The techco trap: you don’t have a technology problem, you have a measurement problem

This Industry Viewpoint was authored by Biju Anidil, Regional VP Sales, EMEA & APAC, Evergent

Every monetisation vendor, mine included, will tell you to modernise your BSS. You have heard it a hundred times, which is why most of you have not acted. The advice is not wrong. It is incomplete, and the missing part is the reason operators stay stuck.

For a decade the industry has chased the same reinvention: telco to techco, the operator remade as a technology company. Done properly that means a software and cloud operating model, AI and data in the core, agile delivery, and revenue from platforms, network APIs and new value pools rather than connectivity alone. It is a change in how the business runs, not a catalogue of services bolted on top. Technology companies reinvest between a tenth and a quarter of revenue into R&D; most telcos reinvest under three percent. That gap is the real distance between ambition and reality.

Here is where it goes wrong. Most operators have bought the technology of a techco, the modernised stacks and multi-year programmes, without adopting its commercial operating model. They still price, measure and move like a telco. That is the techco trap: you have modernised the technology without moving the number that actually matters, which is how fast you turn a commercial opportunity into revenue. Whether that is a streaming bundle or an enterprise network-API product, it still reaches market far too slowly.

The uncomfortable version is simpler. Most operators do not have a technology problem. They have a measurement problem. A real techco scores itself on customer value and speed. Trapped operators still score systems delivered and milestones hit, and almost nothing on speed to revenue. So that is what gets sacrificed.

Why you are actually stuck

Most programmes begin with the right objective and then collide with time. Large IT transformations run two to four years, and by the time they land the market has moved on. But the deeper reason the obvious fix stays undone is not ignorance, it is risk. Your monetisation logic is welded into a stack that is often twenty years old, so ripping it out carries migration risk that can end careers, and it keeps getting deferred. Admitting a multi-year programme optimised the wrong metric is politically expensive in any large operator. These are real obstacles, not excuses, and any vendor who says the fix is simple has never sat in your chair.

Revenue velocity, and what it costs you

A sharper measure is revenue velocity: how quickly you move from identifying an opportunity to earning money from it, counted in weeks from signed partner to first invoiced revenue.

The cost of getting this wrong is not abstract. Take an operator with twenty million subscribers launching a bundled offer that adds five euros a month and reaches one customer in twenty. That is a million subscribers at five euros: five million euros a month, fifteen million a quarter. Launch a quarter late and that fifteen million is not deferred, it is gone: you never recover the lost quarter, and a faster rival may take the window outright. Then multiply by every offer you launch in a year.

This is why the sharper operators have stopped chasing full-stack replacement and modernise only the layer that manages revenue: pricing, bundling, entitlements and billing. After rebuilding its BSS for exactly this, Astro, Malaysia’s leading pay-TV operator, halved its time to market for new offers and cut operational costs by two-thirds, replacing a twenty-year-old platform in nine months, not the multi-year cycle these projects usually run. Commercial agility depends far more on modernising that layer than on replacing everything beneath it.

Agentic AI cannot outrun bad foundations

AI now dominates the conversation, and its potential is real, but its role is misunderstood. Agentic AI is an orchestration layer, not a transformation strategy. It connects information across systems, speeds decisions and automates manual work, and it is only as good as the data beneath it. Point it at fragmented data and inconsistent rules and you simply automate the mess faster. AI can accelerate revenue velocity, but only on a monetisation foundation that is already clean.

Are you in the trap?

Three questions tell you. Does launching a new bundle require a project, or a configuration change? Have your last three launches each taken more than a quarter? Do your AI pilots keep stalling on data quality and entitlement gaps? Two yeses out of three and you are in the techco trap, whatever your roadmap says.

The techco ambition is right, and unchanged. What has to change is the definition of success: not milestones delivered, but revenue captured, and how fast. The operators that win will be the ones that shorten the distance between a commercial decision and the revenue it produces. Everyone else will keep buying transformation and wondering why it never quite arrives.

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