Change Management Strategies For Digital Transformation Success

𝗥𝗶𝗴𝗵𝘁 𝗻𝗼𝘄, 𝟳𝟰% 𝗼𝗳 𝘁𝗵𝗲 𝗙𝗼𝗿𝘁𝘂𝗻𝗲 𝟱𝟬𝟬 𝗮𝗿𝗲 𝘂𝗻𝗱𝗲𝗿𝗴𝗼𝗶𝗻𝗴 𝗱𝗶𝗴𝗶𝘁𝗮𝗹 𝘁𝗿𝗮𝗻𝘀𝗳𝗼𝗿𝗺𝗮𝘁𝗶𝗼𝗻𝘀. 𝗨𝗽 𝘁𝗼 𝟵𝟱% 𝗼𝗳 𝘁𝗵𝗲𝗺 𝘄𝗶𝗹𝗹 𝗳𝗮𝗶𝗹. 𝗪𝗵𝘆? 𝗣𝗼𝗼𝗿 𝗲𝘅𝗲𝗰𝘂𝘁𝗶𝗼𝗻. When I stepped in as CTO, it was clear that if our transformation was going to succeed, we had to improve execution. So, instead of chasing shiny tools or trendy models, we relentlessly focused on the basics. 🧱 Here’s my advice for anyone on this journey: 1️⃣ 𝗦𝘁𝗮𝗻𝗱𝗮𝗿𝗱𝗶𝘇𝗲 𝗳𝗼𝗿 𝗦𝗽𝗲𝗲𝗱 Standardization doesn’t limit creativity — it removes roadblocks. Certified pipelines, test plans, and frameworks eliminate chaos, helping teams deliver faster. 2️⃣ 𝗧𝗵𝗼𝘂𝗴𝗵𝘁𝗳𝘂𝗹 𝗖𝗼𝗻𝘁𝗿𝗼𝗹𝘀 𝗠𝗮𝘅𝗶𝗺𝗶𝘇𝗲 𝗖𝗿𝗲𝗮𝘁𝗶𝘃𝗶𝘁𝘆 You need rules, but only enforce the “no-regret” ones. This gives teams the flexibility to innovate solutions for different regions or customers. 3️⃣ 𝗦𝗲𝗾𝘂𝗲𝗻𝗰𝗲 𝗳𝗼𝗿 𝗦𝘂𝗰𝗰𝗲𝘀𝘀 Take it step by step and front-load complexity. Doing everything in parallel or saving the hardest for last will result in gridlock and deflating surprises. 4️⃣ 𝗧𝗵𝗲 𝗕𝘂𝘀𝗶𝗻𝗲𝘀𝘀 𝗶𝘀 𝗬𝗼𝘂𝗿 𝗖𝘂𝘀𝘁𝗼𝗺𝗲𝗿 Tech teams know a lot, but the business knows best. Demand clear requirements so you can build what's needed... and not bridges to nowhere. 5️⃣ 𝗜𝘁'𝘀 𝗮 𝗧𝗲𝗮𝗺 𝗦𝗽𝗼𝗿𝘁 They’re called ‘digital transformations,’ but they’re really business transformations. Everyone — not just tech — must own it. There's always more to do, but we’ve made huge strides this year:   ✅ Cut over four 40+ year-old mainframes to the cloud ✅ Migrated all North American mainframe pipelines to data fabric ✅ Closed data centers from Alpharetta to Australia ✅ Beat our all-time stability records ✅ Achieved our best-ever tech hygiene stats 𝗧𝗵𝗲 𝗴𝗼𝗼𝗱 𝗻𝗲𝘄𝘀? We won’t be in the 95%. 𝗧𝗵𝗲 𝗯𝗲𝘁𝘁𝗲𝗿 𝗻𝗲𝘄𝘀? We’re now seeing the transformation benefits we envisioned at the start: AI innovation, model precision, next-gen services, enhanced resilience, and more. 🚀 𝗧𝗿𝗮𝗻𝘀𝗳𝗼𝗿𝗺𝗮𝘁𝗶𝗼𝗻 𝗶𝘀𝗻’𝘁 𝗮𝗯𝗼𝘂𝘁 𝗳𝗼𝗹𝗹𝗼𝘄𝗶𝗻𝗴 𝘁𝗿𝗲𝗻𝗱𝘀—𝗶𝘁’𝘀 𝗮𝗯𝗼𝘂𝘁 𝗺𝗮𝘀𝘁𝗲𝗿𝗶𝗻𝗴 𝗲𝘅𝗲𝗰𝘂𝘁𝗶𝗼𝗻. What are digital transformation lessons you've learned? I’d love to know! 👇

Most technology leaders at larger companies will tell you that implementing AI and generative AI at scale is no small task. Many will also tell you that strong change management is one of several components of a successful implementation plan but the most challenging to get right. As widespread use of generative AI has taken shape, there are a handful of themes I’ve heard consistently about change management as it relates to the technology: ✋🏽 Preparing for resistance: Introducing generative AI may be met with apprehension or fear. It's crucial to address these concerns through transparent communication and consistent implementation approaches. In nearly every case we are finding that the technology amplifies people skills allowing us to move faster versus replacing them. 🎭 Making AI part of company culture and a valued skill: Implementing AI means a shift in mindset and evolution of work processes. Fostering a culture of curiosity and adaptability is essential while encouraging colleagues to develop new skills through training and upskilling opportunities. Failure to do this results in only minimal or iterative change. ⏰ Change takes time: It’s natural to want to see immediate success, but culture change at scale is a journey. Adoption timelines will vary greatly depending on organizational complexity, opportunities for training and—most importantly—clearly defined benefits for colleagues. A few successful change management guiding principles I have seen in action: 🥅 Define goals: Establishing clear objectives—even presented with flexibility as this technology evolves—will guide the process and keep people committed to their role in the change. 🛩 Pilot with purpose: Begin small projects to test the waters, gain insights and start learning how to measure success. Scale entirely based on what’s working and don’t be afraid to shut down things quickly that are not working 📚 Foster a culture of learning: Encourage continuous experimentation and knowledge sharing. Provide communities and spaces for people to talk openly about what they’re testing out. 🏅 Leaders must be champions: Leaders must be able to clearly articulate the vision and value; lead by example and be ready to celebrate successes as they come. As we continue along the generative AI path, I highly suggest spending time with change management resources in your organization—both in the form of experienced change management colleagues and reading material—learning what you can about change implementation models, dependencies and the best ways to prioritize successes.

Too often, I see organizations treat change management like a box to check. A big announcement, a training session, and then done. But real change doesn’t work that way. True transformation requires: – Ongoing assessment – Adaptation – Reinforcement Without continuous effort, old habits creep back in, resistance builds, and the change fades. Here’s what effective change management looks like: ✅ 𝐂𝐨𝐧𝐭𝐢𝐧𝐮𝐨𝐮𝐬 𝐜𝐨𝐦𝐦𝐮𝐧𝐢𝐜𝐚𝐭𝐢𝐨𝐧 → People need clarity, not just at the start but throughout the process. ✅ 𝐎𝐧𝐠𝐨𝐢𝐧𝐠 𝐬𝐮𝐩𝐩𝐨𝐫𝐭 → Training once isn’t enough. Reinforcement helps teams adapt and sustain new behaviors. ✅ 𝐑𝐞𝐠𝐮𝐥𝐚𝐫 𝐟𝐞𝐞𝐝𝐛𝐚𝐜𝐤 𝐥𝐨𝐨𝐩𝐬 → Success isn’t set in stone. Organizations must listen, measure progress, and adjust as needed. ✅ 𝐂𝐮𝐥𝐭𝐮𝐫𝐚𝐥 𝐢𝐧𝐭𝐞𝐠𝐫𝐚𝐭𝐢𝐨𝐧 → Real change becomes part of how a company operates, not just a project with an end date. If you want change to last, 𝐜𝐨𝐦𝐦𝐢𝐭 𝐭𝐨 𝐭𝐡𝐞 𝐩𝐫𝐨𝐜𝐞𝐬𝐬, 𝐧𝐨𝐭 𝐣𝐮𝐬𝐭 𝐭𝐡𝐞 𝐞𝐯𝐞𝐧𝐭. The best organizations don’t just manage change. They embrace it as a way of working.

I’ll never forget a conversation I had with the CEO of a major retail chain. They had poured millions into “digital transformation”—a new eCommerce platform, AI-powered analytics, and even a sleek mobile app. But their bottom line hadn’t budged. “We’ve done everything right,” they told me, “But where are the results?” This isn’t an isolated story. Gartner reports that while 91% of organizations engage in digital initiatives, only 40% achieve expected outcomes. Digital transformation isn’t about shiny tools; it’s about delivering measurable value. The Foundation of Tangible Digital Transformation True digital transformation solves real problems and drives outcomes. For the retail chain, their digital investments weren’t integrated. Online data wasn’t personalizing in-store experiences, and AI tools were underutilized. By creating a unified data strategy, we helped them achieve a 20% boost in cross-channel sales within six months. Keys to Success: ◾Define Clear Goals: Always start by asking, “What problem are we solving?” ◾Adopt Technology Strategically: Use tools like AI or IoT only if they align with objectives. For instance, in healthcare, AI reduced diagnosis times by 30%, saving lives. ◾Empower People: Technology succeeds when paired with the right culture. Companies that invest in employee training are 4x more likely to succeed. The Cost of Getting It Wrong Failed digital transformations cost companies over $900 billion annually, according to Forbes. The impact isn’t just financial—it’s reputational. Customers expect seamless experiences. For a telecom client struggling with churn, we implemented a centralized CRM, improving retention by 15% and cutting inefficiencies by 20%. What Tangible Results Look Like: ➡️ Efficiency: Automation saves time and money. ➡️ Revenue Growth: Personalized customer journeys increase retention. ➡️ Customer Satisfaction: Seamless service builds loyalty. For example, AI-powered route optimization helped a logistics client reduce delivery times by 25%, boosting repeat business by 10%. Navigating Challenges Legacy systems, resistance to change, and skill gaps can derail progress. At Devsinc, we tackle these issues with phased migrations and workshops to build confidence in new technologies. The Human Element Digital transformation isn’t just about technology—it’s about people. For the retail chain, success came from reconnecting with customers through personalized interactions, rebuilding trust, and driving sales. The Path Forward Digital transformation is a business necessity. To succeed, you need a clear vision, the right tools, and a focus on measurable outcomes. At Devsinc, we’re passionate about empowering organizations to cut through the noise and achieve lasting impact. Because at its heart, transformation is about creating meaningful change—and that’s a journey worth taking.

I spent years navigating the complexities of digital transformation. Here’s the shortcut to save you countless hours! Digital transformation isn’t just about adopting new technology. It’s about changing how we think and operate as an organization. I remember back when I was at Microsoft, leading a team to drive significant change in our sales approach. We faced numerous challenges:   Resistance from teams stuck in their old ways. Difficulty aligning technology with business goals. The ever‑looming pressure of competition driving innovation faster than we could keep up!  But here’s what I learned through trial and error—and a few sleepless nights:   Start with culture: Technology won’t solve your problems if your teams aren’t on board. Embrace a culture that values learning and adaptability. Get everyone involved early in the process!   Set clear objectives: Identify what success looks like for your organization. Are you looking for efficiency? Increased revenue? Improved customer satisfaction? Define it clearly, so everyone is aligned!   Leverage data: Don’t just collect data—use it! Analyze where you stand, identify gaps, and make informed decisions based on real insights rather than gut feelings alone!   Pilot small initiatives: Before rolling out changes company‑wide, test them out on a smaller scale first! This allows you to gather feedback and make adjustments without disrupting everything at once!   Engage stakeholders continuously: Keep communication lines open with all stakeholders throughout the journey—this builds trust and mitigates resistance down the line!   Iterate constantly: Digital transformation is not a one‑time project; it’s an ongoing journey that requires continual assessment and iteration of processes to stay relevant in today’s fast‑paced market environment! By following these steps, I managed to turn initial skepticism into excitement around our digital initiatives. The result? A much more agile team ready to tackle future challenges head‑on! If you're serious about transforming your organization, embrace these principles—you'll thank yourself later!

65% of AI & Tech Transformations Fail 🚫 Why? Because they forget one thing: People. I've spent 25+ years in healthcare leadership, and here's what I know: transformation fails when we forget the human element. Digital transformations often fall short of expectations. Why? Because we're solving the wrong problem. 7 critical shifts needed in 2025: 1/ From Tools to Trust ↳ Technology doesn't transform workplaces. People Do. ↳ Start with psychological safety and clear communication. ↳ Build trust before introducing new tools. 2/ From Training to Translation ↳ Stop teaching "how to use tools." ↳ Start showing "how tools improve lives." ↳ Connect every change to personal growth. 3/ From Metrics to Meaning ↳ Move beyond efficiency metrics. ↳ Measure impact on well-being and job satisfaction. ↳ Track how transformation enables better work-life integration. 4/ From Control to Collaboration ↳ Replace top-down mandates with team-led initiatives. ↳ Create innovation councils across departments. ↳ Let solutions emerge from front-line expertise. 5/ From Speed to Sustainability ↳ Stop rushing digital adoption. ↳ Build systems that support long-term resilience. ↳ Focus on sustainable change management. 6/ From ROI to Human Impact ↳ Expand success metrics beyond financial returns. ↳ Measure employee engagement and retention. ↳ Track improvements in work-life quality. 7/ From Digital to Hybrid Excellence ↳ Balance automation with human judgment. ↳ Preserve meaningful human interactions. ↳ Create frameworks where technology amplifies humanity. Real transformation isn't about adopting new technology. It's about enabling people to do their best work. In healthcare, I've seen both sides: - Teams that resist change because they don't see the "why" - Teams that embrace change because they shape the "how" The difference? Leadership that prioritizes people over processes. ♻️ Share if this resonates ➕ Follow Dr. Elise Victor for more.

These days I’m sure grateful for the Change Management work I did as a student at Harvard. The data is sobering. 👉 MIT’s NANDA study: 95% of generative AI pilots fail to move into production. 👉 McKinsey: 70% of initiatives remain stuck in development or expansion after a year. 👉 Abandonment: 17% of projects in 2024 → 42% in 2025. 👉 Scaling success: only 5–10% of companies ever get there. The technology is not the problem. The people, processes, and organizational structures are. That’s where John Kotter’s 8 Steps for Leading Change still feel urgent today. AI isn’t just a tool you stack on top of existing workflows. It requires rewiring how companies operate. Yet most organizations continue to treat AI adoption like a software upgrade rather than a deep transformation. ↳ Create Urgency → Leaders assume urgency is obvious. It’s not. AI must be framed with data and stories that make stakes clear: competitors will use efficiency to outscale you. ↳ Build a Guiding Coalition → Pilots run by IT alone fail. Cross-functional coalitions with visible champions succeed. ↳ Form a Strategic Vision → Saying “we’re investing in AI” is not a vision. Linking it to growth, efficiency, and innovation is. ↳ Remove Barriers → Resistance is natural. Job fears are real. Change management has to dismantle these barriers directly. ↳ Generate Short-Term Wins → Early ROI in back-office functions builds trust and momentum. Without visible wins, resistance hardens. ↳ Institute Change → AI sticks when embedded in hiring, training, incentives, and culture. Startups don’t wrestle with this. They scale with AI by avoiding new hires and redesigning work as they go. Large companies face the harder task: unlearning, rewiring, and rebuilding. The lesson from Kotter and from the data is the same: Transformation is not about the technology. It’s about change leadership. If we want AI to succeed inside large companies, we have to stop asking: ❌ “How do we scale the model?” ✅ “How do we scale trust, adoption, and organizational learning?” Three actions to drive forward now: ✅ Use data and stories to prove urgency at every level. ✅ Create early ROI wins and broadcast them widely. ✅ Embed AI into culture, not just IT, through hiring, training, and incentives. Do. Fail. Learn. Grow. Win. Repeat. Forever. ♻️Repost & follow John Brewton for content that helps. 📬 Subscribe to Operating by John Brewton for deep dives on the history and future of operating companies (🔗 in profile).