iBusiness, 2011, 3, 23-29
doi:10.4236/ib.2011.31004 Published Online March 2011 (http://www.SciRP.org/journal/ib)
Coping with Imprecision in Strategic Planning: A
Case Study Using Fuzzy SWOT Analysis
Hasan Hosseini-Nasab1,2, Amin Hosseini-Nasab3, Abbas S. Milani2*
1Department of Industrial Engineering, Yazd University, Tehran, Iran; 2School of Engineering, University of British Columbia, Ke-
lowna, Canada; 3Department of Industrial Engineering, Amirkabir University of Technology, Tehran, Iran
Received December 9th, 2010; revised December 27th, 2010; accepted December 30th, 2010.
ABSTRACT
In this article, it is shown that using the co nventiona l SWOT analysis in the vicinity o f strategic regions in th e matrix of
internal and external factors, ambiguity can exist in defin ing fin a l strateg ies. To cop e with th is difficu lty and to enh an ce
the accuracy of the underplaying decision process, a straightforward fuzzy SWOT analysis is presented a nd exemplifie d
by extracting and analyzing strengths, weaknesses, opportunities and threats in a company known as KPPP. The analy-
sis is performed based on actual field data using 90 external and 85 internal factors and a group of 12 experts. Next to
the identificatio n of the fuzzy SWOT matrix, it is shown that the external threats and intern al weaknesses of KPPP can
have stronger effects compa red to its external opportunities and intern al strengths.
Keywords: Fuzzy Applications, Internal and External Factors, Strategic Planning, SWOT Analysis
1. Introduction
It is well known that a company’s success in today’s
competitive business environment requires its ability to
create and update strategic plans [1-6]. While various
management analysis techniques such as the Total Qual-
ity Management (TQM) [7-10] and Re-engineering [2,4]
have proven to be beneficial for meeting organizational
specific objectives, strategic planning remains the single
most important element for companies’ overall success.
Reported case studies indicate that organizations using
the principles of strategic planning are by far in better
condition in marketing, profitably and beneficiation
[2,4,11,12].
Earlier studies have been performed on improving the
classical strategic planning methods such as the strengths,
weaknesses, opportunities, and threats (SWOT) analysis.
Ghazinoory et al. [13] applied a fuzzy set approach to
both the internal and external factors using conventional
membership functions. The algorithm prioritizes and
extracted the most significant strategies based on inten-
sity of effects. Kuo-liang and Lin Shu-chen [14] pro-
posed a fuzzy SWOT method to evaluate the competitive
environment of different transshipment locations as in-
ternational distribution centers (IDC) in the Pacific-Asian
region. Their work suggested that the fuzzy method iden-
tifies more competitive locations as compared to the
conventional SWOT. Zhangjiajie [15] presented a new
fuzzy decision-making tool for small and medium enter-
prises (SMEs) under a set of ambiguous strategic policies.
The model can assist SMEs to train their own core
strengths and gradually explore their ideal strategies. Lee
et al. [16] presented a mechanism for integrating a fuzzy
cognitive map (FCM) within strategic planning simula-
tions, where FCM helps decision makers understand
complex dynamics between a certain strategic goal and
related environmental factors. Wang and Chang [17]
investigated the properties of fuzzy scenario analysis to
cope with the issue of data shortage and the linguistic
expression of experts. Their study successfully incorpo-
rated the fuzzy set theory into the scenario analysis such
that uncertainties are accounted for. Kahraman1 et al. [18]
proposed a method to evaluate different alternative
strategies for an e-government application in Turkey.
They used the SWOT approach in conjunction with the
analytic hierarchy process (AHP) to prioritize their
strategies. Shuliang et al. [19] proposed a hybrid ap-
proach for integrating a group Delphi, fuzzy sets and
expert systems in developing marketing strategies. The
method was specifically employed to help groups of
managers undertake SWOT analysis. It is worth adding
that next to the strategic planning area, fuzzy sets have
been widely used in a range of applications including

Coping with Imprecision in Strategic Planning: A Case Study Using Fuzzy SWOT Analysis 24
linear and nonlinear control, pattern recognition, financial
systems, etc [13,18,20].
This article is intended to first indentify a potential
imprecision problem in the use of conventional SWOT
analysis for particular strategic planning problems, and
then present an application of a fuzzy SWOT method to
resolve the problem. The method has been exemplified
via a case study on the strategic planning of the KPPP
company. The case is based on actual field data, col-
lected from 12 experts based on 90 external and 85 in-
ternal decision factors. Section 2 reviews the basics of
the conventional SWOT analysis. Section 3 identifies the
potential problem with the conventional SWOT matrix
and extends the analysis to the fuzzy method. Section 4
presents the KPPP’s case study and discusses the results
using a quantitative measure for determining the total
distance between the obtained fuzzy internal and external
factors. Section 5 concludes the article.
2. Basic SWOT Analysis
Strategic planning in an organization can involve making
decisions on allocating resources such as capital and
people. During strategic planning, main objectives are
often presented as vision and mission statements and
subsequently the company’s strengths, weaknesses, op-
portunities, and threats (SWOT) are assessed [21-31]. The
vision statement is an image or state to which the com-
pany aspires. It emphasizes the desire of where the com-
pany would be at a specific time. The nature of a business
is often expressed in terms of its mission indicating the
purpose of the business; for example, to design, develop,
manufacture and market specific product lines for sales
based on certain features to meet the identified needs of
specific customer groups via certain distribution channels
in particular geographic areas. Having built up a picture
of the company’s past and current achievements, the
SWOT analysis can commence. The following four steps
are considered for analyzing the internal factors:
1) All internal factors are scored based on their exist-
ing status in the company. The scores are crisp values
and usually range from −2 to 2 as shown in Figure 1.
2) An overall importance coefficient/weight of 1 to
100 is assigned to each internal factor based on the
viewpoints of experts. The weights are then normalized
such that their sum is one.
3) The weighted score of each factor is calculated by
multiplying the corresponding normalized importance
Figure 1. Scoring of the internal (or external) factors based
on their importance.
coefficient by the score of the factor from Step 1.
4) The summation of the weighted scores is considered
as the overall score of internal factors.
The external opportunities and threats to the company
can fall in the areas such as customers, distribution
channels, identities, substitute products, etc. The same
procedure used for scoring the internal factors can be
employed to evaluate the external factors; i.e., eventually
an overall weighted score for the external factors is esti-
mated.
Next, the company’s overall internal and external
scores are used to locate its position in a SWOT matrix
as shown in Figure 2. The two overall internal and ex-
ternal scores define the coordinates of a strategic point
that fall in one of the matrix cells. The matrix cells nor-
mally indicate known strategies for the managers. For
example, if a company's position is located in cell #1,
growth strategies for adding new products are proposed;
for cell #9, divestiture strategies are considered and so
on.
3. A Fuzzy SWOT Analysis
Whilst a list of strategies should be suggested based on
the final position of a company in the SWOT matrix, the
crisp division of two adjacent cells may be a methodo-
logical limitation. This can be especially problematic
when most of the data collected during the scoring proc-
ess are qualitative. For instance, assuming a company
with a total external score of 1.5 and a total internal fac-
tor of 1.001, the company’s position is then placed in cell
#1 in Figure 2 and therefore, growth strategies for add-
ing new products would be proposed. In a very similar
case, assuming the same external score of 1.5 but with an
internal score of 0.999, the company’s position would be
placed in cell #2 and consequently, a different strategy
such as keeping existing situation would be proposed.
Hence, in such cases, two close internal or external
scores can cause a major difference in the dictated
2
1
-1
-2
-2 1 2
Internal Score
External Score
-1
3 2 1
6 5 4
9 8 7
Figure 2. Matrix of internal and external scores.
–2 –1 1 2
Very weak Weak Strong Very Strong
–
2
–
1
–
1
–
2

Coping with Imprecision in Strategic Planning: A Case Study Using Fuzzy SWOT Analysis25
strategies, while practically there are no large differ-
ences between the companies’ ability and status with
respect to the internal and external factor values (in the
presence example, 0.999 vs. 1.001).
To overcome the above difficulty, a fuzzy scale (Fig-
ure 3) for scoring the internal and external factors may
be considered and consequently, the evaluation matrix
can compass fuzzy regions as shown in Figure 4. Using
this fuzzy approach, the likelihood of a company’s stra-
tegic point falling in a weak/medium or medium/strong
state in the vicinity of two adjacent cells varies gradually
(with a reasonable slope of the membership function). As
a result, a sudden change from the weak to medium or
from the medium to strong state is avoided. For example,
recalling Figure 4, internal scores of 0.999 or 1.001
would both be considered within the intersection of the
weak and medium states.
The following steps are proposed within the fuzzy
SWOT framework:
1) Analyze the background data and define company’s
vision.
2) List the company’s all external environment factors,
including political, economical, social and technological
factors. For each factor, its sub-factors/attributes can also
be defined.
3) List the company’s all internal environment factors,
including those related to the marketing, functional
sources, employee, general management, information
and quality management. For each internal factor, its
attributes can also be defined.
4) List the effective internal and external factors based
Figure 3. Triangular fuzzy numbers for scoring internal and
external factors of the company.
Figure 4. Fuzzy matrix of the internal and external factors.
on the company’s main objectives and activities.
5) Considering a factor (e.g., the j-th factor), define a
triangular fuzzy number (
j
k
A
,
j
k
B,
j
k
C) for each of its
attribute values (e.g., the k-th attribute) based on a scale
of −2 to +2, where −2: complete threat/weakness, −1:
weak threat/weakness, + 1: weak opportunity/strength, +
2: complete opportunity/strength.
j
k
B is the most
probable (average) value,
j
k
A
is the minimum and
j
k
C
is the maximum (note that
j
kjkjk
A
BC). If N experts
(i1,, N

) are employed during data collection, each
expert may define a fuzzy number such as (i
j
k
A
,i
j
k
B,i
j
k
C).
Averaging these fuzzy numbers for the j-th factor, k-th
attribute gives [32]
(
j
k
A
,
j
k
B,
j
k
C) = 1
N (
1
Ni
j
k
i
A


,
1
Ni
j
k
i
B

,
1
Ni
j
k
i
C

). The
process can be repeated for all attributes of external and
internal factors.
6) Define a weight,
j
k, for each attribute based on
its influence on the company’s activities and objectives
by using a scale of 1 to 100 (subsequently the weights
can be normalized to one). Weights may be found by
brain storming among experts or by averaging individual
weights from the experts.
w
7) Calculate an average fuzzy numbers
j
Cfor each
factor based on its attribute values and weights:
j
A

1
j
n
j
kjk
wA


k
,j B

1
j
n
j
kjk
wB


k
, j C
1
j
n
j
kjk
wC


k
;
where
j
n is the number of attributes for the j-th factor.
8) Calculate a total score of the internal factors (FIF)
and a total score of the external factors (FEF) by sum-
ming the corresponding fuzzy scores (
j
A
,
j
B,
j
C) from
the previous step. Note that FIF and FEF will also be
fuzzy numbers.
Weak medium strong
9) Locate the company’s position in a fuzzy SWOT
matrix based on the FIF and FEF values. The located
coordinates should indicate a fuzzy triangular region,
instead of a single point that would normally be obtained
using the conventional SWOT.
4. Case Study
Due to the confidentiality reasons, let us name the com-
pany under study ‘KPPP’. KPPP carried out various na-
tional and international activities. The IT department of
KPPP has the role of facilitating the technology integra-
tion and IT service development towards integrated solu-
tions. This department manages KPPP’s electronic ser-
vices and internal information systems. In the beginning
of 2011, KPPP made the decision that it should revisit its
strategic planning for a better performance.
The company’s vision during strategic planning is de-
fined, e.g., based on a better control over its future, the
–2 –1 1 2
3 2
1
–
1
–
2
weak medi
u
weak medium strong
Fuzzy External Score
t
2 1
6 5 4
9 8 7
2
-1
1
–
2
0
1
Membership function
0 1

Coping with Imprecision in Strategic Planning: A Case Study Using Fuzzy SWOT Analysis 26
need for better circulation, environmental alterations,
opportunities and threats and also cultural modifications.
Considering the opportunity for a strategic evaluation of
the company’s production and service, the vision and
objective of KPPP were defined as follows. ”The com-
pany is capable of continuing the production and service
with a high level of quality and quantity and with a stable
progress, and it can aim at becoming the source of better
services for other related industries. “
1) All potential internal and external factors on
KPPP’s activities and aims were listed.
2) The effective factors were short-listed, regardless of
their form of influence (positive or negative effect). It
was recognized that an exact analysis of internal envi-
ronment is essential in confronting weaknesses by utiliz-
ing strengths. Internal factors were classified into mar-
keting, money, employees, general management, etc. The
main external factors were grouped into political, social,
economical, technological, etc. In total, 5 external and 7
internal factors were used (to be discussed for Tables 3
& 4).
To apply the fuzzy SWOT method of Section III, data
for both internal and external environmental factors were
collected from a committee of 12 experts in the area. In
doing so, the company's general background and its condi-
tion relative to the nation’s activities were accounted for;
e.g., the company's share in job security and employment.
3) The attributes of each factor in Step 2 were identi-
fied. For instance, for the ‘Economical’ factor (Table 1),
attributes were chosen as: more predictable cash flow,
Table 1. Fuzzy external factors (sample data for the “Economical” factor).
fuzzy number Priorities (weights)
1
m
A
1
m
B
1
m
C on scale of
[1-100]
Normalized
value
Factor and its Attributes
1 1.2 1.5 65 0.030 More predictable cash flow
–1.6 –1.3 –1 80 0.035 Breakability to natural disaster
0.1 0.2 0.4 77 0.034 Gaining financial knowledge
0.2 0.5 1.1 80 0.035 Minimum salary
–0.8 –0.4 –0.1 49 0.023 Rate of bank interest
... .... ..... .... .... ....(total of 28 attributes)
Economical
Table 2. Fuzzy internal factors (sample data for the “Employee” factor).
Factor conditions Priorities
Minimum
amount
Most possible
amount
Maximum
amount 0-1 1-100Factor and its Attributes
0.2 0.3 0.6 0.06781 Happy employees
–1.5 –1 –0.5 0.05370 Employee union
–1 –0.6 –0.2 0.06883 Employee shortage
1.1 1.2 1.5 0.06680
Employee with high perform-
ance
0 0.5 1 0.06984
Low level of employee pay-
ment
0 1 1.9 0.05370 Skilled employee
.... .... .... .... .... (total of 15 attributes)
Employee
Table 3. Fuzzy external environmental factor analysis of KPPP.
Final Score (fuzzy average)
Minimum amount Most possible
amount Maximum amount
Number of
factors External Group Title #
–0.0072 0.005 0.0213 24 Political 1
–0.0133 –0.0065 0.0075 28 Economical 2
–0.045 –0.027 0.0091 20 Social 3
–0.062 –0.025 0.002 12 Technological 4
0.103 –0.041 0.018 6 Others 5
–0.23 –0.11 0.034 90 FEF

Coping with Imprecision in Strategic Planning: A Case Study Using Fuzzy SWOT Analysis27
Table 4. Fuzzy internal environmental factor analysis of KPPP.
Final Score (fuzzy average)
Minimum
amount
Most possible
amount
Maximum
amount
Number of
Attributes Factor Group Title #
–0.0745 –0.0451 –0.011 8 Marketing 1
–0.0638 –0.023 –0.0214 5 Money 2
–0.0061 0.02 0.063 11 Activities 3
–0.044 –0.0243 –0.0183 15 Employee 4
–0.0167 –0.0149 –0.0008 21 General management 5
–0.0362 –0.0173 –0.0016 10 Information 6
–0.0251 –0.0002 –0.0043 15 Quality management 7
–0.27 –0.11 –0.018 85 FIF
breakability to natural disaster, gaining financial knowl-
edge, minimum salary, and rate of bank interest.
4) Fuzzy numbers using the linguistic scale of Figure
3 were assigned by each expert and an average score was
found for each attribute of a factor as (
j
k
A
,
j
k,B
j
k).
Sample results are included in Tables 1 and 2 for the
external ‘Economical’ and internal ‘Employee’ factors,
respectively. The weight of each attribute within each
factor category (e.g., political) was also determined con-
tingent to its influence on the KPPP activities. A scale of
1 to 100 was used and the final weights were normalized.
C
1) The attribute scores within each factor group were
averaged and a total score for the factor was calculated as
(
j
A
,
j
B,
j
C); . Complete results are shown in
Tables 3 and 4. For instance, the weighted average of
attribute scores in Table 1 for the ‘Economical’ factor
resulted in (−0.0133, −0.0065, 0.0075) as indicated in
Table 3.
1, ,12j
To locate the strategic position of KPPP in a SWOT
matrix, the FEF and FIF values were calculated by
summing the fuzzy number in Tables 3 and 4, respec-
tively. It was found that FEF= (−0.23, −0.11, 0.034) and
FIF= (−0.27, −0.11, 0.018). Consequently, the locations
of the best, most probable, and worst strategic points
were shown in Figure 5.
4.1. Determining a Distance between the Internal and
External Factors - a Decision-Making Case:
Managers often intend to know which factors (external or
internal) are more influential in their strategic decision
making. The distance between the two fuzzy numbers of
FIF and FEF can be calculated
as:

123
,,aaa
 


123
,,bbb
,dFIFFEF



=

123 123
22
4
aaa bbb
In the KPPP case this gives:

,
0.272( 0.11)0.0180.232( 0.11)0.0340.014
4
dFIFFEF




  
Considering a negative distance (FIF-FEF<0), it could
be recommended that the total effect of the internal
(strengths/ weaknesses) factors is greater than the total
effect of the external (opportunities/threats) factors and
therefore, more focus should be made on reducing the
company’s weaknesses and strengthening its strengths.
Finally, of the three strategic points in the Fuzzy
SWOT matrix in Figure 5, two points have been located
in the threatening area; i.e., emphasizing sizable external
threats and internal weaknesses of KPPP. Therefore,
close attention should be paid to the external threats and
internal weaknesses in making strategies for this com-
pany. The only point located in the desirable area with
positive factor values is point 1 (with the least possible
external threats and internal weaknesses). Nevertheless,
considering the minimum likelihood of this point, no
strategy would be taken up on point 1. In fact, only a
small area portion (< 25%) of the overall triangle has
fallen in the positive region. Both points 2 and 3 belong
to a strategic cell with a score between 0 and −1 (me-
dium-to-week).
5. Conclusions
Internal strengths and weaknesses are vital for strategic
planning of companies to cope with the external threats
and benefit from the external opportunities. One of the
potential shortcomings of the conventional SWOT matrix
was shown and a simple fuzzy SWOT approach was
suggested to overcome the problem. The method was
exemplified using a case study in the KPPP company. It
was shown that the current strategic position of the KPPP
company is identifiable as a three-point region by means

Coping with Imprecision in Strategic Planning: A Case Study Using Fuzzy SWOT Analysis 28
Internal fuzzy factors
Point 3: The worst condition fo
r
internal and external factors
Figure 5. Strategic position of KPPP in the fuzzy SWOT matrix.
of the coordinates of FIF and FEF fuzzy numbers. In
particular, the position of the ideal point with the least
possible external threats and the least possible internal
weaknesses, or the most external opportunities and the
most internal strengths was revealed. Similarly, strategic
points corresponding to the most probable (mean) and
the worst condition were located. Eventually, based on
the general position of the strategic triangle (relative po-
sition of the three points), a realistic strategy can be cho-
sen. In the conventional SWOT analysis, only one point
is identifiable and it may cause a decision ambiguity,
specially in the vicinity of adjacent cells in the SOWT
matrix. Further research is worthwhile to extend the
fuzzy approach to more complex strategic planning mod-
els (e.g., TOWS [33]) where interactions among decision
factors may also be included.
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b
le (mean)
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