Big Data – didn´t ask a question but received a helpful answer!

One morning my attention was drawn to a small Google maps message on my cell phone: “20 minutes to work, light traffic”. I use the “my places” feature occasionally as it makes travelling really convenient. This notification helped me realize that big data stretches far beyond business applications. We are all part of it. Just think of the data our mobile devices are collecting and what these services subsequently learn about our habits every day, every minute: the number of steps we take per day, our heart rate or the streets we use to walk our dogs or drive to work. For some of us, it feels spooky to be observed and surveyed this way; like an invasion into our private lives. Another perspective, another emotion: If we consider big data from a health/medical point of view, it’s not scary at all. In contrast, it seems like a good approach to find new ways to prevent and cure diseases and ultimately make people´s life healthier by collecting and utilizing relevant data.

Big Data. Big = Quantity?

All that brought me to the question: What is big data? There are various definitions but it seems to be common sense that the amount of data that is collected is huge and that the initial purpose is to obtain insights into the customer’s preferences and even personality to adjust offerings and advertisement. But is that all?  Another interesting angle is the definition of the term “big”. There are four factors used to define big data:

• Too big
• Too complex
• Changing too fast or
• Weakly structured

Obviously, quantity is only one of four characteristics. The rest refer to structure, change and complexity. These three attributes provide a perfect segue into the aviation industry.

Big Data on the apron?

An enormous amount of data is produced and processed each day while planning, scheduling and operating in aviation. The data are also enriched with external information such as weather data, passenger and booking information. Updates happen in real-time, creating an everchanging and dynamic situation. At a glance, this information, combined with the resulting decisions that are made defines our picture of what is happening in aviation from a data perspective. Let’s take a closer look at the connection between data evaluation and economics: Catering for example is what we see as a standard service on mid- and long-haul flights.

Did you know that all unopened meals need to be thrown away after arrival at the destination? What is understandable from a hygienic point of view causes some headaches at the airlines with regard to commercial and environmental issues. Therefore, it is vital to accurately estimate the number of meals needed. One way to reduce cabin waste is to offer a pre-order service to the passengers, which is already in place at some airlines. This way, the airline benefits in two respects: The service quality is improved and costs are reduced. But if this pre-ordering option isn’t established, how can you optimize your catering planning and reduce costs and waste? This is where data utilization comes into play as well as one big buzzword: experience value. There are three ways to tap into the experience value:

1. Gut feeling.

2. Evaluation of historic data.

3. Combine options 1 and 2.

I vote for the third option. Data is collected everywhere so the “only” problem that needs to be solved is establishing the right structure and combination to extract valuable findings. Let´s stay with the catering example and list the different types of information that might have an impact:

• Destination
• Time of day and duration of the flight
• Types of meals
• Amount of waste per flight
• Overall amount of waste
• Amount of waste per meal
• Passengers per flight

Although I always liked mathematics and bringing numbers together, this task seems to be very complex. Software support is needed.

The stored data from past flights can be used and processed to provide value for the future. These data need to be classified and sorted to bring the relevant information together for valuable insights. Let´s have a look again at the (incomplete) enumeration above. It is important to assess the relevant information from this list and understand how the various elements are related. How can they be used to create capable KPIs and benchmarks?

Business Intelligence and big data analytics are the keys to master this challenge. The collected data from various sources need to be translated for further processing. Subsequently, it undergoes an evaluation and is visualized for better interpretation. This is a complex challenge as it concerns different departments in an operation and requires a huge amount of data in various formats.

Experience Value by data results in optimized decision making

To sum it up: the results of a proper business intelligence process are better decisions in the future. If the complex, highly unstructured and frequently changing data is processed in the right way and interpreted by the right people, the operations will benefit from:

• Cost reduction
• Better and faster decision making
• Product and service innovations

It clearly shows: big data can do more than tell us if it’s 20 or 25 minutes to work on our smartphone. It tells the caterers how many chicken, pork and vegetarian hot meals they need to load on the next fully booked 777 – maybe without having to dispose of one single leftover at the destination.

What’s your experience with big data in your daily business?

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