New York skyline reflecting the challenge for growing hotel chains to break down revenue silos for multi property management

For many growing hotel chains, revenue strategy starts with good intentions. But when it’s time to execute, alignment often slips. In this article, you’ll discover how to enable clearer visibility into revenue data, how to make better decisions fast, and how to scale your hotel chain without adding complexity.

NB: This is an article from Duetto

Subscribe to our weekly newsletter and stay up to date

As property numbers increase, what began as a centralized approach often turns into a patchwork of property-level decisions. Disconnected tools and manual workarounds pull execution off course. Pricing logic drifts. Forecasts stop lining up. And group and transient decisions get evaluated in isolation.

That leaves cluster revenue managers to stitch together a “portfolio view” after the fact.

This is what silos look like in practice – and for multi-property revenue management teams, they’re one of the biggest barriers to sustainable growth.

Breaking these silos isn’t about adding more tools or tightening control. It’s about creating a unified revenue strategy that can scale across properties, teams, and revenue streams. The first step is seeing where silos are already shaping day-to-day decisions.

What revenue silos look like in multi-property hotel chains

Revenue silos are rarely obvious. They don’t usually appear as a single system failure or a missing report. More often, they show up as friction in the day-to-day work of managing multiple properties at once.

Over time, small inconsistencies start to compound. Decisions and performance are evaluated using different assumptions. Strategy exists at the portfolio level, but execution happens hotel by hotel.

The result is a revenue operation that looks centralized on paper, but behaves differently in practice.

For cluster revenue managers, silos often show up as constant reconciliation:

  • Pulling data from multiple systems
  • Explaining why forecasts don’t match actuals
  • Responding to late-cycle surprises instead of planning ahead

The issue isn’t effort or expertise. It’s that the operating model hasn’t evolved at the same pace as the portfolio. And over time, that chips away at the time and focus needed to manage the portfolio proactively.

Read the full article at Duetto