Timbers Resorts Case Study
Customer Company Size
Mid-size Company
Region
- America
Country
- United States
Product
- Domo
Tech Stack
- Data Analytics
- Data Visualization
Implementation Scale
- Enterprise-wide Deployment
Impact Metrics
- Productivity Improvements
- Cost Savings
Technology Category
- Analytics & Modeling - Real Time Analytics
- Application Infrastructure & Middleware - Data Visualization
Applicable Functions
- Business Operation
Use Cases
- Predictive Quality Analytics
- Real-Time Location System (RTLS)
Services
- Data Science Services
About The Customer
Timbers Resorts is a luxury developer of hotels, residence clubs and resort communities located in some of the most sought-after destinations in the world. The company operates sixteen resorts from the Colorado Rockies to Hawaii to Tuscany. As a global firm, Timbers Resorts needed a solution that could handle data from various locations across 12 different time zones. The company's operations span across interior design, construction, operation, and exchange systems, requiring a comprehensive and integrated solution for data management and analysis.
The Challenge
Timbers Resorts is a global firm that operates sixteen luxury resorts in various locations around the world. The company needed a vertically integrated solution to track interior design, construction, operation, and exchange system information across 12 different time zones. Prior to implementing Domo, the company received reports 20 days after the month closed and had no insight into sales data across zip codes. This lack of real-time data and insights posed a significant challenge for the company in making timely and informed decisions.
The Solution
Timbers Resorts implemented Domo, a data analytics and visualization tool, to address their challenges. Domo provided the company with real-time insights, enabling them to make decisions on-the-fly. The analyzer tool in Domo allowed the company to extrapolate data based on different time frames and metrics, enabling them to drill down to exactly the data they needed. This shift in data accessibility and analysis enabled the company to ask questions they never thought possible because they were now able to see data at a much deeper level. As a result, the company was able to focus more on future planning instead of just looking at historical data.
Operational Impact
Quantitative Benefit
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