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PARETO ANALYSIS
Başak Karakaya
Industrial Engineering Department
Pareto analysis is a formal technique
useful where many possible courses of
action are competing for attention.
Pareto analysis is a creative way of
looking at causes of problems because it
helps stimulate thinking and organize
thoughts.
 This technique helps
to identify the top
20% of causes that
needs to be
addressed to resolve
the 80% of the
problems.
 The value of the Pareto Principle for a project
manager is that it reminds you to focus on the
20% of things that matter. Of the things you do
during your project, only 20% are really
important. Those 20% produce 80% of your
results. Identify and focus on those things first,
but don't totally ignore the remaining 80% of
causes.
History of Pareto Analysis
 The Pareto effect is named after Vilfredo
Pareto, an economist and sociologist who
lived from 1848 to 1923.
 This method stems in the first place from
Pareto’s suggestion of a curve of the
distribution of wealth in a book of 1896.
Whatever the source, the phrase of ‘the
vital few and the trivial many’ deserves a
place in every manager’s thinking. It is
itself one of the most vital concepts in
modern management. The results of
thinking along Pareto lines are immense.
HOW TO USE IT ?
 Step 1: Identify and List Problems
 Step 2: Identify the Root Cause of Each
Problem
 Step 3: Score Problems
 Step 4: Group Problems Together By Root
Cause
 Step 5: Add up the Scores for Each Group
 Step 6: Take Action
The Pareto Chart
A Pareto chart
is a graphical
representation
that displays
data in order
of priority.
This is a simple example of a Pareto diagram using
sample data showing the relative frequency of causes for
errors on websites. It enables you to see what 20% of
cases are causing 80% of the problems and where
efforts should be focused to achieve the greatest
improvement.
Some Problems
Difficulties associated with pareto analysis
 Misrepresentation of the data.
 Inappropriate measurements depicted.
 Lack of understanding of how it should be
applied to particular problems.
 Knowing when and how to use Pareto
Analysis.
 Inaccurate plotting of cumulative percent
data.
Overcoming the difficulties
 Define the purpose of using the tool.
 Identify the most appropriate measurement
parameters.
 Use check sheets to collect data for the likely
major causes.
 Arrange the data in descending order of value
and calculate % frequency and/or cost and
cumulative percent.
 Plot the cumulative percent through the top
right side of the first bar.
 Carefully scrutinize the results. Has the exercise
clarified the situation?
Pareto Analysis Example
Ahmet has taken over a failing service
center, with a lot of problems that need
resolving. His objective is to increase
overall customer satisfaction.
He decides to score each problem by the
number of complaints that the center has
received for each one.
#
Problem
(Step 1 )
Cause
(Step 2 )
Score
(Step 3 )
1
Phones aren’t
answered
quickly enough.
Too few service
center staff.
15
2
Staff seem
distracted and
under pressure.
Too few service
center staff.
6
3
Engineers don’t
appear to be
well
organized.They
need second
visits to bring
extra parts.
Poor
organization and
preparation. 4
4
Engineers don’t
know what time
they’ll arrive.This
means that
customers may
have to be in all
day for an
engineer to visit.
Poor organization
and preparation. 2
5
Service center
staff don’t always
seem to know
what they’re
doing.
Lack of training. 30
6
When engineers
visit,the customer
finds that the
problem could
have been solved
over the phone.
Lack of training. 21
Ahmet then groups problems together
(steps 4 and 5). He scores each group by
the number of complaints, and orders
the list as follows:
1. Lack of training (items 5 and 6) – 51
complaints.
2. Too few service center staff (items 1 and
42) – 21 complaints.
3. Poor organization and preparation (items
3 and 4) – 6 complaints
Figure 1. Ahmet’s Pareto Analysis
0
10
20
30
40
50
60
Lack of TrainingToo Few Service
Center Staff
Poor
Organization
and Preparation
It is the discipline of organizing the
data that is central to the success of using
Pareto Analysis. Once calculated and
displayed graphically, it becomes a selling
tool to the improvement team and
management, raising the question why the
team is focusing its energies on certain
aspects of the problem.
THANKS FOR LISTENING

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Pareto analysis

  • 2. Pareto analysis is a formal technique useful where many possible courses of action are competing for attention.
  • 3. Pareto analysis is a creative way of looking at causes of problems because it helps stimulate thinking and organize thoughts.
  • 4.  This technique helps to identify the top 20% of causes that needs to be addressed to resolve the 80% of the problems.
  • 5.  The value of the Pareto Principle for a project manager is that it reminds you to focus on the 20% of things that matter. Of the things you do during your project, only 20% are really important. Those 20% produce 80% of your results. Identify and focus on those things first, but don't totally ignore the remaining 80% of causes.
  • 6. History of Pareto Analysis  The Pareto effect is named after Vilfredo Pareto, an economist and sociologist who lived from 1848 to 1923.
  • 7.
  • 8.  This method stems in the first place from Pareto’s suggestion of a curve of the distribution of wealth in a book of 1896. Whatever the source, the phrase of ‘the vital few and the trivial many’ deserves a place in every manager’s thinking. It is itself one of the most vital concepts in modern management. The results of thinking along Pareto lines are immense.
  • 9. HOW TO USE IT ?
  • 10.  Step 1: Identify and List Problems  Step 2: Identify the Root Cause of Each Problem  Step 3: Score Problems  Step 4: Group Problems Together By Root Cause  Step 5: Add up the Scores for Each Group  Step 6: Take Action
  • 11. The Pareto Chart A Pareto chart is a graphical representation that displays data in order of priority.
  • 12. This is a simple example of a Pareto diagram using sample data showing the relative frequency of causes for errors on websites. It enables you to see what 20% of cases are causing 80% of the problems and where efforts should be focused to achieve the greatest improvement.
  • 13. Some Problems Difficulties associated with pareto analysis  Misrepresentation of the data.  Inappropriate measurements depicted.  Lack of understanding of how it should be applied to particular problems.  Knowing when and how to use Pareto Analysis.  Inaccurate plotting of cumulative percent data.
  • 14. Overcoming the difficulties  Define the purpose of using the tool.  Identify the most appropriate measurement parameters.  Use check sheets to collect data for the likely major causes.  Arrange the data in descending order of value and calculate % frequency and/or cost and cumulative percent.  Plot the cumulative percent through the top right side of the first bar.  Carefully scrutinize the results. Has the exercise clarified the situation?
  • 15. Pareto Analysis Example Ahmet has taken over a failing service center, with a lot of problems that need resolving. His objective is to increase overall customer satisfaction. He decides to score each problem by the number of complaints that the center has received for each one.
  • 16. # Problem (Step 1 ) Cause (Step 2 ) Score (Step 3 ) 1 Phones aren’t answered quickly enough. Too few service center staff. 15 2 Staff seem distracted and under pressure. Too few service center staff. 6 3 Engineers don’t appear to be well organized.They need second visits to bring extra parts. Poor organization and preparation. 4
  • 17. 4 Engineers don’t know what time they’ll arrive.This means that customers may have to be in all day for an engineer to visit. Poor organization and preparation. 2 5 Service center staff don’t always seem to know what they’re doing. Lack of training. 30 6 When engineers visit,the customer finds that the problem could have been solved over the phone. Lack of training. 21
  • 18. Ahmet then groups problems together (steps 4 and 5). He scores each group by the number of complaints, and orders the list as follows: 1. Lack of training (items 5 and 6) – 51 complaints. 2. Too few service center staff (items 1 and 42) – 21 complaints. 3. Poor organization and preparation (items 3 and 4) – 6 complaints
  • 19. Figure 1. Ahmet’s Pareto Analysis 0 10 20 30 40 50 60 Lack of TrainingToo Few Service Center Staff Poor Organization and Preparation
  • 20. It is the discipline of organizing the data that is central to the success of using Pareto Analysis. Once calculated and displayed graphically, it becomes a selling tool to the improvement team and management, raising the question why the team is focusing its energies on certain aspects of the problem.