Speedy Problem Resolution

Support teams face constant pressure to resolve cases faster without overloading engineering. For one Glean customer, valuable resources were tied up in avoidable tickets, MTTR (mean time to resolution) hovered at nearly two days, and agents spent hours manually triaging cases. Their goal: boost self-solves, improve MTTR, and reduce R&D reliance – without adding more tools. So they embedded Glean in Zendesk, giving agents prompts to quickly gather knowledge across all company data. In triage, agents use Glean to find similar tickets, summarize runbooks and past Jira investigations, and compile clear updates for customers or well-packaged escalations. That streamlined process now drives faster resolutions, smoother knowledge transfer, and consistent workflows—leading to: • 34% increase in self-solves with more future automation planned - this is incredible progress • 24% faster MTTR (1.9 → 1.5 days) • 2–4 hours saved per week for 85% of users (13–26 business days/year) • Reduced R&D involvement in lower-tier tickets By streamlining resolutions, knowledge transfer, and process consistency, the team achieved remarkable results – proof of what’s possible when AI is embedded into everyday workflows. Stories like this are energizing – showing how teams are using Glean to reimagine what they can accomplish.

The best people in any team don’t waste time pointing fingers. They focus on fixing the fire - then making sure it never happens again. Let me show you what I mean. Last month, a few students messaged our support team saying they couldn’t access their course videos right after purchasing. The issue? A glitch during payment confirmation. The system marked them as paid, but the course wasn't assigned. Now imagine two people jumping in. Person A starts with: “Who set up the payment flow?” “Wasn’t this flagged before?” “This shouldn’t have gone live like this.” Person B starts with: “Let’s manually assign the course for now.” “How many students are affected? Let's fix them now.” “Can we write a quick script to patch the cases while engineering investigates?” Same situation. Different starting point. The second approach didn’t ignore the root cause. They just knew when to solve and when to reflect. Later that week, they debugged the trigger logic and helped product prioritize a permanent fix. No drama. No blame. Just fast fixes, followed by long-term improvements. That’s the skill I rate very highly. The ability to walk into chaos and calmly say, “Let’s fix this now, and make sure it doesn’t happen again.” Whether you're in sales, ops, product, or support - this mindset transforms how teams move. #ProblemSolving #SolutionOriented #ProcessThinking #Startups #OperationalExcellence #FixFirstReflectNext

𝗗𝗮𝗶𝗹𝘆 𝗠𝗮𝗻𝗮𝗴𝗲𝗺𝗲𝗻𝘁: 𝗪𝗵𝗮𝘁 𝗶𝗳 𝘆𝗼𝘂𝗿 𝘁𝗲𝗮𝗺 𝗰𝗼𝘂𝗹𝗱 𝘀𝗼𝗹𝘃𝗲 𝗽𝗿𝗼𝗯𝗹𝗲𝗺𝘀 3𝘅 𝗳𝗮𝘀𝘁𝗲𝗿, 𝘀𝘁𝗮𝗿𝘁𝗶𝗻𝗴 𝘁𝗼𝗺𝗼𝗿𝗿𝗼𝘄? In my work with leaders, I discovered 𝘁𝗵𝗿𝗲𝗲 𝗰𝗿𝗶𝘁𝗶𝗰𝗮𝗹 𝗰𝗵𝗮𝗹𝗹𝗲𝗻𝗴𝗲𝘀 that were secretly sabotaging their team's performance: 1. 𝗜𝗻𝘃𝗶𝘀𝗶𝗯𝗹𝗲 𝗣𝗿𝗼𝗯𝗹𝗲𝗺𝘀: Teams were experiencing cascading issues that went undetected for months, creating massive hidden inefficiencies. 2. 𝗥𝗲𝗮𝗰𝘁𝗶𝘃𝗲 𝘃𝘀. 𝗣𝗿𝗼𝗮𝗰𝘁𝗶𝘃𝗲 𝗠𝗮𝗻𝗮𝗴𝗲𝗺𝗲𝗻𝘁: Leaders were constantly firefighting instead of systematically preventing problems. 3. 𝗦𝘁𝗿𝗮𝘁𝗲𝗴𝗶𝗰 𝗠𝗶𝘀𝗮𝗹𝗶𝗴𝗻𝗺𝗲𝗻𝘁: Execution was disconnected from strategic objectives, causing significant performance gaps. These challenges taught me a 𝗽𝗿𝗼𝗳𝗼𝘂𝗻𝗱 𝗹𝗲𝘀𝘀𝗼𝗻: Daily management isn't just a process—it's the heartbeat of organisational excellence. By implementing a structured daily management system, leaders can transform reactive cultures into proactive, high-performance machines. My 𝗯𝗿𝗲𝗮𝗸𝘁𝗵𝗿𝗼𝘂𝗴𝗵 came when I introduced a simple, yet powerful daily management framework. We created visual management, implemented 15-minute daily huddles, and established problem-solving to act when we saw issues. The 𝗿𝗲𝘀𝘂𝗹𝘁𝘀? Dramatic improvements in response times, team alignment, and strategic execution. For senior executives, this isn't just about efficiency—it's about 𝗰𝗿𝗲𝗮𝘁𝗶𝗻𝗴 𝗮 𝗰𝘂𝗹𝘁𝘂𝗿𝗲 𝗼𝗳 𝗰𝗼𝗻𝘁𝗶𝗻𝘂𝗼𝘂𝘀 𝗶𝗺𝗽𝗿𝗼𝘃𝗲𝗺𝗲𝗻𝘁 𝘁𝗵𝗮𝘁 𝘀𝗲𝗽𝗮𝗿𝗮𝘁𝗲𝘀 𝗴𝗼𝗼𝗱 𝗰𝗼𝗺𝗽𝗮𝗻𝗶𝗲𝘀 𝗳𝗿𝗼𝗺 𝘁𝗿𝘂𝗹𝘆 𝗴𝗿𝗲𝗮𝘁 𝗼𝗻𝗲𝘀. 🔑 𝗧𝗮𝗸𝗲𝗮𝘄𝗮𝘆: Start with a 15-minute daily team huddle focused on identifying and solving problems in real-time. Watch how this simple practice can revolutionise your organisation's performance.

For months, one of our biggest operational challenges was the mandatory human touchpoint needed to route customer interactions. Every new support ticket required a Tier 1 agent to read the description, classify the Intent, judge the Sentiment, and then manually route it to the correct specialist or seniority level. This delay was a drain on agent time and, worse, a source of customer frustration. In the last few days we've successfully implemented an AI-powered system using the Gemini API to solve this problem. We trained a model on our historical data to automatically and accurately classify every incoming interaction in real-time. The Model Now Automatically Determines: 🎯 Intent: Is this a 'General Inquiry,' 'Subscription Cancellation,' or 'Billing Inquiry'? 😠 Sentiment: Is the customer 'Neutral' or 'Critical Negative'? 📈 Priority Score: A dynamic score (1-5) that combines intent and sentiment. The Impact is Immediate and Measurable: Eliminated Triage Bottleneck: Senior agents now spend 100% of their time solving problems, not reading tickets. Faster Crisis Response: Critical issues (Priority Score 5) are routed directly to the L3 team in seconds, not minutes. Improved Customer Satisfaction (CSAT): By routing complex issues immediately, we're cutting down on resolution time and reducing the need for costly agent transfers. This shift is a game-changer for our customer experience and a prime example of how targeted AI tools can drive real operational efficiency.

Recently I witnessed a perfect example of how different teams can handle the same type of problem. An internal payment system couldn't get event statuses because another team's service was burning through a shared API rate limit. Instead of 4 calls per day as recommended, they were making erratic calls through inefficient polling. The fix? Simple. Change from continuous polling to the recommended schedule. Maybe 60 minutes of work for one engineer, even without extensive contextual knowledge. Their response? "Please submit this as an Aha idea for our next planning cycle." Meanwhile, at Aurora, we handle operational issues completely differently. When we discover inefficient processes affecting system performance, we: Immediately assess business impact and technical scope Deploy hotfixes within hours, not planning cycles Document the fix and implement monitoring to prevent recurrence Save formal process for actual feature development This approach has helped us maintain 4 9s of uptime on critical data pipelines while other organizations wait for roadmap discussions. The difference? We treat production issues as operational incidents, not feature requests. When systems break or perform poorly, rapid resolution takes priority over process compliance. Good organizations distinguish between different types of work: Feature development follows formal product processes with discovery and planning Operational issues get fast-tracked through engineering channels with immediate triage Performance optimizations get handled as technical debt within existing sprint capacity At Aurora, our leadership empowers our teams to make quick decisions on operational issues while maintaining appropriate governance for new features. It's one of the things that makes working here effective and why I love leading our Enterprise Data & Automation practice. The result? Our data systems stay reliable, our business operations stay smooth, and we can focus planning cycles on actual innovation instead of firefighting. Process should enable better outcomes, not slow them down. The best teams know when to follow process and when to cut through it. What does rapid operational response look like at your organization?

You answer calls within 20 seconds? Congratulations. You're doing the bare minimum. The pandemic fundamentally transformed customer expectations. Those endless hold times? Your customers won't tolerate them anymore. In a competitive market, they'll simply leave. ----- Speed of answer has become the baseline, not the victory many businesses think it is. ----- Think about it: What good is answering quickly if you can't actually solve the customer's problem? It's like showing up to a fire with an empty water bucket – you were quick, but not exactly helpful. The real masters of customer experience know that true success comes from a two-part formula: 1. Answer as quickly as possible 2. Resolve the issue during that first interaction When you fail to resolve issues promptly, you create a high-effort experience. Your customers feel it – and they remember it. Oh boy, do they remember it. ----- 3 Ways To Become A Resolution-First CX Operation ----- 1. Empower your front line: Give your agents the authority to make decisions that solve problems without transfers or escalations. 2. Implement "resolution-first" technology: Use AI tools (like our Agent Assist) that provide agents with real-time suggestions and information specifically designed to solve problems, not just document them. Documenting problems without solving them is basically just journaling. 3. Measure what matters: Stop obsessing over average handle time and start tracking first-contact resolution rates. What gets measured gets improved. And what gets ignored gets... well, ignored. ----- The economics are clear: ----- Companies focused on first-contact resolution see operational cost savings while improving customer satisfaction and loyalty. Just because a call was answered quickly doesn't produce the same result as a call that was resolved quickly. If we respond fast AND resolve issues, we create satisfaction and loyalty – and that's where the true ROI lives. Is your team still celebrating speed metrics while customers remain frustrated? It might be time to refocus your approach before your customers ghost you faster than a bad first date.

There are 4 types of problems. Treat them the same, and you guarantee chaos. Stop solving every problem the same way. You lose time and trust when tools don’t fit. This four-type model comes from Art Smalley. From his book Four Types of Problems. If you lead ops or CI… read it. Here are the four types you must know. Label first… then act. *** 1/. Troubleshooting problems Flow stops and alarms flash. A robot jams and the line halts. Your goal is simple restore flow now. You act fast and bring back control. Tools you use: → Andon calls and team alerts → Clear standard work steps → Quick reset and contain moves No deep study in this moment. Speed wins and flow returns. *** 2/. Gap from standard problems The line runs but misses target. Four percent defects not one percent goal. Now you slow down and dig deep. You find root cause and remove it. Tools you use: → Five Whys to drill down → Pareto charts to spot trends → PDCA cycles to lock gains Discipline beats endless fire fights. You fix it once not ten times. *** 3/. Target state problems Nothing is broken or unstable. But today’s level is not enough. You cut changeover from forty five minutes. You aim for fifteen minutes instead. You test learn and adjust fast. Small trials drive big gains. Tools you use: → SMED to cut waste → A3 thinking for focus → Safe small experiments You build a new better standard. And raise the bar again. *** 4/. Open ended innovation problems You rethink the whole system. Manual checks shift to AI vision. You design a bold future state. You explore before you decide. Tools you use: → Design thinking workshops → Rapid working prototypes → Creative team trials *** Here is the core lesson. Each type needs a different response. Type one needs speed and calm. Type two needs focus and depth. Type three needs trials and learning. Type four needs vision and bold moves. You cannot skip the order. Master basics before big leaps. Next time chaos hits your floor pause. Ask one clear question first. What type of problem is this? That one question builds real skill. *** 🔖 Save this post for later. ♻️ Share to help others choose the right problem type. ➕ Follow Sergio D’Amico for more on continuous improvement. P.S. I shared an infographic in the comments. It shows key takeaways from the book.

Lean Community:  Swarming Problems – Addressing Issues in Real-Time. More from "The High-Velocity Edge:  How Market Leaders Leverage Operational Excellence to Beat the Competition" by Steve Spear. Highly Recommend ⭐ ⭐ ⭐ ⭐ ⭐ High-velocity organizations excel at swarming problems—detecting and addressing issues as soon as they arise rather than allowing them to escalate. Instead of relying on delayed reporting or reactive firefighting, companies like Toyota, Alcoa, and Southwest Airlines emphasize immediate problem-solving at the source to maintain quality, efficiency, and safety. ------------------- 🏆 Real-time problem-solving prevents small issues from becoming major failures. At Toyota, workers on the production line can pull an “andon” cord to halt operations if they detect a defect. This triggers an immediate response from the team, ensuring that the problem is addressed before defective products move further down the line. By focusing on early intervention, Toyota minimizes costly rework and waste while improving overall product quality. 🏆 Swarming problems also accelerates learning and improvement. At Alcoa, any workplace safety incident—no matter how minor—demands immediate attention. Employees investigate the root cause and implement corrective actions right away. This proactive approach significantly reduced injury rates while reinforcing a culture of accountability and continuous improvement. 🏆 For problem-swarming to work, organizations need clear systems and empowered teams. Southwest Airlines, for example, encourages employees to communicate and collaborate across departments when issues arise, ensuring that delays or inefficiencies are resolved swiftly. This ability to respond in real-time keeps operations running smoothly and enhances customer satisfaction. By creating a culture where problems are seen as opportunities for learning rather than failures to be hidden, organizations can boost agility, innovation, and long-term success. -------------------- Questions: 1. Have you experienced a workplace where problems were addressed immediately? How did it impact efficiency and morale? 2. What barriers prevent organizations from implementing real-time problem-solving, and how can they be overcome? 3. Can swarming problems be applied effectively in non-manufacturing industries? What would that look like? Looking forward to your comments! https://a.co/d/gwIBSYD #ContinuousImprovement #CultureMatters

A recent project for North America based client, made me think deeply about how AI can reshape problem-solving in real time. The business faced a common challenge: delays in customer support resolution due to manual workflows and siloed information. We introduced AI agents trained to process, analyze, and respond to customer queries while dynamically pulling data from multiple systems. The impact? • 40% faster issue resolution times • Significant reduction in repetitive manual tasks for the team What struck me most was how the AI agents weren’t just following a script—they adapted based on context, learned from new inputs, and improved accuracy over time. This experience underscored how businesses can leverage AI not just to automate tasks but to create intelligent systems that work alongside teams, solving problems faster and smarter. If you’re exploring AI agents, think about the repetitive processes slowing you down—they’re often the best place to start. How are you using AI in your operations? Would love to hear your thoughts! #AI #AIagents #Automation #CustomerSuccess #america #agent #mobio #consulting #aiexpert

How I use this 60-minute rule to cut through chaos When things get messy, I give myself just 60 minutes to fix it. No long meetings. No going in circles. Just clear thinking, fast. Here’s how it works: First 10 minutes: Figure out the real problem. → What’s actually broken? → What happens if I ignore it? Next 10 minutes: Break the problem into smaller parts. → What can I control? → What’s blocking it? Next 15 minutes: List every idea to fix it. → No judging. Just write. → Look for patterns or combos. Next 15 minutes: Pick one clear path. → Can I do it? → Will it solve the problem for good? Last 10 minutes: Take one small action. → Just start. Don’t overthink. This keeps me and my team moving forward, even on the messy days.