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

“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

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

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

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

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

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

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

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

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

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

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

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