Indonesia Information Technology Report Q3 2014 Pratama provides systems integration solutions for business-to-business networking and internet. Sigma Metrasys Solution maintains SAP licences and project implementation. Strategy Sigma management has said that the company will be strengthening its core role as an IT provider for the whole banking sector. As an innovator in the Islamic banking sector, Sigma is well placed to take advantage of the growing trend in the country. While the company has a strong background in banking and financial IT, it is looking to expand into new sectors, such as autos and manufacturing. The acquisition by PT Telkom was part of the incumbent's strategy to expand its communications services into the IT sector. The merger offers opportunities for Sigma to offer a wider range of services. Products And Partnerships Sigma's flagship product is AlphaBITS, the software initially developed in 1989. It is a core banking system for day-to-day operations, connecting aspects such as delivery channels (teller and customer services) and back-office activities (accounting and general affairs). Developed as an industry-standard banking application, AlphaBITS offers integrated functionality with six main modules (kernel and security, CIF, retail, deposit, loan and general ledger). Using integrated design architecture, AlphaBITS can be incorporated with third-party applications. Sigma has been an innovator in the Islamic banking sector, as an increasing number of Indonesian individuals and companies choose to business with banking institutions that comply with shari'a principles. Sigma has capitalised on this, with its shari'a core banking system designed to follow the principles of Islamic banking. The company's services include consulting, managing IT services, software development services and integrated datacentre operations in the banking (conventional and sharia-based), financial, telecommunications, manufacturing, distribution and other sectors. Among the products offered, Sigma offers cloud computing, datacentre, telecoms managed services, software development services and systems integration. Sigma is a local partner for international IT companies including Oracle, QNX Solutions, IBM and Microsoft. In March 2013, Sigma announced a partnership with US computer technology firm IBM to improve data services. The companies will build an energy-efficient datacentre to meet the requirements of local businesses in Sentul. The project will benefit from IBM and Telkom Indonesia's previous research into resisting natural disasters, such as earthquakes, and their effects on telecoms infrastructure. In January 2014 Sigma announced it would prepare its fourth and fifth data centres in Indonesia in 2014. The data centres will be located in Balikpapan and West Java, and will be tier and centres respectively. The construction will take place through Sigma's partnership with IBM. Sigma reported that the tier data centre could enable it © Business Monitor International Page 65 Indonesia Information Technology Report Q3 2014 to introduce Disaster Recovery Services, which could be a lucrative market given Indonesia is earthquake prone. In March 2014 Sigma signed a Memorandum of Understanding (MOU) with Huawei Tech Investment for the collaboration in the creation of a wholesale data centre to serve Indonesia and its expansion efforts across Southeast Asia. Developments Company Details Following its acquisition by PT Telkom, Sigma expanded its operations and spent USD7mn on a new IT disaster recovery centre in Surabaya. It has signed an agreement with Oracle to provide outsourcing services focusing on large companies, particularly in banking and telecoms. The arrangement centres on helping large companies to focus on core businesses, while the IT partners optimise and maintain IT units. Among the recent wins for the partnership is a tender from Bussan Auto Finance, one of the leading multi-finance companies in Indonesia, to implement various Oracle applications. ■ ■ PT Sigma Citra Caraka DEA I Tower, 8th Floor Kawasan Mega Kuningan JI. Mega Kuningan Barat IX Kav. E43 No. Indonesia ■ Tel: +62 21 576 2150 ■ Fax: +62 21 576 2155 ■ Web: www.sigma.co.id © Business Monitor International Page 66 Indonesia Information Technology Report Q3 2014 Regional Overview BMI forecasts Asia Pacific will be the outperforming region in terms of IT market growth rates over the duration of our medium term forecast to 2018. This is in line with overall economic trends as the region has become an important engine of global growth. Asia is home to not only the two largest emerging markets in India and China, but also a host of rapidly developing frontier markets - making it a prime target for expansion by global vendors. The outlook is however far from homogeneous, there is a wide spread of development levels from Australia, Hong Kong and Singapore through to APAC Forecast To Outperform Annual IT Market Growth In USD (%) Indonesia, Pakistan and Sri Lanka. There is also intense competition between markets in the region vying to attract foreign expertise and investment - as well as promoting domestic industry. Low Hanging Fruit BMI forecasts outperformance for APAC over the medium term as emerging markets are in a sustained period of catch-up growth. The more developed markets in the region - Australia, Hong Kong, e/f - BMI estimate/forecast. Source: BMI. Singapore and South Korea - will not experience the same growth rates, underperforming emerging Asia. This is because in several key product categories these markets are already mature, including retail hardware (desktops, notebook and tablets), as well as enterprise software deployments. However, in emerging Asia there is scope for rapid medium term growth as incomes rise and device prices continue to decline. Whereas developed markets took several decades to reach high levels of IT product and solution penetration among consumers, enterprises and the public sector, in emerging markets this transition is expected to be much faster due to price erosion increasing affordability, and lessons learned from early developers in terms of policy and best practice. © Business Monitor International Page 67 Indonesia Information Technology Report Q3 2014 The area catch-up growth will be most visible is in the retail hardware market where the rapid decline in notebook prices over the past decade, and in tablets since 2012, has deepened the market considerably even before income growth is factored in. Looking ahead, with Microsoft reducing Windows licensing costs for low-end devices, and Android partner vendors competing aggressively on price, effectively commoditising the low-and-mid end of the tablet market, we see the foundation for a significant broadening of device ownership rates over the medium term. Less visible but equally important is the continued investment in IT solutions by enterprises and government. Enterprise modernisation through APAC PC Browsing Traffic By OS (%) And Y-o-Y Change March 2014 informatisation is being promoted by governments across the region in order to improve competitiveness, driving basic ERP deployments and other efficiency saving solutions. Meanwhile, in the public sector government's are utilising the latest e-government and service delivery enhancing solutions, leapfrogging the legacy infrastructure in more developed markets. A development that could drive spending growth even higher is the upgrade spending on operating systems as Microsoft withdraws support for XP from 2014. The magnitude of contribution to spending growth is uncertain, but with the latest Statcounter data Source: Statcounter. showing 23.6% of APAC browsing traffic came from devices running XP there is certainly scope for a wave of upgrades in enterprises and public administration. Strong demand in emerging Asia Pacific markets from the retail, enterprise and public sectors will combine to ensure the region is the outperformer over the medium term. Competing Clouds Another area where Asia has an attractive outlook in part because of lower development levels is in cloud computing. The lower level of legacy on-site enterprise and infrastructure deployments makes the region fertile ground for rapid cloud adoption. Furthermore, the pricing models of cloud services are well suited to © Business Monitor International Page 68 Indonesia Information Technology Report Q3 2014 modernising enterprises that are likely to have less complex requirements and lack the resources for on-site deployments. The cloud computing market in emerging Asia Pacific will continue to be weighted towards less complex services over the medium term, but adoption rates are forecast to increase markedly. Data Boom Driving Cloud Demand APAC Mobile Data Volume Forecast (TB per Month) This has attracted major international investment right across the region - for instance companies such as Google, NetSuite, Salesforce, RightNow, Oracle and Zoho have already established their presence in the Indonesian market primarily through channel partners. Meanwhile, international brand names that have entered the Thai market include Amazon Web Services, NTT Communications, Adobe and Google - facing local competition from TRUE Internet Data Centre, CAT, DTAC and TOT. Finally, in the Philippines local telecoms operators have made major investments in datacentre capacity, Source: Cisco VNI 2014 with PLDT announcing in March 2014 that it will spend PHP3bn on the construction of two new data centres, one in metropolitan Makati and a second, to be opened in 2015, in Paranaque. Its data centres business grew by 60% in 2013 and the new facilities will continue that growth momentum. While the focus in emerging Asia will be on low-level deployments, there is also a dynamic of competition between developed markets in the region vying to be regional centres for cloud services and other emerging technologies. The competition between Hong Kong and Singapore to become regional cloud computing hubs is well known, with large scale inward investment both to tap demand from the large and lucrative financial sectors and to serve as a base for service provision across the region. For instance, in Q114 Pacnet and Digital Ocean opened new data centre facilities in Singapore, with both firms stating that regional opportunities were behind the choice of Singapore as a location for data centres. Meanwhile, Hong Kong has attracted investment from global leaders such as NTT Communications, Savvis, IBM and Rackspace. There is however also competition in Asia to position as hubs for emerging technologies such as big data analytics. For instance In March 2014 the South Korean Science, ICT and Future Planning Ministry © Business Monitor International Page 69 Indonesia Information Technology Report Q3 2014 announced it would inject KRW4.9trn (US$4.6bn) in information infrastructure in 2014. The ministry will invest KRW3.9trn in 786 projects headed by government bodies, with a further KRW978bn invested in 5,990 projects by provincial authorities. Key areas targeted for investment in 2014 include KRW302bn for cyber security, KRW68bn for mobile technologies and KRW243bn for Internet of Things (machine-tomachine communications). However, South Korea is some way behind Singapore. In August 2013, the Infocomm Development Authority of Singapore (IDA) partnered with Revolution Analytics, a commercial provider of software, services and support for the open source 'R' project, to form a business analytics centre of excellence. The centre will operate as a channel through which local companies can reach the expertise of global organisations to develop new solutions. The IDA's efforts are likely to help Singaporean enterprises use big data, and lay the foundations for expanding across the region. The opportunity in data analytics is huge, with 80% of enterprises surveyed by EMC stating that use of big data will lead to better decision making in their organisation. The survey, released in September 2013, questioned 130 respondents, of which 63% believed that big data will be a key factor determining winners and losers, while 37% stated they had already benefited from competitive advantage via the use of big data. The areas respondents believed big data will prove most beneficial were data centre automation (83%) and cyber security (64%). While the outperformance of Asia in terms of market growth will primarily be underpinned by low-hanging fruit and catch-up growth, there is also significant activity at the technological frontier that means emerging technologies are also expected to be an important component of the medium term growth story. © Business Monitor International Page 70 Indonesia Information Technology Report Q3 2014 Demographic Forecast Demographic analysis is a key pillar of BMI's macroeconomic and industry forecasting model. Not only is the total population of a country a key variable in consumer demand, but an understanding of the demographic profile is key to understanding issues ranging from future population trends to productivity growth and government spending requirements. The accompanying charts detail Indonesia's population pyramid for 2013, the change in the structure of the population between 2013 and 2050 and the total population between 1990 and 2050, as well as life expectancy. The tables show key data points from these charts, in addition to important metrics including the dependency ratio and the urban/rural split. Population Pyramid 2013 (LHS) And 2013 Versus 2050 (RHS) Source: World Bank, UN, BMI © Business Monitor International Page 71 Indonesia Information Technology Report Q3 2014 Population Indicators Population (mn, LHS) And Life Expectancy (years, RHS), 1990-2050 Source: World Bank, UN, BMI Table: Indonesia's Population By Age Group, 1990-2020 ('000) 1990 1995 2000 2005 2010 2013e 2015f 2020f 178,633 194,113 208,939 224,481 240,676 249,866 255,709 269,413 0-4 years 21,905 21,572 21,029 22,729 25,074 23,869 22,804 22,101 5-9 years 22,098 21,680 21,398 22,410 24,067 24,920 24,936 22,695 10-14 years 21,051 22,064 21,633 22,212 22,651 23,394 23,988 24,864 15-19 years 19,614 20,914 21,976 21,454 20,780 21,697 22,506 23,848 20-24 years 17,770 19,329 20,708 20,276 19,750 20,062 20,541 22,271 25-29 years 15,424 17,489 19,076 20,214 21,225 20,156 19,500 20,301 30-34 years 12,983 15,169 17,250 18,546 19,763 20,769 20,982 19,286 35-39 years 9,960 12,734 14,940 16,737 18,456 19,084 19,527 20,757 40-44 years 7,789 9,715 12,489 14,536 16,502 17,585 18,194 19,278 45-49 years 7,216 7,529 9,446 11,782 14,035 15,356 16,178 17,871 50-54 years 6,535 6,878 7,222 9,355 11,557 12,797 13,626 15,746 55-59 years 5,369 6,095 6,467 7,491 8,606 10,024 11,041 13,063 60-64 years 4,130 4,846 5,557 5,809 6,155 7,136 8,010 10,328 65-69 years 2,850 3,543 4,210 4,467 4,683 5,068 5,496 7,193 70-74 years 1,921 2,251 2,841 3,168 3,469 3,698 3,888 4,609 Total © Business Monitor International Page 72 Indonesia Information Technology Report Q3 2014 Indonesia's Population By Age Group, 1990-2020 ('000) - Continued 1990 1995 2000 2005 2010 2013e 2015f 2020f 75-79 years 1,221 1,330 1,585 1,791 1,987 2,328 2,556 2,900 80-84 years 579 687 761 1,100 1,349 1,235 1,196 1,569 85-89 years 179 233 282 319 470 564 592 540 90-94 years 35 46 61 75 87 112 132 171 95-99 years 12 12 14 22 100+ years e/f = BMI estimate/forecast. Source: BMI, World Bank, UN Table: Indonesia's Population By Age Group, 1990-2020 (% of total) 1990 1995 2000 2005 2010 2013e 2015f 2020f 0-4 years 12.26 11.11 10.06 10.13 10.42 9.55 8.92 8.20 5-9 years 12.37 11.17 10.24 9.98 10.00 9.97 9.75 8.42 10-14 years 11.78 11.37 10.35 9.89 9.41 9.36 9.38 9.23 15-19 years 10.98 10.77 10.52 9.56 8.63 8.68 8.80 8.85 20-24 years 9.95 9.96 9.91 9.03 8.21 8.03 8.03 8.27 25-29 years 8.63 9.01 9.13 9.00 8.82 8.07 7.63 7.54 30-34 years 7.27 7.81 8.26 8.26 8.21 8.31 8.21 7.16 35-39 years 5.58 6.56 7.15 7.46 7.67 7.64 7.64 7.70 40-44 years 4.36 5.00 5.98 6.48 6.86 7.04 7.12 7.16 45-49 years 4.04 3.88 4.52 5.25 5.83 6.15 6.33 6.63 50-54 years 3.66 3.54 3.46 4.17 4.80 5.12 5.33 5.84 55-59 years 3.01 3.14 3.10 3.34 3.58 4.01 4.32 4.85 60-64 years 2.31 2.50 2.66 2.59 2.56 2.86 3.13 3.83 65-69 years 1.60 1.83 2.01 1.99 1.95 2.03 2.15 2.67 70-74 years 1.08 1.16 1.36 1.41 1.44 1.48 1.52 1.71 75-79 years 0.68 0.69 0.76 0.80 0.83 0.93 1.00 1.08 80-84 years 0.32 0.35 0.36 0.49 0.56 0.49 0.47 0.58 85-89 years 0.10 0.12 0.14 0.14 0.20 0.23 0.23 0.20 90-94 years 0.02 0.02 0.03 0.03 0.04 0.04 0.05 0.06 95-99 years 0.00 0.00 0.00 0.00 0.00 0.00 0.01 0.01 © Business Monitor International Page 73 Indonesia Information Technology Report Q3 2014 Indonesia's Population By Age Group, 1990-2020 (% of total) - Continued 100+ years 1990 1995 2000 2005 2010 2013e 2015f 2020f 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 e/f = BMI estimate/forecast. Source: BMI, World Bank, UN Table: Indonesia's Key Population Ratios, 1990-2020 Dependent ratio, % of total working age Dependent population, total, '000 Active population, % of total Active population, total, '000 1990 1995 2000 2005 2010 2013e 2015f 2020f 67.3 60.8 54.6 53.5 53.5 51.7 50.3 47.4 71,844 73,413 73,807 78,280 83,848 85,201 85,603 86,665 59.8 62.2 64.7 65.1 65.2 65.9 66.5 67.8 106,790 120,700 135,132 146,201 156,828 164,665 170,106 182,749 Youth population, % of total working age 60.9 54.1 47.4 46.1 45.8 43.8 42.2 38.1 65,054 65,316 64,060 67,351 71,792 72,183 71,728 69,660 Pensionable population, % of total working age 6.4 6.7 7.2 7.5 7.7 7.9 8.2 9.3 Pensionable population, total, '000 6,789 8,097 9,747 10,929 12,057 13,018 13,875 17,005 Youth population, total, '000 e/f = BMI estimate/forecast. Source: BMI, World Bank, UN Table: Indonesia's Rural And Urban Population, 1990-2020 1990 1995 2000 2005 2010 2013e 2015f 2020f Urban population, % of total 30.6 35.6 42.0 45.9 49.9 52.2 53.7 57.2 Rural population, % of total 69.4 64.4 58.0 54.1 50.1 47.8 46.3 42.8 Urban population, total, '000 54,633 69,015 87,758 103,120 120,155 130,453 137,400 154,123 Rural population, total, '000 124,000 125,098 121,180 121,361 120,521 119,412 118,309 115,290 e/f = BMI estimate/forecast. Source: BMI, World Bank, UN © Business Monitor International Page 74 Indonesia Information Technology Report Q3 2014 Methodology Industry Forecast Methodology BMI's industry forecasts are generated using the best-practice techniques of time-series modelling and causal/econometric modelling. The precise form of model we use varies from industry to industry, in each case being determined, as per standard practice, by the prevailing features of the industry data being examined. Common to our analysis of every industry is the use of vector autoregressions. They allow us to forecast a variable using more than its own history as explanatory information. For example, when forecasting oil prices, we can include information about oil consumption, supply and capacity. When forecasting for some of our industry sub-component variables, however, using a variable's own history is often the most desirable method of analysis. Such single-variable analysis is called univariate modelling. We use the most common and versatile form of univariate models: the autoregressive moving average model (ARMA). In some cases, ARMA techniques are inappropriate because there is insufficient historic data or data quality is poor. In such cases we use either traditional decomposition methods or smoothing methods as a basis for analysis and forecasting. We mainly use OLS estimators and in order to avoid relying on subjective views and encourage the use of objective views, BMI uses a 'general-to-specific' method. BMI mainly uses a linear model, but simple nonlinear models, such as the log-linear model, are used when necessary. During periods of 'industry shock', for example poor weather conditions impeding agricultural output, dummy variables are used to determine the level of impact. Effective forecasting depends on appropriately selected regression models. BMI selects the best model according to various different criteria and tests, including but not exclusive to: ■ R2 tests explanatory power; adjusted R2 takes degree of freedom into account; ■ Testing the directional movement and magnitude of coefficients; ■ Hypothesis testing to ensure coefficients are significant (normally t-test and/or P-value); ■ All results are assessed to alleviate issues related to auto-correlation and multi-collinearity;. © Business Monitor International Page 75 Indonesia Information Technology Report Q3 2014 BMI uses the selected best model to perform forecasting. Human intervention plays a necessary and desirable role in all of BMI's industry forecasting. Experience, expertise and knowledge of industry data and trends ensure analysts spot structural breaks, anomalous data, turning points and seasonal features where a purely mechanical forecasting process would not. Sector-Specific Methodology A number of criteria drive our forecasts for each IT variable. IT forecasting is complicated due to the fragmented nature of the market, with little transparency of vendor data and low apparent agreement between many sets of figures in terms of market definition, base and methodology. In addition, forecasts are affected by consideration of a variety of internal and external political and economic factors. Within best-practice techniques of time-series modelling, our quarterly updated forecasts are improved substantially by intimate knowledge of the prevailing features of each local market. Individual variables taken into account in creating each forecast include: ■ Overall economic context, and GDP and demographic trends; ■ Underlying 'information society' trends; ■ Projected GDP share of industry; ■ Maturity of market structure; ■ Regulatory developments and government policies; ■ Developments in key client sectors such as telecommunications, banking and e-government; ■ Technological developments and diffusion rates; ■ Exogenous events. Estimates are calculated using our own macroeconomic and demographic forecasts. Sources Additional sources used in IT reports include national ministries and ICT regulatory bodies, national industry associations, and international industry organisations such as the International Telecommunication © Business Monitor International Page 76 Indonesia Information Technology Report Q3 2014 Union (ITU), officially released company results and figures, and international and national industry news agencies. Risk/Reward Ratings Methodology BMI's Risk/Reward Ratings (RRR) provide a comparative regional ranking system evaluating the ease of doing business and the industry-specific opportunities and limitations for potential investors in a given market. The RRR system divides into two distinct areas: Rewards: Evaluation of sector's size and growth potential in each state, and also broader industry/state characteristics that may inhibit its development. This is further broken down into two sub categories: ■ Industry Rewards (an industry-specific category taking into account current industry size and growth forecasts, the openness of market to new entrants and foreign investors, to provide an overall score for potential returns for investors). • Country Rewards (a country-specific category, factoring in favourable political and economic conditions for the industry). Risks: Evaluation of industry-specific dangers and those emanating from the state's political/economic profile that call into question the likelihood of anticipated returns being realised over the assessed time period. This is broken down into two sub categories: ■ Industry Risks (an industry-specific category whose score covers potential operational risks to investors, regulatory issues inhibiting the industry and the relative maturity of a market). • Country Risks (a country-specific category in which political and economic instability, unfavourable legislation and a poor overall business environment are evaluated to provide an overall score). We take a weighted average, combining industry and country risks, or industry and country rewards. These two results in turn provide an overall Risk/Reward Rating, which is used to create our regional ranking system for the risks and rewards of involvement in a specific industry in a particular country. For each category and sub-category, each state is scored out of 100 (100 being the best), with the overall Risk/Reward Rating a weighted average of the total score. As most of the countries and territories evaluated are considered by BMI to be 'emerging markets', our rating is revised on a quarterly basis. This ensures the rating draws on the latest information and data across our broad range of sources, and the expertise of our analysts. © Business Monitor International Page 77 Indonesia Information Technology Report Q3 2014 Sector-Specific Methodology In constructing these ratings, the following indicators have been used. Almost all indicators are objectively based. Table: It Risk/Reward Ratings Indicators Indicator Rationale Rewards Industry IT market value, US$bn Denotes breadth of IT market. Large markets score higher than smaller ones. Sector value growth, % year-on-year (y-o-y) Denotes sector dynamism. Scores based on annual average growth over five-year forecast period. Government initiatives and spending Denotes spending boost provided by public sector, which can be a crucial determinant of sector development. Hardware, % of total sales Denotes maturity of market. A high proportion of hardware sales, compared to services/ software, indicates that the overall IT market is immature. Country Urban-rural split Urbanisation is used as a proxy for development. Mainly rural states score lower. GDP per capita, US$ A high GDP per capita supports long-term industry prospects. Overall score for Country Rewards is also affected by the coverage of the power transmission network across the state. Risks Industry Intellectual property (IP) laws Markets with fair and enforced IP regulations score higher than those with endemic counterfeiting. ICT policy Subjective evaluation of official policy towards IT development, as enshrined in statute and tax code. Country Short-term external risk Rating from BMI's Country Risk Ratings (CRR). It evaluates the vulnerability to external shock, which is the principal cause of economic crises. Such a crisis would cut investment. Short-term financial risk Rating from CRR, to denote risk of currency crisis and stability of banking sector. The former would hit revenues in hard currency, while the latter would curtail investment funding. Trade bureaucracy Rating from CRR to denote ease of trading with the state. Legal framework Rating from CRR denotes the strength of legal institutions in each state - security of investment can be a key risk in some emerging markets. Bureaucracy Rating from CRR denotes ease of conducting business in the state. Corruption Rating from CRR denotes the risk of additional illegal costs/possibility of opacity in tendering/business operations affecting companies' ability to compete. Source: BMI © Business Monitor International Page 78 Indonesia Information Technology Report Q3 2014 Weighting Given the number of indicators/datasets used, it would be wholly inappropriate to give all sub-components equal weight. The following weighting has been adopted: Table: Weighting Of Components Component Rewards Weighting, % 70, of which - Industry 65 - Country 35 Risks to 30, of which - Industry 40 - Country 60 Source: BMI © Business Monitor International Page 79 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. [...]... Monitor International Page 17 Indonesia Information Technology Report Q3 2014 Industry Forecast Table: IT Industry - Historical Data And Forecasts (loccur mn) (Indonesia 2011-2018) Country 2011 2012 2013e 2014f 2015f 2016f 2017f 2018f 47968081 56285746 63884322 71748482 80953812 0.7 0.7 0.7 0.7 0.7 0.7 0.7 0.7 Indonesia IT market value, IDRmn Indonesia IT market value, % of GDP Indonesia Computer hardware... International Page 32 Indonesia Information Technology Report Q3 2014 Market Overview Hardware BMI forecasts the hardware market in Indonesia will reach a value of IDR50.5trn in 2014, an increase of 11.3% from 2013 Increased demand from both the retail and enterprises is expected to drive growth in 2014, with demand for tablets and hybrids expected to be particularly strong The Indonesian hardware market... services spending is expected to increase from IDR12.3trn to IDR20.8trn Indonesia GVA By Sector (%) 2014f f - BMI forecast Source: BMI, National Statistics, World Bank, UN © Business Monitor International Page 23 Indonesia Information Technology Report Q3 2014 Wireline Table: Telecoms Sector - Wireline - Historical Data & Forecasts (Indonesia 2011-2018) 2011 Main telephone lines in service, '000 Main... towards Indonesia' s long term economic growth prospects Given the nature of Indonesian politics where the personality is more important than party politics, Jokowi stands a good chance of being able to canvass strong enough public support in order to push through such unpopular but necessary reforms © Business Monitor International Page 28 Indonesia Information Technology Report Q3 2014 Table: Indonesia. .. Business Monitor International Page 14 Indonesia Information Technology Report Q3 2014 Economic SWOT Analysis Strengths ■ Indonesia' s strategic location between the Indian and Pacific Oceans and its adjacency to major east-west trade routes make it an important economy in the region Indonesia is also resource-rich and is the world's largest producer of palm oil ■ Indonesia has a low cost and large supply... Indonesia Information Technology Report Q3 2014 2014 Outlook BMI considers the overall economic environment to be conducive for IT market expansion in 2014 However currency weakness will weigh on sales Industry Trends - IT Market 2011-2018 despite the announcement from several leading vendors that they will absorb some of the potential impact on prices BMI forecasts 5.4% real GDP growth in 2014 and... Telkom and Microsoft launched cloud services in Indonesia, driving the development of the market by offering new services and increasing levels of education among customers about potential uses © Business Monitor International Page 22 Indonesia Information Technology Report Q3 2014 Summary The value of the hardware market is predicted to grow from IDR50.5trn in 2014 to IDR77.7trn in 2018, with PC sales (including... resumption of the Cepu field, which occurred in late 2009, may help to alleviate Indonesia' s dependence on foreign oil given its small boost to production output, but we expect this bounce to be short-lived © Business Monitor International Page 15 Indonesia Information Technology Report Q3 2014 SWOT Analysis - Continued ■ Indonesia is perceived as one of Asia's riskier destinations This leaves the economy... connections in Indonesia to reach 11.9mn by 2018, representing a penetration rate of 4.5% © Business Monitor International Page 25 Indonesia Information Technology Report Q3 2014 Macroeconomic Forecasts Economic Analysis BMI View: Current Jakarta governor Joko Widodo's (Jokowi) runaway favourite tag for the presidential elections leads us to believe that it may not be too premature to deliberate Indonesia' s... to believe that it may not be too premature to deliberate Indonesia' s economic trajectory under a Jokowi-led administration Below, we highlight three sectors that could witness upside potential if and when Jokowi assumes the presidency © Business Monitor International Page 26 Indonesia Information Technology Report Q3 2014 The Jokowi Effect Indonesia - Jakarta Stock Exchange Index Source: Bloomberg . Q3 2014 www.businessmonitor.com INDONESIA INFORMATION TECHNOLOGY REPORT INCLUDES 5-YEAR FORECASTS TO 2018 ISSN 1750-5070 Published by:Business Monitor International Indonesia Information Technology Report. 12.4% 2014- 2018, with Indonesia& apos;s IT market reaching a total value of IDR114.6trn in 2018. Indonesia Information Technology Report Q3 2014 © Business Monitor International Page 18 2014 Outlook BMI. 78 Table: Weighting Of Components 79 Indonesia Information Technology Report Q3 2014 © Business Monitor International Page 5 BMI Industry View BMI View: the Indonesian IT market is forecast to