Kadin Indonesia-Jetro, 2006 1 www.kadin-indonesia.or.id SME CAPACITY BUILDING IN INDONESIA
Tulus Tambunan
Kadin Indonesia –JETRO, May 2006 Recent Development
In Indonesia, small and medium enterprises (SMEs) have historically been main player in domestic economic activities, especially as a large provider of employment opportunities, and hence a generator of primary or secondary source of income for many households. For low income or poor farm households in rural areas, SEs, i.e. units of less than 20 workers, in non-farm activities are especially important. These enterprises have also been playing as an important engine for the development of local economies and communities. However, as compared to many other APEC more developed economies, Indonesian SMEs are not yet been proved to have contributed significantly their value added to the country’s economy. Instead, they have been more important as the locus of most employment than of gross domestic product (GDP) growth in Indonesia.
In the last few years, the Indonesian government has recognized the importance of having modern SMEs as an important element in creating a sophisticated economy, especially through their role in developing inter-industry linkages, or as supporting industries producing components and parts for large enterprises (LEs) either, via market mechanisms or subcontracting systems or other forms of production linkages. In developed countries, it is the role of SMEs to act as suppliers to industries producing final goods, therefore creating a permanent, vibrant and inter-linked industrial base. Indonesia has suffered from the lack of a sophisticated domestic supplier network, which would have allowed intermediate inputs, components, and parts to being produced locally instead of being imported (Banerjee, 2002). 1
Also recently, the SMEs as a group in the country has been recognized to have another important role to play, namely as an important engine for development and growth of exports of non-oil and gas, particularly in manufacture. This stems from evidence showing that the most successful cases of SMEs development in East and Southeast Asian countries like South Korea, Taiwan, Hong Kong, and Singapore, have directly related to trade and the adoption of
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Kadin Indonesia-Jetro, 2006 2 www.kadin-indonesia.or.id export-oriented strategies. The experiences of these countries indicate that SMEs can compete effectively in both domestic and international.2
Last, but not least, SMEs could also play a powerful role in energizing agriculture through the development of high competitive agricultural-based (agro) industry. Agricultural-based production is a clear area where the country has enormous room for development, simply because Indonesia is a large agrarian economy owning a huge variety of agricultural commodities. Unfortunately, until know this country’s potential has not yet been exploited very well, as compared to its regional and international counterparts. Even, in the last few years Indonesia has become an important importing country for many agricultural commodities including rice and a variety of vegetables and fruits.3
The importance of SMEs for the Indonesian economy is observable reflected by their relatively huge number of units. Indeed, a significant feature of the Indonesian economy is the domination by this category of enterprises, in particular small enterprises (SEs). Totally, in all sectors of the economy, the number of SMEs is huge and it keeps growing; though there was a decline during the 1997 economic crisis. Their number of units is larger than that of LEs. Especially SEs can be found in all over the country, in urban as well as rural areas. Such entities contribute the bulk of units and employment in sectors such as agriculture, trade, manufacturing industry and transportation.
SEs’ continuing role as the locus of most employment in Indonesia is reflected in the fact that in 1997, SEs contributed more than 39.7 million units, or constituted about 99.8% of all business units in that year, and there were an estimated more than 40 million units in 2001 (Table 1). In 1998, as the economic crisis has had a devastating impact on almost all economic sectors in the country, many companies from all sizes went bankrupt. Based on data from Menegkop & UKM, there was an estimated almost 3 million SEs were out of business, and the number of MEs (medium enterprises) and LEs declined by respectively 14.2% and 12.7%. In 2000, there were about 38.99 million units of SEs with average annual sales of less than Rp.1 billion per unit, or accounted for about 99.85% of total number of enterprises in Indonesia. In the same year, there were 55,061 units of MEs, with annual sales in the range of more than Rp. 1 billion and less than Rp. 50 billions, or accounted for 0.14% of all firms. In 2001, the total number of SEs was predicted to increase to more than 40
2
Chapter VI presents recent data on export performance of Indonesian SMEs.
3
million units, whereas MEs to about 57.7 thousand units.
Table 1. Total Enterprises by Size Category
Size Category 1997 1998 1999 2000 2001
∑ SEs 39,704,661 36,761,689 37,804,536 38,985,072 40,137,773
∑ MEs 60,449 51,889 51,798 55,061 57,743
∑ LEs 2,097 1,831 1,832 1,946 2,095
Total 39,767,207 36,815,409 37,858,166 39,042,079 40,197,611 Source: Menegkop & UKM
The importance of SMEs in Indonesia in terms of GDP contribution is always less than their role as a source of employment. Official data from Menegkop & UKM show that in real terms, GDP of SEs in 1997 was 38%. In 1998, when the crisis reached its worst level with the economic growth of minus 13%, output contribution of SE to the formation of real GDP rose slightly to a level of almost 41%; though in nominal value it declined. In 1999, the share increased to about 41.3%, and after that in 2000, it declined again slightly to 40.4%. During the crisis period (1997-1998), the growth rate of total SEs’ output was minus 19.3%, and after the crisis (1998-2000), they performed much better, though the average growth rate per year was still negative of about 2.5%. The largest GDP contribution of SEs was in agriculture, not in manufacturing industry. Again, as shown before by other indicators, this is reflected in the fact that these enterprises traditionally are strong in agricultural production; not yet in industrial production as their counterparts in other APEC economies like Japan, South Korea, and Taiwan.
[image:3.595.144.472.607.707.2]Recent data from BPS on distribution of GDP by size group of enterprises for the period 2000-2003, indicate that SMEs performed relatively better than their larger counter-parts. As illustrated in Figures 1 and 2, GDP share of SEs during that period increased from 39.7% in 2000 to about 41% in 2003. Whereas, the role of MEs in the formation of GDP was relative stable in around 15%, and that of LEs fell from about 45.5% to 43%.
Figure 1 Distribution of GDP by Size Group of Enterprises: 2003 (%)
SE, 39.74
ME, 14.77 LE, 45.49
Figure 2 Distribution of GDP by Size Group of Enterprises: 2003 (%)
SE, 41.11
ME, 15.61 LE, 43.28
Source: BPS.
[image:4.595.145.431.91.181.2]The report also gives some information about GDP contributions of different size groups of enterprises by sector, which shows that SEs still keep their advantages in local resource-based and labor intensive sectors, such as agriculture and trade, hotels, and restaurants (Table 2). Their GDP contributions on average from these two sectors during that period under review were more than 75%. The GDP contribution of MEs was concentrated in various tertiary sector, with the biggest share found in finance, rent and service sector. Whereas, the share of GDP contribution of LEs was found heavily in mining, manufacturing industry and electricity, gas and clean water supply sectors.
Table 2 Structure of GDP by size and sector: 2000-2003 (%)
Sector SE ME LE Total
1 2 3 4 5 6 7 8 9
GDP GDP without oil & gas
85.74 6.73 15.14
0.52 43.88 75.60 36.69 16.80 35.59
40.55 46.22
9.09 2.96 12.98
6.80 22.57 20.81 26.64 46.47 7.16
15.22 17.19
5.17 90.30 71.89 92.68 33.55 3.59 36.67 36.73 57.25
44.24 36.60
100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0
100.0 100.0 Source: BPS.
[image:4.595.84.525.416.576.2]the lowest rates found in SEs.
Figure 3 Contribution to GDP Growth by Size Group of Enterprises, (%)
2.02 0.82 2.08
1.42 0.58 1.46
1.52 0.62 1.55
1.68 0.69 1.73
0 1 2 3 4 5
2000 2001 2002 2003
LE
ME
SE
Source: BPS.
Figure 4 Rates of Output Growth by Size Group of Enterprises, (%)
0 2 4 6
SE 4.13 3.45 4 4.29
ME 5.06 4.64 4.17 5.24
SME 4.4 3.8 4.05 4.57
LE 5.64 2.98 3.19 3.45
2000 2001 2002 2003
Source: BPS
Lack of Productivity
The greater GDP contribution of SMEs does not mean, however, that productivity, either partial, for example, labor productivity (defined as value added per worker), or total of all factors used (i.e. total factor productivity -TFP) in these enterprises is higher than that in LEs.4It is mainly because their number of enterprises is huge, not because their greater productivity as compared to LEs. Given the fact that SMEs lack of capital, technology and skilled men power, it is hard for these enterprises to achieve increasing return to scale in their production process.5 The labor productivity gap between SMEs and LEs is one of the largest
4
Labor productivity rather than TFP is often used in analyzing productivity growth in SMEs, as the ratio is a useful indicator of a sort of progress, since enterprises that cannot raise it will not be able to remain competitive as wages rise. The difference between TFP and labor productivity is that the former measures the relative efficiency of SMEs and its advance over time, whereas the latter does not. Unfortunately, the TFP measure is more difficult to operational due to problems in the measurement of fixed and human capital.
Kadin Indonesia-Jetro, 2006 5 www.kadin-indonesia.or.id
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Kadin Indonesia-Jetro, 2006 6 www.kadin-indonesia.or.id observed in developing countries.6
In Indonesia there is a number of studies which provide ample evidence that labor productivity is much greater in LEs, which the result that, though SMEs had higher percentage of employment than LEs had, they generated percentage of total value added less than LEs did. For instance, based on data census on manufacturing sector for 1975-1996 from BPS, estimates from Rice and Abdullah (2000) show that in 1975 value added per worker (1990 Rp’000) in cottage and household industries (CHIs) was 132 and increased to 572 in 1996, and that of small-scale industries (SSIs) increased from 959 to 1,371. For the same period, those from medium-scale industries (MSIs) and large-scale industries (LSIs) rose respectively from 4,088 and 9,055 in 1975 to 9,055 and 12,495 in 1996.
By using the same data census, estimates from Berry et al. (2001) show that the labour productivity gap between SMEs as a group and LEs has remained substantial. The ratio was 9.4 in 1975 and 9.1 in 1996. Over the entire period (1975-96), labor productivity appears to have grown most for CHIs, with more modest (and quite similar) estimates for SSIs, MSIs and LSIs.7However, their estimates suggest continued growth in labor productivity among LSIs, while a possible slowdown for smaller sized of production units (Figure 5).8
Data from the Ministry of Industry (MoI) may give some clue about the differences in technological capability by size of firms at the national level. Table 3 shows (although it varies by sub-sector) that on average, the value added-labor ratio increases by size of enterprise, suggesting that in larger enterprises the level of technology is higher than that in the smaller ones,. This finding as also confirmed by many other studies does not come, however, as a surprise, given the fact that especially micro or cottage enterprises (CHIs) in Indonesia (as in many other developing countries) are traditional enterprises adopting manual modes of production (i.e. low degree of mechanization). They also lack of the necessary inputs to increase productivity, such as skilled workers, capital to buy new machines and modern tools, information on new machines or production tools, and know how to improve their methods of production.9 On the contrary, LSIs are usually very highly mechanized/computerized, their production processes are much better managed and
6
See among others Liedholm and Mead (1999), and Berry and Mazumdar (1991).
7
As explained in Berry et al. (2001), labor productivity figures are difficult to interpret for the household establishments that make the bulk of the CHIs group, because effective hours worked (rather than numbers of workers) in these enterprises tend to be quite variable, and extremely hard to measure. According to them, it is probably that productivity per hour worked increased less than the observed value added per worker, but nonetheless rose considerably.
8
See other studies on labor productivity gap between SMEs and LEs in Indonesia from, for example, Hill (1997, 2001), and Timmer (1999).
9
Kadin Indonesia-Jetro, 2006 7 www.kadin-indonesia.or.id organized, and they generally employ highly skilled workers. For instance, in the food and beverages industry, micro enterprises are very simple food and beverages processing units mostly for local markets as compared to big companies such as Unilever and Indofood. This is, however, not only the Indonesian, as the labor productivity gap between SMEs and LEs is one of the largest observed in developing countries, simply because LEs have relatively large endowments, including technology and know how.10
Table 3. Differences in Labor Productivity in Indonesian Manufacturing Industry by Size of
Enterprise and Sub-sector, 2000 (average of value added per worker; in 000 rupiah).
ISIC CHIs SSIs MSIs LSIs
31 32 33 34 35 36 37 38 39
Food, beverages & tobacco
Textiles, garments, leather & footwear Wood & wood products
Paper, printing & publications
Chemicals (incl. fertilizers) & rubber products Cement & non-metallic mineral products Basic iron & steel products
Transport means, machinery & its tools Other manufacturing
2,339 1,746 2,103 3,981 1,782 3,346 3,374 5,492 4,973
2,539 4,855 6,743 5,723 7,812 3,071 7,011 5,402 6,097
25,806 24,271 12,403 18,953 50,849 8,849 395,344 45,127 12,701
67,309 27,237 30,236 103,938 68,968 63,327 142,243 130,589 22,946 Note: MoI defines SSIs as business establishments having assets (excluding land and building) maximum Rp200 million and revenues per year Rp1 billion or less. The Ministry does not define explicitly micro enterprises. In this table, the Ministry adopts the definition of Biro Pusat Statistik (BPS): micro (CHIs): 1-4 workers; SEs (or in manufacturing: SSIs): 5-19 workers; MEs (MSIs): 20-99 workers; and LEs (LSIs): 100 or more workers.
Source: MoI (database).
BPS data on SSIs and CHIs also come with the same evidence showing that labor productivity increases by size. First, as shown in Table 4, the average value added-labor ratio in the CHIs and SSIs together as one group is lower than that in MSIs and LSIs combined. The labor productivity in CHIs and SSIs is so low that despite the fact that their total number of establishments and total workers employed are much larger than those in MSIs and LSIs, their share in total output (gross value added) is smaller than those of the later two size groups of industries. Second, Table 5 shows that the average labor productivity in CHIs is lower than that in SSIs. However, the gap in productivity varies not only over time, but also across industries. During the period under review, differentials between SSIs and CHIs tended to be larger in many industries, except in the paper, printing and publications (34) industries which declined from Rp4.1 to Rp1.8 million, in cement and non-metallic mineral products (36) from Rp1.5 to Rp1.1 million, and even in the miscellaneous manufacturing industries the differential is reversed from Rp3.5 to –Rp3.4 million. In other words, only in these three industry groups CHIs have experienced higher
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Kadin Indonesia-Jetro, 2006 8 www.kadin-indonesia.or.id rates of growth in labor productivity than that in SSIs. In manufacturing as a whole, the overall rate of growth in labor productivity in the SSIs is also lower than that (in) of the CHIs, i.e. about 153.7% and almost 170%, respectively.
Table 4. Productivity (P) and Output Share (Q) in Manufacturing by Size, 1999-2002
1990 2000 2001 2002
P Q P Q P Q P Q
MSIs + LSIs CHIs & SSIs 115.28 8.35 90.52 9.48 143.99 9.11 91.65 8.35 164.7 10.98 91.5 8.5 166.31 12.36 89.9 10.06
Note: P in Rp million and Q in %.
Source: BPS (Profil Industri Kecil dan Kerajinan Rumah Tangga, 2002).
Table 5. Labor Productivity between Micro and Small Enterprises in Manufacturing Industry by Sub-
sector, 1996-2001 (Rp million per worker per year).
Period ISIC* Size category
1996 1998 1999 2000 2001
31 CHIs
SSIs 3.3 6.9 7.2 16.4 6.8 14.3 6.99 17.0 7.99 25.1
32 CHIs
SSIs 2.3 9.4 5.98 19.98 5.4 19.2 5.7 19.1 6.3 21.2 33 CHIs SSIs 2.1 8.9 4.4 15.3 5.1 17.4 4.95 17.1 6.2 20.2 34 CHIs SSIs 5.3 9.4 9.8 13.5 8.1 11.2 13.7 15.1 16.5 18.3 35 CHIs SSIs 3.2 9.1 7.8 10.7 3.1 15.4 6.1 20.8 7.8 59.8 36 CHIs SSIs 2.3 3.8 4.5 5.6 5.2 5.2 5.9 10.0 7.2 8.3 37 CHIs SSIs 5.0 13.3 12.7 11.4 6.9 6.2 12.3 26.2 26.5 38.3 38 CHIs SSIs 4.9 9.2 9.2 17.4 12.8 14.2 14.9 16.9 15.3 30.6 39 CHIs SSIs 4.4 7.9 9.2 8.1 7.8 8.4 11.98 15.4 15.7 12.3 Total CHIs SSIs 2.8 7.4 5.96 14.3 6.1 13.9 6.4 15.97 7.5 19.7 Note: * = see Table 3.
Source: BPS (Indikator Industri Kecil & Kerajinan Rumah Tangga 1996-2001)
Kadin Indonesia-Jetro, 2006 9 www.kadin-indonesia.or.id Institute concludes that CHIs need to be strategically developed for several reasons, including that they are productive economic activities, and thus, what is needed is capacity building and not the establishment of new enterprises, and if they are appropriately empowered, they can easily grow into modern SSIs. In its report on SSIs and CHIs. BPS states that the lack of capital, technology and human resource is the main cause of low productivity in CHIs and SSIs.
Although, no data are available on the productivity of SMEs by rural and urban areas, since the majority of these enterprises, especially from cottage and small categories, are found in rural areas, while big companies, including most of MNCs are located in or near big cities like Jakarta, Tangerang, Bekasi, Bogor, and Surabaya, it can be assumed that the bulk of these enterprises, especially the CHIs and SSIs are unproductive.. This assumption is simply based on the fact that in rural areas, especially in the provinces outside of Java, the physical infrastructure is not yet well developed, transport facilities are bad, access to information and capital market is very limited, and good facilities for education and highly skilled workers are not available.
Development Constraints
In less developed countries (LDCs), SMEs are facing obstacles that are sometimes similar to those experienced by LEs. However, SMEs, especially the smaller ones are much more vulnerable in relation to these problems. The nature or complexity of many of these problems is also related to the size of enterprises or activities. The smaller the size of enterprises the more complex the problems they face. The problems may differ from region to region and between one industry-group to another. Although the problems vary even between individual enterprises in the same size category and within a branch of activity, there are certain problems which are common to all SMEs which are linked to three groups of issues: infrastructure, institution, and economic issues. The infrastructure issues include poor and/or expensive infrastructure such as transport, storage facilities, water, electricity, and telecommunication, lack of working premises, and poorly developed physical markets.
The second issues include no access to formal training and, as a result, lack of skills in
particular as regards basic economic skills and managerial expertise, lack of formal
schooling sometimes even resulting in illiteracy, limited access to property rights, limited
access to formal finance and banking institutions, excessive government regulations in
areas such as business startup, in particular as regards cumbersome, time demanding and
Kadin Indonesia-Jetro, 2006 10 www.kadin-indonesia.or.id
products, etc., and ewer market opportunities due for instance to non-compliance to
international standards. The latter issues include excessive registration and transaction costs of starting or operating businesses, limited access to technology, lack of opportunities for
bulk purchase of inputs, lack of working capital: credit has to be obtained from informal
sources such as friends or relatives or non-banking financial agencies with unfavourable
terms, and insufficient funds do not allow for further investments (UN, 2001).
These obstacles are more or less interlinked and create vicious circles of bad
performance or business stagnation or low competitiveness of SMEs in LDCs as compared
to their counterparts in developed/ industrialized countries. For instance, the main reasons
for the lack of funds or skills is that the SMEs, especially the micro ones cannot access
resource institutions such as banks and other financing institutions, training and education
institutions, marketing and consultancy firms, etc. In fact, all these various obstacles create
an overall context that in itself constitutes a barrier of further development or business
improvement to these enterprises (Tambunan, 2006).
The 2003 (recent) survey on SEs and micro enterprises (MIEs) from Central Bureau of Statistics (BPS) in all sectors in Indonesia shows the typical problems of these enterprises in Indonesia (Table 6). As can be seen, the main problems faced by the majority of the respondents are lack of capital and marketing difficulties. In Indonesia, although there are various government sponsored SME credit schemes, the majority of them, especially SEs and MIEs located in rural/backward areas never received any credit from banks or other financial institutions. They depend much on their own savings, money from relatives and credit from informal lenders for financing their daily business operations. In marketing, SMEs in general do not have the resources to explore their own markets. Instead, they depend heavily on their trading partners for marketing of their products, either within the framework of local production networks and subcontracting relationships or orders from customers.
Kadin Indonesia-Jetro, 2006 11 www.kadin-indonesia.or.id characterized by manual operation and high labor intensity, but very low labor productivity. Lack of funds and skilled workers and various other operational constraints largely account for the technological backwardness of this size group of enterprises. There is a good reason why they do not mention lack of technology and skill as problem. They may not aware of that problem or they do not see it as a serious problem for their business as many SE and MIE entrepreneurs usually modify or repair their own machines.
Table 6. Main Problems faced by SEs and MIEs in Manufacturing Industry, 2003
SEs MIEs Total SEs and MIEs
Have no problem
Have problem -Raw material -Marketing -Capital
-Transportation/Distribution -Energy
-Labor cost -Others
Total SEs & MIEs
46,485 (19.48)*
192,097 (80.52) 20,362 (10.60) 77,175 (40.18) 71,001 (39.96) 5,027 (2.62) 40,605 (2.4) 2,335 (1.22) 11,592 (6.04)
238,582 (100.00)
627,650 (25.21)
1,862,468 (74.79) 400,915 (21.53) 552,231 (29.65) 643,628 (34.56) 49,918 (2.68) 50,815 (2.73) 14,315 (0.77) 150,646 (8.09)
2,490,118 (100.00)
674,135 (24.71)
2,054,565 (75.29) 421,277 (20.50) 629,406 (30.63) 714,629 (34.78) 54,945 (2.67)
55,420 (2.7) 16,650 (0.81) 162,238 (7.90)
2,728,700 (100.00) Note: * = %
Source: BPS (SUSI 2003)
Also, lack of human resource is not mentioned in Table 6. However, no doubt that lack of human resource is also responsible for the lack of productivity in SMEs in Indonesia. Table 7 shows only a small portion of total entrepreneurs in MIEs and SEs who have higher education diplomas. The table also shows that female entrepreneurs are less educated than their male counterparts. With respect to higher education, less than 1% of total female entrepreneurs who have university diplomas, as compared to their male counterparts at 6.5%.
Table 7: Education of Entrepreneur in Non-Farm MIEs and SEs by Gender, 2003 (%)
Level of education Female Male
Not finished primary school Finished primary school
Finished high school first degree (SMP) Finished high school second degree (SMA) Higher education
27.88 40.82 18.62 11.77 0.91
14.27 39.49 25.87 18.37 6.5
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