Skip to main content

France Telecom Triple-Play Profitability Issue

According to Forrester Research, French consumers are very interested in broadband triple play � and they enjoy the most advanced and competitive xDSL-based triple-play market in Western Europe. But that doesn't mean that incumbent telco France Telecom will make money on its triple-play offering.

Forrester's new, detailed, bottom-up P&L model looks at the profit potential from 15 main revenue categories across 17 countries and concludes that the vendor-recommended solution would be financial suicide for FT.

Forrester predicts a cumulative per-subscriber loss of �4,311 in year 10, thanks to low revenue growth and massive backhaul costs. The key problem is that French consumers want triple play � but they don't want to pay a lot for TV services, thereby limiting revenue growth. What can FT expect if it continues down this path? High investment costs and lots of price and content competition for TV subscribers.

There are significant lessons to be learned by observing the advanced European broadband services market, and attentive North American telcos would be wise to closely follow FT's progress as it continues to be displaced by more innovative and agile competitors.

Popular posts from this blog

AI Agents Have Memory. Where is The Security?

Enterprise AI adoption keeps running into the same wall: the moment sensitive data, model weights, or agent memory leave a tightly controlled environment, security teams lose visibility into what happens to them while the workload is actually running. Confidential computing exists to close that gap, and new research from ABI Research shows the technology has matured enough, across CPUs, GPUs, containers, and now agentic AI, to become a foundational requirement for enterprises building sovereign AI infrastructure: computing environments they control end to end rather than simply rent. Protection is Moving From CPUs to GPUs ABI Research finds that CPU-based confidential computing is closest to mass-market adoption, the product of years spent hardening chip-level isolation for general workloads. GPU-based confidential computing is now generating the strongest momentum, and for good reason. It addresses one of the largest unresolved gaps in AI security: protecting data and models while inf...