Interpretation guidelines and caveats

Generally valid:

• Comparing your organization to peers that share industry, size band, and region
• Comparing towers that are in scope and mapped consistently
• Comparing unit costs where both cost and volume definitions match

Risky or invalid:

• Cross industry comparisons with wildly different business models
• Comparing a partial scope of IT to full scope benchmarks
• Mixing different accounting treatments without adjustment

If the underlying concept of “peer” does not hold, the metric is at best directional.

Common scope differences:

• Some organizations include telecom and operational technology in IT, others do not
• Shared services may be fully allocated into IT in some cases and left in corporate overhead in others
• Cloud and SaaS costs may be centralized in IT in some organizations and distributed in others

When you see a large gap:

• First verify scope and mapping
• Only then label it as performance difference

Benchmark gaps can reflect:

• Real inefficiency
• Strategic choices (higher service levels, more resilience)
• Different sourcing decisions (insource vs outsource, cloud vs on premise)
• Legacy footprint and technical debt

Being above benchmark is not automatically “bad.” Being below is not automatically “good.” The question is whether the difference is justified and understood.

There are two sides to data quality:

• Peer data quality – governed by provider rules and sample thresholds
• Your data quality – governed by your TBM model, mapping, and volume sources

Watch for:

• Entire towers or metrics missing for you
• Year over year swings that clearly come from remapping, not operations
• Volumes that have not been updated in years

Use benchmarks to highlight where detailed data review is needed, not just where to cut.