STEP #3 - ANALYZE
ORGANIZE & ANALYZE DATA
Step #3 - ANALYZE
The MEASURE phase produced the baseline
performance of the process. Having stratified the
data in the baseline performance, it became
possible to pinpoint the location or source of the
problems by building a factual understanding of
the existing process conditions and problems,
which will help to focus the problem statement. In
the ANALYZE phase, you will develop theories of
root causes, confirm the theories with data, and
finally identify the root cause(s) of the problem.
The verified cause(s) will then form the basis for
your solutions in the next phase - IMPROVE.
The tools used most commonly in the Analyze
phase are:
·
Affinity Diagrams - was covered in the
Define phase.
·
Brainstorming
·
Cause-and-Effect Diagrams
·
Control Charts - covered in the Measure
Phase
·
Data Collection Forms - covered in the
Measure Phase
·
Data Collection Plan - covered in the
Measure Phase
·
Design of Experiments
·
Flow Diagrams
·
Frequency Plots - covered in the Measure
Phase
·
Hypothesis Tests
·
Pareto Charts - covered in the Measure
Phase
·
Regression Analysis
·
Response Surface Methodology
·
Sampling - covered in the Measure Phase
·
Scatter Plots
·
Stratified Frequency Plots
Organizing Potential Causes
Once the problem has been focused, the team will
create a list of potential causes and then set out
to organize those causes in order to see any
potential relationship between cause and effect.
An underlying assumption of many of the tools
used in the Analyze phase is that the data roughly
fits a normal distribution. Causes are verified so
that improvements focus on the deep cause, not
on the original symptom. Thus, the next step is to
generate a lot of potential causes, organize them,
and decide which potential causes to verify.
Brainstorming
In the Analyze phase, brainstorming is used to
generate a lot of ideas quickly to identify potential
causes. Brainstorming encourages creativity,
involves everyone, generates excitement and
energy, and separates people form the ideas they
suggest. The important thing to remember is that
to NEVER downplay anyone's ideas. Remember
that every thought or idea suggested should be
placed on the board, regardless of how
inappropriate it may seem at first.
Brainstorming Methods - two main methods
employed:
·
Rounds - go around in turn, one item per
turn, until everyone passes or has no
further idea to input.
·
Popcorn - anyone calls out ideas, no order,
until all ideas are out and none remain
to be offered.
Guidelines:
·
Start with silent "think" time
·
Freewheel - don't hold back.
·
NO CRITICISM of any idea.
·
Hitchhike - build upon other ideas or
suggestions.
·
The more ideas, the better
·
Post ideas using post-it notes.
The Five Whys
To push to reach the root cause, start with the
focused problem statement and then ask why at
least five times. An example of a problem
statement is "customers complain about waiting
too long to get connected to staff during lunch
hours." Thus the scenario on the chalkboard
would be:
WHY does this problem happen? Backup
operators take longer to connect callers.
WHY does it take backup operators longer?
Backup operators don't know the job as well as
the regular operator/receptionist does.
WHY don't backup operators know the job as
well? There is no special training, no job aids to
make up for the gap in experience and on-the-job
training for them.
WHY isn't there special training or job aids? In the
past, the organization has not recognized this as a
problem.
WHY hasn't the organization recognized this as a
problem? The organization has no system to
identify training needs.
Graphic displays can help you structure possible
causes in order to find relationships that will shed
new light on the problem. Most people have had
the experience of "solving" a problem over and
over again; however, the actions taken were
merely attacking the same problem repeatedly
and not actually finding the root cause. Use of a
cause-and-effect (or "fishbone") and a tree
diagram can help make your solutions more
effective the first time around by making sure that
you reveal the actual deep causes of a problem.
Cause-and-Effect Diagram
Again I refer you to the Cause-and-Effect Diagram
within this web site:
Cause-and-effect diagrams graphically display
potential causes of a problem. The layout shows
the cause-and-effect relationship between the
potential causes.
Why use cause-and-effect diagrams?
·
To stimulate thinking during a brainstorm
session for potential causes.
·
To understand relationships between
potential causes.
·
To track which potential causes have been
investigated, and which proved to
contribute significantly to the problem.
It is common for people working on improvement
efforts to jump to conclusions without studying
the causes, target one possible cause while at the
same time, ignoring other potential causes, thus
the aim has been at the surface symptom. Cause-
and-effect diagrams are designed to help alleviate
that tendency by:
·
Providing a structure to understand the
relationships between many possible
causes of a problem, rather than only one.
·
Giving people a framework for planning
what data to collect.
·
Serving as a visual display of causes that
have been studied.
·
Helping team members communicate
within the team and with the rest of the
organization.
When to use a cause-and-effect diagram?
1.
A large number of potential causes makes it
difficult to focus the analysis.
2.
there is lack of clarity about the relationship
between different potential causes.
How to construct a cause-and-effect diagram.
1.
Review the focused problem statement.
2.
Identify possible causes.
3.
Sort possible causes into reasonable
clusters.
4.
Choose a cluster and label a main one.
5.
Develop and arrange bones for that
particular cluster.
6.
Develop other main bones for other cluster
ideas.
7.
Add title, date, and contact person.
8.
Select possible causes to verify with data.
Verifying Causes
A lot of thinking and effort goes into constructing
a cause-and-effect diagram, however, these
diagrams only identify the possible causes. You
also need to collect data to confirm which
potential cause actually contributes to the
problem.
Which causes to verify:
You likely identified many potential causes on
your cause-and-effect diagram or other tool.
Now you need to set priorities and collect data on
only the most likely causes.
Mark on the diagram which potential causes you
want to verify.
In order to set priorities you should:
·
Review all the potential causes.
·
Identify which are the most likely
contributors to the problem.
·
Consider how measurable each of these
likely contributors are.
·
Consider which of the causes you should
take action on.
·
If these considerations don't help you
narrow the list significantly, have each team
member vote on the top two or three
choices.
In general, it pays to focus on the causes you can
most easily collect data on. However, some
important causes may be hard to measure or
observe, and you may need to be creative in
coming up with ways to get data for some of
those causes. Often, performing a simple
experiment (where you change the targeted factor
and observe the effect) will help you determine
the best course of action. Knowing which
potential causes you could really change will also
help you focus your efforts. It doesn't help to put
a lot of effort into gathering data on something
that you have no control over or cannot change.
Testing a theory with data:
·
The potential cause is really a theory that
two factors, or a cause and an effect, are
related to each other.
·
You need data to verify whether the cause
and the effect relationship really exists.
·
You can analyze existing data to test that
theory, or collect new data.
Analyzing cause-and-effect data will be easier if
you know which tool to use. The type of data you
will collect determines what tools you can use.
The FOCUS of the Analyze phase is: Y = f(X1, X2,
X3…..Xn) where Y is the output or effect and the
X's are the input and process variables that drive
Y. The main question to be answered in the
Analyze phase is, "What vital few process and
input variables affect CTQ (critical-to-quality)
process performance or output measures?"
Process or Data Door
It is recommended to go through both doors to
make sure that the potential causes are not
overlooked.
Process Door - Detailed Process Maps, Value
Added Analysis, Cycle Time Analysis.
·
To improve the understanding of process
flow.
·
To tackle cycle-time problems.
·
To identify opportunities to reduce process
costs.
Data Door - Stratification, Scatter Diagrams, Multi-
vari Plots
·
To understand the drivers of variation in the
process.
·
To tackle quality problems and waste.
·
To understand the root cause of difference
between outputs.
Process Door
Flow diagrams - graphical displays that make a
process visible and understandable.
Reasons to use them are:
·
To create a common understanding.
·
To clarify the steps in a process.
·
To identify improvement opportunities in a
process (complexity, waste, delays,
inefficiencies and constraints).
·
To uncover problems within the process.
·
To reveal how the process operates.
When should you use a flow diagram?
·
To create a common understanding.
·
To clarify steps in a process.
·
To build consensus on how a process
actually operates and how it should operate.
·
To understand the cause of common
problems with how all units are processed.
Types of Flow Diagrams
Basic or high-level flow diagram.
Activity Flow Diagrams
These are specific about what happens in a
process. They often capture decision points,
rework loops, complexity, logic, and so forth.
Deployment Flow Diagrams
These types of diagrams reveal the detailed steps
in a process, and depict which people or groups
are involved in each step.
Which flow diagram technique should I use?
How to create a flow diagram - When creating a
flowchart, work with a group so that you can met
multiple viewpoints.
1.
Brainstorm action steps.
a.
Write these on post-it notes and place
on the wall or use a flipchart.
b.
Make sure you include the steps that
occur when things go wrong.
2.
Arrange the steps in sequence.
a.
Be consistent in the direction of flow -
time should always flow from top to
bottom, or left to right.
b.
Use appropriate flowchart symbols
that everyone knows - use standard
symbols.
3.
Check for missing steps or decision points.
4.
Number the steps
Value-Added and Non-Value-Added Steps
Value Added Steps
1. Customers are willing to pay for it.
2. It physically changes the product.
3. It's done right the first time, every time.
Non-Value Added Steps
· Are not essential to produce output.
·
Do not add value to the output.
·
Include:
·
Defects, errors, omissions
·
Preparation/setup, control/inspection
·
Over-production, processing, inventory
·
Transporting, motion, waiting, delays
CYCLE-TIME REDUCTION
Understanding Cycle Time:
·
Provides a better understanding of the
process.
·
Shows the impact of non-value-added steps
on the time to produce product or
service.
·
Identifies bottlenecks or constraints in the
process.
Reducing Cycle Time:
·
Helps increase predictability in the process.
·
Helps reduce waste and rework, which
reduces costs.
·
Provides a competitive advantage by
reducing cycle time.
When analyzing cycle time, focus on the "thing" or
object and not on the people.
Process Analysis Review:
·
Create an activity or deployment flowchart
to map out the steps.
·
Use opportunity flowcharts or other
approaches to identify waste and complexity.
·
Measure cycle time so you can calculate
both value-added and non-value-added
time.
·
Identify the constraints or bottlenecks:
·
Any resource whose capacity limits the
amount of information or material that
flows thru the process.
·
Any resource whose capacity is equal to or
less than the demand placed upon it.
DATA DOOR
Stratified Frequency Plots - When one variable has
continuous data and another has attribute or
discrete data, the best option for analyzing results
is stratified frequency plots.
·
Gather continuous data for each of the
attribute types or categories. Collect data
on number of defects for each of the four
different types of customized orders.
·
Create a frequency plot for each category.
Use the same numeric scale and plot
size for each plot so you can easily compare
multiple plots.
·
Look for patterns.
Discrete X and Continuous Y
THEORY - Variation in training, technique and
procedures at different locations accounts for
much of the variation in how long it takes to
complete a function. For example - oil
changes/lubes.
DATA - Measure time needed to complete a lube
job at different locations.
Cause (X) = discrete data (location).
Effect (Y) = continuous data on time needed
to complete oil change/lube.
In the example above, the lubes done at location
B are generally faster than those completed at
location A or location C. The next step for this
company would be to see if they can discover the
cause for these differences.
Continuous X and Discrete Y
THEORY - The more time spent with a customer,
the more likely you will make a sale.
DATA - Measure the time spent with the customer
and separate into two categories (Made the sale
vs. Didn't make the sale).
The above example illustrates that most of the
sales were made when the sales representative
spent 25 to 45 minutes with the customer. Most
non-sales occurred when the sales representative
spent 20 minutes or less with the customer.
CONTINUE TO PART TWO OF ANALYZE NEXT- -
PART TWO
© The Quality Web, authored by Frank E. Armstrong, Making Sense
Chronicles - 2003 - 2016