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Fundamental Analysis II: Industry Analysis

Irrespective of specific economic situations, some industries might be expected to perform better, and share prices in these industries may not decline as much as in other industries. This identification of economic and industry specific factors influencing share prices will help investors to identify the shares that fit individual expectations.

Industry analysis is a type of business research that focuses on the status of an industry or an industrial sector (a broad industry classification, like “manufacturing”). The industry classification is economy specific. The boundary of each industry may vary from country to country or from analyst to analyst. A complete industrial analysis usually includes a review of an industry’s recent performance, its current status, and outlook for the future. Many industry analyses include a combination of qualitative and statistical data.

Industry analysis demands an insight into the segments/sectors/subdivisions of overall economic activity that influence particular industries, and the relative strength or weakness of a particular industry within an economic environment. Industry classification is mostly on the basis of products offered though other classification such as business cycle can be used (cyclical industry).

 

 

As per product based classification an industry is a set of businesses that produce similar products used by customers for similar purposes. We can define an industry broadly or narrowly, depending upon the purpose of the analysis. The “computer industry” includes a variety of specialty areas: software, hardware, peripheral devices, as well as personal computers, servers, and mainframe computers. An overly broad definition will not meet the practical needs of investment analysis, since it is very difficult to analyse all manufacturers and technologies of different types of products on a single base. The government coding system assigns numbers to industries as also the stock markets. The Bombay Stock Exchange Industry Groups are an example of industry categorisation that are popular among the investment community.

Major subcategorisations of industry groups could be as follows:

Investors could define their own industry classification. Usually for investment purposes, a broad category grouping competitive business within might be desired by the investors.

Such industry definition should include:

• Economic sector—manufacturing, distribution (wholesale or retail), services, and so on.
• Products or services—a list of what is offered by the industry
• Geographic scope—local, regional, national, or international.

The industry definition may also include a listing of major market segments. For example, a computer manufacturer may divide the industry into five market segments: personal computers, microcomputers, mini computers, and main frames. Few competitors operate in multiple segments while most operate in one or two segments. There are several businesses that are engaged in multi-product, multi-sector activities covering a wide geographical area. It is difficult to bring such businesses under a single sectoral classification and can rather be viewed as a separate industry.

STANDARD INDUSTRIAL CLASSIFICATION (SIC)

A common method of classifying businesses or industries by type is the Standard Industrial Classification System, commonly referred to as the SIC Code. It divides virtually all economic activity into divisions that are further broken up into numbered, major groups. SIC codes get progressively more specific as the number of digits increases. A two digit SIC code indicates the broad industry category (eg, furniture). Adding a third digit might further specify a type of furniture (eg, home furniture or office furniture). The fourth digit narrows the industry categories still further (wooden household furniture or metal household furniture). A full listing of SIC codes is an important tool in industry analysis.

Investors perform industry analysis because they believe it helps them isolate profitable investment opportunities.

As security analysts are trying to find undervalued securities or sectors, the information contained in a sector forecast is valuable. Presumably higher growth sectors will have faster earnings and cash flow growth than other sectors. Higher forecasted cash flow levels and lower risk perceptions of such sectors may lead analysts to believe that their share prices or bond credit quality will have greater appreciation potential than those of other sectors.

Industry analysis usually tries to find answers to the following questions:

• Is there a difference between the returns for alternative industries during specific time periods?
• Will an industry that performs well in one period continue to perform well in the future? That is, can we use past relationships between the market and an industry to predict future trends for the industry?
• Do companies within an industry show consistent performance over time?
• Are there risk differences between different industries?
• Does the risk for individual industries vary or does it remain relatively constant over time?

Links between the Economy and Industry Sectors

The economic performance of a country, to a large extent, determines the—favourable or unfavourable— climate for its industrial participation. With global movement of funds/investments made easy, the world itself is a market place and industries tend to sprout in countries where economic policies and environment are conducive. Industries cluster in a specific economic locality because:

• Businesses will have to respond to customers’ demands for solutions that match their specific needs.
• Businesses will innovate infinite models of their products to suit different specifications and ensure the maximum amount of applications.
• Market places will become the interfaces for these efficiently assembled commodities, often in real time.
• An increasingly competitive world where only the strongest, most successful companies will survive makes businesses choose their economic environment.
• Business opportunities across economies arise from rapid technological changes, privatisation of state enterprises and relaxation of trade barriers.
• In a global economy, the location of business’s functional areas is relevant since companies compete with other companies in their industry.

Industry analysis is more relevant than economic analysis since the final investment decision is to identify investment opportunities. This helps in the next process, that of focusing on companies with sustainable competitive advantage in their respective industries. The ability to compute the growth rate of an industry helps in the better pricing of specific companies/securities.

There is a need to analyse the current status of the industry and forecast the conditions in which a business now operates or will operate in the future. There are two very strong reasons to do an industry analysis. First, it provides an awareness of the market performance and ability to anticipate the future of the industry. Second, it is an important part of any company’s business plan. Capital providers such as financial markets and financial institutions hence require an industry analysis before agreeing to participate in an company’s capital.

The Stock Market and the Business Cycle

Business cycles are observed fluctuations in the economy: economic expansion followed by economic decline (a recession or, in severe cases, a depression) and then recovery. Business cycles are identified through changes in several economic measures, such as output, employment, stock prices, wages, spending, and money supply. While examining the performance of industries over time it is important to be aware of business cycles and how they may impact investment analyses. Especially when deciding on the choice of an industry, it is most important to select two years that are at the same point in a business cycle. For example, analysing an industry for two years in which the economy is expanding will be correct rather than examining a year of depression and a year of boom. The difference arising between the comparative data are not out of industry specific reasons, but out of the inherent nature of the economy itself.

Figure 10.2 depicts changes in real Gross Domestic Product (GDP) since 1950. According to the data below, India has experienced recessions during 1953–54 and 1971–72. These recessions were quite short relative to the overall long period of expansion experienced by our country. The boom period for the economy could be stated to begin from 1974–75. Thus, for analysing industries, we have several years of expansion while for comparing a depressed time there are relatively few years for comparison. The business life cycle states that all economies face the four stages of business: namely, recovery, boom, recession, and depression. However, in practice, all these four stages need not necessarily be equidistant from each other in relation to time. Economic recovery/recession may take a longer time duration than the boom or depressive stages. The alternative situation may also prevail in some economies.

It is important to note that if quarterly data or regional or state data are used the economic recession/ expansion will tend to be different from what has been depicted above. This is because certain states’ GDP performance has not shown the extent of recession as depicted in the overall economic scenario for India, while certain states are still facing a continuity of recession despite the overall economic boom. The discrepancies that arise in detecting recession/expansion [patterns between the different states], within the nation’s economy is similar to the discrepancies that arise among the economic sectors and industries within each sector.

The concept of a product cycle clearly defines changes in growth patterns among industries. The rise and fall in customer interest is known as the “product life cycle” and is depicted in Figure 10.3. The introductory stage creates an interest in the product in the minds of customers. The growth stage is where product awareness spreads and customer interest shows a rise. In the maturity stage, the product acquires popularity in the market. The saturation stage sees an almost stable situation with no new customers showing interest in the product. The decline stage sees a withdrawal of customer interest from the product. Unless there is product modification/innovation it is difficult for the product life cycle to show an up trend from the decline stage. New products and markets emerge as industries evolve. In any stage of the business life cycle the organisation might face the product life cycle. The product life cycle curve will depend on the extent of technology and innovation prevalent in the industry.

An overlap of business and product life cycle stages is illustrated in Figure 10.4. Time differentiates the movement of the business and product cycle curves. While a product life cycle is shorter, the business life cycle is longer and comprises a series of product life cycles.

The product life cycle needs to be understood if an industry analysis is to be interpreted meaningfully. The stages in a product life cycle and the tools used by business houses to extend the product life cycle stage are given in Figure 10.5. During the introduction or early growth stage, business houses indulge in product innovation. This addition to value helps them to achieve high growth rates in the next product life cycle stage. Businesses, besides concentrating on research and development, also focus on credibility building techniques. There is a tendency for the businesses to enter into the capital market at this stage, since they need to finance the fast growth expected out of their product innovation.

The establishment of standards, creation of brand awareness, tools to widen the market of the product and the development of product standards characterises the growth stage. There is no more room for product innovation at this stage and hence process innovation dominates the activities. The process innovation helps in the competitive positioning of the product. The standards that have been developed for the product also indicate the end of research and development activities with respect to the product. There is also scope for creation of external value. Brand building becomes necessary to distinguish among the numerous market entrants.

The consolidation stage is the extension of the maturity stage; this includes creating external value and reaching new markets. The product is still able to survive consumer interest and the onslaught of further competition determines the period of the consolidation stage. When competition is too high, during the stability stage, business houses think of strategies such as mergers/takeovers to stabilise competition. There is pooling of resources among competitors and cost cuts and reductions are highlighted. The process innovation of products continues till this stage. When process innovation exercises are exhausted, the firm enters the decline stage. The decline stage is a crucial stage for business houses. The decline stage has to be characterised by research and development programmes and if the business is able to bring out an innovative and new product, the business cycle will move in the positive direction due to the positive growth from the product life cycle. On the other hand, failed product launches can lead to a slump and a recession period for the business.

A two factor influence on the product life cycle, namely the growth stage of the market (business cycle) and the market share of the product (product cycle), lead to a success or a failure sequence (Figure 10.6). The successful continuation of the product cycle through the business life cycle is through the movement of low market share to a high market share/growth. The reverse move from a high market share to a low area results in a failed business performance.

Industries go through these growth cycles; initial product development being the first stage. Businesses in this stage are generally unprofitable, new and untried, and pose significantly higher risks for new investors. As the industry matures, it goes through a stage of rapid expansion. At this point investors have a clearer picture of the future and are more attracted to the industry. The economic environment may have only a little influence on the industry and investor activity at this point. This is also the stage during which new entrants spend heavily to gain market dominance. As a result, companies will often show little or negative earnings as cash flow is plowed back into the business for purposes of growth.

The final stage is that of mature growth. Industry leaders are established by competitive dominance. Many consolidations and mergers take place. Now investors expect the companies to be profitable and expect that the industry performance will be more influenced by the economy. The characteristics of each stage is given in Table 10.1.

The identification of the stages is through the industry analysis.

There are many sources of information to perform industry analysis, ie, investment firms, business and trade periodicals, trade associations, and government agencies.

The tools used for conducting an industry analysis is listed below:

Data Needs for an Industry Analysis

Industry analysis requires a variety of quantitative and qualitative data. Though one single source for all the data needs might not be found, industry associations, business publications and the Department of Economic Analysis perform a comprehensive industry analysis. A suggestive—though not an exhaustive— list of data categories that are utilised for performing industry analysis is listed below:

Data Categories

• Product Lines
• Complementary Products
• Product Growth
• Product Pattern (seasonal, cyclical)
• Technology of Production and Distribution
• Economies of Scale
• Suppliers
• Labour
• Buyers and their behaviour
• Substitute Products
• Product Rate
• Determinants of Product Success
• Cost Structure
• Value additions existing/feasible
• Logistics
• Marketing and Selling
• Market Segmentation
• Distribution Channels
• Raw material Sources
• Raw material Rate
• Marketing Practices
• Innovation
• Raw material Requirements
• Social, Political, Legal Environment

TOOLS FOR INDUSTRY ANALYSIS

Industry analysis examines the performance in terms of certain established accounting parameters, and qualitative grading. In other words, industry analysis involves the analysis of data in terms of:

• Cross-sectional industry performance,
• Industry performance over time,
• Differences in industry risk,
• Prediction about market behaviour, and
• Competition over the industry life cycle.

Cross-sectional Industry Performance

Cross-sectional industry performance is aimed at finding out if the rates of return among different industries varied during a given time period. Analysts usually compare the performance measured in terms of growth in sales, profits, market capitalisation and the dividend of various industries. Similar performances during specific time periods for different industries would indicate that such type of industry analysis is unnecessary. As an example, assuming the stock market registered a growth of 10% and an analysis of all industries showed a uniform growth of around 5% to 8%, it might seem futile to find out an individual industry that is a best performer. On the other hand, a wide variation in growth across industries, ranging from 80% to -20% to a stock market growth rate of 50%, would require the examination of those industries that contribute heavily towards a stock market up trend.

Industry Performance over Time

Analysts also perform a detailed exploration of industry performance over time, to identify the stage of product life cycle that the industry is expected to face. Usually a time duration of 3 to 5 years is considered to determine whether industries that perform well in one time period would continue to perform well in subsequent time periods. In many economies, the forecast of industrial performance has been the most difficult task. The compositional change in the industry and the product definition variation, due to technological change and innovation, restrict the ability to successfully forecast the future performance of the industry.

Differences in Industry Risk

Industry analysis besides focusing on industry rates of return, also has to consider industry risk measures. Industry risk specifically investigates two questions:

1. Does risk differ across industries in a given time period?
2. Are industry risk measures stable over time?

Risk is measured in terms of variability in returns/productive value. Business risks inherent in industries measured though the operating profit margin deviations, usually confirm a wide variation in the risk pattern of industries. Risk pattern can also be expected to vary depending on the economic situation/ expectations associated with that time duration. Stability of risk measures over time hence would examine the nature of risk.

Industry risk measured in terms of market performance of shares belonging to a particular industry group also identifies the investment market perception about industry risk.

Prediction about Market Behaviour

Predicting market behaviour can be through a qualitative assessment of the strengths and weaknesses of the industry on the whole. Assessing strengths (S) and weaknesses (W) also leads to the evaluation of opportunities (O), and threats (T). This is termed “SWOT analysis”.

A SWOT analysis places an industry between environmental trends (opportunities and threats) and internal capabilities. SWOT analysis is equally applied in industrial analysis as well as in evaluating individual organisations. SWOT analysis involves an examination of the industries’ Strengths (internal), Weaknesses (internal), Opportunities (external), and Threats (external). It helps to evaluate an industry’s position to exploit its competitive advantages or defend against its weaknesses. Strengths and weaknesses involve identifying the industry’s own (internal) abilities or lack thereof. Opportunities and threats include external situations such as competitive forces, technologies, government regulations, domestic and international economic trends and so on.

• Strength is a resource or capacity the industry can use effectively to achieve its objectives. The strengths of an industry provide a comparative advantage in the marketplace. Perceived strengths can include good customer service, high quality products, strong customer need, customer loyalty, innovative R&D, or strong financial resources. To retain strengths, the industry must continue to be developed, maintained, and defended through innovative projects.
• Weakness is a limitation, fault, or defect in the industry that will keep it from achieving its objectives. Weaknesses result when competitors have potentially exploitable advantages over the industry. Once weaknesses are identified, the industry can select strategies to mitigate or correct the weaknesses. For example, an industry that caters only to the domestic player would have the weakness of catering to one economy in a global market setting. Another example of an industry weakness would be a small size industry with poor financial resources either due to lack of product awareness on innovation.
• Opportunity is any favourable situation in the industry’s environment. It is usually a trend or change, or an overlooked need that increases demand for a product or service and permits the industry to enhance its position. Opportunities are environmental factors that favour the industry. It can include a growing market for the industry’s products, shrinking competition, favourable exchange rate shifts, confidence in the industry’s future, or identification of a new market or product segment.
• Threat is any unfavourable situation in the industry’s environment that is potentially damaging to its strategy. The threat may be a barrier, a constraint, or anything external that might cause problems to the industry. Threats are environmental factors that can hinder the industry in achieving its goals. Examples would include a slowing domestic economy (or sluggish overseas economies for exporters), an increase in industry competition, threat of new entrants, buyers or suppliers seeking to increase their bargaining power, or new competitive technology that can affect the industry. By recognising and understanding opportunities and threats an investor can make suitable forecasts, regarding how the industry can exploit opportunities and mitigate threats.

In general, an effective investment strategy is one that takes advantage of the industry’s opportunities by employing its strengths and wards off threats by avoiding them or by correcting or compensating for weaknesses.

The first part of any SWOT analysis is to collect a set of key facts about the industry and its environment. This will include facts about the industry’s markets, competition, financial resources, facilities, employees, inventories, marketing and distribution system, R&D, management, environmental setting (eg, political, economic, social, technological (PEST) trends), history, and reputation.

The second part of a SWOT analysis is to evaluate data to determine whether they constitute strengths, weaknesses, opportunities or threats for the industry. The consolidation and analysis of such qualitative results may sometimes lead to inaccurate predictions of market behaviour.

The qualitative analysis requires a possible framework for identifying and analysing the strengths and weaknesses of an industry. This is given in Table 10.2.

The table will help in grading the relative strengths and weakness of an industry. The identification of the presence of the factors prevalent in an industry can be tick marked against the corresponding industry characteristics. The grading scale can then be consolidated and a final opinion on the overall dominant strengths and weaknesses derived.

 

 

The consolidated report of the characteristics in the first column could be interpreted as major strengths of the industry. The characteristics dominant in last column would be the weakness of the industry. The swot analysis does indicate the steps that an industry ought to enter into and the examination of the effective steps taken by the industry to confirm its position. Swot analysis strategies can be described through Figure 10.7. This identifies the strategies that are to be entered into by an industry when the industry has internal strengths while the external environment has more of threats for the industry. When the internal environment is weak and the external environment also poses a threat to the industry, then the industry must avoid this situation and must try to find a route to exit from the present position. The existence of internal weakness in the industry, but with an opportunity from the external environment, indicates industry must adapt a search strategy to push itself up the growth curve. The strategy usually employed by industries that have internal strengths and the advantage of external opportunities is exploitation.

QUANTITATIVE INDUSTRY ANALYSIS

Industries provide a lot of information related to their performance, employment potential, production, sales, etc. The data is made available both at the national as well as at the state level. For a complete analysis and interpretation of industry performance, both quantitative and qualitative analysis should be performed at the state as well as the national level. Three types of quantitative data analysis can be performed to identify the right industry for investment opportunities. They are employment data analysis, input-output analysis and earnings data analysis. The scope for such analysis is that the extent of risk inherent in an investment environment can be known and this will be useful in choosing industries that will prove to be successful investment decisions. Besides productivity data, the examination of employment potential is crucial for predicting the future growth of an industry. Industries expecting high growth potential take the first initiatives of recruiting more employees to cater to the scenario. Also, when an industry faces a consolidation stage, the first step in most instances would be to cut excess employment. Hence, analysing employee data gives an investor a forecast of industry growth potential.

Analysing Employment Data

Employment data provides a lot of insight into the future of an industry. The product life cycle stage can be predicted effectively using employment data analysis. A review of employment data also helps in identifying and understanding the successful key industries. Employment data reveals the extent of dependence associated with a specific industry. Employment data can also be used to help

• In identifying industries that are growing and those that are declining,
• Evaluating the importance of an industry to an economy, and
• Determining the competitiveness of industries.

Data that are needed for a detailed analysis of the employment scenario of an industry may be categorised as follows:

• industry wise total employment in the current year and an earlier year
• Industry wise emolument data in the current year and an earlier years.

Data Selection

The Annual Survey of Industries (http://mospinic.in) makes available employee data (manufacturing sector in India), both electronically and well as in published format. The types of data available are:

Employees: Includes all workers and persons receiving wages and holding clerical or supervisory or managerial positions. They may be engaged in administrative office, store keeping section and welfare section, sales department as also those engaged in purchase of raw materials and so on, or purchase of fixed assets for the factory.

Estimating the Duration of Analysis

A shorter duration is preferable especially in terms of investment decisions in a changing market environment. A longer duration of analysis may be taken up if the data is to be used for predictive purposes, especially when statistical tools such as regression analysis is applied to derive a forecast model.

Estimating a Base Year

Data by itself would be less meaningful since there is no meaningful comparison. On the other hand if data is presented as a relative measure that is, by comparing it with a base year, a more meaningful interpretation can be made. Hence, to calculate change over time, data is required for a base year and the recent year. The base year may be two, five, ten, or any number of years earlier than the most recent year used in the analysis. The choice will depend on the economic stage that the industry is functioning in. If the economy is going through a short period of decline/recovery (eg, four years or less than four years), it is probably best to select a year prior to that downturn/upswing. This should provide a more accurate picture of how industries are performing.

Quantitative Tools for Analysing Employment Status

Employment Share of Sub-industry For each of the sub categories of industries the share of employment, internally in its industry classification and in terms of the economy can be analysed. For instance, fabricated metal products representation in total employment, and its representation within the manufacturing industry could be analysed. If we looked only at the share of total employment, the fabricated metal industry could get lost, even though it could be very important in the manufacturing sector.

The data that will be compared to identify the share of sub-industry employment status are:

• employment in a sub-industry classification
• total employment in that industry

To determine each sub-industry’s share of employment within its industry classification, employment in the sub-industry is divided by total employment in that industry.

For instance, if employment in knitted products is 600 and total employment in textiles is 11,500, knitted products’ share of employment will be 5.2 per cent. A significant share highlights the importance of the sub-industry.

Change in Employment Although an industry may not currently register a significant share of employment, it may be exceeding all other industries in terms of growth in employment. Hence, there is a need to study the industry employment scenario further and try to understand what is driving its growth. The reasons for this industry’s growth may provide useful information that can help in forecasting the stage of economic development that an industry is undergoing.

For this purpose a relative measure of employment quotient is determined using the

• industry’s share of employment for current year
• industry’s share of employment for a base year

To determine the growth or decline of employment in an industry over a specific period of time, the change in the number of employees is divided by the number of employees in the base year. The formula for computing the change of employment in an industry is given as follows:

For the furniture industry assume there are 1500 employees in the most recent year and the total number of employees in the same industry was 1200 employees in the base year, then the percentage change in employment is found as [( 1500/1200)−1] × 100, i.e., 25%. This is the increased employment potential in the industry. A negative percentage would imply that the employment potential has declined in that specific industry, making the investors wary of investment.

For example, if the fabricated metal products industry is growing quickly, it may be useful to study the change in employment of the primary metals industry, which could potentially supply inputs to the fabricated metal products industry. Such sub-analysis would explain the reason for growth or decline in an industry.

Location Quotients The location quotient is a measure of an industry’s concentration in an area relative to the rest of the nation. It compares an industry’s share of regional employment with its share of national employment. Location quotients require several assumptions, including uniform regional consumption patterns and labour productivity across the country. Location quotients could serve as a quick and useful tool in determining a region’s key industries.

A location quotient is measured as an industry’s share of regional employment over the industry’s share of national employment. If the location quotient is 1 then the industry ’ s share of regional employment is the same as that industry’s share nationally. That is, the industry is functioning only in a specific region. Several inherent factors of the industry itself might contribute towards a location quotient of 1; for instance, the availability of raw materials for that industry might result in a location factor of 1. A location quotient much greater than 1 means the industry employs a greater share of the regional workforce than it does nationally. A location quotient that is less than 1 implies that the industry’s share of regional employment is smaller than its share of national employment.

The computation of the location quotient involves two relative measures, namely, share of regional employment of an industry and its share of national employment. The data needed to compute this quotient is:

• a specific region’s employment in an industry
• a specific region’s total employment
• national employment in an industry
• total national employment

Stated in an elaborate form:

A location quotient greater than 1 may also be interpreted as that the industry is producing more goods and services than are consumed regionally. Here, the industry could be exporting the goods or services out of the area and, in the process, bringing new value into the area. Industries that bring value into the area help the regional economy grow. Similar interpretations can be made if employment data relating to a nation is compared with world employment levels.

Just because a location quotient is greater than 1, it does not necessarily mean that an industry is competitive or growing in that region. It may mean that the industry is not as efficient and employs more people than the national average to produce the same level of output. Other measures, such as earnings or value-added per employee, and changes in employment should be computed to determine whether the industry is actually experiencing high growth and has a competitive advantage in a specific region.

Change in Location Quotient Another way to use location quotients is to look at how they have changed over a period of time. This comparison will be useful in identifying whether each industry is increasing or decreasing its concentration and their respective importance in a specific region relative to other regions. This is a relative measurement of the location quotient of the current year with that of the base year. The data requirement for computing this equation will be for two years, the current year as well as the base year. They are as follows:

1. Location quotient for the current year, for which:
   • a specific region’s and nations employment in an industry
   • a specific region’s and nations total employment
2. Location quotient for a base year, for which:
   • a specific region’s and nations employment in an industry
   • a specific region’s and nations total employment

The simplified equation based on the previous formula will be:

Where LQ represents location quotient.

The growth or decline in the change in LQ will give a better idea of how the industries’ importance to the regional economy has changed over time. This information, along with the location quotients themselves, provides a useful analytical tool for understanding the performance of a region’s industries.

The calculations performed allows the grouping of the region’s industries into any one of the following four categories:

• Large location quotient that is declining or increasing.
• Small location quotient that is declining or increasing.

Each category might indicate the prevalence of different economic policies and may entail a different development approach. For example, if a region wanted to promote the expansion of manufacturing, it might focus its efforts on the industries that have large, but declining location quotients and on those that have small, but increasing location quotients. Industries with large location quotients are obviously quite important to the current economy, and to lose them might cause considerable hardship.

There are also industries that have small, declining location quotients. These industries are not as important to the economy and apparently do not have much potential in the region. On the other hand, industries with small but growing location quotients may be a source of considerable future growth for the economy. Similar analysis can be done for sub-industry classification.

Empolyment Shift Analysis Employment shift analysis provides a picture of how well the region’s current mix of industries is performing and how well individual industries are doing. The analysis can be used to examine three components of regional growth:

National growth, Industry mix, and Competitiveness

Employment shift analysis will provide the portion of total employment growth due to growth of the national economy, a mix of faster or slower than average growing industries, and the competitive nature of the industries in the region.

The formula to compute the employment shift analysis can be broken down into four separate sections: the national growth component, the industry mix component, the competitiveness component, and the total effect.

1. National growth Component The national growth component is the share of regional employment growth that can be attributed to the growth of the national economy. This assumes that if the national economy grew by, for example, 5 per cent, then we can expect the regional economy to grow by 5 per cent.

   The calculation for the national growth component is quite simple.

   Step 1: Compute the change in national growth and divide it by the base year’s total national employment.

   

   Step 2: Multiply base year employment for each industry in the region by the growth rate computed in step 1.

   

   Step 3: Adding up the result for each industry will give the total national growth component.

   

   Using simple and fictitious data in the table below, the national growth rate can be computed.

   Step 1: Average national growth rate: (30,000 ÷ 27,000) − 1 = 11.1 per cent.

   Step 2: Multiply the regional base year employment of 350 by [(30,000/27,000)−1] 11.1 per cent to get 389 in the durable goods industry. For non-durable goods, similarly multiply 450 by 11.1 to get 500.

   Step 3: Adding these two figures (389 + 500) gives 889 as the national growth component or share of the region’s total employment growth.

   These calculations are shown in the following table.

   

   The national growth component of each industry tells us that the employment potential in the industry can be attributed to the growth of the national economy. We might also say that if the industries we are considering grew at the same rate as the same group of industries nationally, then the number of employment created in this example would be 889. However, in 2000 since 950 employment opportunities were created, we need to examine what might have account for the additional 61.

   There can also be instances when the number of jobs created regionally could be lower than the number of jobs that would have been created if the industries grew at the national rate. For example, if the computed total national growth component was 1000 in comparison with the actual 950 employees there is again a need to account for the missing 50 employees. The industry mix and competitiveness components can be used to explain this difference.

    

2. Industry Mix Component Industry mix looks at employment that may be attributed to the region’s mix of industries. This analysis calculates the employment created or not created in each industry due to the difference in that industry’s national growth rate and the average national growth rate. It also provides the employment created or not created as a result of the region’s overall industry mix.

   Each industry’s national growth may have been favourable, neutral, or unfavorable. If an industry experienced favourable growth it means that its employment growth rate exceeded the average national growth rate for all industries. If the growth is neutral, the industry grew at the average national rate. If the growth is unfavourable, the industry grew less quickly than the national growth rate.

   Once these net rates are applied to a region’s base year employment then it can be examined as to how much of the region’s employment growth was affected by its concentration of high-growth and low-growth industries. In specific terms the result of how much employment were created (or not created) in each industry because of its favourable or unfavourable growth rate can be determined by the industry mix component.

   The steps in the computation of industry mix component is as follows:

   Step 1: Compute the national growth rate of the industry.

   

   Step 2: Identify the industry mix differential, ie, difference between national average growth rate and industry’s national growth rate.

   

   Step 3: Now each industry’s employment change due to industry mix differential can be worked out.

   

   Step 4: The total industry mix component is then derived by adding all the industry mix employment changes.

   

   The illustrative data table used earlier can be considered again to examine how each industry’s growth rate differs from the national growth.

   National growth rate: (30,000 ÷ 27,000) − 1 = 11.1 per cent

   Sub-industry growth rate:

   Durable Goods:	(14,000 ÷ 13,000) − 1 = 7.7 per cent
   Non-durable Goods:	(16,000 ÷ 14,000) − 1 = 14.3 per cent

   For durable goods, subtract the national growth rate of 11.1 from the industry growth rate of 7.7 to get -3.4 per cent. For non-durable goods, subtract 11.1 from 14.3 to get 3.2 per cent.

   By multiplying these percentages by the base year employment data, it can be concluded that 14 additional employment were created in non-durable goods because the region has a favourable industry mix. The results also indicate that because durable goods were not growing as quickly as the national average, employment potential of 12, which would have been created if the regional economy matched the national economy, were not generated. Since more employees work in non-durable goods than in durable goods, when the industry mix components for each industry are added together the result is positive. This means that because the region’s economy has a more favourable mix of industries than the nation as a whole, two additional employment were created. There calculations are depicted in the table below.

   

   Industries that are growing faster than the national average may be more dynamic and have bright futures. However, these industries might also have increasing demand for labour, that may exceed the local supply if adjustments are not made to anticipate future demands of these industries.

   There may be a variety of reasons as to why some industries experience negative employment changes. For example, the industry’s importance may be declining nationally, it may be going through a cyclical change that does not coincide with the rest of the economy’s business cycle. The industry may have altered its production so that it is producing the same, but not employing as many people; or it may have ineffective management and processes that hinder its ability to expand.

    

3. Competitiveness Component After calculating the national growth and industry mix components, the next step is to look at the employment created (or not created) as a result of the region’s competitiveness. The assumption is that once national growth and the mix of industries have been identified, any additional employment growth must be due to the region’s competitive advantage. The competitiveness component measures the ability of the regional economy to capture a growing share of each industry’s growth.

   The competiveness component computation is as follows:

   Step 1: Compute the industry’s regional growth rate.

   

   Step 2: Difference in industry’s regional growth rate and the industry’s national growth rate is computed next.

   

   Step 3: Each industry’s employment change due to competitiveness differential is calculated using the competitiveness differential.

   

   Step 4: The final result is the addition of all the competitiveness employment change figures computed using step 3 above.

   

   Using the same illustration given earlier, an examination of the competitive strength of each regional industry can be compared.

   Step 1 and 2: For durable goods, subtracting the industry’s national growth rate of 7.7 from the regional growth rate of 14.3 gives a net change of 6.6 per cent. For non-durable goods, subtraction of 14.3 from 22.2 gives a net change of 7.9 per cent.

   National industry growth rate:

   Durable Goods:	(14,000 ÷ 13,000) − 1 = 7.7 per cent
   Non-durable Goods:	(16,000 ÷ 14,000) − 1 = 14.3 per cent

   Regional industry growth rate:

   Durable Goods:	(400 ÷ 350) − 1 = 14.3 per cent
   Non-durable Goods:	(550 ÷ 450) − 1 = 22.2 per cent

   Competitiveness Differential:

   Durable Goods:	14.3−7.7 = 6.6 %
   Non-durable Goods:	22.2−14.3 = 7.9%

   Step 3: By multiplying these percentages by the base year employment data, it is observed that 23 additional employment potential were created in the durable goods industries and 36 empolyment were created in the non-durable goods industries.

   Step 4: Addition of these two figures gives us the total competitive position of 59 employments that were created in the region.

   These calculations are depicted in the table given below

   

   If the total competitive component is positive, the region has gained additional employment over those that can be attributed to national growth and the region’s industrial structure. If the total competitive component is negative then the region was less competitive than the national average.

   Employment-shift analysis examines employment changes and not changes in income, earnings, or value-added, which are alternative measures of an industry’s size. For example, although healthy industries usually expand and recruit more employees, in some cases the industry may actually reduce their number of employees to increase their competitiveness, earnings, and profits.

Analysis of Emoluments Data

Emolumets data provide another useful tool to help identify key industries in a region and serves as a complement to employment data. Although an industry may employ a high percentage of workers, it may not offer those workers high wages or it may only recruit employees on a seasonal, part time, or temporary basis.

Data generally do not distinguish among industries that pay low wages, those that require seasonal or temporary work, and those that do both. However, an inference can be drawn that industries with large numbers of employees, large wages and salaries, and, thus, high pay per employee are more important to the region than other industries. Another way to look at how well various industries pay their employees is to examine wage/salary expenses data by industry, which is also published by the Annual Survey of Industries in India.

Total emoluments is defined as the sum of wages and salaries, employer’s contribution to provident fund and other funds and workmen and staff welfare expenses.

Total Emoluments by Industry

Industry wise emolument expenses as a percentage of total income identifies the employee payment scenario in the economy. This percentage indicates the extent of labour or capital intensiveness of an industry. The region’s share of emoluments in the emoluments of a nation, however indicates the total contribution of an industry to a specific region. An examination of this figure across regions would shows any disparity in wage payments.

Emoluments per Employee by Industry

Emoluments per employee compares average wages and salaries of a region’s industries. Although there are a variety of limitations of such analysis, emolument per employee by industry provides another useful tool through which to view and compare industries.

The computations uses the following data:

• A specific region’s emolument by industry
• A specific region’s employment by industry

An industry that employs a large number of workers, yet having a relatively low average emolument per employee, is likely to play a different role in the economy from an industry with fewer employees but a high average emolument per employee. The former may pay low wages, employ a large number of part time workers, or both. Conversely, the latter may pay high wages, employ a large number of full time employees, or both.

Comparing emolument per employee with the industry growth analysis provides another dimension for analysing the data. High-growth industries with high average emoluments per employee are likely to have more attention in an economic development program than low growth, low average emoluments per industry.

Change in Emolument per Employee by Industry

Another useful measure is to examine how average emolument per employee has changed over time. As is the case with the employee data, a review of changes in emolument may lead to a better understanding of how an industry’s presence in the region may be changing. The data used for this are:

• emolument per employee by industry in the current year
• emolument per employee by industry for a base year

Calculate the change in emolument per employee for each industry using the base year data.

A positive change indicates good prospects for the industry whereas a negative change indicates an industry slowdown.

National Comparison of Average Emolument per Employee

Another way to analyse the emolument data is to compare the average regional emolument per employee with the national average for each industry. The calculation provides a starting point for further analysis of both individual industries and the regional economy as a whole. With respect to specific industries, the comparison will identify those industries that pay more or less than similar industry groupings nationally. The analysis also provides a broader picture of how average regional pay generally compares with the national average.

This figure is derived from the region’s percentage of national average emolument per employee for each industry. To calculate the percentage for each industry, the industry’s regional emolument per employee is divided by the industry’s national emolument per employee. The data required are:-

• regional emolument per employee by industry
• national emolument per employee by industry

An illustration of the emolument analysis is given below. When the regional emolument of Rs 12,000 per employee for industry A is divided by the national emolument of Rs15,000 per employee, the result is 0.8. Multiplying this by 100 gives 80 per cent. Thus, the average regional emolument per employee is only 80 per cent of the national average for that industry. In industry B, the regional emolument per employee is 106 per cent of the national average for the industry.

The results provide a general picture of how average pay in the region compares with that of the nation. If most of the percentages calculated are less than or more than the national average, the analyst might conclude that wages in the region generally fall behind or exceed those of the nation as a whole.

The emolument data and comparisons offer a rough picture of what is happening in terms of wages/ salaries in the region. Industries that pay very well may be camouflaged if highly aggregated data is used. The comparison also implies a certain level of consistency among industries within each industry grouping and that the regional industry has the same structure as its national counterpart. Hence, the emolument data analysis is to be interpreted carefully, and whenever possible detailed analysis has to be carried out before coming to a conclusion.

Input-Output Analysis

Employment and emolument data can help reveal general trends and patterns within an economy’s industries. However, in situations where additional detail is needed, particularly about the transactions between individual industries in an economy, input-output analysis can provide this information. Many states and regions use input-output analysis to try to understand the economic impact of various programmes, projects, and industry gains or losses. Illustrations of input-output analysis are the impact of efforts to encourage tourism, the addition of a new manufacturing plant to the area, the development of a new airport and so on.

Input-output analysis utilises multipliers that take into account inter-industry relationships. These relationships consist of each industry’s distribution of inputs purchased from and sold to other industries, including the government. The Annual Survey of Industries in India also provides details of total input and output value for industries.

Total Input comprises total value of fuels, materials consumed, as well as expenditures such as cost of contract and commission work done by others on materials supplied by the factory. It includes cost of materials consumed for repair and maintenance of factory’s fixed assets, including cost of repairs and maintenance work done by others to the factory’s fixed assets, inward freight, and transport charges. It also comprises of rates and taxes (excluding tax), postage, telephone and telex expenses, insurance charges, banking charges, cost of printing and stationery, and purchase value of goods sold in the same condition as purchased.

Total Output comprises total ex-factory value of products and by-products manufactured as well as other receipts such as receipts from non-industrial services rendered to others. It comprises additionally work done for others on material supplied by them, value of electricity produced and sold, sale value of goods sold in the same condition as purchased, addition in stock of semi-finished goods, and own construction.

Industry Earnings Data Analysis

Earnings data are another useful source of information on a region’s industry. Earnings by place of work data are a measure of economic output generated within a region. Thus, earnings are a useful measure of the total size of the regional economy as well as a source of information on the size of specific industries. Earnings data are also a good complement to employment data.

Earnings by Region It is useful to examine how earnings by region have changed over time. This analysis will be particularly useful when compared with employment and emolument data for the same time period.

• earnings by region for the current year
• earnings by region for a base year

The above data are used to compute the percentage change in earnings by region.

Infrastructure Sector

Infrastructure is the foundation of economic, industrial, and social development. The growth of infrastructure development on the economy is significant and it’s role as a stimulator of economic growth is indisputable.

With liberalisation and technological upgradation, private sector participation in infrastructure services has gained momentum. Today public-private partnership has emerged as a vital tool to build, manage and operate infrastructure services efficiently.

The economic reform initiative in India has raised the annual growth rate to 5–6 per cent. This has exerted pressure on the existing infrastructure. It is evident that to sustain and accelerate higher economic growth rate in the county, India needs to build, upgrade, and modernise its infrastructure. An Expert Committee on Infrastructure under Dr Rakesh Mohan, has projected a total fund requirement of about US$ 346 billion during 1996–2006. Consequently, apart from augmenting public sector investment into infrastructure, the Government of India has introduced a series of reforms to attract private sector participation and foreign direct investment.

Indian Textile Industry

The chief characteristics of the Indian textile industry are summarised are below:

• The Indian textile industry is one of the largest segments of the Indian economy, accounting for over one-fifth of the total industrial production
• The industry has a complex structure marked by the presence of large scale production units as well as small scale independent units
• The industry is manufacturer driven, where manufacturing entails large scale operations and retailing is the weakest link

Spinning Industry

• India is the third largest producer of cotton in the world and also has a strong production base for synthetic fibres
• The Indian spinning industry is dominated by cotton yarn, which also accounts for 80 per cent of the total value of yarn exports
• With an installed capacity of 37 mn. spindles, India accounts for about 20 per cent of the world’s spindle capacity

Weaving and Knitting Industry

• The fabric production industry can be divided into 3 sectors, viz, powerloom, handloom, and mill sector
• The decentralised sector accounts for 95 per cent of the total cloth production
• Knitted fabric forms 18 per cent of the total fabric production
• Despite the largest loomage in the world, India’s share in shuttle-less looms is very small (1.35 per cent)

Indian Fabric Processing Industry

• Processing is the weakest link in India’s entire textile chain
• The processing industry is decentralised and is marked by hand processing units, independent units and the composite mill sector
• The Indian processing industry uses low end technology with little investment initiative in technology upgradation
• The Indian fabric processing industry lacks R&D and innovation

Garment Manufacturing Sector

• The apparel industry is the largest foreign exchange earner, accounting for 12 per cent of India’s exports
• Small scale fabricators dominate the garment manufacturing sector
• Most of the manufacturing units use medium level technology applications

Steel Industry

• India is the tenth largest producer of steel in the world, but its per capita consumption is one of the lowest. The industry has been going through difficult times for the last five years due to overcapacity, poor demand growth, and declining tariffs
• Product price tends to remain unprofitable
• Imports that had been strong during 1999–2000 have been adversely affected due to the imposition of anti-dumping duties by the United State
• The difficult times have prompted the industry to restructure and improve operational efficiencies. Large additional capital investments are required
• Difficult times have also resulted in changes in the way steel is being marketed across the country. The customer is emerging as the king. The industry tried using the Internet as a marketing channel.
• Globally there is a move to cut production capacity to reduce overcapacity, boost steel prices and improve the performance of the steel industry

Cyclical Industries

Cyclical industries are those industries whose long term performance registers rises and falls as a result of external economic cycles, usually the national business cycle. Cyclical industries generally do well during periods of strong economic growth and do poorly during recessions. Typical cyclical industries are automobile manufacturing, residential construction, air travel, and machine tool manufacturing. An input output analysis identifies these industries’ performance.

	Output Value	Input Value
Automobile Manufacturing
Residential Construction
Machine Tool Manufacturing

There are a few counter cyclical industries. These industries do relatively better in recessions than in good times. Construction industry and cement industry exhibit this pattern, because the government may fund public works projects during recessions to offset unemployment.

Seasonal Industries

Seasonality refers to the distribution of business activity throughout the year. If an industry lacks a seasonal pattern, it is reasonable to expect that its sales will be distributed fairly evenly throughout the year. Seasonal industries have a disproportionate amount of activity in one part of the year and correspondingly less in the others. Agriculture is a seasonal industry in India. Another example is the woolen clothes retailers who do about 60 per cent of their year’s business during the four winter months.

Agricultural production, at current prices, increased by a whopping 93.87 per cent from the base year (1993–94) to Rs 4,30,088 crore during the fiscal 2000–01. The country’s agricultural production during 1993–94 stood at Rs 2,21,834 crore, according to the data released by the Ministry of Agriculture.

However, agricultural production’s percentage share in the gross domestic product (GDP) showed a decline over the same period to 22.7 per cent from 28.4 per cent in 1993–94. The fall in agricultural production has been continuing from the year 1995–96.

Strengths:

• Diversification in the sector
• Focus on high-value crops
• Top producer in the world for several commodities
• Agricultural output is no more food grain oriented
• There has been a remarkable growth in non-farm activities

Weaknesses:

• Low productivity
• Inadequate infrastructure
• Inadequate linkage with the industry
• Lack of market orientation

Opportunities:

• Substantial reduction in agriculture tariffs
• Introduction of technology farming
• Scientific outlook of cultivation process
• Priority status among industries

Threats:

• International competition
• Dry soil
• Shift of agricultural labour
• Income potential low due to innumerable intermediaries

The Confederation of Indian Industry, through its specialised sectoral infrastructure committees on power, telecom, surface transport, housing, urban infrastructure and civil aviation, plays a proactive role in policy formulation, business development, and dissemination of information.

Consumer Durable Goods Industry

The consumer durable goods industry is inevitably most essential for any economy. The consumer durable goods industry is also referred to as the fast moving consumer goods sector (FMCG). A SWOT analysis of the fast moving consumer goods sector is provided below:

Strengths:

• Well established distribution network extending to rural areas
• Strong brands in the FMCG sector
• Low cost operations Weaknesses:
• Low export levels
• Small scale players limit ability to invest in technology and achieve economies of scale
• Several similar products

Opportunities:

• Large domestic market
• Export potential
• Increasing income levels will result in faster revenue growth

Threats:

• Imports
• Tax and regulatory structure
• Slowdown in rural demand

Swot Analysis of Indian Pharmaceutical Sector

Strengths:

• Cost competitiveness
• Well developed industry with strong manufacturing base
• Well established network of laboratories and R&D infrastructure
• Access to pool of highly trained scientists, both in India and abroad
• Strong marketing and distribution network
• Rich bio-diversity
• Competencies in chemistry and process development.

Weaknesses:

• Low investments in innovative R&D
• Lack of resources to compete with MNCs for new drug discovery research and to commercialise on a worldwide basis
• Lack of strong linkages between industry and academia
• Lack of culture of innovation in the industry
• Low medical expenditure and healthcare expenditure in the country
• Inadequate regulatory standards
• Production of spurious and low quality drugs tarnishes the image of the industry at home and abroad

Opportunities:

• Significant export potential
• Licensing deals with MNCs (Multinational Companies)
• Marketing alliances to sell MNC products in domestic market
• Contract manufacturing arrangements with MNCs
• Potential for developing India as a center for international clinical trials
• Niche player in global pharmaceutical R&D

Threats:

• Product patent regime poses serious challenge to domestic industry unless it invests in research and development
• R&D efforts of Indian pharmaceutical companies hampered by lack of regulatory requirement.
• Drug Price Control Order puts unrealistic ceilings on product prices and profitability and prevents pharmaceutical companies from generating investible surplus
• Export effort hampered by procedural hurdles in India as well as non-tariff barriers imposed abroad
• Lowering of tariff protection

SUMMARY

Industry analysis helps in both selection of industry and to diversify investments suitably to fit the specific risk requirements of investors. Though there ought to be a definite link between industry and economy, some industries outperform the economy while others under perform the expectations.

Tools that are used for an industry analysis are cross sectional industry scrutiny, performance over time, evaluation of risk measures, SWOT analysis, and quantitative industry analysis in terms of employment potential, location advantages, growth rates, input-output analysis and industry earnings potential.

CONCEPTS

• Standard industry classification	• Industry cycles
• Cross sectional industry performance	• Industry risk
• Input output analysis	• Competitiveness differential
• SWOT analysis	• Industry growth rate
• Location quotient	• Employment shift analysis

SHORT QUESTIONS

1. What are the objectives of industry analysis?
2. What are the tools of industry analysis?
3. What are the sources of information for industry analysis?
4. What is the purpose of standard industry classification?
5. What are industry cycles?

ESSAY QUESTIONS

1. Explain the technique of industry analysis?
2. How does industry analysis help investment decisions?
3. How do you analyse industry risk?
4. How is the performance of an industry to be assessed for investment purposes?
5. How do you analyse the competitiveness of an industry?