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The Usage of Failure Modes and Effects Analysis Technique while Process Improvement
in Managerial Accounting Courses
By: Cengiz YILMAZ
Faculty of Business Administration, Afyon Kocatepe University, Turkey
(Tel: 00 90 505 6625019 E-mail: ylmzcc@yahoo.com)
Abstract
Failure mode and effect analysis is a widely accepted and useful technique for the
practitioners, which explicitly exposes the failures and their mod in a specific system, besides
the technique critically analyses the relationship between the causes and effect of the failures.
In this study, it is tried to draw a framework for process improvement in managerial
accounting courses by using FMEA model. FMEA is used for identifying the risk factors and
determining the risk priority numbers of the potential risks in terms functional and
characteristic bases. In the study, most risky main factor (subject) in managerial accounting
courses was “Measuring relevant costs and revenues for decision making”. This main factor
includes of three sub-factors respectively; lack of analytic abilities, lack of managerial
thinking, lack of fundamental accounting capabilities. These three sub-factors are subjected to
the process improvement; reminding of mathematical rules, reminding of basic managerial
subjects and reminding of basic accounting principles. Additionally, more questions are
solved during the course about the subject. This first step improvement positively affected the
success of students. In the light of actual improvement an estimation of further improvement
results projected at the end of the study. Hence this study a framework is drawn for
improvement in managerial accounting courses which can be modified to the other courses
easly for risk assements and the improvements. It is believed that study can increase the
academicians’ knowledge (for increasing efficiency in the courses) and control capacity.
Keywords; FMEA, Managerial Accounting Course, Risk Priority Numbers, Process
Improvement.
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INTRODUCTION
Managerial accounting courses play crucial roles in business administration. Business
decisions for higher internal efficiency including product costing, planning, budgeting
performance evaluation and feedback which are the main subjects of managerial accounting
courses. Besides, in some cases managerial accounting subjects are closely related with
marketing, finance, and human relations. So, managerial accounting capabilities can be
considered as a linking factor that examines variety of settings within the businesses for
providing external and internal efficiency.
The health of managerial accounting information and decision makers’ capabilities of
appraising such information can directly affect correctness (or appropriateness) of managerial
decisions, consequently the success of the firm. Success of the managerial accounting courses
or improvements in them might affect the success of the students and consequently the
success of the firm, and even the success of an economy.
In this perspective academicians (in this case accounting lecturers) are the main responsible
bodies who should improve the educational process. First step for process development in
such courses can be measuring the risks and failures in existing courses. There are several
approaches that can be used for determining the risk factors. This study preferred to apply and
adapt the FMEA model (which can be considered relatively easy and practical) to display
failures and risks for managerial accounting courses. Study took place in economics and
administrative sciences faculty of Afyon Kocatepe University, in Turkey.
FMEA is well known model used for analyzing failures, their potential causes and effects.
FMEA can be used in early stages of establishing new systems as an early warning tool to
examine the risks and faults before the complete set up realized, which could reduce the
potential renewal costs in early stages by giving a chance to decision makers to take
necessarily precautions. FMEA can also be used in exploring and exhibiting the faults in
existing systems which is the main consideration of the study; adopting FMEA model to
display risks and failures in existing accounting courses to see the existing faults for fixing
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and enhancing the system, which is one of the purpose of lecturers: strengthening the
capabilities of students in the related courses.
1. Data collection and methodology
Study took place in Afyon Kocatepe University, Economics and Business Faculty. Students
who took managerial accounting courses subjected to the study. Data collection is completed
by several methods such as: interviews, visual monitoring and questionary survey. Interviews
with the accounting lecturers as well as students provided valuable information about the risk
factors. In the light of risk factors a questionnaire survey is prepared and applied to the
students.
After defining the risk factors for every stage, risk parameters such as: Severity of risks (S),
Probability of occurrence (O) and detection probability of risk (D) are measured.
Then the Priority Risk Numbers (PRN) for every factor is calculated by using FMEA. Finally
these risks are ranked in terms of risk priorities and listed from highest to the lowest for the
process improvement. Process improvement included reminding and repetition of certain
basic mathematical rules, which is critically improved the analytical capabilities of students.
This improvement could be monitored during the courses quite obviously. Again, reminding
and repetition of certain basic managerial rules also contributed to the students’
understanding; managerial thinking. Even though majority of the students had enough
knowledge on accounting, some of them needed little bit of reminding and repetition of
certain basic accounting rules and regulations. In the study, education system is considered as
combination of three stages; input, process and output.
2. Failure Mode and Effects Analysis (FMEA)
Failure mode and effects analysis (FMEA) is used for identifying the existing or potential
failures/risks early stages of the establishment of systems, processes, methodologies, and the
product and/or service development activities.
FMEA initially used in US army to develop flight control systems. In 1960s FMEA
intensively has begun to put into practice in aviation industry. Later on ford motor co. has
started to use the method in their plants. Since then several academicians have been studied
the subject either to improve the technique or to implement it in different areas. Price and
others (1995) used the technique for evaluation of risks in flame systems. Vandenbrande
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(1998) implemented the technique for determination of environmental risks. Houten and
Kimura (2000) studied the risks in virtual product designs and visual maintenance systems.
Some other studies related to FMEA applications are: Cristiano and others (2000); product
development, Price (1996); determination of risks by using simulation models, Musubeyli
(2004); Customer expectations, Teoh and Case (2004); data analyzing, Tari and Sabater;
(2004) and Atmaca (2005); automobile industry, Kılıç (2005); occupational health and safety,
Su and Chou (2008); six sigma projects, Plaza and Medrano (2007); Improvement in
Electronic Engineering Education; and Eleren and Elitaş (2007) target costing and FMEA,
Eleren (2007) process development in education.
Some other studies concentrated on developing the technique. For instance; Ben-Daya and
Raouf (1996) revised the model and used PRN on logarithmic scale. Bevilacqua and others
(2000) applied PRN numbers on Monte Carlo simulations.
Obviously, technique could be applied to vast variety of sectors and subjects, since it is
simple, practical and logical technique. Besides, by the FMEA, system managers or engineers
could track the whole system failures (entire fault chain) from root to end effects of the
failures. Therefore, risk of neglecting hidden or insignificant risks can be reduced.
Literature studies on FMEA mostly concentrated on early stages of establishment of new
systems. It is believed that FAME can be and should be used in existing systems, as well, for
process development purposes. For instance continuous improvement and development
activities are basic functions in Total Quality Management that requires frequent monitoring
and controlling of failures and mode. Potential failures and risks can change within the time
depending on unnumbered factors and there is no clear time table which exhibit the timing of
these changes. For this reason, decision makers repeatedly have to apply FAME to identify
risks and failures to take precautions early.
FMEA can be applied in the cases of
 designing of new systems, products, processes, methods or models,
 need for changes in existing systems, products, processes, methods or models,
 Improving new systems, products, processes, methods or models.
In the cases of multi and/or inter systems organization members’ contributions to FMEA
becomes more crucial. Their knowledge about the system; how the system works, features
and characteristics of system, specific targets, weaknesses and strengths should be put into
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consideration. Systematic and coordinated cooperation in between the team members and the
analysts are a necessity for a healthy analyze.
Nowadays FMEA studies are becoming more and more focused on inter-discipline studies.
Inter studies, in between FMEA with fuzzy logic, with multi criterion decision making,
artificial neural networks and simulations are becoming more popular.
2.1.
Failure Modes and Effects Analysis
Types Failure modes and effect analysis could be classified under four headings in terms of
which purpose it is used for. These are: FMEA applications for systems, for designs, for
services and processes. System FMEA is used for measuring the risks for sub-systems.
Design FMEA examines the potential failures and mode while designing phase of the new
products, technologies and tries to find out possible precautions for the risks. Service FMEA
enables the users to investigate the potential failures before service activities actualize.
Process FMEA is used for analyzing the process and its sub-processes and mostly provides
valuable information for process development.
Implementation processes of FMEA might include the following steps.
These are;

defining and determining of functions

defining and determining of failures

determining the reasons of failures

measuring the occurrence

measuring the severity of failures

availability of detection ,

Determination of priority risk number (PRN) and ranking them in an order starts from
highest to the least.

Taking the necessarily precautions to reduce the risks.
After determining possible error types and their possible reasons and effects, the probability
of occurrence has to be measured by using historical quantitative information or by using the
experience of professionals. This is followed by calculation of magnitude of the failure which
is measuring the level of negative effects of anticipated event. FMEA can be useful in the
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cases where severity, probability of occurrence can be measured (or classified), and the
detection of failures are possible. The Risk Priority Number (RPN) can be measured as; the
result of multiplication of Severity of risks (S), Probability of occurrence (O) and detection
probability of risk (D). I.e. RPN = S x O x D
By listing risk priority numbers, from highest to the least one, high risk factors can be listed.
In some cases where there are too many risk factors, minor risks can be ignored.
Determining the risk factors by FMEA would be a useful tool to achieve progress
improvement activities. Progress development activities in managerial accounting courses
would reduce the prior risk factors. FMEA can be (or should) be applied to the courses after
the process development activities. Hence the course managers or the decision makers might
have feedback to evaluate the results of the activities, if there is a real improvement (degree of
improvement) or not?
3. Implementation of FMEA on Managerial Accounting Courses
Aim of the study: is to detect and expose the prior risks factors that might lead the courses
fail and to list these risks in according to their potential risk levels by using FMEA method.
The results of FME Analyses that gives the list of prior risk will be a base for progress
improvement.
Methodology: primary information for the study is provided by a questionnaire survey,
applied to the students who are taking managerial accounting courses. Additionally,
interviews with managerial accounting lecturers took place to benefit their experiences for the
study. FMEA analyses on the subject enabled us to determine the prior risk factors which
provided valuable base (information) for Progress improvement.
Scope of the study: study took place in Afyon: a small city at the center of Turkey.
Participants of the study were the students who are taking managerial accounting courses in
different departments.
Data preparation: Quantitative data used for the calculation of risk priority numbers such as
severity occurrence and detection varied in between 1 and 10. Questionnaire subjected to the
students who took the course at least at ones. Results of the questionnaire provided data about
the students’ perspectives on severity and occurrence. Risk of detection probability is
determined by the decision maker in the light of interviews took place with the lecturers.
Open ended questions provided valuable data about the risk factors that might have negatively
affected the success of the students. These factors are used in questionnaire scales where
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Likert scale was ranging in between 1 and 10. The scale has been subject to a pilot evaluation
(n = 40, Cronbach's. Alpha = 0.905).
Survey questionnaire subjected to 225 students (the Cronbach's alpha = 0.944). Participants
are asked to evaluate given risk factors in terms of severity and occurrence. Weights of the
results taken separately and then rounded. Besides, interview with 7 teaching staff helped us
to determine the risk factors and parameters. Hence we could be able to make comparisons.
Implementation and results: study implemented in two stages: in the first stage risks and
priorities listed by using FMEA. In the second stage; progress improvement applied to risk
factors.
System and risk analysis As mentioned before the aim of the study is to identify and list the
(prior) risk factors and to apply progress improvement on them in managerial accounting
courses. Related data is presented in the tables attached. In the study, educational system is
defined as a system that consists of three subsystems: input (students, lecturers, materials,
physical equipment etc.,), process (education process) and output (success). These systems are
also divided into 12 subsystems.
All the expected or encountered problems and failures are defined as risk factor. These factors
are listed in table-1 which lists the risk factors and their codes that are used to calculate the
RPN.
Risk Priority Numbers (PRN) were calculated by multiplication of the Risk parameters
(SxOxD); as exhibited in table-2.
Calculated PRNs are listed in a descending order (table-2). They are ordered by two
techniques. First: all Risk factors are listed from highest to the lowest one and they are
enumerated in according to their Priority Risk Numbers. Second: all the factors listed and
enumerated within their sub-systems.
Initial FMEA analysis of risk factors (in main systems) has shown that highest risk priority
was “crowd, noise, small class sizes” with 0.441 PRN which is classified under the Basic
Requirements and Preparation.
This is followed by “repetition to the course subjects” with a score of 0.324. A striking
sample about repetition came into the light during the interview with a lecturer.
According to the lecturer, he was very much determined to teach certain subject. After
theoretical explanations he did some numeric samples about the subject. In addition to this, he
spent six additional lecturing hours (two weeks) for the subject. During this 6 hours of
lecturing every student (by one by) have solved a different problem about the subject by
himself or by herself. At least at ones and some students have solved the problems twice in
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front of the lecturer almost without a difficulty. Lecturer has informed the students that he
will ask a similar question in the final exam. One month later, in the final exam similar
question is asked to the students but the result was disappointment. Because the students were
overconfident about the subject and they did not repeat it. Result was failure.
When the risk factors are evaluated on the basis of sub-systems, first place (in terms of high
risk ranking) is taken by “Measuring relevant costs and revenues for decision making” with 9,
31%. This is followed by Income effects of different alternative cost accumulation systems
with 9, 07%. Least risky subsystem was introduction to management accounting with a 4,
06%.
Process Improvement planning
Obviously, it is better to start process improvement activities with the highest Risk priority
number factor. Because improving highest PRN factor can provide more improvement to the
system which is also improves cost efficiency. RPNs can draw a road map for more efficient
process improvement activities. If the sources is not enough for the improvement or if there is
no permission for the improvement, second highest PRN factor should be selected for the
improvement. In this study, improvement is applied to the sub-systems, not to the main
systems. Here, in the sub-systems, highest risk priority number is appeared in “Measuring
relevant costs and revenues for decision making”.
Process development for the main systems:
 Improvement of training processes should start with determining of Risk Priority
Factor.
 Selected factors are analyzed and the potential reasons of the problem are exposed.
Their possible measures are determined and evaluated.
 Theoretically; when the improvement process applied to the educational process, RPN
has to drop from the existing levels (RPN’s can be min 1 if O=1, S=1, D=1 and max
1000 if O=10, S=10, D=10).
 Theoretical improvement level is calculated on the bases of expected drop on the RPN.
Degree of improvement can be measured with following formula; (RPNbi –
RPNai)/RPNbi, here RPNbi= RPN before the improvement and RPNai= RPN after the
improvement.
 After each improvement FME Analyses has to be repeated. Because the effects of the
improvement, might affect the other factors differently (negatively or positively).
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Therefore order in RPN rankings might change. In such cases the new highest priority
numbered factor has to be the first in the ranking for the next improvement.
 Improvement processes may not be economically efficient for every factor. If the
expected benefits of improvement is less than the costs decision makers has to
reconsider the process. In some cases some steps can be skipped.
 Actual improvements has to be measured after implementing improvement progresses
Process development for the sub-systems: complex systems consists of several sub-systems.
Sub-systems can play crucial roles in the main system, any ignored small failure or risk in a
sub-system can destroy the main system seriously and consequently the whole system. But
analyzing only the main systems may not represent the failures in sub-systems, therefore it
can mislead the decision makers and hide where the main risks exist. That is why it is better to
analyze the main systems in consideration to the sub-systems. In this study both the main
systems and the sub-systems are analyzed. In the existing study, improvement process applied
to the highest RP Numbered sub-system which is “2.7.Measuring relevant costs and revenues
for decision making” with the 867 RPN. Other sub-systems can be seen table-2.
Improvement stages for the subsystem process development is listed as below:
 Definition of factors that might affect the quality of outputs
 Regroup the related factors that can be classified as the subsystems of the main
process.
 Analyzing of risk factors and proposing the solutions in considering the cause effect
relations. (See table 3).
 Calculation of RPN’s for each factor and for each sub-system
 Listing of sub-systems in according to their RPN’s from highest to the least. In our
case there were 14 sub-systems.
 Select the highest RP Numbered sub-system and implement the improvement process.
In the existing study it is: Measuring relevant costs and revenues for decision making”
with the 867 RPN.
 Controlling and monitoring the results: after the improvement process RP Numbers
has to be recalculated to see if there is an improvement.
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Indeed, even if the results are in the expected range, improvement processes has to be
implemented periodically, as long as the organization’s sources allows (time, money,
capabilities), because organizations has to improve themselves to became more competitive to
cope with fierce competition.
 Graph 1 represents the improvements within 14 subsystems. Improvement activities
are applied to each educational process.
 In every, repetition appropriate solutions to the risks should be scheduled and applied
to the relevant processes. Theoretically realization of improvement processes should
decrease the RPN of the specific process.
In the light of these, results of improvement process for the study are represented in
table-3.
Estimated Degree of improvement is calculated by the following formula: (RPNbi – RPNai) /
RPN see table 4
4. Process Improvement in managerial accounting courses:
In this study improvement process is scheduled under 14 steps which consists several actions.
Improvement processes for sub processes are planned in according to their RPN scores from
highest to the lowest. Here 2.7. Measuring relevant costs and revenues for decision making
had the highest RPN score (see table3; 867pts). Sor improvement has started from this point.
Three main sources of failure were a) Lack of analytic abilities b) Lack of managerial
thinking and c) Lack of fundamental accounting capabilities. These three factors subjected to
the improvement. Repetation of basic mathematical rules, and giving more and more samples
about the analytical subjects enhanced the students’ analytical capabilities. Managerial
capabilities enforced by repeting the main managerial subjects. To enhance lack of
fundamental accounting knowledge basic accounting priciples including GAAP (generally
accepted accounting principles) repeated and reminded in the lectures as much as possible.
The other propositions for the possible improvements are listed on table-4.
Implementing of such measures caused changes in risk parameters. Table-5 represents first
stage improvement results.
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After the first step, distribution of scores and the sequence of the listing have changed. See
table 6. Similarly, after every step, suggestions should be implemented to the related sub
systems. After the first step of the improvement, RPN of sub-system 2.7 has gone down and it
became 12th in the row.
Table-1 represents the marginal and cumulative improvements. First three steps for
improvements has actually tested and the other step are the proposed and estimated
improvements.
Table-1: Marginal & Cumulative Improvement
improvement no
1
2
3
4
5
6
7
8
9
10
11
12
13
14
marginal improvement
606
593
564
502
466
433
407
381
330
255
204
110
55
28
cumulative
606
1199
1763
2265
2731
3164
3571
3952
4282
4537
4741
4851
4906
4934
of
12,3
12
11,4
10,2
9,4
8,5
8,2
7,7
6,7
5,2
4,1
2,2
1,1
0,6
cumulative percentage
12,3
24,3
35,7
45,9
55,4
64,1
72,4
80,1
86,8
92
96,1
98,3
99,4
100
improvement
percentage
improvement
improvement
Graph-1 represent cumulative improvements. Initial improvement considerably high but
amonth of improvements is decreasing after every improvement.
Cumulative Improvement
6000
5000
4000
3000
2000
Graph-1. Cumulative improvement.
This result is consistant with the law of diminishing return. As represented graph-2 every
stage of improvement provides less and less return ie.. law of diminishing return.
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Graph-2. Marginal improvement after each improvement.
Marginal improvements for every improvement constantly decreasing: 1st improvement 606,
2nd 593 and the last improvement only 28 points. That is why decision makers has to evaluate
the costs and benefits of improvement in every new improvement. Cost benefit relation for the
improvement should be considered.
In the literature there is no clear indication about how many times a company has to
implement improvement processes. But one might clearly suggest that imprrvements has to be
implemented until the cost of improvement is equal or less than the total expected benefits.
5. CONCLUSION
Managerial accounting courses play a crucial role in business administration courses.
Managers have to have certain degree of managerial accounting capabilities to take correct
decisions and to manage their firms efficiently. However, every process (including managerial
accounting training process) might contain certain degree of failure and risk depending on
several factors. In this study managerial accounting courses considered as a systems consists
of several main systems that are involving sub-systems. According to the study highest PRN
in main systems were “2.7. Measuring relevant costs and revenues for decision making”
which were involving six sub-system a) Lack of analytic abilities, b) Lack of managerial
thinking, c) Lack of fundamental accounting capabilities, d) Lack of concentration, e)
Deficiencies in lecturer (less sampling and explanation etc.), f) deficiencies related to location
(noise crowd etc.). Unfortunately, it was not possible to make improvements for every subsystem and for every main system. Only three out of six sub-systems have been subjected to
improvement activities these were: a) Lack of analytic abilities, b) Lack of managerial
thinking, c) Lack of fundamental accounting capabilities. Analytical abilities improved by
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reminding of analytical rules and by giving further samples about them. Similarly, managerial
abilities improved by reminding of managerial aspects. Finally, basic of accounting and
Generally Accepted Accounting Principles are repeated before the course and some times
during the course.
Obviously, these improvements mostly performed by the lecturer. There are some other
improvements might have been performed by the other parties for instance students and
management etc., that could be subject to future studies.
After every improvement it has been monitored that there were some improvement. After 1 st
improvement there was 606 points of decrease in RPN. In the second improvement this
number is gone down to 593 points and in the last one it was it was 564 points. Other
improvements are the expected improvements calculated in according to law of diminishing
return.
References
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Ben-Daya, M., and Abdul Raouf, (1996). A Revised Failure Mode and Effects Analysis Model, International Journal of Quality
& Reliability Management, Vol. 13 Iss 1 Pp. 43 - 47
Bevilacqua M, Braglia M, Gabbrielli R. (2000). Monte Carlo Simulation Approach for Modified FMECA in a Power Plant.
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Dergisi, 9,:2, 1-25.
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Plaza, I.; Medrano, C.T (2007) “Continuous Improvement in Electronic Engineering Education”, Education, IEEE
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97-100,
ANNEXES:
Table-2: determination of risk factors and parameters by using data gathered from
questionnaires
OCCURANCE
SEVERITY
Risk Factors (Failures)
Mean
Code
Mean
Code
Lack of knowledge, experience of the lecturer
2,13
2
4,91
5
Deficiencies in preparation of lesson and presentation
2,03
2
3,81
4
Difficulties in accessing the basic textbooks
1,23
1
4,97
5
Lack of physical facilities (classroom equipment, etc.)
1,87
2
3,01
3
Exceed number of students, noise chaos etc.
7,14
7
6,81
7
Attendance, class prejudice against to the course
7,06
7
0,82
1
pre-course preparation
4,21
4
4,28
4
concentration of student
4,87
5
5,09
5
Repetition of topics
5,92
6
3,22
6
Student's personal or family related problems
2,14
2
5,21
5
Lack of fundamental accounting capabilities
2,23
2
4,83
5
Lack of understanding basic accounting terms and concepts
1,99
2
5,05
5
Lack of analytic abilities
1,14
5
6,99
7
Lack of managerial thinking
4,01
4
5,16
5
Lack of concentration
3,09
3
7,16
7
Deficiencies in lecturer (less sampling and explanation etc.)
2,28
2
6,16
6
Deficiencies related to location (noise crowd etc.)
2,99
3
5,29
5
Lack of fundamental accounting capabilities
2,13
2
5,11
5
Lack of managerial thinking
3,19
3
4,97
5
Lack of analytic abilities
5,14
5
6,89
7
Lack of managerial thinking
4,24
4
5,00
5
Lack of concentration
2,89
3
7,12
7
Deficiencies in lecturer (less sampling and explanation etc.)
2,03
2
6,07
6
November 22-23, 2015
Oxford, UK
14
13th Global Conference on Business & Economics
ISBN : 9780974211428
Deficiencies related to location (noise crowd etc.)
3,13
3
5,08
5
Lack of analytic abilities
5,10
5
6,97
7
Lack of fundamental accounting capabilities
1,96
2
4,99
4
Lack of managerial thinking
4,04
4
5,10
5
Lack of concentration
3,07
3
7,07
7
Deficiencies in lecturer (less sampling and explanation etc.)
2,04
2
6,18
6
Deficiencies related to location (noise crowd etc.)
2,80
3
5,14
5
Lack of analytic abilities
5,22
5
7,13
7
Lack of managerial thinking
4,07
4
5,20
5
Lack of concentration
3,15
3
6,83
7
Deficiencies in lecturer (less sampling and explanation etc.)
2,10
2
6,08
6
Deficiencies related to location (noise crowd etc.)
3,21
3
5,02
5
Lack of analytic abilities
4,97
5
6,94
7
Lack of managerial thinking
4,24
4
5,10
5
Lack of fundamental accounting capabilities
2,04
2
4,96
5
Lack of concentration
3,20
3
7,22
7
Deficiencies in lecturer (less sampling and explanation etc.)
1,83
2
5,86
6
Deficiencies related to location (noise crowd etc.)
3,30
3
4,86
5
Lack of analytic abilities
4,90
5
6,89
7
Lack of managerial thinking
4,08
4
5,14
5
Lack of concentration
3,18
3
7,21
7
Deficiencies in lecturer (less sampling and explanation etc.)
1,98
2
5,94
6
Deficiencies related to location (noise crowd etc.)
3,09
3
4,92
5
Lack of analytic abilities
5,03
5
7,22
7
Lack of managerial thinking
4,23
4
5,21
5
Lack of concentration
2,99
3
7,12
7
Deficiencies of lecturer (less sampling and explanation etc.)
2,24
2
5,90
6
Deficiencies related to location (noise crowd etc.)
3,23
3
5,12
5
Lack of analytic abilities
5,19
5
7,15
7
Lack of managerial thinking
4,04
4
5,14
5
Lack of fundamental accounting capabilities
2,11
2
4,12
4
Lack of concentration
3,02
3
7,01
7
Deficiencies in lecturer (less sampling and explanation etc.)
1,99
2
5,85
6
Deficiencies related to location (noise crowd etc.)
3,16
3
5,01
5
Lack of analytic abilities
5,17
5
6,87
7
Lack of managerial thinking
3,87
4
4,85
5
Lack of concentration
3,29
3
7,14
7
Deficiencies in lecturer (less sampling and explanation etc.)
1,59
2
4,96
6
Deficiencies related to location (noise crowd etc.)
2,96
3
4,74
5
Questions that are exceed the content.
0,86
1
2,94
3
Difficulty of questions
2,88
3
6,89
7
restricted exam time period
2,30
2
4,05
4
partial understanding or misunderstanding of questions
2,07
2
7,80
8
unexpected surprising questions
3,10
3
5,20
4
November 22-23, 2015
Oxford, UK
15
13th Global Conference on Business & Economics
ISBN : 9780974211428
SEVER (1-10)
DETECT (1-10)
RPN /1000)
RPN NO
2
5
7
70
54
2
4
6
48
60
1
5
7
35
63
d) lack of adequate physical equipment
e) crowd, noise, small class sizes and volumes in
comparison to the number of students
a) attendance problem, negative prejudice against to the
course
b) preparation of students for the lecture
2
3
3
18
64
7
7
9
441
1
7
1
3
21
65
4
4
6
96
33
c) concentration of students during the lecture
5
5
8
200
12
d) repetition after the lecture
6
6
9
324
2
e) personal or family related problems of students
2
5
5
50
59
a) Lack of fundamental accounting capabilities
2
5
7
70
55
Risk Factors (Failure Modes)
Main
Sub
I-Inputs
1.1.basic
requirements and
preparation
1.2. basic
requirements and
preparation of
students
2.1.Introduction to
management
accounting
a) lack of knowledge, experience and authority of the
lecturer
b) deficiencies in preparation or representation techniques
of lecturer
c) lack of basic and prolonging books
b) Lack of understanding basic accounting terms and
concepts
a) Lack of analytic abilities
2.2.Cost assignment
2.5.Income effects of
different alternative
cost accumulation
systems
II- Process
2.6.Cost-volume-profit
analyses
November 22-23, 2015
Oxford, UK
5
6
60
5
7
9
315
3
4
5
7
140
24
c) Lack of concentration
d) Deficiencies in lecturer (less sampling and explanation
etc.)
3
7
8
168
13
2
6
7
84
44
e) Deficiencies related to location (noise crowd etc.)
3
5
6
90
34
2
5
6
60
58
3
5
6
90
35
a) Lack of analytic abilities
5
7
9
315
4
b) Lack of managerial thinking
4
5
7
140
25
c) Lack of concentration
d) Deficiencies in lecturer (less sampling and explanation
etc.)
3
7
8
168
14
2
6
7
84
45
e) Deficiencies related to location (noise crowd etc.)
3
5
6
90
36
a) Lack of analytic abilities
5
7
9
315
5
b) Lack of fundamental accounting capabilities
2
4
6
48
61
c) Lack of managerial thinking
4
5
7
140
26
d) Lack of concentration
e) Deficiencies in lecturer (less sampling and explanation
etc.)
3
7
8
168
15
2
6
7
84
46
f) Deficiencies related to location (noise crowd etc.)
3
5
6
90
37
a) Lack of analytic abilities
5
7
9
315
6
b) Lack of managerial thinking
4
5
7
140
27
c) Lack of concentration
d) Deficiencies in lecturer (less sampling and explanation
etc.)
3
7
8
168
16
2
6
7
84
47
e) Deficiencies related to location (noise crowd etc.)
3
5
6
90
38
16
612
6,57%
11
691
7,42%
130
1,40%
10
14
57
b) Lack of managerial thinking
2.3.Accounting entries a) Lack of fundamental accounting capabilities
for a job costing
system
b) Lack of managerial thinking
2.4.Process costing &
Joint and by-product
costing
2
GROUP NO
OCCURE (1-10)
SYSTEM
RPN GROUP WEIGHTS
Table-3: Failure Modes and Effects Analysis (initial)
797
8,56%
150
1,61%
4
13
797
8,56%
5
845
9,07%
2
797
8,56%
6
13th Global Conference on Business & Economics
2.7. Measuring
relevant costs and
revenues for decision
making
2.8.Price decisions
and profitability
analyses
2.9.Decision making
under condition of
risk and uncertainty
2.10.Capital
investment decisions
III.- Output
2.11.Budgeting
3.1.Exams
ISBN : 9780974211428
a) Lack of analytic abilities
5
7
9
315
7
b) Lack of managerial thinking
4
5
7
140
28
c) Lack of fundamental accounting capabilities
2
5
7
70
56
d) Lack of concentration
e) Deficiencies in lecturer (less sampling and explanation
etc.)
3
7
8
168
17
2
6
7
84
48
f) Deficiencies related to location (noise crowd etc.)
3
5
6
90
39
a) Lack of analytic abilities
5
7
9
315
8
b) Lack of managerial thinking
4
5
7
140
29
c) Lack of concentration
d) Deficiencies in lecturer (less sampling and explanation
etc.)
3
7
8
168
18
2
6
7
84
49
e) Deficiencies related to location (noise crowd etc.)
3
5
6
90
40
a) Lack of analytic abilities
5
7
9
315
9
b) Lack of managerial thinking
4
5
7
140
30
c) Lack of concentration
d) Deficiencies of lecturer (less sampling and explanation
etc.)
3
7
8
168
19
2
6
7
84
50
e) Deficiencies related to location (noise crowd etc.)
3
5
6
90
41
a) Lack of analytic abilities
5
7
9
315
10
b) Lack of managerial thinking
4
5
7
140
31
c) Lack of fundamental accounting capabilities
2
4
2
16
66
d) Lack of concentration
e) Deficiencies in lecturer (less sampling and explanation
etc.)
3
7
8
168
20
2
6
7
84
51
f) Deficiencies related to location (noise crowd etc.)
3
5
6
90
42
a) Lack of analytic abilities
5
7
9
315
11
b) Lack of managerial thinking
4
5
7
140
32
c) Lack of concentration
d) Deficiencies in lecturer (less sampling and explanation
etc.)
e) Deficiencies related to location (noise crowd etc.)
3
7
8
168
21
2
6
7
84
52
3
5
6
90
43
a) unexpected surprising questions
1
3
5
15
67
b) Difficult questions
3
7
7
147
22
c) inadequate exam time period
2
4
6
48
62
d) partial understanding or misunderstanding of questions
2
8
9
144
23
e) unexpected surprising questions
3
4
6
72
53
9316
TOTAL
November 22-23, 2015
Oxford, UK
17
867
9,31%
1
797
8,56%
7
797
8,56%
8
813
8,73%
3
797
8,56%
9
426
4,57%
12
13th Global Conference on Business & Economics
ISBN : 9780974211428
Table-4. Risk factors; causes and possible measures
RISK FACTORS
2.7. a)
Lack of analytic
abilities
2.7. b)
Lack of
managerial
thinking
2.7. c)
Lack of
fundamental
accounting
capabilities
2.7. d)
Lack of
concentration
2.7. e)
Deficiencies in
lecturer (less
sampling and
explanation etc.)
2.7. f)
Deficiencies
related to
location (noise
crowd etc.)
CAUSE OF RISK FACTORS
The deficiencies in previous education process: lack of basic
mathematical and statistical knowledge, lack of analyzing
capabilities of the students since nonexistence of related
courses (in previous educational system) such as system
analyses or numeric analyses etc., and the dominance of
inductive logic.
Deficiencies in individual studying capabilities and in self
disciplining; without a planning. Hesitations to teamwork,
POSSIBLE MEASURES FOR THE RISK FACTORS
Temporary solution: preparation courses which
includes basic subjects of math and statistics.
Permanent solution: establishing a feedback
mechanism with the previous course staffs in related
subjects to increase their efficiencies.
Deficiencies in basic knowledge of fundamental accounting
principles
Frequently repeating the basics of accounting
Lack of concentration or interest to the managerial accounting
subjects before, after and during the courses
Providing materials to the students for improving
their self-studying habits; in some cases developing
study programs for them. Creating opportunities to
Enhance their communications to encourage their
team work activities.
Preparing more updated and interesting cases for
the related subject, giving striking samples
Providing more subject related samples that
represent the critical points clearly.
Concentrating on too much of theory, poor samples that do not
represent the cases clearly which might lead the students to
memorize.
Uncomfortable atmosphere; design of the rooms, crowd and
noise. Lack of authority of the lecturer.
Repeating basics of management
Providing certain degree of authority which might
limit the noise. Dividing the classes if they are
overcrowded or giving the lectures in a larger lecture
rooms or amphitheaters
Table -5: results of the first step the improvement
SUB PROCESS : 2.7
INITIAL SCORE
FINAL SCORE (After Improvement)
RISK FACTORS
RPN
(/1000)
RANKNO
OCCURANCY
(1-10)
SEVERITY
(1-10)
DETECTION RPN
RPN(1-10)
(/1000) NO
2.7. a) Lack of analytic abilities
315
7
1
7
9
63
51
2.7. b) Lack of managerial thinking
140
28
1
5
7
35
61
2.7. c) Lack of fundamental accounting capabilities
70
56
1
5
7
35
62
17
1
7
8
56
54
48
1
6
7
42
59
39
1
5
6
30
63
2.7. d) Lack of concentration
168
2.7. E) Deficiencies in lecturer (less sampling and
84
explanation etc.)
2.7. F) deficiencies related to location (noise crowd
90
etc.)
November 22-23, 2015
Oxford, UK
18
13th Global Conference on Business & Economics
ISBN : 9780974211428
a) Lack of knowledge, experience of the lecturer
2
5
7
70
49
b) Deficiencies in preparation of lesson and presentation
2
4
6
48
56
1
5
7
35
60
d) Lack of physical facilities (classroom equipment, etc.)
2
3
3
18
65
e) Exceeding number of students, noise chaos etc.
7
7
9
441
1
a) Attendance, class prejudice against to the course
7
1
3
21
64
4
4
6
96
30
5
5
8
200
11
d) Repetition of topics after the course
6
6
9
324
2
e) Student's personal or family related
2
5
5
50
55
a) Lack of fundamental accounting capabilities
2
2.0.
Introduction
to b) Lack of understanding basic accounting terms and
management accounting concepts
2
5
7
70
50
5
6
60
52
I-Input
1.1. basic requirements
c) Difficulties in accessing the basic textbooks
and preparation
1.2. basic requirements b) pre-course preparation
and preparation of
c) concentration of student during the course
students
a) Lack of analytic abilities
5
7
9
315
3
b) Lack of managerial thinking
4
5
7
140
22
c) Lack of concentration
3
d) Deficiencies in lecturer (less sampling and explanation
etc.)
2
7
8
168
12
6
7
84
40
3
5
6
90
31
2
5
6
60
53
3
5
6
90
32
a) Lack of analytic abilities
5
2.3. Process costing &
4
Joint
and
by- b) Lack of managerial thinking
product costing
c) Lack of concentration
3
d) Deficiencies in lecturer (less sampling and explanation
etc.)
2
7
9
315
4
5
7
140
23
7
8
168
13
6
7
84
41
2.1. Cost assignment
II- Process
e) Deficiencies related to location (noise crowd etc.)
2.2. Accounting entries a) Lack of fundamental accounting capabilities
for a job costing
system
b) Lack of managerial thinking
e) Deficiencies related to location (noise crowd etc.)
3
5
6
90
33
a) Lack of analytic abilities
5
7
9
315
5
2.4. Income effects of b) Lack of fundamental accounting capabilities
2
different alternative
c)
Lack
of
managerial
thinking
4
cost accumulation
systems
d) Lack of concentration
3
e) Deficiencies in lecturer (less sampling and explanation
etc.)
2
4
6
48
57
5
7
140
24
7
8
168
14
6
7
84
42
f) Deficiencies related to location (noise crowd etc.)
3
5
6
90
34
a) Lack of analytic abilities
5
7
9
315
6
b) Lack of managerial thinking
4
5
7
140
25
c) Lack of concentration
3
d) Deficiencies in lecturer (less sampling and explanation
etc.)
2
7
8
168
15
6
7
84
43
e) Deficiencies related to location (noise crowd etc.)
3
5
6
90
35
a) Lack of analytic abilities
5
7
9
63
51
b) Lack of managerial thinking
4
2.6. Measuring relevant
c)
Lack
of
fundamental
accounting
capabilities
2
costs and revenues
for decision making d) Lack of concentration
3
e) Deficiencies in lecturer (less sampling and explanation
etc.)
2
5
7
35
61
5
7
35
62
7
8
56
54
2.5. Cost-volume-profit
analyses
November 22-23, 2015
Oxford, UK
6
7
42
59
f) Deficiencies related to location (noise crowd etc.)
3
5
6
30
63
a) Lack of analytic abilities
5
7
9
315
7
19
GROUP NO
RPN
GROUP
WEIGHTS
Risk Factors (Failure Modes)
RPN NO
Sub
RPN /1000)
Main
DETECT (1-10)
SYSTEM
SEVER (1-10)
OCCURE (1-10)
Table-6: Failure Modes and Effects Analysis (After Improvement first)
612
7,03%
10
691
7,93%
9
130
1,49% 14
797
9,15%
3
150
1,72% 13
797
9,15%
4
845
9,70%
1
797
9,15%
5
261
3,00%
12
797
6
13th Global Conference on Business & Economics
ISBN : 9780974211428
b) Lack of managerial thinking
4
2.7. Price decisions and
c)
Lack
of
concentration
3
profitability
analyses
d) Deficiencies in lecturer (less sampling and explanation
etc.)
2
7
140
26
7
8
168
16
6
7
84
44
e) Deficiencies related to location (noise crowd etc.)
3
5
6
90
36
a) Lack of analytic abilities
5
7
9
315
8
b) Lack of managerial thinking
4
2.8. Decision making c) Lack of concentration
3
under condition of d) Deficiencies of lecturer (less sampling and explanation
risk and uncertainty etc.)
2
5
7
140
27
7
8
168
17
6
7
84
45
e) Deficiencies related to location (noise crowd etc.)
3
5
6
90
37
a) Lack of analytic abilities
5
7
9
315
9
b) Lack of managerial thinking
4
5
7
140
28
2
2.9. Capital investment c) Lack of fundamental accounting capabilities
decisions
d) Lack of concentration
3
e) Deficiencies in lecturer (less sampling and explanation
etc.)
2
4
2
16
66
7
8
168
18
6
7
84
46
2.10. Budgeting
III.- Output
5
3.1. Exams
f) Deficiencies related to location (noise crowd etc.)
3
5
6
90
38
a) Lack of analytic abilities
5
7
9
315
10
b) Lack of managerial thinking
4
5
7
140
29
c) Lack of concentration
3
d) Deficiencies in lecturer (less sampling and explanation
etc.)
2
7
8
168
19
6
7
84
47
e) Deficiencies related to location (noise crowd etc.)
3
5
6
90
39
a) unexpected surprising questions
1
3
5
15
67
b) Difficult questions
3
7
7
147
20
c) inadequate exam time period
2
4
6
48
58
d) partial understanding or misunderstanding of questions
2
8
9
144
21
e) unexpected surprising questions
3
4
6
72
48
TOTAL
November 22-23, 2015
Oxford, UK
8710
20
9,15%
797
9,15%
7
813
9,33%
2
797
9,15%
8
426
4,89%
11