THE UTILISATION OF BIG DATA IN INDONESIAN TOURISM MANAGEMENT

Transcription

1 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

2 2 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

3 1. TOURISM IN INDONESIA 3

4 I declare tourism as the leading sector. Tourism as a leading sector is a good news, and all other Ministries must support tourism development. 4

5 The Government PRIORITY SECTOR DEVELOPMENT Annual Work Plan 2017: 5

6 INDONESIA S FOREIGN EXCHANGE RECEIPTS BASED ON BUSINESS FIELD No 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 CPO 15,965 2 Coal 22,759 Coal CPO Tourism*) CPO 16,787 CPO Coal 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 Clothes 6,229 6 Clothes 6,216 Electrical Equipment 7,021 Electrical Equipment Electrical Equipment 4,561 7 Electrical Equipment 5,104 Chemicals 6,486 Rubber Jewelry 4,119 8 Chemicals 4,124 Rubber 6,259 Paper Paper 4,032 9 Paper 3,723 Paper 5,379 Jewelry Chemicals 3, Textile 1,948 Jewelry 3,914 Chemicals Rubber 3, Wood 1,203 Textile 3,853 Textile Textile 1, Jewelry 202 Wood 3,780 Wood Wood 1,279 Source: Statistics Indonesia & MoT of Indonesia, 2017 *) Pleniminary 6

7 INDONESIA S FOREIGN EXCHANGE RECEIPTS PROJECTED FOREIGN EXCHANGE RECEIPTS FROM KEY SECTORS IN INDONESIAN ECONOMY In 2020, tourism sector will be the largest contributor to Indonesia s Revenue Billion USD Oil & Gas Coal Tourism CPO Rubber Source: R&D Department,

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 %, and the target achievement was %. PERFORMANCE ACHIEVEMENT Period Month on Month Year on Year Month on Month Year on Year Target Growth Target Growth Jan 814,303 1,032, % 814,303 1,032, % 900, % 900, % Feb 888, , % 1,702,612 1,990, % 900, % 1,800, % Mar 915,019 1,066, % 2,617,631 3,057, % 1,000, % 2,800, % Apr 901,095 1,142, % 3,518,726 4,199, % 1,000, % 3,800, % May 915,206 1,150, % 4,433,932 5,349, % 1,100, % 4,900, % Jun 857,651 1,111, % 5,291,583 6,460, % 1,100, % 6,000, % Jul 1,032,741 1,379, % 6,324,324 7,840, % 1,200, % 7,200, % Aug 1,031,986 1,404, % 7,356,310 9,245, % 1,300, % 8,500, % 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 Source: Indonesia Statistics,

9 2. WHY BIG DATA 9

10 What is Big Data? 3V of Big Data a. High Velocity, fast b. Huge in Volume c. HighVariety 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 Source: Eurostat (2016) 10

11 The Value of Big Data 11 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

12 The Importance of Big Data 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 :

13 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 Million Internet Users 106 Million Active SocMed Users Million Mobile Phone Subscribers 92 Million Active Mobile Social Users Source : We Are Social, Hootsuite

14 Hyperconnected Society 14 When hang out with friends When on the beach When watching the game When on a date When on sightseeing When having the meals

15 15 Hyperconnected Society People Transform to Hyperconnected Society Global Player as DOMINANT PLAYER INDONESIA as a MARKET

16 Trend in Industry 16 Time Series & Linier Real time & Exponential OLD WORLD NEW WORLD Visible Enemy Single Supply- Demand Invisible Enemy Supply- Demand Network

17 Tren in Industry 17 Buying Owning Taking over ASET Capital Expenditure Collaborating ASET ASET is not required Owning The ASET Idle Capacity Access to the ASET Optimizing Idle Capacity

18 Digital Company Value 18 MARKET CAP INDONESIA TRANSPORTATION COMPANY BY 2016 Product (Service) Conventional 9,8 T 12,3 T Product (Service) Distruption 20 T 38 T *

19 19 Big Company is Now Digital Company Indonesia Football League Sponsor 90 s 2000 s 2017

20 Digital Tourism? The 3T Revolution 20 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

21 Digital Company Tourism e-tourism Portal Market Cap digital companies are much higher compared to conventional companies Benchmark Market Value Market Cap (US$ Bn) Reve nue EV/ EBITDA EBITDA OTA The Priceline Expedia Inc Orbitz Traveloka Average 15.5 Metasearch Tripadvisor Ctrip.com Homeaway Yelp Inc Average 49.3 Offline Travel Agent (IDR Milyar) Panorama 630 1, Bayu Buana 371 1, 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 Business Model Fee/Trx Discount Advertising 4.Nusatrip 5.Tiket2 6.Agoda Indonesia 1. Tripadvisor 2. utiket Fee/Pageview (Hotel) Fee/trx (Airlines) Advertising 4. Skyscanner 5. Wego 1. Detiktravel 2. Wonderful Indonesia Advertising Listing fee Valadoo Rev/Trx 21

22 Development of Big Data for Official Statistics Accurate vs Speed The Fast eats The Slow Government Policy Public behavior changes in accesing data & information In-time to respond on any issues Late (not up to date / not on the current situation) information causing ineffective & inefficiency in decision making process Big data as a Quick response solution in Government Policy Making (Decision making process) The implementation of Big Data is a Smart City (Control & Optimizing resources for public services) Eurostat (2016) 22

23 23 African Proverb When the music changes so does the dance If we fail to listen we will be out of step Professor Denise LIEVESLEY

24 3. BIG DATA IMPLEMENTATION IN INDONESIA 24

25 Indonesia Digital Tourism Configuration 25 Mobile Positioning Data

26 Input Process Output Outcomes 26 PROCESS INPUT OUTPUT Traveler Using mobile and other devices for travel (pretrip, trip and post-trip) MASSIVE OF DATA (BIG DATA) Big data Analytics TRAVELERS MOVEMENT, BEHAVIOR AND SENTIMENT DASHBOARD INPUT OUTPUT PROCESS OUTCOME 3P rojection Insight for better decision and better management in Tourism Sector. SUSTAINABLE TOURISM DEVELOPMENT

27 The 3Ps 27 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 TOURIST PEOPLE MOVEMENT (Domestic & Foreigner) DESTINATION READINESS TOURIST SENTIMENT (ACCESS, AMENITIES, ATTRACTION) MARKET PROFILE & TREND CROWD CONTROL COMPETITOR INTELLEGENCE PEOPLE READINESS MARKET PERFORMANCE 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

28 Indonesia Tourism Intelligence 28 DASHBOARD (Int l Tourist, Domestic Tourist, Destination Devlpmnt, Human Resources) TOURIST PEOPLE MOVEMENT (Domestic & Foreigner) TOURIST SENTIMENT (ACCESS, AMENITIES, ATTRACTION) CROWD CONTROL MARKET PERFORMANCE COMPETITOR INTELLIGENCE DESTINATION READINESS PEOPLE READINESS MARKET PROFILE & TREND

29 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 29

30 4. THE BIG DATA & THE AGENDA OF SUSTAINABLE TOURISM DEVELOPMENT IN INDONESIA 30

31 Conventional Vs. Big Data 1. Sensus vs Sampling 2. User Generated Content (UGC) vs Guided Questions (GQ) 3. Fast & Accurate 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 31

32 32 The Role of Big Data in Sustainable Tourism Development People Planet PROFIT: CREATING VALUE ADDED TO THE ECONOMY SUSTAINABLE TOURISM Profit PEOPLE: IMPROVING QUALITY OF LIFE PLANET: MAKING THE WORLD A BETTER PLACE

33 Creating Value Added for The Economy (Profit) 33 suppliers demands ( always connected traveller experiences) e-hotel e-resto e-carental e-show e-tours Airlines Hotel Restaurant Car Rental Show Tou rs Tourism / Travel Exchange (TTX) Online Booking 1. Airlines domestic international 2. Hotels/villas/pondok wisata 3. Restautrants 4. Car Rentals 5. Show/Attractions 6. Tour Package 7. others : taxi, etc Hot Deals Electronic Directory 1. POI Hotels/Resto Sightseeing Attractions/Cultural Spas, etc. 1. Hospitals/Police St./Gas Station/ATM, etc. 2. News/Events 3. Traffic/Weather Itinerary Plan Comm Svc Purchase Horizontal Platform Recommendation System, User Generated Content, Business Intelligence, Reward Point, Big Data etc. Payment System SocMed Analytic Pre/Post-Trip Tourist Experiences online Travel Agents (OTA) distributors traditional & personal Travel Agents e-travel Corporate During-Trip Tourist Experiences Mobile Apps (Hi-City) Mobile Web (Hi-Indonesia)

34 Improving Quality of Life (People) 34 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

35 Making The World a Better Place (Planet) 35 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

36 5. THE USE OF MOBILE POSITIONING DATA IN TOURISM STATISTICS 36

37 37 Data Sources for Tourism Statistics 01 WAS Main Source: administrative data from the Immigration check point. NOW Main Source: administrative data from the Immigration check point. Other data source: Mobile Positioning Data 02 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 UNDERESTIMATED NUMBER OF TOURIST FLOW 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.

38 The Advantages of MPD 38 Automatic / Machine (No human intervention) 1 2 Non-Stop 24 x 7 x 52 / Continuous Wide Coverge Capture tourist traffics beyond the border point gate 3 4 Identified Length of Stay & Pattern

39 Scenario of Filtering Data 39 Visitor Activate Foreign IMSI Gross MPD Tourist Not MPD Tourist No Has Been Detected in the other part of the country (Span-Check) Yes Combining with the nearest Immigration Check Point Data No Usual Environment 7/20 (7 Consecutive / 20 days accumulative) Yes Net MPD Tourist IMSI: International Mobile Subscriber Identity

40 MPD As A Monitoring & Controlling Tools 40 From Jan to Jul 2017, the MPD Traffics mostly came from cross border foreign tourist through Nunukan and Belu District The MPD traffics centered in cross-border doorway between Indonesia Malaysia and Indonesia - Singapore

41 41 RESULTS & IMPLICATION 1. Data quality can be improved by utilizing MPD 2. Though the size of Indonesian cross-border foreign tourist is below 5% ( 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 Mobile Positioning Data

42 5. CONCLUDING REMARKS 42

43 43 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.

44 THANK YOU 44