Whenever I sit in conversations about technology cost, I notice how quickly the dialogue narrows. The questions are usually: How much are we spending? Can we reduce it? That isn’t transformation—it’s accounting.
Real transformation is about shifting the conversation from cost to value. From “how much do we spend?” to “what outcomes does this spend enable, and how can we optimise them?”
This is where Technology Business Management (TBM) comes in.
TBM is a framework—a kind of Rosetta Stone—that translates the language of IT into the language of business. It helps you say: “This isn’t just $10M on infrastructure—it’s what powers digital sales, customer onboarding, or real-time analytics.” But here’s what I’ve learned: TBM, on its own, isn’t enough.
Why the Meta Model Matters
TBM gives us the vocabulary, but the meta model gives us the story. The meta model is what ties spend to applications, applications to services, services to outcomes. It says: this $5M spend supports the payments platform, which underpins 40% of annual revenue. Without it, cost transformation risks becoming blind trimming—optimising line items instead of reshaping how technology drives value.
The Gap in Real-Time Data
Even with a meta model, the challenge is that IT today doesn’t stand still. Workloads shift across clouds, containers spin up and vanish, API calls multiply by the second. The static spreadsheets that many TBM programs rely on just can’t keep pace. And that’s where I see the need to bring in Observability and AIOps.
Observability as the Pulse
Observability is the pulse of modern IT. Logs, metrics, traces—it’s the data that tells you what’s happening right now. It shows you not just where the money is spent, but how those systems are behaving, performing, and consuming resources in real time.
AIOps as the Interpreter
The problem, of course, is that the volume of this data is overwhelming. And that’s where AIOps comes in.
AIOps acts as the interpreter. It takes the flood of observability signals and adds context. It tells you:
- This anomaly in CPU belongs to the payments service.
- This degraded response time risks breaching an SLA.
- This failure could impact $10M in revenue.
Suddenly, an ops incident isn’t just noise—it’s a business event.
The Combined Power
Now, imagine stitching this together:
- Observability captures a spike in errors in your payment system.
- AIOps detects the pattern, predicts SLA risk, and links it to the payment service.
- The TBM meta model ties that service to $200M in annual revenue.
The CIO doesn’t just get an alert. They get a statement: “If unresolved in 30 minutes, potential exposure = $5M in lost revenue.” That’s cost transformation in motion. Not just cutting cost, but actively protecting and optimising value in real time.
Why the Board Cares
At the end of the day, boards don’t want to see metrics like MTTR, CPU utilisation, or log counts. They care about EBITDA, margins, customer retention.
The power of TBM + meta model + AIOps/Observability is that it finally connects the dots. You can say:
- “Improving MTTR by 15% protected $20M in revenue.”
- “Right-sizing underutilised resources saved $8M in opex and accelerated two product launches.”
- “Proactive detection avoided $3M in SLA penalties.”
Suddenly, technology spend isn’t a black hole—it’s a strategic lever.
For me, the lesson is clear. TBM gave us the structure. The meta model gives us the meaning. Observability and AIOps give us the real-time voice. Together, they let us shift the conversation: from IT as overhead to IT as a driver of value. And that, in my view, is what cost transformation should really be about. Not less spend. Smarter, value-driven spend—alive, contextual, and deeply tied to business outcomes.
C
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