Elevate 2017- Innovation Forum: Airnguru- What do biology and airline pricing have in common?

1. Javier Jiménez CCO Airnguru

2. Javier Jiménez Airnguru

3. Javier Jiménez • Introduction • Evidence #1: Time to Market reports • Evidence #2: RBD Mapping and the Longest Common Subsequence • Conclusion

4. “The reason why it is so difficult for existing firms to capitalize on disruptive innovations is that their processes and their business model that make them good at the existing business actually make them bad at competing for the disruption. — Clayton Christensen

6. — Sun Tzu , The Art of War

7. Information Build-up Time to collect data and produce relevant competitive and market information Response Design Time to design the price adjustment and react to the changes in the market Approval & Publishing Time to approve, upload and publish the new prices and rules of the fares t2t1 t3 t1+t2+t3 = Time to Market

8. • The average time to market that we have seen is 20.5 [hrs], but there is a great deviation from airline to airline • These differences can be caused by differences in any of the steps in the pricing process • Improvements in time to market reduce exposure to losses in market share and dilution. 13.22 13.82 18.5 18.63 18.67 18.77 23.72 25.11 25.27 25.82 26.26 27.51 27.83 30.95 65.42 78.98 81.9 94.02 0 20 40 60 80 100 I? B? A? L? A? L? D? Q? U? A? KL C? L? J? A? E? E? D? Time to Market ranking [hrs]

9. 0 500 1,000 1,500 2,000 2,500 3,000 3,500 4,000 0 10 20 30 40 50 60 Thousands Time to Market by DOW [hrs] Records Time to Market 0 500 1,000 1,500 2,000 2,500 0 10 20 30 40 50 60 70 80 0:00 1:00 2:00 3:00 4:00 5:00 6:00 7:00 8:00 9:00 10:00 11:00 12:00 13:00 14:00 15:00 16:00 17:00 18:00 19:00 20:00 21:00 22:00 23:00 Thousands Time to Market by TOD [hrs] Records Time to Market

10. • The average time to market that we have seen is 20.5 [hrs], but there is a great deviation from airline to airline • These differences can be caused by differences in any of the steps in the pricing process • Improvements in time to market reduce exposure to losses in market share and dilution. 13.22 13.82 18.5 18.63 18.67 18.77 23.72 25.11 25.27 25.82 26.26 27.51 27.83 30.95 65.42 78.98 81.9 94.02 0 20 40 60 80 100 I? B? AA L? AC LH D? Q? U? A? K? C? L? J? A? E? E? D? Time to Market ranking [hrs]

13. What is Cystic Fibrosis? Cystic fibrosis (CF) is a genetic disorder that affects mostly the lungs, but also the pancreas, liver, kidneys, and intestine. Long-term issues include difficulty breathing and coughing up mucus as a result of frequent lung infections. Unaffected “Carrier” Father Unaffected “Carrier” Father Unaffected 1 in 4 chance Unaffected “Carrier“ 1 in 4 chance Affected 1 in 4 chance

14. What is Cystic Fibrosis? In the 80’s a group of scientists tried to find the gene that produced the cystic fibrosis. They managed to narrow the search to a small region in chromosome 7, but at the time genetic mapping techniques were limited, so they couldn’t narrow the search to a specific gene. ? Chromosome 7

15. What is Cystic Fibrosis? To solve the problem they selected known genes and compared them with chromosome 7 using Sequence Comparison But how did they do it? Sequence 1: G A A T T C A G T T A Sequence 2: G G A T C G A 27.7% match… Not very similar ✓ ✕ ✓ ✓ ✕ ✕ ✓ ⎯ ⎯ ⎯ ⎯ 63.4% match… much better… G A A T T C A G T T A G G A T C G A ✓ ✕ ✓ ✓ ⎯ ✓ ⎯ ✓ ⎯ ⎯ ✓ ? Chromosome 7

16. Longest Common Subsequence Dynamic Programming Sequence 1: G A A T T C A G T T A Sequence 2: G G A T C G A 27.7% match… Not very similar ✓ ✓ ✓ ✓ ✕ ✕ ✓ ⎯ ⎯ ⎯ ⎯ - G A A T T C A G T T A - 0 0 0 0 0 0 0 0 0 0 0 0 G 0 1 1 1 1 1 1 1 1 1 1 1 G 0 A 0 T 0 C 0 G 0 A 0 G A A T T C A G T T A 𝑆𝑖,𝑗 = max ൞ 𝑆𝑖−1 + 0 𝑆𝑗−𝑖 + 0 𝑆𝑖−1,𝑗−1 + 1, 𝑖𝑓 𝑉𝑖 = 𝑊𝑖

17. Sequence 1: G A A T T C A G T T A Sequence 2: G G A T C G A 45.5% match… Not very similar ✓ ✓ ✓ ✓ ✕ ✕ ✓ ⎯ ⎯ ⎯ ⎯ - G A A T T C A G T T A - 0 0 0 0 0 0 0 0 0 0 0 0 G 0 1 1 1 1 1 1 1 1 1 1 1 G 0 1 1 1 1 1 1 1 2 2 2 2 A 0 1 2 2 2 2 2 2 2 2 2 2 T 0 1 2 2 3 3 3 3 3 3 3 3 C 0 1 2 2 3 3 4 4 4 4 4 4 G 0 1 2 2 3 3 4 4 5 5 5 5 A 0 1 2 2 2 2 2 5 5 5 5 6 ✓= ✕= ⎯ = G A A T T C A G T T A Longest Common Subsequence Dynamic Programming

18. Sequence 1: G A A T T C A G T T A Sequence 2: G G A T C G A 45.5% match… Not very similar ✓ ✓ ✓ ✓ ✕ ✕ ✓ ⎯ ⎯ ⎯ ⎯ G A A T T C A G T T A G G A T C G A ✓ ✕ ✓ ✓ ⎯ ✓ ⎯ ✓ ⎯ ⎯ ✓ - G A A T T C A G T T A - 0 0 0 0 0 0 0 0 0 0 0 0 G 0 1 1 1 1 1 1 1 1 1 1 1 G 0 1 1 1 1 1 1 1 2 2 2 2 A 0 1 2 2 2 2 2 2 2 2 2 2 T 0 1 2 2 3 3 3 3 3 3 3 3 C 0 1 2 2 3 3 4 4 4 4 4 4 G 0 1 2 2 3 3 4 4 5 5 5 5 A 0 1 2 2 2 2 2 5 5 5 5 6 Longest Common Subsequence Dynamic Programming ✓= ✕= ⎯ =

19. Sequence 1: G A A T T C A G T T A Sequence 2: G G A T C G A 45.5% match… Not very similar ✓ ✓ ✓ ✓ ✕ ✕ ✓ ⎯ ⎯ ⎯ ⎯ G A A T T C A G T T A G G A T C G A ✓ ✕ ✓ ✓ ⎯ ✓ ⎯ ✓ ⎯ ⎯ ✓ - G A A T T C A G T T A - 0 0 0 0 0 0 0 0 0 0 0 0 G 0 1 1 1 1 1 1 1 1 1 1 1 G 0 1 1 1 1 1 1 1 2 2 2 2 A 0 1 2 2 2 2 2 2 2 2 2 2 T 0 1 2 2 3 3 3 3 3 3 3 3 C 0 1 2 2 3 3 4 4 4 4 4 4 G 0 1 2 2 3 3 4 4 5 5 5 5 A 0 1 2 2 2 2 2 5 5 5 5 6 ✓= ✕= ⎯ = Longest Common Subsequence Dynamic Programming

25. Sequence 1: G A A T T C A G T T A Sequence 2: G G A T C G A 45.5% match… Not very similar ✓ ✓ ✓ ✓ ✕ ✕ ✓ ⎯ ⎯ ⎯ ⎯ G A A T T C A G T T A G G A T C G A ✓ ✕ ✓ ✓ ⎯ ✓ ⎯ ✓ ⎯ ⎯ ✓ - G A A T T C A G T T A - 0 0 0 0 0 0 0 0 0 0 0 0 G 0 1 1 1 1 1 1 1 1 1 1 1 G 0 1 1 1 1 1 1 1 2 2 2 2 A 0 1 2 2 2 2 2 2 2 2 2 2 T 0 1 2 2 3 3 3 3 3 3 3 3 C 0 1 2 2 3 3 4 4 4 4 4 4 G 0 1 2 2 3 3 4 4 5 5 5 5 A 0 1 2 2 2 2 2 5 5 5 5 6 Longest Common Subsequence Dynamic Programming ✓= ✕= ⎯ =

28. They found that a similarity with ATP (an organic chemical related to energy transfer and secretion) was presented in the position q 32.2 of the chromosome. Sequence 1: G A A T T C A G T T A Sequence 2: G G A T C G A 45.5% match… Not very similar ✓ ✓ ✓ ✓ ✕ ✕ ✓ ⎯ ⎯ ⎯ ⎯ G A A T T C A G T T A G G A T C G A ✓ ✕ ✓ ✓ ⎯ ✓ ⎯ ✓ ⎯ ⎯ ✓ - G A A T T C A G T T A - 0 0 0 0 0 0 0 0 0 0 0 0 G 0 1 1 1 1 1 1 1 1 1 1 1 G 0 1 1 1 1 1 1 1 2 2 2 2 A 0 1 2 2 2 2 2 2 2 2 2 2 T 0 1 2 2 3 3 3 3 3 3 3 3 C 0 1 2 2 3 3 4 4 4 4 4 4 G 0 1 2 2 3 3 4 4 5 5 5 5 A 0 1 2 2 2 2 2 5 5 5 5 6 63.4% match… more similar ✓= ✕= ⎯ = Longest Common Subsequence Dynamic Programming

29. Eureka! The CFTR gene The gene they found after applying the algorithm resulted to be the gene responsible for Cystic Fibrosis CFTR gene Cystic Fibrosis Transmembrane Regulator gene A T C A T C T T T G G T G T T Sequence of nucleotides in CFTR gene Deleted in many patients with cystic fibrosis

30. Now… let’s go back to the algorithm - G A A T T C A G T T A - 0 0 0 0 0 0 0 0 0 0 0 0 G 0 1 1 1 1 1 1 1 1 1 1 1 G 0 1 1 1 1 1 1 1 2 2 2 2 A 0 1 2 2 2 2 2 2 2 2 2 2 T 0 1 2 2 3 3 3 3 3 3 3 3 C 0 1 2 2 3 3 4 4 4 4 4 4 G 0 1 2 2 3 3 4 4 5 5 5 5 A 0 1 2 2 2 2 2 5 5 5 5 6

31. Now… let’s go back to the algorithm - Y H A S K M P N G Q A - 0 0 0 0 0 0 0 0 0 0 0 0 Y 0 1 1 1 1 1 1 1 1 1 1 1 H 0 1 1 1 1 1 1 1 2 2 2 2 L 0 1 2 2 2 2 2 2 2 2 2 2 V 0 1 2 2 3 3 3 3 3 3 3 3 M 0 1 2 2 3 3 4 4 4 4 4 4 S 0 1 2 2 3 3 4 4 5 5 5 5 Q 0 1 2 2 2 2 2 5 5 5 5 6

32. Market MIA-SCL - Economy (AA vs LA)

33. Market NYC-LON - Economy (AA vs DL)

Elevate 2017- Innovation Forum: Airnguru- What do biology and airline pricing have in common?

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Elevate 2017- Innovation Forum: Airnguru- What do biology and airline pricing have in common?