THE UTILISATION OF BIG DATA IN INDONESIAN TOURISM...
Transcript of THE UTILISATION OF BIG DATA IN INDONESIAN TOURISM...
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THE UTILISATION OF BIG DATA IN INDONESIAN TOURISM MANAGEMENT
I GDE PITANA Deputy Minister for International Marketing, Ministry of Tourism, Republic of Indonesia The 11th UNWTO/PATA Forum on TOURISM TRENDS AND OUTLOOK 11 October 2017
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OUTLINE 1. TOURISM IN INDONESIA 2. WHY BIG DATA 3. BIG DATA IMPLEMENTATION IN INDONESIA TOURISM 4. THE BIG DATA & THE AGENDA OF SUSTAINABLE TOURISM
DEVELOPMENT 5. BEST PRACTICE: THE USE OF MOBILE POSITIONING DATA FOR
TOURISM STATISTICS 6. CONCLUDING REMARKS
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1. TOURISM IN INDONESIA
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“I declare tourism as the leading sector. Tourism as a leading sector is a good news, and all other Ministries must support tourism development”.
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The Government PRIORITY SECTOR DEVELOPMENT Annual Work Plan 2017:
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Source: Statistics Indonesia & MoT of Indonesia, 2017
INDONESIA’S FOREIGN EXCHANGE RECEIPTS BASED ON BUSINESS FIELD
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No 2013 2014 2015 2016
Commodity Value (mio USD) Commodity Value
(mio USD) Commodity Value (mio USD) Commodity Value
(mio USD) 1 Oil & Gas 32,633 Oil & Gas 30,318 Oil & Gas 18.574 CPO 15,965
2 Coal 22,759 Coal 18.697 CPO 16.427 Tourism*) 13.568 3 CPO 16,787 CPO 18.615 Coal 14.717 Oil & Gas 13,105
4 Tourism 10,054 Tourism 11,166 Tourism 12,225 Coal 12,898
5 Rubber 6,706 Clothes 7,450 Clothes 6.410 Clothes 6,229
6 Clothes 6,216 Electrical Equipment 7,021
Electrical Equipment 4.510 Electrical Equipment 4,561
7 Electrical Equipment 5,104 Chemicals 6,486 Rubber 3.564 Jewelry 4,119
8 Chemicals 4,124 Rubber 6,259 Paper 3.546 Paper 4,032
9 Paper 3,723 Paper 5,379 Jewelry 3.319 Chemicals 3,700
10 Textile 1,948 Jewelry 3,914 Chemicals 3.174 Rubber 3,242
11 Wood 1,203 Textile 3,853 Textile 1.927 Textile 1,848
12 Jewelry 202 Wood 3,780 Wood 1.352 Wood 1,279
*) Pleniminary
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Source: R&D Department, 2014
PROJECTED FOREIGN EXCHANGE RECEIPTS FROM KEY SECTORS IN INDONESIAN ECONOMY “In 2020, tourism sector will be the largest contributor to Indonesia’s Revenue”
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INDONESIA’S FOREIGN EXCHANGE RECEIPTS
0
5
10
15
20
25
2015 2016 2017 2018 2019
Oil & Gas Coal Tourism CPO Rubber
Bill
ion
USD
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Source: Indonesia Statistics, 2017 8
INTERNATIONAL TOURIST ARRIVALS 2017 Until August 2017, ITA to Indonesia has reach more than 9.2 Million arrivals. Compare to the same period last year it was growth +25.68%, and the target achievement was 108.77%.
Period PERFORMANCE ACHIEVEMENT
Month on Month Year on Year Month on Month Year on Year 2016 2017 2017 2016 2017 2017 Target Growth Target Growth
Jan 814,303 1,032,930 26.85% 814,303 1,032,930 26.85% 900,000 114.77% 900,000 114.77% Feb 888,309 957,583 7.80% 1,702,612 1,990,513 16.91% 900,000 106.40% 1,800,000 110.58% Mar 915,019 1,066,588 16.56% 2,617,631 3,057,101 16.79% 1,000,000 106.66% 2,800,000 109.18% Apr 901,095 1,142,180 26.75% 3,518,726 4,199,281 19.34% 1,000,000 114.22% 3,800,000 110.51% May 915,206 1,150,067 25.66% 4,433,932 5,349,348 20.65% 1,100,000 104.55% 4,900,000 109.17% Jun 857,651 1,111,616 29.61% 5,291,583 6,460,964 22.10% 1,100,000 101.06% 6,000,000 107.68% Jul 1,032,741 1,379,961 33.62% 6,324,324 7,840,925 23.98% 1,200,000 115.00% 7,200,000 108.90%
Aug 1,031,986 1,404,664 36.11% 7,356,310 9,245,589 25.68% 1,300,000 108.05% 8,500,000 108.77% Sep 1,006,653 8,362,963 1,400,000 Oct 1,040,651 9,403,614 1,600,000 Nov 1,002,333 10,405,947 1,700,000 Dec 1,113,328 11,519,275 1,800,000
Total 11,519,275 9,245,589 15,000,000
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2. WHY BIG DATA
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What is Big Data?
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3V of Big Data a. High Velocity, fast b. Huge in Volume c. HighVariety
Source: Eurostat (2016)
Big Data is extremely large volume of data, wide variety of data and high velocity of data, thus it needs specific technical architecture and analytical method to gain insight that gives new value to the business. Big data is often associated with 3Vs, whereby the definition of Big Data is not only
in terms of large volume of data, but also other indicators. Others 4Vs : Veracity, Visualization, Variability, and Value
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The Value of Big Data
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Creating Value from All Data
Leveraging Emerging Technology & Complete Analytics Value Chain
Actionable Insights; Hidden Inefficiencies
Business Growth through Continous Data-Driven Innovation
Paradigm Shift
Pattern Recognition
Stakeholder Value
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The Importance of Big Data
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Big data is changing the way people within organizations work together. Insights from big data can enable all employees to make better decisions—deepening customer engagement, optimizing operations, preventing threats and fraud, and capitalizing on new sources of revenue.
COMPETITIVE ADVANTAGE
Data is emerging as the world’s newest resource for competitive advantage
DECISION MAKING
Decision making is moving from the elit few to the empowered many
VALUE OF DATA As the Value of data continues to grow, current systems won’t keep pace
Source : http://www.gartner.com/it-glossary/big-data, https://www.ibm.com/big-data/us/en/,
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The Digital World
7.4 Billion World Population 3.7 Billion Internet Users 2.7 Billion Active SocMed Users 8 Billion Mobile Phone Subscribers 2.5 Billion Active Mobile Social Users
262 Million of Population 132.7 Million Internet Users 106 Million Active SocMed Users 371.4 Million Mobile Phone Subscribers 92 Million Active Mobile Social Users
Source : We Are Social, Hootsuite 2017
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Hyperconnected Society
When hang out with friends…
When on a date… When on sightseeing…
When on the beach… When watching the game…
When having the meals…
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Hyperconnected Society People Transform to
Hyperconnected Society
Global Player as DOMINANT PLAYER INDONESIA as a MARKET
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Trend in Industry
OLD WORLD
NEW WORLD
Single Supply-Demand
Visible Enemy
Time Series & Linier
Invisible Enemy
Real time & Exponential
Supply-Demand Network
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Tren in Industry
Buying Owning
Taking over ASET
Owning The
ASET
Capital Expenditure
Idle Capacity
Collaborating ASET
ASET is not
required
Optimizing Idle Capacity
Access to the ASET
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Digital Company Value
9,8 T 12,3 T
MARKET CAP INDONESIA TRANSPORTATION COMPANY BY 2016
Product (Service) Conventional
20 T 38 T *
Product (Service) Distruption
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Big Company is Now Digital Company
90’s – 2000’s 2017
Indonesia Football League Sponsor
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Digital Tourism? The 3T Revolution
TELECOMUNICATION + DIGITAL COMMON PLATFORM
SHARING ECONOMY
Google, Facebook, Whatsapp
TRANSPORTATION + DIGITAL COMMON PLATFORM
SHARING ECONOMY
Uber, LCC, Gojek
TOURISM + DIGITAL COMMON PLATFORM
SHARING ECONOMY
Tripadvisor, Traveloka, Travelio
*Digital Tourism Revolution is the Natural Revolution
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Digital Company Tourism
Indonesia Market OTA (Airline/Hotel) Meta Search Travel (POI) Portal Tour Package
Top Player (based on Alexa Traffic rank)
1. Traveloka 2. Tiket.com 3. Pegi-pegi
1. Tripadvisor 2. uTiket
1. Detiktravel 2. Wonderful
Indonesia
Valadoo
Business Model
• Fee/Trx • Discount • Advertising
• Fee/Pageview (Hotel) • Fee/trx (Airlines) • Advertising
• Advertising • Listing fee
Rev/Trx
Benchmark Market Value
4.Nusatrip 5.Tiket2 6.Agoda
Indonesia
4. Skyscanner 5. Wego
e-Tourism Portal
Market Cap
(US$ Bn) Reve nue EV/
EBITDA EBITDA
OTA The Priceline 62.3 8.44 18.67 3.29 Expedia Inc 12.5 5.76 16.69 0.75 Orbitz 1.3 0.9 11.14 0.14 Traveloka 1.1 0.1 Average 15.5
Metasearch Tripadvisor 11.94 1.25 31.03 0.375 Ctrip.com 8.83 1.18 -1.66 -5.31 Homeaway 3.05 0.45 38.69 0.065 Yelp Inc 3.53 0.38 129.14 0.02 Average 49.3
Offline Travel Agent (IDR Milyar) Panorama 630 1,973 7.2 144 Bayu Buana 371 1,676 3.6 48
Market Cap digital companies are much higher compared to conventional companies
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Development of Big Data for Official Statistics
Accurate vs
Speed
The Fast eats
The Slow
Public behavior changes in accesing data & information
Late (not up to date / not on the current situation) information causing ineffective & inefficiency in decision making process In-time to respond on any issues
Government Policy
Big data as a Quick response solution in Government Policy Making (Decision making process)
Eurostat (2016)
The implementation of Big Data is a Smart City (Control & Optimizing resources for public services)
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When the music changes so does the dance If we fail to listen we will be out of step
African Proverb
Professor Denise LIEVESLEY
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24 3. BIG DATA IMPLEMENTATION IN INDONESIA
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Indonesia Digital Tourism Configuration
Mobile Positioning
Data
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Input Process Output Outcomes
Traveler
Using mobile and other devices for travel (pre-trip, trip and post-trip)
TRAVELERS MOVEMENT,
BEHAVIOR AND SENTIMENT
MASSIVE OF DATA (BIG DATA)
DASHBOARD
INPU
T O
UTPU
T
INPU
T O
UTP
UT
PROCESS PROCESS Big data Analytics
Insight for better decision and better
management in Tourism Sector.
3P rojection
SUSTAINABLE TOURISM
DEVELOPMENT
OUTCOME
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The 3Ps
PERFORMANCE PROJECTION PROMOTION
Data Collection: 1. No. of International Arrivals &
Domestic Tourist 2. Travel Pattern / Tourist Movement
Identify Future Trend: 1. Destination Tourism Products
Culture, Nature, Man-made 2. Origination Customer Profiling
Frequency, LoS, SES 3. Timeline Seasonality
Effective Marketing Strategy: 1. Branding, 2. Advertising, and 3. Selling
Source: Integrated system with Immigration, Mobile Positioning Data, Secondary Statistics Data
Source: Crawling social media data, Integrated Monitoring System
Source: Crawling social media data, Secondary Statistics Data
TOURIST PEOPLE MOVEMENT
(Domestic & Foreigner)
MARKET PROFILE & TREND
COMPETITOR INTELLEGENCE
TOURIST SENTIMENT (ACCESS, AMENITIES,
ATTRACTION)
CROWD CONTROL PEOPLE READINESS
DESTINATION READINESS
MARKET PERFORMANCE
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Indonesia Tourism Intelligence
TOURIST PEOPLE MOVEMENT
(Domestic & Foreigner)
MARKET PROFILE & TREND
COMPETITOR INTELLIGENCE
TOURIST SENTIMENT (ACCESS, AMENITIES,
ATTRACTION) CROWD CONTROL
PEOPLE READINESS DESTINATION READINESS
MARKET PERFORMANCE
DASHBOARD (Int’l Tourist, Domestic Tourist, Destination Devlpmnt, Human Resources)
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HYPERCONNECTED SOCIETY CHANGE DATA SIZE
If You Can't Measure It, You Can't Manage It
- Peter Drucker -
Austrian-born American management consultant, educator, and author, whose writings contributed to the philosophical and practical foundations of the modern business corporation
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4. THE BIG DATA & THE AGENDA OF SUSTAINABLE TOURISM DEVELOPMENT IN INDONESIA
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Conventional Vs. Big Data
The information in big data is used for decision making process that required a fast response.
Budget efficency compare to the conventional data collection methods
1. Sensus vs Sampling 2. User Generated
Content (UGC) vs Guided Questions (GQ)
3. Fast & Accurate
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The Role of Big Data in Sustainable Tourism Development
People Planet
Profit
SUSTAINABLE TOURISM
PROFIT: CREATING VALUE ADDED TO THE ECONOMY PEOPLE: IMPROVING QUALITY OF LIFE PLANET: MAKING THE WORLD A BETTER PLACE
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Creating Value Added for The Economy (Profit)
During-Trip Tourist Experiences
onlineTravel Agents(OTA)
Corpo-rate
Pre/Post-Trip Tourist Experiences
distributors
demands(“always connected traveller experiences)
OnlineBooking
ElectronicDirectory
1. Airlines• domestic• international2. Hotels/villas/pondok
wisata3. Restautrants4. Car Rentals5. Show/Attractions6. Tour Package7. others : taxi, etc
1. POI• Hotels/Resto• Sightseeing• Attractions/Cultural• Spas, etc.1. Hospitals/Police St./Gas
Station/ATM, etc.2. News/Events3. Traffic/Weather
Horizontal PlatformRecommendation System, User Generated
Content, Business Intelligence, Reward Point, etc. Big Data
Analytic
Comm Svc PurchaseHot Deals
Itinerary Plan
Payment System SocMed
e-tours
e-hotel
e-resto
e-show
e-carental
e-travel
Airlines
Hotel
Restaurant
Car Rental
Show
Tou
rism
/ T
rave
l Exc
hang
e (T
TX
)suppliers
traditional & personalTravel Agents
Mobile Apps(Hi-City)
Mobile Web(Hi-Indonesia)
Tours
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Improving Quality of Life (People)
Cellular Operators
LBA
THE INDONESIA TOURISM INTELLIGENCE DASHBOARD
Tourist Flow Visitor Management The Human Resources Readiness (Quality & Quantity) Employment
The Destination Readiness Culture Based Tourist Sentiments Services, Product Preferences
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Making The World a Better Place (Planet)
Cellular Operators
LBA
THE INDONESIA TOURISM INTELLIGENCE DASHBOARD
Tourist Flow Visitor Management Tourist Sentiments Environmental, Safety & Security Crowd Management Travel Pattern Tourist
Movement & Distributions Destination Readiness Nature Based
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5. THE USE OF MOBILE POSITIONING DATA IN TOURISM STATISTICS
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Data Sources for Tourism Statistics
WAS NOW
01
02
Main Source: administrative data from the Immigration check point.
Other data source: Cross-Border Survey conducted by Statistics Agency in order to obtain tourist data at the border with limitless immigration function
Challenges: 1. Geographical Condition 2. Limited Resources 3. The outnumber access to enter
Indonesia 4. Huge Coverage Area 5. Sampling Methods
01 02 Main Source: administrative data from the Immigration check point.
Other data source: Mobile Positioning Data
The MPD is implemented at cross-border area in 25 regencies in which Immigration Check Point is not available (limitless immigration function) and the Cross-Border Survey is difficult to be
conducted due to geographical condition and the availability of resources.
UNDERESTIMATED NUMBER OF TOURIST FLOW
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The Advantages of MPD
1 2
4 3
Automatic / Machine
(No human intervention)
Wide Coverge Capture tourist traffics beyond
the border point gate
Non-Stop 24 x 7 x 52 / Continuous
Identified Length of Stay & Pattern
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Scenario of Filtering Data
Not – MPD Tourist
Gross MPD Tourist Visitor Activate Foreign IMSI
Has Been Detected in the other part of the
country (Span-Check)
Usual Environment 7/20 (7 Consecutive / 20
days accumulative) Net MPD Tourist
Combining with the nearest Immigration
Check Point Data
IMSI: International Mobile Subscriber Identity
No
No
Yes
Yes
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MPD As A Monitoring & Controlling Tools
The MPD traffics centered in cross-border doorway between Indonesia – Malaysia and Indonesia - Singapore
From Jan to Jul 2017, the MPD Traffics mostly came from cross border foreign tourist through Nunukan and Belu District
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RESULTS & IMPLICATION
Mobile Positioning Data
1. Data quality can be improved by utilizing MPD 2. Though the size of Indonesian cross-border foreign
tourist is below 5% (www.bps.go.id) of total Indonesian foreign tourists, but it promising and improving the general picture.
3. Preliminary ground check investigation indicates that MPD quite accurate to measure cross-border foreign tourists traffic
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5. CONCLUDING REMARKS
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THE CLOSING THE BIG DATA The use of Big Data in this digital era is inevitable Big Data creates opportunities to produce high-quality information which is more
details, timely, and relevant to many purposes and uses When used in planning and decision making process, Big Data will Increase
competitiveness of destinations, Enhance the tourists’ experiences, and Increase the residents’ quality of life
Big Data can be an effective tools in planning, monitoring & evaluating tourism development in sustainable way
THE MPD MPD increase the quality of tourism statistics. MPD creates opportunities for developing tools on visitor management. MPD is recommended not only to be used in tourism statistics, but also for other
sectors in related to human mobility such as: transportation, population, safety & security and other economic activities.
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THANK YOU