javier jiménez - atpco | we fuel the future of air travel. · · 2017-11-17javier jiménez cco...
TRANSCRIPT
Javier Jiménez
• Introduction
• Evidence #1: Time to Market reports
• Evidence #2: RBD Mapping and the Longest Common Subsequence
• Conclusion
“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
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
• 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.
13.2213.82
18.518.6318.6718.77
23.7225.1125.2725.8226.2627.5127.83
30.9565.42
78.9881.9
94.02
0 20 40 60 80 100
I?B?A?L?A?L?D?Q?U?A?KLC?L?J?
A?E?E?D?
Time to Market ranking [hrs]
0
500
1,000
1,500
2,000
2,500
3,000
3,500
4,000
0
10
20
30
40
50
60
Tho
usa
nd
s
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
0:0
0
1:0
0
2:0
0
3:0
0
4:0
0
5:0
0
6:0
0
7:0
0
8:0
0
9:0
0
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
Tho
usa
nd
s
Time to Market by TOD [hrs]
Records Time to Market
• 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
18.518.63
18.67
18.77
23.72
25.1125.27
25.82
26.26
27.5127.83
30.95
65.42
78.98
81.994.02
0 20 40 60 80 100
I?B?
AA
L?
ACLHD?
Q?
U?
A?K?
C?
L?
J?
A?E?
E?
D?
Time to Market ranking [hrs]
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” FatherUnaffected
“Carrier” Father
Unaffected
1 in 4
chance
Unaffected
“Carrier“
1 in 4 chance
Affected
1 in 4
chance
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
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
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 = max൞
𝑆𝑖−1 + 0𝑆𝑗−𝑖 + 0
𝑆𝑖−1,𝑗−1 + 1, 𝑖𝑓 𝑉𝑖 = 𝑊𝑖
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
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
✓=
✕=
⎯ =
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
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
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
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
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
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
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
✓=
✕=
⎯ =
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
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
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
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
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
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