A Hybrid, Adaptive Regression PLF Forecasting Model
PLF measures the capacity utilization for airlines and the bettering of this KPI affects the plan and costs of complementary functions such as workforce, fuel, catering and ground services. Obase PLF Optimization solution is built on a hybrid adaptive regression model and forecasts PLF with smallest error margin possible. The model delivers an optimum revenue and enables the business units to cleverly act on price and campaigns.
Revenue Optimization
Advanced Forward Forecasting
Empowered Business Units
Increase in Profitability
Performance Efficiency
Decrease in Operational Costs
Passenger Load Factor (PLF) indicates the efficiency of the airline: filling seats and generating revenues. The bettering of this KPI affects the plan and costs of complementary functions such as workforce, fuel, catering and ground services.
While forecasting PLF is difficult as it’s highly affected by seasonality, unpredictable demand and even political & economical issues, Obase PLF Optimization solution has been able to deliver above industry standard results by building airline-specific models to forecast the aggregate passenger traffic in a certain time frame, region or an individual flight.
Aras Kargo
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Mehmet Zeki Güngör
BI ManagerAras Kargo
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We have been using the MicroStrategy solution in our operations for more than 10 years in Obase consultancy. It was important for us to reduce the reporting requests from users. We reduced the incoming report requests by further increasing the use of self-service BI structure and training users.
Mehmet Zeki Güngör
BI ManagerAras KargoTurkish Airlines
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"Turkish Airlines Empowers BI with MicroStrategy Enterprise platform and Obase expertise. Obase solutions allow us visualization of transaction services and mobile applications in one place. With MicroStrategy capabilities, it provides us unified development environment for desktop and mobile."
İbrahim Oral Emül
Big Data and BI ManagerTurkish AirlinesBorusan Otomotiv
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"Borusan Otomotiv has been developing a CRM application in its own field for about 10 years. Borusan Otomotiv decided to implement a new CRM application. In moving to the new CRM infrastructure, it aimed to solve the quality problems that occurred in the database for 10 years, to improve the quality of customer dedication and data. Borusan Otomotiv preferred the IBM Information Server product family and the business alliance with OBASE to solve all these problems."
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