Last week I chatted with an ops lead who said:
“We’re drowning in questions and nobody owns anything.”
Classic.
Tickets come in from everywhere:
• website forms
• shared inbox
• Slack pings
• account managers
• sales “urgent” messages
So what happens?
• No clear owner.
• No deadline.
• No escalation.
• No backup when someone is out.
And Ops becomes the human router.
Here’s the fix I walk through in the video:
a simple ticket routing system inside Salesforce.
It does 4 things:
1) Create the case the second a customer asks a question
2) Assign it to the right rep automatically
3) Notify them in the tools they actually check
4) Stamp an SLA and escalate if it’s not handled
If you’re early, start with round robin.
It stops the “why do I always get the hard ones” drama.
If you’re scaling, route by:
• ticket type
• account type
• territory
• special requests for high touch accounts
This is how you stop support from being a guessing game.
And how you stop being the person everyone pings when customers get mad.
Ever feel like your team is drowning in tickets, with response times so slow you start to dread opening your inbox?
That was us. Our old IT Service Management tool just wasn't cutting it. It was a black box, really.
No real insight into what was actually *happening* business-wise, or how incidents were connected. So, lots of manual digging, endless escalations, and honestly, a lot of frustrated users.
We knew something had to change. We’d spend hours trying to piece together trends or link current problems to past ones, and it felt like we were always playing catch-up.
So, we gathered everyone. Business folks, internal teams, you name it. We really dug into what was missing and what was actually needed on the ground.
Then, we worked with engineering to build it out. Lots of back and forth, tweaking workflows based on early feedback. It wasn't exactly a smooth ride, but we kept pushing.
The goal was a single pane of glass. A place where you could see the whole story of an issue, its history, how it related to other things, and automated assignments and escalations.
And you know what? It actually worked.
We launched a unified system for our global users. The results surprised even us.
Ticket response times dropped by 60%. Our customer satisfaction scores jumped 50%. And escalations? Down by a whopping 90%.
It’s amazing what happens when you actually have the data and visibility to make informed decisions, instead of just reacting.
Anyone else ever been in a similar boat with their tools? What’s your biggest challenge with current systems? I’d love to hear your experiences.
#ITSM#DigitalTransformation#CustomerExperience#ServiceManagement#ProblemSolving
This week I shadowed my tech lead during on-call, and it gave me a deeper appreciation for what great incident handling really looks like.
A few takeaways that stood out:
• Reproduce the bug locally first, whenever possible.
Building a small unit test around the issue helps turn an unclear production problem into something concrete and debuggable.
• In on-call, priority is often user impact.
If a bug is blocking users, the first goal is to stop the application from crashing. Log the exception, keep the system stable, and then investigate the root cause with a clear head.
• Be careful with how “fixed” is marked.
We had a case where a bug was marked fixed by an automated tool before it reached prod, which created confusion for users. It was a good reminder to use the right workflow and make sure status reflects reality.
• Communication matters as much as the fix.
If something is taking longer than expected, keep the user updated in the bug with progress and ETA. Always think from the customer’s perspective before diving into the solution.
• Ask for help early.
If the direction is unclear or the issue is taking longer than expected, reaching out to seniors is not a weakness, it is part of doing the job well.
This experience reinforced something important for me: good engineering is not just about writing code, but about owning impact, protecting users, and staying calm under pressure.
#OnCall#SoftwareEngineering#LearningByDoing#EngineeringCulture#IncidentResponse#Google
Incident Management isn't "logging a ticket and waiting."
In a modern IT organization, it's an end-to-end real-time workflow that connects monitoring, prioritization, support teams, automation, CMDB, SLAs, and knowledge—all to restore service fast and minimize business impact.
Here's the Incident Management model I align teams to (ITIL-aligned and platform-friendly for tools like ServiceNow):
What great Incident Management aims to do
· Restore service quickly
· Minimize business impact
· Follow SLAs (and escalate before breaches)
· Improve user satisfaction
· Capture knowledge and reduce repeat incidents
Incident Lifecycle (end-to-end)
1. Incident creation (user + system alerts)
2. Categorization & prioritization (Impact + Urgency = Priority)
3. Assignment (right resolver group: L1/L2/L3)
4. Investigation & diagnosis (logs + CMDB + known errors)
5. Resolution (fix/workaround/change)
6. Verification (confirm service restored)
7. Closure (document + update knowledge)
8. Post-incident activities (metrics + RCA + Problem record if needed)
The architecture that makes it "real-time"
· User & channels: portal, email, phone, chat/bot, mobile
· ITSM tool layer: workflow automation, SLA mgmt, dashboards, notifications
· Support layers: Service Desk (L1) → Technical Teams (L2) → Engineering (L3)
· Monitoring & alerting: events auto-create incidents
· CMDB: impact analysis + faster diagnosis
· Knowledge base: known errors, solutions, FAQs, best practices
Where teams win big: Automation
· Auto ticket creation from monitoring
· Auto assignment + routing
· SLA tracking + escalation automation
· Chatbot support for L1
· Smart notifications to stakeholders
If your Incident Management process doesn't connect the priority matrix + SLA targets + monitoring + CMDB + knowledge, you'll always be reactive—no matter how strong the team is.
What's your biggest gap today: prioritization, assignment accuracy, diagnosis speed, or automation?
#IncidentManagement#ITSM#ITIL#ServiceNow#ITOperations#MajorIncidentManagement#SLAManagement#CMDB#Monitoring#Observability#AIOps#Automation#ServiceDesk#ProblemManagement#ChangeManagement#DigitalTransformation
"As AI-enabled systems integrate into critical applications across defense, financial services, healthcare, and other sectors, organizations face an urgent need for systematic incident response processes. Most lack the frameworks, procedures, and infrastructure to respond effectively when these systems fail or cause harm.
This white paper presents a comprehensive framework adapting proven reliability engineering practices from complex systems domains to AI-specific characteristics. The framework provides both a generalizable seven-step process and tailored guidance for different stakeholders, enabling coordinated ecosystem response while allowing customization for specific operational contexts.
...
Rather than inventing new approaches, the framework draws on:
● Aviation safety for systematic investigation, identifying root causes in complex systems
● Financial crime enforcement for standardized cross-organizational reporting, enabling pattern recognition while protecting proprietary information
● Healthcare adverse event reporting for blame-free investigation cultures surfacing human factors
● Cybersecurity incident response4 5 for rapid response protocols, clear escalation paths, and pre-defined containment procedures that enable swift action under pressure
● Reliability engineering6 for tracking improvement over time through quantitative metrics These proven approaches can be adapted for AI-specific challenges including non-deterministic behavior, context-dependent failures, and system-of-systems interactions. The framework complements existing AI incident and governance frameworks by providing operational detail for implementing the incident response capabilities these standards require.
The Seven-Step Process
The framework centers on seven interconnected steps forming a complete incident response cycle. The process is intentionally generalizable, enabling organizations to adapt severity criteria, investigation methodologies, and verification approaches to their specific contexts.
Additionally, organizations may drop reorganize to repeat some of the steps.
1. Detect: Identify the incident through monitoring and user feedback
2. Assess: Evaluate severity and potential impact using established criteria
3. Stabilize: Execute pre-planned procedures to contain harm
4. Report & Document: Document incident details using standardized structures and notify stakeholders
5. Investigate & Analyze: Determine root cause through systematic analysis
6. Correct: Implement solutions to address root causes, reduce recurrence, and mitigate realized harm
7. Verify: Test and validate corrections, then monitor for effectiveness"
Heather Frase, Ph.D., CAMSVeraitech
Steps to Solve Support Tickets in SAP
Success isn’t fixing fast, it’s fixing right the first time.
Every unresolved ticket costs time, trust, and sometimes entire workflows.
The real difference between good and great SAP support lies in method not luck.
Here’s how the most efficient SAP teams handle tickets end-to-end:
✅ 1. Acknowledge the Ticket
-Respond quickly.
-Assign the right priority (Critical, High, Medium, Low).
-Set expectations with users, because clarity upfront builds credibility.
✅ 2. Gather All Details
-Ask for transaction codes, error messages, user IDs, and exact reproduction steps.
-Screenshots and logs are your evidence, never work without them.
✅ 3. Analyze the Issue
-Replicate it in a test or sandbox client.
-Check key transactions:
-ST22 → Short dumps
-SM21 → System logs
-ST03N → Workload analysis
-Patterns here often expose the real story.
✅ 4. Identify the Root Cause
-Missing or inconsistent master data?
-Authorization or role issues?
-Customization gaps?
-Or a genuine SAP standard bug?
-Define before you design.
✅ 5. Propose & Implement the Solution
-If user side, give guided correction steps.
-If system-side, raise a change request for configuration or development fixes.
✅ 6. Test & Validate
-Perform all changes in QA before moving to production.
-Capture screenshots, log outputs, and approval sign-offs.
-Quality assurance isn’t a formality, it’s your safeguard.
✅ 7. Communicate & Close
-Explain the resolution in plain business terms, no technical echo chamber.
-Update the ticket with evidence, then confirm closure with the user.
SAP support isn’t just technical, it’s operational storytelling.
Each log you analyze, each fix you document, builds resilience into the enterprise.
P.S. Don’t just solve SAP tickets, master the system that creates them.
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Follow Alok Kumar for more such amazing content on SAP & Enterprise Tech Transformation.
Leading Through a P1 Incident:
As technology leaders, we know that P1 incidents are not a matter of if—but when. What defines us isn’t avoiding them, but how we operate when they occur.
At #Zelle, the principles we follow during a P1 are simple but non-negotiable:
1️⃣ Stabilize First, Diagnose Second: Contain the impact, ensure safety of the ecosystem, and restore critical services before chasing root cause.
2️⃣ Clear Roles, One Commander: Every incident has a single Incident Commander. This avoids confusion and keeps the team aligned. Everyone else plays their role—engineering, comms, support—without overlap.
3️⃣ Communication is as Critical as Resolution: Our partners and users deserve transparency. Timely updates—internal and external—are as important as fixing the issue itself. Silence creates uncertainty.
4️⃣ Data Over Assumptions: In a crisis, adrenaline tempts us to jump to conclusions. We rely on observability, logs, metrics, and cross-checks before making calls. Facts > instincts.
5️⃣ Post-Mortems are Sacred: When the fire is out, the learning begins. Every P1 gets a blameless post-incident review. We document what happened, what worked, what failed, and what we’ll improve—because resilience is built iteratively.
Operating in a P1 is about discipline under pressure. It’s where culture, process, and technology converge. The goal isn’t just recovery—it’s building trust every single time.
Happy Friday!
#Leadership#CTO#EngineeringManagement#DigitalResilience#EWS#Zelle#TechLeadership#CrisisManagement#Innovation#LearningCulture
How to #Reduce IT Tickets by 40% Without #Hiring More People
After 25 years in IT leadership, I’ve realized something simple —
most IT teams don’t need more people; they need fewer repeat problems.
Every CIO talks about #automation, #AI, or #outsourcing#efficiency, but the real magic starts with simplifying service and building #accountability — across both customer and vendor ecosystems.
⚙️ The Real Problem Isn’t Ticket Volume — It’s Ticket Design
In every service review, you’ll hear:
“We closed 8,000 #tickets this month.”
“Average #resolution time down 10%.”
But ask users if IT feels better — and the silence says it all.
Because closing tickets faster isn’t success. #Preventing them is.
We’re solving #symptoms, not #causes.
🚀 Step 1: #Eliminate#Repetition at the Source-
Nearly 40% of tickets come from #avoidable, recurring issues — password resets, access delays, failed changes, misconfigurations.
#Automate what #repeats twice:-
Use self-service within #ITSM tools (ServiceNow, Jira, Fresh service, etc.).
Strengthen #problem#management ownership — not just incident closure.
The goal isn’t faster closure, it’s fewer #reopening.
🧠 Step 2: Move from #SLA to #XLA Thinking-
Dashboards showing 99% SLA compliance don’t prove success if users still struggle.
An SLA is #transactional; an XLA (Experience Level Agreement) is #transformational.
Track:-
How often the same issue recurs.
How users feel about the service.
How incidents affect business flow.
And remember — more SLAs with 100% targets don’t mean excellence.
They often serve the vendor, not the enterprise. Simplify.
Focus on outcomes, not paperwork.
⚖️Step 3: Fix the #Ownership Loop-
Most enterprises lose time between vendors, #L2/L3 teams, and user departments — everyone waiting for the other to act.
The solution isn’t hiring more people. It’s clear #accountability.
Define ownership and #escalation beyond the tool.
#Governance isn’t about finding who’s at #fault — it’s about ensuring the issue never returns.
🔧 Step 4: #Measure What Matters-
To truly reduce tickets by 40%:
Track repeat incident rate.
Measure #root cause #elimination.
#Reward teams for prevention, not closure.
Every ITSM tool already has #analytics. Use them to build preventive #intelligence, not just #dashboards.
💬 My Take-
Reducing IT tickets isn’t a staffing problem — it’s a #strategy problem.
When IT starts measuring experience instead of effort, the results follow.
That’s what defines #intelligent IT — not just efficient #operations.
#CIO#Leadership#ITServiceManagement#DigitalTransformation#TechnologyLeadership#EnterpriseIT#ITGovernance#ITOperations#CIOCommunity#LeadershipHiring#HiringForCIO#Headhunters#ServiceExcellence#ITStrategy#ITSM#SLAs#ProblemManagement#ExperienceManagement#Automation#ITSupport#ITLeadership
🛑 6 Hours in an Outage Call: What I Learned About Human Nature vs. Engineering
I just hopped off a 6-hour operation outage call. If you’ve been in the trenches, you know the energy: exhaustion, caffeine-fueled theories, and a lot of voices in the room.
When the stakes are high and the site is down, human psychology often defaults to four "Stereotype Traps" that actually delay recovery:
1️⃣ **The Defensive:** "It’s not my fault/i didn’t change anything."
2️⃣ **The Forensic:** "Why did this happen?" (Prematurely investigating the root cause).
3️⃣ **The Hunter:** "Who did it?" (Looking for a person to blame).
4️⃣ **The Grabber:** "Let me be in charge" (Adding to the "Too Many Cooks" syndrome).
Worst of all? **The Incident Tourist.** The bystander with no skin in the game who chimes in just to feel important, consuming the precious bandwidth of the engineers actually doing the work.
🛠️ The Shift to a High-Performance Mindset
To get out of the "war room" faster, we have to aggressively steer the conversation back to two things: **Customer Impact** and **Rapid Mitigation.**
Here are the best practices I saw (and a few I wish we’d used sooner):
* **Prioritize Mitigation over Repair:** Don’t try to perform surgery while the patient is bleeding. Use the simplest "hack" to stop the impact—roll back, toggle a flag, or failover—and save the elegant code fix for tomorrow.
* **The Power of the Frequent Communication:** Appoint a "Scribe" to summarize every 15–20 minutes. State clearly: *What we know, what we’ve ruled out, and what the current hypothesis is, who is doing what next.* Outage handling is a collective process of going from ignorance to enlightenment, bringing system from chaos back to order. This simple repetition is amazingly effective for participants to keep a clear mind, discover new facts, focus on the right things, and form new hypothesis.
* **Clear the Noise:** If you aren’t contributing data or executing a command, the best thing you can do is stay on mute. High-maturity teams separate the "Technical Bridge" from the "Stakeholder Bridge" to protect the engineers' focus.
**The goal isn't to find the truth in the heat of the moment; it's to restore service.** We do the forensics during the Post-Incident Review (PIR), not while the 500 errors are spiking.
Have you ever seen an "Incident Tourist" derail a call? How do you keep your team focused on the customer when the pressure is on? ⬇️
#SRE#DevOps#IncidentManagement#EngineeringCulture#SystemAvailability#TechLeadership