6 Keys to Good Data

Cheryl McMaster, CHA, CRME Director, Third Party & Commercial Operations, Sonesta, HSMAI Revenue Optimization Rising Leader Council Member 

As our industry and technology become more complex, clean data is critical. Managing a pricing strategy to drive REVPAR is only one layer to the equation. When a new system is implemented, the best outcome is an integration that allows for a holistic look at the new data available. Even with access to data, we must be wary of the accuracy to avoid a “garbage in, garbage out” scenario when deciding. The HSMAI Revenue Optimization Rising Leaders Council recently discussed this topic and brainstormed our top keys to good data.  

1. Clean Data = Clear Decisions

Clean data is not just about having neat spreadsheets; it’s the cornerstone of making decisions that drive results.

2. Centralize Systems

The more we integrate, the more fragmented our data can become. A single source of truth in a centralized system can make sure everything aligns and lead to better decisions. 

3. Share Data

Sharing data across teams can help craft strategies that are in tune with guest preferences and buying behaviors.  

4. Don’t Miss the Forest for the Trees

Instead of getting bogged down in the nitty-gritty, take a step back and look at the bigger data picture. 

5. Be Adaptable

If the current system or approach feels like trying to fit a square peg in a round hole, it might be time to seek alternatives.  

6. AI Can Help

Let machines do the heavy lifting of data analysis and set up automated processes. This allows us to focus on what humans do best – creativity, innovation, and building genuine connections. 

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Questions for Your Team:  

  1. How many systems are you extracting data from regularly? How many of those systems integrate in a meaningful way to drive powerful decisions versus piecemealing the information together?
  2. What is the biggest data gap in your world today that you wish you could fill to make better decisions?
  3. Each department uses different data sets. What data commonly used in the revenue management discipline could benefit other teams? What data from other teams could improve your decisions in revenue management if you had access?
  4. What are best practices you’ve learned to find the “needle in the haystack” – sifting through all available data to find actionable insights?

Categories: Revenue Management
Insight Type: Articles