The Problem with Measurement (in ITSM)
Goodhart’s Law says that once a metric becomes a target, it stops being a good metric, and this article traces that pattern through IT service desk ticket counts, school test scores, and social media algorithms. It connects the idea to the Observer Effect in physics and the Probe Effect in IT monitoring, then lays out five rules for using metrics without letting them run the show.
What Governance Looks Like After AI
AI governance requires more than policies and committees. Discover why organizations need visibility of their AI agents, clear ownership, lifecycle information and reliable change records to govern AI effectively.
Ticket Handoffs Between IT, Customer Support, and Engineering: Where They Break and How to Automate Them Safely
Ticket handoffs between IT, customer support, and engineering can lead to lost context, unclear ownership, and unresolved customer issues. Discover where handoffs break down and how to automate them safely.
How Open-Source ITSM Teams Actually Find Add-Ons – And Why the Catalog is Still Broken
Open-source ITSM add-ons for Znuny, OTOBO, and Zammad aren’t hard to find because they don’t exist. They’re hard to find because there’s no shared catalog. This article shares the six main places where plugins hide, explains why .opm compatibility is more fragile than it looks, and lays out a six-step checklist for testing an add-on before it reaches production.
Small Business Doesn’t Mean Small Technology Decisions
A butcher shop drowning in paper invoices taught Mark Patnaude that small businesses don’t get simpler technology problems, just less room to recover from the wrong call. He argues the fix isn’t scaled-down enterprise bureaucracy but “minimum effective discipline,” and offers a five-question test any SMB can use before making a decision it can’t afford to get wrong.
AI and the Data “Trapped” in ITSM Tools
Our industry has talked about the data trapped in ITSM tools for years, but the real issue isn’t collection; it’s collecting without a purpose. This piece looks at unused and underutilized ITSM data, why CMDBs are the classic example, and how AI is finally positioned to spot what’s wasted, what’s underused, and what should be collected next.
Service Financial Management in ITIL 4: What the Practice Covers and How It Works
Every digital product carries a cost, but few organizations can say what that cost is, let alone what drives it. ITIL 4’s Service Financial Management practice turns spending on people, technology, suppliers, and process into information leaders can act on. This article looks at how the practice builds cost models, plans budgets, and why the answer differs depending on whether IT is core to the business or a supporting function.
Why ITSM Transformation Fails at the People Layer
Every ITSM transformation plan gives the platform an owner, a budget, and a schedule, while adoption gets a communications plan. Gartner and Bain data suggest that gap is where most programs fall short: leaders approve the model without knowing what it will ask of them, and practitioners wait to see whether it lasts. The piece makes the case for planning the people layer as a funded workstream.
When Your CMDB Needs Dialysis: Filtering the Toxins Before They Spread
At 60% average data accuracy and 5 million configuration items, a Fortune 50 CMDB is carrying roughly 2 million duplicate, stale, or orphaned records. Salil Kulkarni prices what this costs: $16 million a year in licensing overrun, plus $20 million in engineer time chasing bad data, before outages or security exposure enter the count. The fix proposed is a pre-processor that filters data before it reaches the CMDB.
AI Agents: How to Add Conversational AI Without Replacing Your ITSM Platform
Many IT service desks are buried in password resets and status requests, and the usual response is a full ITSM platform migration. Aditya Santhanam argues for a cheaper route: wrap conversational AI around the ITSM tool you already run, so AI agents work inside existing records, SLAs, and rules. The article covers seven use cases, a six-step rollout, what to keep humans on, and the metrics that show it works.
Fine-tuning Service Management Boards: How to Find the Waste Hiding Between “Resolved” and “Closed”
Most IT service desks can say exactly how long resolution took last month. Ask how long closure took, and the room goes quiet, because the SLA clock had already stopped by then. This article sets out six closure-stage patterns worth tracking, from zombie backlogs to calendar-driven closing, and how to redesign a Kanban board around aging and closure lag rather than the metrics resolution reports already cover.
ITIL: Best Practice or Business Necessity? Why Service Management Prevents Technology Waste
Iran is rich in oil and gas, yet poor governance has held its technology sector back. A MedaNet practitioner with two decades of ITIL experience there argues the real problem was never a shortage of equipment; it was buying systems without managing them. Drawing on work across banks, oil and gas, and petrochemical companies, the article sets out why ITIL matters as a discipline for using what you already own.
Service Desk Automation: How to Automate Resolution, Not Just Ticket Handling
An employee reports a dropped VPN connection, and every step of the IT service desk automation fires perfectly: intent read, ticket routed, history attached. The VPN still does not work. This gap between a well-handled ticket and a solved issue is the most common outcome in IT service desk automation today. The article maps a five-level outcome ladder and how to measure verified resolution instead of ticket volume.
Revamping Traditional IT Budgets: The Practical Fix for Exploding AI Spending
AI costs are spiraling across enterprises, and budgets built for predictable per-seat SaaS costs were never designed for open-ended, per-token inference. Erhan Giral of BMC Helix walks through why unmonitored AI agent loops and repeated context re-sends are driving the overrun, and lays out how intelligent model routing can cut inference costs while keeping most of the quality frontier models deliver.
How Hard Is It to Change Your ITSM Platform?
A renewal quote arrives and the board asks whether it is time to switch ITSM platforms. Incumbents call migration too risky, challengers call it painless, and neither answer is worth trusting. Drawing on churn poll data and five factors, from data and integrations to change management and contract terms, this article sets out where the real difficulty sits and how to avoid ending up back where you started.