deloitte’s 2025 Global Human Capital Report (https://deloi.tt/4lbuME2), my colleagues Victor Reyes, David Mallon, and Amy Sanford suggest taking a non-traditional approach to valuation when technology investments aim to:     • Reshape the nature of work (AI writing tools)  • Amplify or enhance human capabilities (augmented reality goggles for maintenance workers)  • Deliver value across multiple functions (AI-powered collaboration or meeting tools)  • Have an undefined time horizon (Digital experience hub)    I encourage you to explore the report to learn how some organizations are monitoring business and human outcomes to measure success and continuously enhance their results. When both human and technological advancements are improved together, the whole is greater than the sum of its parts.

The latest Boston Consulting Group (BCG) data mirrors what we’re seeing at Spendflo: CFOs are doubling down on technologies that drive intelligence, not infrastructure.This signals a broader move away from CapEx-heavy, asset-driven IT toward intelligence-led, outcome-focused digital transformation. It’s not just about tools — it’s about enabling smarter, faster orgs What’s in? 🟢 AI/ML (including GenAI): +48% net spending increase 🟢 Cloud services: +36% 🟢 Security: +29% What’s out? 🔴 Devices: -21% 🔴 Server infrastructure: -26% 🔴 IT operations and systems management: -14% With every shift, procurement becomes more complex, distributed, and critical. Procurement teams now need to manage: * More complex tech categories (e.g. GenAI platforms, cloud-native tools) * Dynamic pricing and usage models (e.g. consumption-based contracts) * Higher expectations around ROI and agility At Spendflo, we saw this coming. That’s why we’re building the future of procurement: ✅ Centralized visibility across all vendors ✅ Expert-led negotiations on next-gen tech ✅ Real-time benchmark data to validate every dollar spent ✅ AI-powered end to end procurement workflows If you're still using outdated tools to manage modern tech investments, you’re not just behind—you’re bleeding margin. It’s time to make procurement a growth function. Not just a gatekeeper. Siddharth Sridharan Ajay Vardhan Nivas Ravichandran Giridharan Kalyanaraman ( Giri ) Edward Kim Siddhant Mittal Jimmy Hallsworth VARUN D B Shravi Sharma Kalyan Tripathy Adithiya Shiva Mahasweta Bhattacharya Uttaran Baruah Hunter Berry #Spendflo #Procurement #CFO #SaaS #ITBudget #GenAI #FinOps #FutureOfWork