Boeing 737 Big Data Blunder!

Apr 20, 2016 — Megan Howse
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I was travelling recently and booked a long travel day with limited time in between flights. There I was…hanging out in economy seating…for my 5 hour flight…directly over lunch hour…and I was getting hangry!

i-was-quite-surprised-by-some-things-on-my-american-airlines-international-economy-class-flight.jpgThe food and beverage cart arrived  and I excitedly had my credit card waiting (I had been staring at the in-flight menu for the past 40 minutes). I asked for the turkey sandwich and a glass of tomato juice (what is it about flying and drinking tomato juice?!)  I was informed they were out of sandwiches, wraps, snack boxes and all of the food except the usual “salty or sweet.” I got one of each and decided I was sure I would live. 

As I sat there savoring my drink I thought, “Why on this data-capable-earth would they run out of ALL the food!?” In my mind it would be a simple calculation of an over-sold flight, length of time in air, and time of day combined with average sales on that regular flight to determine they should go ahead and stock more food. Had the airline also foreseen the snowstorm that took place that day they would likely have been even more easily able to predict flight delays, frustrated passengers and growling stomachs.

Use data to create better experiences

Based on this example, it is clear that companies that use their existing data and react to big data trends the fastest, will be the ones to make the most profit. Big data allows retailers to aggregate their existing metrics with external data to predict and capitalize on trends. Understanding how, when and where consumers will buy creates the ability to manage stock and meet demand.

Retailers using big data will ultimately create a better experience and influence consumer decisions, giving them a competitive edge. While this example would have been an easy metric to calculate, big data isn’t always so easy. There is no out of the box solution to this form of critical thinking and hypothesis.

Inspire your inner big data geek! 

  • Trends on Fleek – By using things like social media and web browsing, companies can understand what the buzz is about and predict trends. Walmart uses big data to track millions of transactions, inventory levels and competitors daily. They then combine that information with web information, social media, and product releases. By working months ahead to predict hot items such as popular video games, they can stock up and truly deliver to their customers.
  • Weather Forecast & Beyond – By looking at demographics, economics, spending habits, etc. You should be able to make accurate forecasts to avoid inventory nightmares or decreases in sales. Identifying any gaps or losses creates an opportunity to overcome any objections. One hotel chain, Red Roof Inn, used big data to increase sales rather than seeing decreases during bad weather. The hotel chain used easily available weather and flight cancellation information combined with their locations near those airports to target mobile ads to stranded travelers, making it easy for them to book a nearby hotel.
  • Laws of Customer Attraction – By understanding who the customer is that you’re trying to attract, you can decide how they want you to put products in front of them. How do they interact with you? What is the best way to gain their attention? How do you get them into your stores? Macy’s used big data to understand that millennials were their most common demographic. They then developed an area called One Below in the basement of one of their New York flagship locations. Features include selfie walls, wearables, 3D printers and tons of customization options to attract the trend setters to visit and ideally become lifetime customers.

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Topics: Retail Operations, Customer Experience, Business Intelligence

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