As a CX leader with over 15 years of experience in automation, AI-driven workflows, and ITIL-aligned service management, I’ve learned that managing technical teams is less about being the smartest person in the room and more about fostering trust, aligning priorities, and empowering specialists to thrive. Let’s face it: technical staff often are more specialized than their managers—and that’s a good thing. But the real challenge lies in balancing their expertise with the “big picture” demands of the business. Here’s how I’ve made it work, both in my career and for organizations I’ve advised.
Trust Is the Foundation (But It’s a Two-Way Street)
Technical teams thrive on autonomy. I’ve seen firsthand how micromanagement kills innovation—like the time a DevOps engineer on my team spent weeks rebuilding a legacy system only to hit a compliance roadblock because leadership hadn’t communicated evolving SLAs. This is where frameworks like ITIL’s Incident and Problem Management processes shine. By codifying escalation paths and post-incident reviews (learn more about SLAs here), we created clarity without stifling creativity.
Real-world example: At Toyota, the “Andon Cord” empowers frontline workers to halt production if they spot an issue—a blend of trust and structured escalation. Managers don’t need to hover, but they do need systems to ensure problems surface early.
Bridging the Knowledge Gap Without Playing “Tech Hero”
You don’t need to debug Python scripts at 2 a.m. to lead a technical team. But you do need enough fluency to ask the right questions. When I led a global IT team at a Fortune 500 company, my value wasn’t in coding prowess—it was in aligning their work with Continuous Service Improvement (CSI) principles. For instance, when AI-driven chatbots reduced ticket volume by 30%, I advocated for redirecting freed-up capacity to proactive problem management, tying it directly to customer satisfaction metrics.
Pro tip: Use automation to close feedback loops. Tools like ServiceNow’s Predictive AIOps or Azure Monitor can surface trends your team might miss while heads-down troubleshooting. Gartner’s research on AIOps adoption highlights how this balances autonomy with oversight.
Invest in Growth—Or Watch Talent Walk Out
Technical skills decay rapidly. Early in my career, I managed a network engineer whose expertise in legacy systems was critical but outdated. Instead of sidelining him, we partnered with Pluralsight for cloud certification training (see our guide to upskilling technical teams). Within six months, he was leading our Azure migration—a win for him, the team, and retention.
Real-world example: Microsoft’s “Skills for Jobs” program combines personalized learning paths with gamified badges, reducing attrition by 22% in technical roles.
The Art of “Doing More With Less” (Without Burning Out Your Team)
Let’s be honest: resource constraints are a constant. During the pandemic, my team faced a 40% spike in incidents with a 15% headcount reduction. We survived by automating Tier-1 ticket routing using ChatGPT-4 integrations and doubling down on Change Management rigor. By documenting every major incident in a centralized KB (with AI tagging recurring issues), we cut MTTR by 25%.
Key takeaway: Prioritize employee satisfaction. As Zappos famously proved, happy teams drive happy customers. Check out our case study on balancing employee and customer needs.
Where Theory Meets Practice
In my prior role as Head of CX Operations, I spearheaded a Lean ITIL overhaul that reduced critical incident resolution times by 40% year-over-year. How? By empowering engineers to self-organize during outages while enforcing blameless post-mortems. The secret sauce? Trusting specialists to own solutions while I focused on removing roadblocks—like securing budget for an AI-powered root cause analysis tool.
Final Thoughts: Embrace the Paradox
Leading technical teams is a paradox: you must be both a strategic partner and a humble student. Celebrate your team’s expertise, but never stop asking, “How does this align with our customers’ needs?” And remember—your job isn’t to have all the answers. It’s to build a system where the right answers can emerge.
