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Lufthansa Systems Lido OC TFR module cuts costs and emissions
Finding an optimal route for each flight is the daily challenge of every flight planner. In this process, every calculation is based on a variety of parameters which have to be incorporated and optimized against each other in regard to costs, flight time and fuel efficiency. Besides such factors as weather conditions and country-and airport-specific regulations, flight planners also need to adhere to current air traffic capacity and flow management rules. These highly complex rules, also known as Traffic Flow Restrictions (TFR), are set by air traffic control authorities in order to guarantee a smooth traffic flow while at the same time optimizing ATC capacity and safety. Common examples of such Traffic Flow Restrictions are temporary restrictions of certain flight paths, restrictions for certain aircraft, flight levels or routes, as well as restrictions for take-off and landing.
Airlines use a set of company routes or standard route bundles which are defined by each carrier for its flights. These company routes form the basis for the actual operational flight plan (OFP) on the day of departure. Consequently, airlines are also required to check their routing for a particular flight against the latest ATC rules in order to ensure a legal route. This fundamental task is usually performed manually by flight planners.
Lufthansa Systems has recently presented its innovative TFR module which is an add-on to its successful flight planning solution Lido Operations Center (Lido OC). As an industry first, the module automatically considers even partly restricted airways, suggesting by-passes where legally permitted, for the most effective combination of airway segments. Therefore the bundle of possible routings is enhanced by those routes which are partly restricted resulting in even a larger pool of possible routings that can be considered for an optimal flight planning. Automating this process with Lufthansa Systems’ new Lido OC module is an enormous step forward and enables dispatchers to focus on other important tasks.
By optimizing the process of flight planning through the TFR module, an airline can further enhance ecological and economical efficiency. Benchmark analyses have shown that the new tool can generate savings of up to two percent in fuel burn which helps airlines to reduce CO2 emissions and to save cost - something that has become crucial for Airlines. Network carriers, regional and budget airlines alike directly save costs and reduce emissions with this latest innovation in airline IT.
Direct routing or good price?
Unique IT tool from Lufthansa Systems analyzes buying behavior and helps airlines optimize their flight program
When choosing a flight, customers often have to weigh up the benefits of a cheap ticket against those of a convenient flight schedule. If they opt for an inexpensive flight, they will usually have to put up with an inconvenient itinerary. As both cost and convenience play a key role in airlines' strategic network planning, Lufthansa Systems collaborated on an academic project with the University of Augsburg to develop a so-called price attribute. This innovative and unique concept takes full account of the way that different ticket prices influence customers' choice of routes and thus affect long-term network planning. Airlines can use this information to optimize their pricing policies while simultaneously ensuring the profitability of their flight schedule.
An airline that is able to analyze the price sensitivity of its customers can devise better strategies to deal with competitors who offer lower prices or better flight connections. A capacity to carry out such analyses is becoming increasingly important as competitive pressures on airlines increase. Lufthansa Systems has also investigated the factors that influence a customer's choice of flight. Is the passenger's priority to reach his destination as quickly or as cheaply as possible, and how much is he prepared to pay for each of these alternatives?
By way of illustration, a customer may have a choice of two flights for his overseas trip. The first option will take him straight to his destination in 10 hours 20 minutes, with no transfers. The cost of this non-stop is EUR 1,100. The second option, at EUR 800, would cost significantly less but the customer would have to accept a stopover, extending the total journey time to 17 hours. If the flight schedule is the only criteria, the customer will choose the non-stop flight. If, however, price is also a consideration, it is difficult to tell how great an influence the price difference might have on the customer's decision.
This is exactly the problem tackled by the price attribute in Lufthansa Systems' NetLine/Plan network planning suite. The price attribute reveals how important the ticket price is to passengers compared to the quality of the flight schedule. The tool uses historic data to analyze passenger preferences and predict customer behavior. In simplified terms, it calculates the maximum price level at which a non-stop flight will still be preferred over a transfer connection, whilst still providing the airline with the best possible return.
Based on the example above, the airline offering the direct flight must assess what price the customer will pay for a more convenient arrangement and what effect this price has on the profitability of the flight. The cheaper airline, on the other hand, will wonder how much more it has to discount a flight with its comparatively unattractive schedule in order to appeal to as many passengers as possible without becoming unprofitable. In both cases, these are strategically important decisions for which the NetLine/Plan forecast model can provide a firm basis.
Lufthansa Systems partnered with the Department of Business Mathematics at the University of Augsburg in the development of the price attribute. This research institute has top-level expertise in the areas of revenue management and market research/ data analysis, two of the key disciplines required in the development of the solution. The project thus benefited from an ideal combination of academic knowledge and practical experience, and so provided the ideal conditions under which to create a successful network planning model of the highest order.
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