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Hotel Gran Bilbao Forecasts Occupancy Rates Using AI

While they expertly deliver innovation and quality to their customers, Callaway Golf’s previous planning and reporting tool wasn’t making the cut. To evolve their enterprise, the sports giant decided to replace their outdated planning software with SAP Analytics Cloud for planning.

Together with Avvale, Callaway Golf successfully implemented SAP Analytics Cloud across their global enterprise in just 6 months. Now, Callaway Golf has a single, consolidated planning solution that has enabled streamlined expense and asset plans so they can focus on what they do best– revolutionizing the sporting world with cutting edge equipment.

Delivering unique, highly personalized guest experiences drives Hotel Gran Bilbao (HGB) in Spain.  They know that no two guests are the same and therefore no two rooms are exactly alike. Artwork is paired bespoke to each room as an inspiration to guests. With such an acute focus for guest experience, HGB saw an opportunity to become even more proactive with preditions and services. 

The Challenge

HGB partnered with Avvale to assist with determining Revenue Per Available Room (REVPAR). This is the key metric that measures revenue per available room that is based on several factors including set time horizon, whether weekly, monthly, yearly, etc. To calculate this KPI it is necessary to have these two variables, percentage of occupancy on the total available rooms and the average daily rate (ADR).
 
To begin this project, Avvale interviewed Hotel Directors, Revenue Directors, Partners, and potential clients. It was concluded that there was no solution in the market that evaluated both external and internal indicators when predicting demand and hotel occupancy. It was clear a tailor-made solution was needed. Not only that, but a solution that could be applied to other smaller and larger businesses.  
 

After analyzing the independent business/hotel network in Spain, it was determined that the solution can replicate certain aspects of their business models. In the case of HGB, it was essential to strengthen direct sales to improve its profitability. A necessity of this tool is to allow for a more effective and profitable management of the channel strategy to increase profitability. 

 

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The Approach

Avvale co-developed a new solution with the Hotel Gran Bilbao and successfully implemented it with the intention of improving the revenue management strategy. 

To create stronger predictions, various algorithms and predictive models based on Deep Learning (neural networks) were combined while factoring variables such as past occupancy, average booking price, channel, segment, room types, or other data external to the hotel. All this connected to the data of the Property Management System (PMS) of the hotel to create a full view of current and future occupancy.
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The Challenge

Before integrating SAP Analytics Cloud, Callaway Golf's planning landscape centered around SAP's legacy planning solution, Business Planning and Simulation (BPS). While BPS met Callaway Golf's planning needs for many years, the enterprise began to experience limitations with their old solution:

  • Disconnected plans across the board: As Callaway Golf expanded and acquired new brands, planning processes greatly differed across the enterprise with some business units using Excel spreadsheets and others using legacy solutions for planning.
  • Outdated planning functionalities: The existing legacy planning solution lacked many modern functionalities. Among them, salary calculations and asset depreciation automation needed improvement. As a result, it became difficult to create detailed and accurate forecasts across the globe.
  • Significant IT support: The legacy solution required continuous management from IT to maintain runtime. IT had to carve out a full day every week to manually maintain the solution.
  • No single source of truth: Various departments and brands used different data sources, which led to data silos across the organization, making it difficult to gain a clear picture of the enterprise's planned expenses.
  • Rigid user interface: Legacy forecasting system was difficult to navigate and lacked working functions and calculations across the board, such as planning on depreciation and existing assets, adding vendors or members on the fly, and breaking down their cost center expense planning forecasts.

The Approach

With Avvale experts on their side, Callaway Golf laid out the following goals for their new planning landscape with SAP Analytics Cloud:

  • Crowdsource and consolidate plans across the enterprise to gain a global overview of their planned expenses and expand the input capabilities to each responsible owner.
  • Leverage elevated planning functionalities to create faster and more accurate forecast cost center expense and asset reports. The ability to customize calculations enhances and automates the reporting metrics.
  • Harness the power of self-service analytics to alleviate IT from the burden of simple maintenance and data entry requests, so they can focus on high-ROI tasks.
  • Maximize user-driven admin capabilities to control the management of calculations and forms.
  • Create new KPls driven by the business needs.

When SEM-BPS was the center of Callaway Golf's planning landscape, flexibility was a huge factor that was missing. SAP Analytics Cloud contains powerful scenario planning capabilities that help organizations quickly uncover actionable insights to make data-driven decisions. For Callaway Golf, SAP Analytics Cloud's modern planning functionalities provided users with the ability to:

  • Add members on the fly
  • Plan on existing as well as planned assets and automatically calculate the depreciation of values
  • Test "what-if" scenarios for deeper analysis by creating private versions of plans
  • Customize the solution based on their current business process
  • Perform driver-based calculations
  • Empower users to execute end-to-end planning scenarios, without the help of IT

The Impact

Leveraging real-time insights through data management, Hotel Gran Bilbao can predict demand and hotel occupancy with 90% accuracy over a one-month time horizon and almost 89% accuracy over a ninety-day time horizon. Because of this, the hotel has experienced an increase in REVPAR. Predictive scenarios manage potential challenges and hotel service consumption for accurate service and scheduling, further driving down operations costs. Most importantly, Hotel Gran Bilbao can focus on what they do best-- delivering exceptional service and hospitality. 

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