Amy S Friend- STC- To Err Is Human: Applying Six Sigma Quality to Technical Communications

To Err Is Human: Applying Six Sigma Quality Concepts
To Technical Communications
Amy S. Friend
Executive Summary
This paper is the third and last in a series applying quality concepts to
technical communications. The series has explored cycle time, cost of
quality, and now six-sigma defects to improve overall operational
effectiveness and customer satisfaction.
Fred McFadden describes six-sigma as “one customer driven approach that
provides an overall framework for quality improvement.” (McFadden, pp.
37). Good improvement programs address both defects and cycle time as
leading indicators predicting improvement of lagging indicators such as
customer satisfaction and cost of quality.
Focus on quality improvement can yield attractive and necessary results for
companies. In an internet article, two major companies share good reasons
to get involved in “Achieving Six Sigma”:
• “Allied Signal reported cost savings exceeding $800 million from its Six
sigma related...initiative.”
• “At GE, the average project is five months in length and yields an 80%
reduction in defects, generating $70,000 to $100,000 in savings.”
This paper examines some basic steps to sigma quality that will reduce
defects in products, processes and services. It will cover both operational
formulas and managerial processes that are used to achieve improvements.
A case study illustrates the steps applied to technical communications.
What is Sigma Quality?
Sigma is a measure of quality for products, processes, or services.
The Greek letter sigma represents standard deviation, which is a common
measure of variability used in statistics. Defects are often caused by too
much variability in the process. Such defects result in the inability to meet
customers’ requirements or operational effectiveness.
Sigma refers to a specific level of quality quantified by a number of defects.
Six-sigma is a specific level of quality equivalent to 3.4 defects per million
opportunities. Six-sigma has become the rating that signifies best-in-class
status. Refer to the table for defects for each sigma level.
Sigma Level Defects Per Million Opportunities
3.0 66,811

To Err Is Human: Applying Six Sigma Quality Concepts To Technical Communications, Amy Friend, c 1999
4.0 6,210
5.0 233
6.0 3.4
Table: Sigma Level for DPMO
Six-sigma also refers to a methodology to reach optimum quality levels.
This methodology provides metrics to quantify and track quality and process
steps to improve quality levels. Some of the “Steps to Six-Sigma” and
equations are covered in this paper.
1. Define products, services, and processes
2. Identify customer requirements
3. Compare product with requirements
4. Describe the process
5. Improve the process
6. Measure quality and productivity
Figure: Steps to Six-Sigma
The Sigma methodology used to reduce defects is applicable to any product,
service, or process. These steps resemble a generic problem-solving model.
Applications of Sigma
Six-sigma has been primarily used in manufacturing. However, many
quality conscious companies have applied the sigma quality concepts to
improve products, services, and processes. Since the concept of six-sigma
helps to answer the question “how good is good enough?” It is used to
improve many kinds of businesses, including technical communications.
The Schaumburg Central Engineering Service Group was one of the first to
apply six-sigma to technical communications. Information Services at
Motorola continued the application in their work. Examples from Motorola
will be used to illustrate applications.
Defects
Defects can be defined as:
• Any variation in a product, process, or service which would prevent us
from meeting the needs of the customer and/or which adds cost, whether
or not it is detected.
• In practice, it is non-conformance to a customer-driven specification.
• Any non-conformance, interruption of the flow, or intervention in the
flow.

Examples of Product Defects in Technical Communications:
• Document cover is torn
• Mis-spelled words
• Incorrect content in publication
Examples of Service Defects in Technical Communications:
• Incomplete order shipped to customer
• Job estimate not completed on time
• Printing not completed on time
Examples of Process Defects in Technical Communications:
• Subject Matter Expert is not available for specified time
• Illustrations need to be redone
• Computer needs to be repaired
• Product is not available on time
• Writer is not trained on software as prescribed
• Meetings start late
Observed Defects
Observed defects are those defects found within the scope of our operation,
before the customer receives the product or service. It is advantageous to
find defects before customers do to limit the impact on customer
satisfaction, loyalty, and retention. Such observed defects may be part of the
process or the products/services. A number of steps are built into our
processes to enable us to catch these defects:
• Development of templates, styles, and standards
• Training of employees to do their jobs
• Reviews by Subject-Matter Experts to ensure the content is correct
• Validations and verifications by target audience to ensure clarity and
relevence of content
• Reviews by editors to ensure adherence to styles and standards
• Approvals by management on plans to ensure fulfillment of client
requirements
Observed defects are leading indicators of the final product quality. If
defects are caught and corrected during our processes, you can eliminate
escaped defects before the customer sees them. Unnessesary rework can also
be eliminated.

Escaped Defects
Escaped defects are those errors that we miss and that reach customers.
Inspections and reviews are not 100% effective, so some defects will reach
the customer. We hear about some of these defects in the form of customer
complaints. Some defects the customers don't catch either.
Since customers do not report many escaped defects, we typically count
only observed defects as part of process improvement. However, it is
important to track escaped defects as they are a key source of customer
dissatisfaction. Both observed and escaped defects should be used to make
improvements. Many folks focus improvements on observed defects
because they can be tracked more reliably. Escaped defects are used to
better understand causes of customer dissatisfaction.
Units
Just counting defects may not provide enough information to analyze the
quality on an ongoing basis over time. To look at the rate of improvement
over time, the number of defects is compared against the number of units.
A Unit is:
• The normal end product or output of the process
• What the customer buys, the saleable unit
Examples of units in Technical communications include:
• Service Manual
• Operators Guide
• Newsletter
• Student Guide
• Video program
• Software Manual
DPU
The defects-per-unit (DPU) compares the number of observed or counted
defects to the number of units processed. Looking at the DPU provides some
benefits:
• Suppose that your Newsletter group issued one newsletter this week
with a total of one observed defect for the week; last week, the group
issued six newsletters, with a total of two observed defects for the week.
• If you only count defects, you find one defect this week and two last
week. This week looks better than last week.
• If you look at DPU, you find that this week 100% of units contained
defects. Last week, only 33% of units contained defects.

• If there is variability in the process volume, looking at the DPU will
normalize the variability somewhat so that you can make valid
comparisons of the quality from one week to the next.
Figure: Tracking DPU for Newsletter Quality
In the figure above, notice the reduction in defects per unit (DPU) as
improvements are implemented.
Opportunities
Opportunities are used when it is necessary to compare a simple product,
process, or service to a more complex one. For example: is it fair to compare
the DPU of a Newsletter process to that of a Service Document process?
No! The Newsletter process is simpler, shorter, and has fewer chances for
errors than that of the Service Documentation process. Two aspects to keep
in mind when identifying opportunities include:
• Opportunities are counted by the people who own/do the process
• Opportunities are measured once and do not change unless the process
changes
DPO
Defects per Opportunity (DPO) takes observed Defects per Unit (DPU) and
divides them by the number of opportunities (O) per unit.
DPMO
Typically this number is very small. Multiply by a million to get a number
that is easier to deal with. The result is called Defects Per Million
Opportunities (DPMO).
DPU is typically the measure used to track internal operations. DPMO is the
number used to identify the sigma level and is also the number used when
benchmarking with other external organizations.
1998 Newsletter DPU
0
10
20
30
40
50
1 2 3 4 5 6 7 8 9 10 11 12
Month
DPU

Equations
DPU = Total Number of Defects Counted .
Total Number of Units Completed in same time
DPO = DPU .
Total Number of Opportunities
DPMO = DPO X 1 million
SIGMA
It is the DPMO number that identifies the sigma level. While there are
lengthy calculations that can be done to determine the sigma level for the
DPMO, it is easier to use a Sigma Table.
Sigma Level Defects Per Million Opportunities
3.0 66,811
3.5 22,750
4.0 6,210
4.5 1,350
5.0 233
5.5 32
6.0 3.4
6.5 0.3
Table: Sigma Look-up Table
How is Sigma used?
Sigma is used to:
• Benchmark with other companies
• Improve the quality of products, processes, and services
• Improve customer satisfaction
• Set challenging goals for teams and companies

How do I start?
Measure Current Defects
1. Define Defects
First define the defects for your product, service and/or process. Define
them in terms of what is important to the customers.
It may be helpful to brainstorm defects. Consider the customer complaints
received. Consider the things that really upset the process owners. Look at
the process flow to help generate the list.
The Motorola team used error categories to define defects in their
publications.
Error Category Types of Defects
Text Structure Defects of grammar, syntax, spelling,
reference accuracy, cohesiveness of thought,
ambiguity, and consistency in abbreviations
and terms
Graphic Aspects Defects of illustration quality and the
consistency of the illustrations to the format
required both by the client and the Technical
Communications Group’s graphics standards
Client Direction Defects exceeding a stated reading-grade
level, not adhering to customer or internal
department specifications, or incorrect page
layout
Technical Accuracy Defects found in the process of a Subject-
Matter Expert (SME) review of technical
text (i.e. the theory is incorrect as stated), or
validation/verification of the text by the
customer. Customer in this case may be
either the SME or an external end-user
Procedural Accuracy Defects found during a “tabletop” validation
(reading the steps) of all procedural material,
or by actually using the steps to operate the
equipment described in the document to see
if they work
Table: Motorola Error Categories
These categories are used for all kinds of publications, regardless of length
or purpose. They provided a common frame of reference for every
document checked. These categories make the metric more specific in terms
of what is most important to the customers, not the internal process owners.
They also enable the team to pinpoint the areas that need the most
improvement later in the process.

2. Count Defects
Next, count the defects. How many errors are there? Keep a tally of each
kind of defect.
It is important to ensure consistency of how defects are counted. To do this
consider these aspects:
1. Develop a defect counting tool.
2. Train editors/writers on use of the tool and definition of defects.
Keep tools simple and easy to use. The more complex a tool is, the more
chance there is for people to not use them or to not use them correctly.
Training people on how to use tools and apply quality concepts helps to
ensure that the results are meaningful, consistent, and accurate. Demonstrate
how to apply defect-tracking tools. Provide coaching on the job while
people are just starting to use new tools.

Refer to the figure for an example of how Motorola applied the concept of a
tool.
Publication Quality Tracking Form
Job title: “Georgia” Proposal
Date: May 12,
1993
Team Leader: G. Giddy
Charge Number: 12345-4321 Job Number: 5512
Client/Customer: Joan Smythe
Applicable
Specifications:
Standard Newsletter format
Sample Size (pg.) Sample = 30 + 0.3 (147-30) = 41
Weighting Factors Pages
Checked
Customer
Weight
Defects
Counted
A. Text Structure
• Spelling
• Grammar
• Syntax
• Ref. Accuracy
• Consistency
41 0.6 2
B. Graphic Aspects
• Illustration quality
• Consistent to
format
Simple:
Medium:
Complex:
8 0.25 2
C. Technical
Accuracy
• Tabletop
validation
• SME review
0 0
D. Procedural
Accuracy
• Tabletop
• Validation/verific
ation
0 0
E. Client/Customer
Direction
• Reading grade
level
• Page layout
• Spec adherence
41 0.15 1
Table: Motorola Matrix Check Sheet Example

Notice that Motorola also applied two more factors:
• Customers weight the importance of each element. This helps to focus
improvements on areas most important to customers’ requirements.
• Determination of appropriate sample size. Publication departments
produce thousands of pages or screens of documentation. Defining a
significant sample size allows the department to not have to count
defects on every page/screen of every document.
A Case Study
Figure: Sample Process
This example shows a simple process for developing a newsletter. The
process starts with a request to write a newsletter and ends when the
customer receives the newsletter.
In this example a unit is defined as one newsletter request. Defects tracked
include:
• Text Structure
• Graphic Aspects
• Client Direction
• Technical Accuracy
• Procedural Accuracy
The table analyzes the DPU for this simple process:
SME
Correct?
Type
Newsletter
Mail
Newsletter
Proofread Approve
Request
Gather content
No Yes
Customer

Gather Type Proofread Approve Mail
Observed
Defects
0 2 10 0 0
Units 20 20 20 20 20
DPU 0 0.1 0.5 0 0
Cumulative
DPU
0 0.1 0.6 0.6 0.6
Table: Defect Analysis for DPU
• The Units row shows that 20 newsletters were completed during this
period.
• The Observed Defects row shows 2 defects found in typing, ten defects
found in proofreading, and zero defects found in approval and mailing.
• The DPU row shows that, normalized over 20 newsletters, .1 defects per
unit were found in typing and .5 defects per unit were found in
proofreading.
• The Cumulative DPU row shows the running total DPU for each step,
the total cumulative DPU being .6.
By analyzing the process this way, you can quantify the overall quality
level, check that proper inspections are built-in, and identify areas of the
process that need improvement.
Some escaping defects were identified through customer complaints. Two
customers found errors in their newsletters and one newsletter was not
received. While these defects were not calculated as part of the defect
analysis, they are helpful to understand improvements needed.
Now we want to be able to compare the quality of the newsletters with the
quality of the customer user guides. To do this, factor in the opportunities.
Gather Type Proofre
ad
Approve Mail Total
DPU 0 0.1 0.5 0 0 0.6
Opportunities 20 180 5 1 2 208
DPO 0 .0005555 0.1 0 0 0.002884
DPMO 0 555 100000 0 0 2884.6
SIGMA Level 7 5 4.6
Table: Defect Analysis for DPO
• The DPU row is carried over from the previous table.
• The Opportunities row shows the number of opportunities identified for
each step. There are a total of 208 opportunities for defects in the

newsletter process. To get these each step was analyzed by the writers.
The number of opportunities remains the same each week unless there is
a change to the process.
• To calculate the DPO, divide the DPU by the number of opportunities.
• The Total DPO for the process is .002884.
• To calculate the DPMO, multiply the DPO by one million. The final
DPMO for the newsletter process is 2884.6.
• To determine the sigma level, look up the DPMO in the SIGMA Table.
The cumulative sigma level for the newsletter process is 4.6.
How do I improve Sigma?
Analyze Baseline Data
Understand the defect calculations for the process. What defects are
counted? What opportunities were include? What is the DPU of the process?
Is the process stable? You’ll need to understand your process very
thoroughly to compare it to others.
How Good Is Good Enough: Set a Goal
A six-sigma rating indicates best-in-class status. However, six-sigma may
not be the best goal for every application. Some cases may require higher
than six-sigma and others may allow for less than six-sigma. To identify the
best goal, you need to understand what is expected and what is possible.
What do your customers expect? Are the results of a six-sigma process
acceptable? For examples, refer to the table below:
Comparing Performance:
99.9% Defect Free 6 Sigma
Wrong prescriptions 20,000 per year 68 per year
Babies dropped 15,000 per year 51 per year
Unsafe drinking water 1 hour per month 12 seconds per
month
No telephone service or
television
10 minutes per
week
2 seconds per week
Short or long landings at
O’Hare
2 per day 5 per 2 years
Incorrect surgical procedures 500 per week 88 per year
Lost articles of mail 2,000 per hour 160 per day

Table: Comparing Performances
Also, we need to understand what is possible. How capable is our process?
How good are other similar processes? How much room for improvement is
there? A statistician may be helpful in calculating the process capability. If
you don’t have such a resource, what does your experience tell you about
the quality of the process? Is there room for improvement? Conduct some
research to determine how good competitors perform and how good is good
enough.
The December 1994 issue of Quality Progress reports that “most quality-
conscious companies averaged a four-sigma level at the beginning of 1990,
with the exception of the domestic airline flight fatality rate, which was
better than six sigma.” This points out the need for different goals depending
on how critical the results are.
If it is not possible to compare to other departments outside your company,
compare with other processes inside your company. Comparitive processes
need not be competitive processes. You can learn a lot by understanding
other processes that have different products with similar goals. For example,
any company regardless of their product can learn about great customer
satisfaction from observing the practices of LLBEAN or Disney.
Analyze
If there is a gap to close, then work to close the gap. The rate of
improvement will depend on the size of the gap and the impact on customers
needs. If your business is eroding quickly due to large defect issues, you
may want to speed of the rate of improvement. If your process shows that it
is already at a higher sigma rate than competitors or that customer
complaints are not severe, then the rate of improvement may be slower. It
may only be necessary to improve enough to stay ahead of the pack.
Conduct Defect Analysis
Prioritize the types, frequency, and cost of defects. Target root cause
analysis based on frequency and financial impact.
Check out the process flow map and look for opportunities to make the
process more robust. Are there places where verifications and checks can be
added to prevent defects before they escape to the customers?
Find Underlying Causes and Remove Through Projects
Determine root causes of defects by either:
• Asking “why?” 5 times
• Completing an Fishbone Cause and Effect Diagram
Table: Example of 5 Why’s

Improvements may take many forms. They may be changes to:
• Process (i.e. eliminate, simplify, or automate steps to process, addition
of editor)
• Policies (i.e. requirements in approvals)
• People (i.e. training, entry skills, etc.)
• Tools/equipment (i.e. upgrade of tools to include more robust spell-
checker)
Verify and Monitor Improvement
Continue to track the DPU. Verify that the process stays in control. If the
DPU falls below target levels, identify the cause and make corrections. This
step is most important to ensure that the time invested to make
improvements is not wasted later due to lack of conformance to process
improvements.
Case Study Continued
Comparitive Process: Web Page Development
Since this group has no external processes to compare against, they
compared against another process in the company: the web development
process.
Gather Input &
Design
Edit Approve Post Totals
Defects Observed 0 2 10 0 0 12
Units 20 20 20 20 20 20
DPU 0 0.1 0.5 0 0 0.6
Opportunities 5 100 5 1 1 112
DPO 0 0.001 0.1 0 0 0.005357
DPMO 0 1000 100000 0 0 5357.1
SIGMA Level
Table: Defect Analysis for Web Process
Pareto Defects
Defect Quantity Cost
Text Structure 2 $50
Graphics 3 $150

Client direction 0 $0
Technical
Accuracy
6 $300
Procedural
Accuracy
1 $25
Total 12 $525
Table: Example of
Root Cause Analysis
This example applies the method of asking “why?” five times for the
problem of too many technical defects.
Why? Answer
1. Why are there so many technical
errors?
Errors are not noticed during
technical proofreading.
2. Why are errors not noticed? SME’s do not see them.
3. Why don’t SME’s see errors? They don’t know a lot about the
product.
4. Why don’t SME’s know a lot
about product?
They don’t have a lot of time to
work with the product.
5. Why don’t SME’s have much
time to work with the product?
There isn’t a product available for
them in the department.
Table: Example of 5 Why’s
Possible Improvements
In the example, the real problem to address is getting enough equipment and
product exposure for the Subject Matter Experts.
Summary
In a time when competition is strong and the need for value is increasing,
every person in any job must continue to improve how they work. Six-sigma
provides some basic tools to apply to help us achieve this. Metrics like DPU
enable us to track and monitor the health of our processes. Metrics like
DPMO enables us to compare our quality to others so that we can answer
the question “how good is good enough?” Using accepted quality tools such
as process flow mapping, graphing data, and root cause analysis enable us to
focus limited resources in the best ways. To err is human, but not every
human strives for improvement. Six-sigma is one methodology to attain
good quality products, services and processes.

References
• McFadden, Fred R. (1993). “Six-Sigma Quality Programs.” Quality
Progress; June, pp. 37-42.
• Fontenot, Gwen, Behara, Ravi, and Gresham, Alicia (1994). “Six sigma
in Customer Satisfaction.” Quality Progress; December, pp. 73-75.
• Tadikamalla, Pandu R. (1994). “The Confusion Over Six sigma
Quality.” Quality Press; November, 1994, pp83-85.
• National Center for Manufacturing Sciences (1996). An Introduction to
Six Sigma. (Interactive Distance Learning Course Guide). National
Center for Manufacturing Sciences, Inc., US.
• Holt, Roger W. & Millman, Jack H. (1993). A Methodology for
Measurement of Publications Quality. Motorola University Press,
Addison-Wesley Publishing Group, Reading Massachusetts.
• Smith, Bill. (1993) “Six Sigma Quality: A Must Not A Myth.” Machine
Design; February 12, pp.63-66.
• Pyzdek, Thomas. (1996) The Complete Guide to the CQM. Quality
Publishing, Inc., Tucson, Arizona
• Cortada, James, & Woods, John (1995). McGraw-Hill Encyclopedia of
Quality Terms & Concepts. McGraw-Hill, Inc., USA.
• Allied Signal (1999). Achieving Six Sigma [Online]. Available:
http://wwwmpcps.com/A6S.html[1999, February].
• Eastman Kodak Company (1996). Getting Started With 10X. Rochester,
NY.
Amy S. Friend
Amy Friend is a Certified Quality Improvement Facilitator for Eastman
Kodak Company. In this position she helps groups to improve their
processes using quality principles. Prior to this, Amy developed and
delivered training programs as an Instructional Designer.
Amy is also Adjunct Faculty at RIT where she teaches Instructional Design
Principles. She develops and teaches classroom and distance-learning
courses.
Amy has served as President, Vice President, and Treasurer for the
Rochester Chapter of STC. She presents frequently for STC and has
presented/published at the International-level. She has chaired the spectrum
planning committee twice and has been a volunteer on this committee for
the past seven years. Currently she is serving as Web Master and Strategic
Planning Committee Chair. She has published a number of articles and
presentations on a variety of process improvement topics including cost of
quality, cycle time, dealing with change, and sigma quality.

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