SWOT Analysis of Gorakhpur as a Smart City

Submitted by:

ARUN PRATAP MISHRA

M.PHIL

Supervision:

Dr. Anjan Sen

Department of Geography

Delhi School of Economics

University of Delhi

Delhi-110007

1. Introduction

Globally, the simultaneous trends of accelerating urbanization and worsening climate change

have created a sense of urgency that has underscored the importance of the city as arguably

the most viable unit of governance to effect efficient and significant change. The widely-cited

statistic of the 2008 urban-rural tipping point, which shifted the balance for the first time in

history to a world with more urban than rural inhabitants, bears particular relevance to this

focus on cities (UN, 2008). Organizations like C40, a network of the world’s megacities, see

this as an opportunity to undertake meaningful action to reduce greenhouse gas emissions by

sharing best practices, often technologically enabled, to improve energy efficiency (C40

Cities). As cities are gaining prominence as the most practical level of government to target,

the smart city concept has shifted from being a conceptual framework to becoming an actual

urban planning model. The smart city has emerged in this context of dynamic change,

offering solutions that go beyond conventional policies and tools by integrating technology

and data management into the core components of city life.

This recent upsurge of interest in the promise of the smart city from a practical perspective is

what motivates the research reported in this proposal. Given the widespread adoption of

smart city policies and initiatives in large, potentials and limitations of Gorakhpur as a smart

city by SWOT analysis will be studied. That is what I have sought to do in my research.

Before taking up these issues, however, it is necessary to further explain what is meant by the

smart city and the global setting in which it emerged.

2. Conceptual Framework

The concept of “smart city” is evolving as a new approach to mitigate and remedy current

urban problems and make urban development more sustainable.

The smart city concept originated from that of the ‘information city’, and incrementally

evolved to an idea of an ICT-centered smart city. The concept of the smart city has six main

dimensions: a smart economy, smart mobility, a smart environment, smart people, smart

living, and smart governance. It is defined as being “smart when investments in human and

social capital and traditional (transport) and modern (ICT) communication infrastructure fuel

sustainable economic development and a high quality oflife, with a wise management of

natural resources, through participatory governance.”

The European Union (EU), in particular, has devoted constant efforts to devising a strategy

for achieving urban growth in a smart sense for its metropolitan city-regions. Other

international institutions and think tanks also believe in a wired, ICT-driven form of

development. The Intelligent Community Forum produces, for instance, research on the local

effects of the worldwide ICT revolution. The OECD and EUROSTAT Oslo Manual stresses

instead the role of innovation in ICT sectors and provides a tool kit to identify consistent

indicators, thus shaping asound framework of analysis for researchers on urban innovation.

At a meso-regional level, we observe renewed attention for the role of soft communication

infrastructure in determining economic performance. (Caragliu, Del Bo and Nijkamp, 2011)

Smart cities can be identified along six main axes or dimensions:

• Smart Economy

• Smart Mobility

• Smart Environment

• Smart People

• Smart Living

• Smart Governance

SMART ECONOMY implies Competitiveness, characterized by innovative spirit,

entrepreneurship, economic image & trademarks, productivity, flexibility of labour market,

international embeddedness, and ability to transform.

SMART PEOPLE emphasises Social and Human Capital, characterized by level of

qualification, affinity to life-long learning, social and ethnic plurality, flexibility, creativity,

cosmopolitanism/open-mindedness, and participation in public life.

SMART GOVERNANCE involves Participation, characterized by participation in decision-

making, public and social services, transparent governance, and political strategies &

perspectives.

SMART MOBILITY entails Transport and ICT, characterized by local, national and

international accessibility, availability of ICT-infrastructure, and sustainable, innovative and

safe transport systems

SMART ENVIRONMENT emphasises Natural resources, characterized by attractivity of

natural conditions, pollution, environmental protection, and sustainable resource management

SMART LIVING implies Quality of life is characterized by cultural facilities, health

conditions, and individual safety, housing quality, education facilities, touristic attractivity,

and social cohesion

These six axes connect with traditional regional and neoclassical theories of urban growth

and development. In particular, the axes are based - respectively - on theories of regional

competitiveness, transport and ICT economics, natural resources, human and social capital,

quality of life, and participation of citizens in the governance of cities. A city can be defined

as ‘smart’ when investments in human and social capital and traditional (transport) and

modern (ICT) communication infrastructure fuel sustainable economic development and a

high quality of life, with a wise management of natural resources, through participatory

action and engagement. (Caragliu, 2009)

3. Nature of Problem

Against the background of economic and technological changes caused by the globalization

and the integration process, cities in India face the challenge of combining competitiveness

and sustainable urban development simultaneously. Very evidently, this challenge is likely to

have an impact on issues of Urban Quality such as housing, economy, culture, social and

environmental conditions.

The population of India is 1210 million with approximately 31.17 or 377 million living in

urban centres and it is expected that the share of urban population will increase to about 40%

of total population by the year 2021. This is in sharp contrast to only 60 million (15 percent)

who lived in urban areas in 1947 when the country became independent. During the last sixty

years the population of the country has grown two and half times, while the urban India has

grown by nearly five times. The positive role of urbanization has often been over-shadowed

by the deterioration in the physical environment and quality of life in the urban areas caused

by widening gap between demand and supply of essential services and infrastructure. It is

further associated with many problems, such as high levels of poverty, environmental stress,

risks to productivity, high health costs, and lack of access to basic services, such as water

supply, sanitation, and housing. The insufficient availability of services, inadequate

awareness and also poor operation and maintenance has also given rise to poor city

conditions. Hence, therefore, proper study of resources both in terms of human and monetary

and awareness among people will in turn improve the smartness of the city

Establishing two smart cities in each of India's 28 states: that is the goal of the wide-ranging

project introduced by the Indian government to inject smart technology into cities home to

between 500,000 and one million people an ambition that goes hand in hand with seven other

smart-city projects already under way.

Urbanization is rampant in India, where an average of 30 people move from rural areas to the

city every minute. The country is set to build 500 new cities over the next 20 years to house

700 million more city dwellers by 2050, according to a study by consulting firm Booz &

Company.

4. Literature Review

4.1 Prior Theoretical Models of Technologically-Based Cities

To understand the smart city, it is useful to begin with the conceptual relatives of the model.

While limited in scope, they set the theoretical framework for the more holistic notion of the

smart city currently understood by the urban planning sphere. The foundations of the concept

lie in Dutton’s wired city (1987), which promised to use emerging telecommunications

technology to provide unprecedented amounts of information to households and businesses

through “information highways” that ultimately would create a communications-centric

society. Another precursor to the smart city is the digital city, a technologically-defined city

that uses widespread broadband infrastructure to support e-Government and “a global

environment for public transactions” ( Mitchell, 2000). Rather than replace the concrete

world with a virtual city, the digital city uses open industry standards to create a “service-

oriented computing infrastructure” that serves the needs of urban residents and encourages

information sharing and collaboration (Yovanof and Hazapis, 2009). Ishida (2000)

documents how Amsterdam and Helsinki—two modern smart cities—began digital city

projects in 1994 and 1996, respectively, that focused primarily on providing a “democratic

forum” for communication among citizens and with the municipality. Foreshadowing the

current concerns about a deepening digital divide in the smart city, the theoretical model of

the digital city identifies the danger of exacerbating the challenges of the “information

poor”—those who lack knowledge and social capital—despite their goals of social inclusion

(Ishida, 2000).

The diffusion of sophisticated technology at the citizen-level, however, is not the only

component of the smart city. In his discussion of the continued relevance of the physical city,

Glaeser (2011) argues that it is the spatial concentration of human capital—as seen in Silicon

Valley, for example—and not the technology itself, that will ultimately be the driver of

innovation in the cities of the future. The social capital component is crucial, as clustering of

skilled people in metropolitan areas has driven a “brain gap” between “smart” cities and their

less skilled counterparts (Berry and Glaeser, 2005; Glaeser and Berry, 2006). While this

academic conception of the smart city is limited to human intelligence and creativity—

unmistakably related to Richard Florida’s (2002) creative class and magnet cities—the social

dimension is a significant part of smart city rhetoric in the policy sphere as well. Not

surprisingly, the qualities of equity, accessibility, and just governance are stressed by many

political working groups exploring the implementation of smart cities. For instance the North

Sea Region Programme’s Smart Cities project aims to deliver better e-services to its

constituents in the North Sea region (The North Sea Region Programme, 2012), and the

Citizen Card in Zaragoza, Spain allows citizens to use public Wi-Fi, buses, sports centers,

museums, libraries, and other services with an integrated smart card (Ayuntamiento de

Zaragoza, 2012).

The intelligent city is a more comprehensive concept developed from the combination of the

digital city and the knowledge society. It is defined as a “multi-layer territorial system of

innovation” made up of digital networks, individual intellectual capital, and the social capital

of the city and its institutions, which together constitute collective intelligence (Komninos,

2008). This highly academic definition emphasizes an important point that suggests the move

towards the broader smart city concept: the mere existence of ICT does not guarantee the

development of an intelligent city. Economic competitiveness and innovation achieved

through the knowledge-based economy mark a city as intelligent, allowing it to generate a

“spatial competitive advantage” through industrial districts, regions, and learning clusters that

produce sophisticated R&D and are supported by digital networks and artificial intelligence

(Komninos 2008). What ultimately makes a city intelligent is its ability to innovate and

capitalize economically—an accomplishment that is aided by ICT, but not assured by it.

Similar to the intelligent city is the u-city, short for ubiquitous city, which refers to the

environmentally-friendly city that incorporates ubiquitous computing in buildings, open

space, and infrastructure (Lee et al. 2008).

Many variations on the smart city, such as the u-city, have been offered as a panacea to

unsustainable levels of urban consumption and emissions. For example, the concepts of the

“urban metabolism” and eco-efficiency are the foundation of the eco-tech city, which adopts

a new design paradigm that combines information technology with environmental technology

to create “ecologically-inspired tools of urbanism” (Bogunovich, 2002). Lim and Liu’s

(2010) futuristic “Smartcity” promotes urban agriculture and the integration of nature into the

urban form, ultimately allowing the creation of closed cyclical systems. Finally, the recently

coined u-eco city approaches a more pragmatic definition of the smart city by combining the

use of ICT The environmental aspect of the smart city has been discussed thoroughly in

projections about continued urbanization and the increasing demand for resource-depleting

commodities. Many variations on the smart city, such as the u-city, have been offered as a

panacea to unsustainable levels of urban consumption and emissions. For example, the

concepts of the “urban metabolism” and eco-efficiency are the foundation of the eco-tech

city, which adopts a new design paradigm that combines information technology with

environmental technology to create “ecologically-inspired tools of urbanism” (Bogunovich,

2002). Lim and Liu’s (2010) futuristic “Smartcity” promotes urban agriculture and the

integration of nature into the urban form, ultimately allowing the creation of closed cyclical

systems. Finally, the recently coined u-eco city approaches a more pragmatic definition of the

smart city by combining the use of ICT with green technology to reduce carbon emissions,

manage land and water pollution, and track waste (Lee, 2011).

The environmental aspect of the smart city has been discussed thoroughly in projections

about continued urbanization and the increasing demand for resource-depleting commodities.

Many variations on the smart city, such as the u-city, have been offered as a panacea to

unsustainable levels of urban consumption and emissions. For example, the concepts of the

“urban metabolism” and eco-efficiency are the foundation of the eco-tech city, which adopts

a new design paradigm that combines information technology with environmental technology

to create “ecologically-inspired tools of urbanism” (Bogunovich, 2002). Lim and Liu’s

(2010) futuristic “Smartcity” promotes urban agriculture and the integration of nature into the

urban form, ultimately allowing the creation of closed cyclical systems. Finally, the recently

coined u-eco city approaches a more pragmatic definition of the smart city by combining the

use of ICT with green technology to reduce carbon emissions, manage land and water

pollution, and track waste (Lee, 2011).

While most discussions of the “green” potential of smart cities are purely theoretical, Hin and

Subramaniam (2012) examine the deployment of intelligent transportation systems, such as

electronic road pricing, as a practical solution with ecological benefits through their case

study of Singapore’s innovative ICT-based transportation policies. While the authors restrict

themselves to the smart mobility component of the model, they acknowledge that the “‘smart

city’ is thought to involve the operation of at least six dimensions with the prefix ‘smart’”:

people, living, economy, mobility, environment, and governance. This comprehensiveness is

the distinguishing factor of the smart city, which integrates a number of physical,

institutional, and digital components to create a holistic definition of what smart planning

would look like. This recent shift in the use of the smart city as a practical—rather than

theoretical—planning term has led to the delineation of the functional characteristics of the

model. While no modern smart city has achieved all aspects their entirety, attempts to define

these characteristics provide a basis for the continued development of smart cities.

4.2 The Smart City

Though the smart city has recently emerged as a widely discussed urban planning model both

in the policy and theoretical spheres, there is a remarkable lack of consensus on the term’s

definition. In general, the smart city is characterized by the extensive use of internet and

communications technology (ICT) infrastructure to drive urban growth through the improved

delivery of city services, environmentally sustainable development, and growth of social

capital. Much of the literature on smart cities comes from one perspective, however,

concentrating heavily on either the technological, environmental, or social element; little

attention is paid to the governance component, and it is only recently that more holistic

definitions have emerged.

The six characteristics mentioned by Hin and Subramaniam (2012)—people, living,

economy, mobility, environment, and governance—were developed by Giffinger et al. (2007)

to rank the “smartness” of medium-sized cities across Europe. They broke the six areas into

74 measurable indicators such as the flexibility of the labor market and sustainable resource

management. The study was instrumental in attempting to operationalize the smart city rather

than study it theoretically, and more importantly, in developing the six criteria often

referenced in smart city policies worldwide. Townsend’s similarly holistic model shows the

smart city more generally as the intersection of urbanization and ubiquitous digital

technology, with four main “intelligent” drivers: the commons, markets, design and planning,

and governance (Institute for the Future, 2010). Rather than break the city down into sections

—the model of six characteristics recalls the legacy of department-led city governance—this

understanding of the smart city identifies the scales at which ICT can impact urban human

interactions.

The literature acknowledges the lack of consensus on a single meaning for the smart city and

consequently, articles often start with a redefinition of the term (Caragliu et al, 2011; Hin and

Subramaniam, 2012; Hollands, 2008; Nam and Pardo, 2011). These evolving definitions

make the analysis of the smart city somewhat inconsistent; as a point of departure for

productive discussion, then, Schaffers et al. (2011) accept a previously established definition

of the smart city: “when investments in human and social capital and traditional (transport)

and modern (ICT) communication infrastructure fuel sustainable economic growth and a high

quality of life, with a wise management of natural resources, through participatory

government” (Caragliu et al., 2011). The smart city distinguishes itself from its predecessors

in its emphasis on the specific instrumentation that will enable urban problem solving,

specifically embedded systems—sensor technology, mobile phones, smart meters, etc.—and

big data—large and complex datasets used to analyze urban life (Schaffers et al., 2011). The

most important ICTs that contribute to the physical smart city are widespread broadband

connectivity, smart personal devices, open data infrastructures, public technology, mobile

phones, smart meters, etc.—and big data—large and complex datasets used to analyze urban

life (Schaffers et al., 2011). The most important ICTs that contribute to the physical smart

city are widespread broadband connectivity, smart personal devices, open data

infrastructures, public interfaces, and cloud computing (Institute for the Future, 2010).

5. Research Objectives

1. To analyze the Spatio-Temporal pattern of development of Gorakhpur city.

2. To evaluate whether Gorakhpur qualifies as a smart city.

3. SWOT analysis of Gorakhpur as a smart city.

6.Study Area

Figure: Location of Study Area

Gorakhpur is a city in the eastern part of the state of Uttar Pradesh in India, near the border

with Nepal. Gorakhpur occupies the north eastern corner of the state of Uttar Pradesh, and is

located to the north of the river Ghaghra. It is about 265 km east of the capital city Lucknow,

on National Highway No 28. Gorakhpur is located between Latitude 26º 13‟ N and 27º 29' N

and Longitude 83º 05' E and 83º 56‟ E. It is the administrative headquarters of Gorakhpur

District and Gorakhpur Division. Gorakhpur is famous as a religious centre: city was home to

Buddhist, Hindu, Muslim, Jain and Sikh saints and is named after the medieval saint

Gorakshanath. It is also the birthplace of Paramhansa Yogananda, Chandragupta Maurya.

The city is also home to many historic Buddhist sites, Imambara, an 18th century dargah, and

the Gita Press, a publisher of Hindu religious texts.

In the 20th century, Gorakhpur was a focal point in the Indian independence movement.

Today, the city is also a business centre, hosting the headquarters of the North Eastern

Railways, previously known as Bengal Nagpur Railways, and an industrial area, GIDA

(Gorakhpur Industrial Development Authority) 15 km from the old town.

Gorakhpur city is well connected to all major cities of India. The North Eastern Railways

station is situated in the city, which is one of the most utilized forms of transportation.

Frequent bus services are also available from Gorakhpur to cities including Varanasi,

Lucknow, Kanpur. The main bus stand is located near the railway station. Gorakhpur also has

a airport, which is just eight km from the city.

If we look at the overall identity of Gorakhpur as a city, it is evident three are some factors

which are playing major role in the nurturing of Gorakhpur as a city of major importance.

These are mainly related to religious significance of the city, transportation hub and strategic

significance of the city. Gorakhpur is considered a religious center containing many historic

temples and sites for both Hinduism and Buddhism. It is named after the ascetic Guru

Gorakshnath, a saint that popularized “Hath Yoga” a form of yoga which concentrates on

mastering natural power. The Gorakhnath Temple where he studied is a major tourist

attraction in the city of Gorakhpur. Gorakhpur city is also at the short distance from the

pilgrimage centre of Kushinagar, the place where Buddha died. Gorakhpur is also a

transportation hub because it serves as the headquarters of the North Eastern Railway, one of

the 16 major railway zone in India. The station offers Class A railway station facilities. On

October 6, 2013, Gorakhpur became the world's Longest Railway platform. Gorakhpur has

potential to be a strategic city because of its proximity to Nepal and China Border. An air

force station in Gorakhpur was established in 1963 as Gorakhpur Airport, with a variety of

planes and services, most notably Jaguar fighter planes and the second oldest helicopter unit

of Indian Air Force (No. 105 Helicopter Unit). It is one of the biggest air force stations in

Asia. where aircraft regularly land and take off, with runways, navigational aids, and major

facilities for the commercial handling of passengers and cargo in the country of India.The air

force station, Gorakhpur which is extremely vital for the Defence of the eastern part of the

country is equipped with the latest and most sophisticated fighter and bomber planes and

equipments and it comes under the Central Air Command (CAC) headquartered at

Bamrauli,Allahabad.

7.Data Base and Methodology

Data for this research would be collected primarily from secondary sources and primary

sources. Primary data for this research would be collected through a questionnaire survey,

interview of people, who are living in Gorakhpur.

The secondary data would be obtained from state and central government ministerial reports,

Uttar Pradesh Statistical Hand Book 2012, Economic survey of India 2013, Economic Survey

of Uttar Pradesh 2012, District Statistical Hand Book of Gorakhpur, Election Commission of

India website, Cense2001, 2011. For methodology concerns, the methodology and indicators

developed by Centre of Regional Science (SRF), Vienna University of Technology, Vienna,

Austria on Smart city has been adopted withsome modification according to the study area.

To describe a smart city and its six characteristics, it is necessary to develop a transparent and

easy hierarchic structure, where each level is described by the results of the level below. Each

characteristic is therefore defined by a number of factors. Furthermore each factor is

described by a number of indicators. The factors were defined in a series of workshops

having the overall target of smart city development. Finally 31 factors were chosen to

describe the 6 characteristics. To analyse the performance in each factor 1-4 indicators were

selected and assigned to each factor, taking total of 74 indicators.

In total 74 indicators were selected for the evaluation, whereas 48 (65 %) are based on local

or regional data and 26 (35 %) are based on national data.The complete list of indicators is as

follows:

SMART ECONOMY

Factor:Innovative spirit

Indicator: Level

1. R&D expenditure in % of GDP (Regional )

2. Employment rate in knowledge-intensive sectors (Regional)

3. Patent applications per inhabitant (Regional)

Factor:Entrepreneurship

Indicator: Level

1. Self-employment rate (Local)

2. New businesses registered (Local)

Factor: Economic image & trademark

1. Importance as decision-making Centre (HQ etc.) (Regional)

Factor: Productivity

Indicator:

1. GDP per employed person(Local)

Factor: Flexibility of Labour market

1. Unemployment rate (Regional)

2. Proportion in part-time employment (Local)

Factor: International embeddedness

1. Companies with HQ in the city quoted on national stock market (Local)

2. Air transport of passengers (Regional)

3. Air transport of freight(Regional)

SMART PEOPLE

Factor: Level of qualification

1. Importance as knowledge Centre (top research Centre,Top universities etc.)

(Regional)

2. Population qualified at levels 5-6 ISCED (Local)

3. Foreign language skills (National)

Factor: Affinity to life-long learning

1. Book loan per resident (Local)

2. Participation in life-long-learning in % (Regional)

3. Participation in language courses (National)

Factor: Social and ethnic plurality

1. Share of foreigners (Local)

2. Share of national born abroad (Local)

Factor: Flexibility

1. Perception of getting a new job (National)

Factor: Creativity

1. Share of people working in creative industries (National)

Factor: Cosmopolitanism/open mindedness

1. Voters turnout at Indian elections (Local)

2. Immigration-friendly environment (attitude towards immigration) (National)

3. Knowledge about the India (National)

Factor: participation in public life

1. Voters turnout at city elections (local)

2. Participation in voluntary work (National)

SMART GOVERNANCE

Factor: participation in decision-making

1. City representative per resident (Local)

2. Political activity of inhabitants (National)

3. Importance of politics for inhabitants (National)

4. Share of female city representatives (Local)

Factor: Public and social services

1. Expenditure of the municipal per resident in PPS (Local)

2. Share of children in day care (local)

3. Satisfaction with quality of schools (National)

Factor: Transparent governance

1. Satisfaction with transparency of bureaucracy (national)

2. Satisfaction with fight against corruption (National)

SMART MOBILITY

Factor: Local accessibility

1. Public transport network per inhabitant (local)

2. Satisfaction with access of public transport (national)

3. Satisfaction with quality of public transport (national)

Factor: (Inter-) national accessibility

1. International accessibility (regional)

Factor: availability of ICT-infrastructure

1. Computers in households (national)

2. Broadband internet access in households (national)

Factor: Sustainable innovative and safe transport systems

1. Green mobility share (non-motorized individual traffic) (local)

2. Traffic safety (local)

3. Use of economical cars (national)

SMART ENVIRONMENT

Factor: Attractivity of natural conditions

1. Sunshine hours (local)

2. Green space share (local)

Factor: Pollution

1. Summer smog (local)

2. Particulate matter (local)

3. Fatal chronic lower respiratory per inhabitant (regional)

Factor: Environmental protection

1. Individual efforts on protecting nature (national)

2. Opinion on nature protection (nature)

Factor: Sustainable resource management

1. Efficient use of water (use per GDP) (local)

2. Efficient use of electricity (use per GDP) (local)

SMART LIVING

Factor: Cultural facilities

1. Cinema attendance per inhabitant (local)

2. Museum visits per inhabitant (local)

3. Theatre attendance per inhabitant (local)

Factor: Health condition

1. Life expectancy (local)

2. Hospital beds per inhabitant (local)

3. Doctors per inhabitant (local)

4. Satisfaction with quality of health system (national)

Factor: Individual Safety

1. Crime rate (local)

2. Death rate by assault (regional)

3. Satisfaction with personal safety (national)

Factor: Housing quality

1. Share of housing fulfilling minimal standards (local)

2. Average living area per inhabitant (local)

3. Satisfaction with personal housing situation (national)

Factor: Education facilities

1. Student per inhabitant (local)

2. Satisfaction with access to educational system (national)

3. Satisfaction with quality of educational system (national)

Factor: Touristic attractivity

1. Importance as tourist location (overnights, sights) (regional)

2. Overnights per year per resident (local)

Factor: Social cohesion

2. Perception on personal risk of poverty (national)

3. Poverty rate (national)

Standardizing and aggregating data:

To compare the different indicators it is necessary to standardize the values. One method to

standardize is by z-transformation. This method transforms all indicator values into

standardized values with an average 0 and a standard deviation 1. It has the advantage to

consider the heterogeneity within groups and maintain its metric information. Furthermore a

high sensitivity towards changes is achieved.

The secondary data will also be analyzed with the help of various useful statistical methods

and techniques, different cartographic techniques. Different software like MS Excel, Arcview

and SPSS will be applied.

SWOT Analysis

In the 1960’s and 70’s, Albert Humphrey is said to have developed this strategic planning

tool using data from the top companies in America at the time. A SWOT Analysis looks at

the strengths, weaknesses, opportunities and threats that are relevant to an organization in a

new venture. A SWOT Analysis is a tool which allows users to look at the direction a

company or organization may wish to move towards in the future. A SWOT Analysis is a

useful tool, which in conjunction with others can help make in-formed decisions.

By specifying clear objectives and identifying internal and external factors that are either

helpful or not, a short and simple SWOT analysis is a useful resource which may be

incorporated into an organizations strategic planning model.

Strengths- Internal attributes that are helpful to the organization to achieving its objective

Weaknesses – Internal attributes that are harmful to the organization to achieving its

objective

Opportunities – External factors that help the or-ganization achieve its objective

Threats - External factors that are harmful to the organization to achieving its objective

After identifying the SWOT’s, identification of the factors and their interdependence helps

clarify the steps needed to achieve the ending objectives.

Internal and External Factors

The aim of any SWOT analysis is to identify the key internal and external factors that are

important to achieving the objective. SWOT analysis groups key pieces of information into

two main categories:

Internal factors – The strengths and weaknesses internal to the organization.

External factors – The opportunities and threats presented by the external

environment.

The internal factors may be viewed as strengths or weaknesses depending upon their impact

on the organization's objectives. What may represent strengths with respect to one objective

may be weaknesses for another objective. The factors may include all of the 4P's; as well as

personnel, finance, manufacturing capabilities, and so on.

The external factors may include macroeconomic matters, technological change, legislation,

and socio-cultural changes, as well as changes in the marketplace or competitive position.

The results are often presented in the form of a matrix.

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