Demand planning is a crucial aspect of an airline’s operations strategy. As such, the aviation industry requires robust demand forecasting capabilities.
These demand forecasting tools need to have long and short-term planning functions. As a result, the sector can devise long-term business plans as well as respond to immediate issues. Many airlines and airports forecast short-term demand based on anecdotal evidence and experience. Although quick-to-hand, this approach tends to lack accuracy. Therefore, to enhance the accuracy of reactive demand planning, the aviation industry needs to develop more sophisticated forecasting models.
Big data: The key to agile and accurate demand planning
Big data technologies are changing the way airlines forecast sales and demand. In the past, agents recorded bookings manually. That is, when a customer bought an airline seat or package holiday, this would be manually logged in the system. From here, the airline would analyse sales to estimate market size, popularity and preferences. So, for example, an airline could identify that non-stop flights between London and New York sold well and adjust their demand strategy accordingly.
Although this may seem like a sensible approach, the Internet brought a wealth of new intelligence opportunities. Now, airlines can capture information about potential clientele as well as paying customers. For instance, airlines can gather data about booking attempts, abandoned carts, and search requests. With the right tools, airlines have the ability to know their customers better than ever. As such, big data is transforming the way that airlines operate, from demand planning to customer service.
With big data comes big challenges
For many players in the aviation industry, the key challenge to unlocking the power of big data lies in siloed information. In order to gain the richest intelligence, companies need to identify fragmented datasets and collate them into a single, accessible data lake. Useful data can be found across the organization, from transaction systems, to mobile apps, to customer service records. Once this data in aggregated, airlines, airports and agents can build a comprehensive overview of the customer.
Furthermore, many businesses struggle to fully understand the potential of big data. For example, customer preferences are but the tip of the iceberg; big data can be used to develop sophisticated revenue management models. Through advanced analytics, airlines can optimize seat allocations, fares and itineraries, depending on customers’ individual preferences. In order to extract the most reliable, detailed intelligence from this data, airlines need to follow five key rules. These are:
- - Always challenge model assumptions
- - Aggregate a growing big data pool to drive increasingly accurate analysis
- - Continually refine sales forecasts as big data enables greater detail
- - Think broadly and consider what else can be optimized
- - Apply big data principles across business functions
Big data: Enhancements beyond demand planning
Big data analysis can optimize every aspect of an airline’s business functions. From demand planning, to sales forecasts, to customer service, the aviation industry needs to deploy advanced analytics to drive improvement. Furthermore, once one area reaches peak optimization, management should review every level for further enhancement. As such, there is no such thing as “peak optimization” only the imperative to continually improve across all aspects of the business.