Tuesday, November 3, 2009

Visual Controls Make "Cents"

As many of you know, in addition to consulting, I am an adjunct professor at a college with a large number of international students. Normally I teach statistics, but recently I had the opportunity of familiarizing newly arrived international students with U.S. cultural and business communications.

As part of the workshop for new international students, I engaged the class in a discussion about what they have found to be problematic since their arrival in the United States. Surprisingly the one reoccurring topic that challenged the students, was our coins.

At first I was stunned. Of all the things in this country, the most challenging to newly arrived foreigners was our coins? After considering this for a moment, it made perfect sense. How?

Think about it, the designed system lacks visual clues; it relies almost entirely on the tribal knowledge of the user. It is hardly intuitive; the smallest coin, the dime, is worth more than the larger penny and nickel! Now combine that with the fact that none of our coins have large, easy to read numbers denoting worth; we can “cents” and understand how this combination can pose problems for newly arrived foreigners.

Given the lack of effective visual controls on the coins, it’s easy to comprehend why the newly arrived find this challenging and frustrating.

Now ask yourself, what in your business is not visually intuitive and causes problems? Simply put, are problems going undetected because the visuals controls in your workplace are ineffective? Can you walk into a material storage location and see what needs to be reordered? Can the leaders tell the status of the business simply by walking through the facility and observing?

Excellent examples of effective visual controls are the arrival and departure boards at an airport. First of all, these boards are easy to use, clearly labeled, and very intuitive. Even if you have never been in an airport before, you can look at the board and obtain the information about your flight. Not only does the board display the information, it will provide visual alerts by flashing when flights are changing status.

This information is not closely held and limited to only the airport’s managers. The status of every flight into and out of the airport is readily available and viewable by all. Just as importantly, the board provides only the necessary information and doesn’t overwhelm the traveler with unnecessary details. The required information is freely placed into the hands of those who need it and problems are easy to see.

Now expand on that concept and apply it your business. Does your staff know the status of inventories, deadlines, and other critical information? Are your visual controls improving information flow and process control?

More importantly, what benefits can you experience from an effective visual workplace?

Higher job satisfaction – Individuals experience less stress because they have the required information to perform their jobs
Safer work environment – Walkways are clearly labeled keeping individuals at a safe distance from moving vehicles and machinery
Higher quality – Fewer defects/errors as problems become easy to see
Greater efficiencies - Required information/material is readily available resulting in less downtime
Improved appearance – Workplace is neat and orderly
Improved Bottom Line – Reduced errors plus greater efficiency equals a better bottom line.

A visual workplace, which is often times associated with a 5S program, should be self-ordering, self-explanatory, and self-regulating.

If your business is experiencing problems because you can’t tell the status of the business simply by walking through and using tools deployed as part of a visual workplace, then I encourage you to consider launching a lean sigma program. It makes “cents.”

Please leave your comments or email me directly at royce.williard@gmail.com

Learn more about the author by checking my LinkedIn profile at http://www.linkedin.com/in/roycewilliard

 2009, The Williard Group

Photo Source:

Figure 1: Public Domain Photo of U.S. dime. Source: Clipart Graphics


Friday, October 23, 2009

The Use Of Lean Visual Controls In Retail

OK, I confess. I’m one of “those” people. You know, one of “those” Apple people. If you didn’t know this before, know that I love my iMac, MacBook, and 2 iPhones. But this is not a blog about how pleased I am with Apple products and their customer service. Rather, it is a blog about Lean Sigma visual controls in the retail industry.

The other day my MacBook would not start up. I was left standing there in front of my class of graduate students with the day’s entire lecture on my beloved MacBook, staring at a black screen. After calling technical support and speaking to a real person almost immediately, I quickly learned that the issue was hardware related.

The next day, I found myself walking into the local Apple Store so my computer could be physically tested. Moments after I walked in, I asked a store employee in a blue t-shirt if I needed to check in for my appointment. He said “Yes, see that guy in the orange t-shirt, check in with him.” No other description was necessary. Simple but effective, just as lean is supposed to be.

I later asked and learned that the Apple Store uses the following color code for their employees, the sales people are in turquoise, the technical people are in blue, and the concierges are in orange. Need to talk to a sales person, simply find someone in a turquoise t-shirt. It is elegant in its simplicity and effectiveness. Kudos to Apple for being a role model in the use of visual controls to identify different job functions in a retail environment.

A special thank you to the Apple Store employees for allowing me to take and use this photo as an example of visual controls.

Please leave your comments or email me directly at royce.williard@gmail.com

Learn more about the author by checking my LinkedIn profile at http://www.linkedin.com/in/roycewilliard

Post Author: Royce Williard

Copyright 2009, The Williard Group

Wednesday, October 21, 2009

A Lean Six Sigma look at the Infant Mortality Rate in the U.S.

In my last post, I analyzed the performance of the U.S. health care system based on a statistical review of the information contained in the World Health Organization’s database. Since that article was published, I have been asked numerous questions regarding health care within each state. In response to those questions, I recently completed a deeper statistical review of the Infant Mortality Rate (IMR) in the U.S.. The facts and conclusions are detailed below.

The U.S. has the highest per capita spend on health care in the world and had an IMR of 6.86 per 1000 live births for period 2002 -2004. In 2006, based on World Health Organization data, the U.S. was tied for 39th for the lowest IMR with countries such as Lithuania, Serbia, Slovakia, and Thailand.

Even more shocking, the 2006 mean IMR for the 30 countries with the highest per capita health care spend, was 3.9 per 1,000 live births. Simply put, if the U.S. simply were to achieve the mean IMR for the 30 total spending countries, there would have been over 12,000 more live births!


Live Births 2004


Mean IMR of 40 highest spending countries


Additional Live Births

United States






Next came the question, does every state in the U.S. have approximately the same IMR? Or do some states actually have higher levels? If so, how high?

To answer these questions, I obtained the report detailing the IMR by state and the District of Columbia and conducted another analysis. The data is from 2002 – 2004.

Armed with the IMR rates on all 50 states plus the District of Columbia, I constructed a histogram to graphically summarize and display all the data. From the graph below, we can see that:

  • The largest number of states has an IMR of between 6.00 and 6.99 per 1000 live births.
  • Four states produced exceptionally good IMR statistics of between 4.00 and 4.99.
  • The poorest performing areas posted IMRs above 9.00 per 1000 live births.

Additionally, the median IMR rate of the 50 states plus the District of Columbia was 6.94. As previous stated the U.S., as a whole, recorded an IMR of 6.86 for this period.

More specifically, the four states with the highest IMR are as follows:

1. District of Columbia 11.42

2. Mississippi 10.32

3. Louisiana 9.95

4. Tennessee 9.05

This data was shocking. Imagine my surprise to learn that an infant born in Bulgaria, Malaysia, or Russia actually has a higher probability of survival than does an infant born in Washington DC!

The four states with the lowest IMR are as follows:

1. Vermont 4.68

2. Massachusetts 4.80

3. Minnesota 4.85

4. New Hampshire 4.93

For a complete look at all 50 states plus the District of Columbia, please refer to the following control chart.

So now that we know which of the 50 states and the District of Columbia have the highest and lowest IMRs, the question yet to be answered is why? To explore that question, I obtained data from the U.S. Census Bureau on income.

After reviewing that data and comparing it to the IMR information, I was able to determine that a high correlation exists between IMR and the percent of the population living at or below 125% of the poverty level. In fact, these two variables have a correlation coefficient of 0.645.

Simply put, all this means is as the percent of individuals living at or below 125% of poverty increases, so does the IMR. This data may be viewed on the following scatter plot.

So why are our government officials not outraged over the IMR in this country? Most likely because it doesn’t happen in their neighborhoods, but that fact may be changing. Based on U.S. Census Bureau data, the 46 million uninsured have an income distribution as follows:·

  • 14,561,000 (24.4%) of those making less than $25,000 annually are uninsured
  • 14,977,000 (20.6%) of those making between $25,000 and $49,999 annually are uninsured
  • 8,300,000 (14.1%) of the making between $50,000 and $74,999 annually are uninsured
  • 8,740.000 (8.5%) of those making $75,000 and more are uninsured.

The following histogram details the number of uninsured by income level based on the U.S. Census Bureau’s report “Income, Poverty, and Health Insurance Coverage in the United States: 2005”.

Clearly some number of individuals opt out of health insurance. But, when considering the income distribution, I believe the high cost of insurance excludes some number of those who are self-employed or covered by employer plans.

Furthermore, the U.S. has long been a champion of human rights. In fact, in 1966, the U.S. signed the United Nations’ International Covenant on Economic, Social and Cultural Rights. This document contains the following provision:

Article 12

1. The States Parties to the present Covenant recognize the right of everyone to the enjoyment of the highest attainable standard of physical and mental health.

2. The steps to be taken by the States Parties to the present Covenant to achieve the full realization of this right shall include those necessary for:

(a) The provision for the reduction of the stillbirth-rate and of infant mortality and for the healthy development of the child;

(b) The improvement of all aspects of environmental and industrial hygiene;

(c) The prevention, treatment and control of epidemic, endemic, occupational and other diseases;

(d) The creation of conditions, which would assure to all medical service and medical attention in the event of sickness.

Since that time, our health care system has evolved into the most expensive in the world, costing a staggering 15.3% of the GDP. Yet, this country is tied for 39th in the world on IMR and results in an estimated loss of 12,000 lives annually.

We can do better. As an expert in lean six sigma enterprise and a father of two children who died shortly after birth, I assure you, we can achieve so much more in saving the lives of our future. Unless immediate, corrective action is taken, health care and the right to life will become a privilege reserved only for the wealthy.

Learn more about the author by checking my LinkedIn profile at http://www.linkedin.com/in/roycewilliard


Martin, J. A., Kung, H. C., Mathews, T. J., Hoyert, D. L., Strobino, D. M., Guyer, B., & Sutton, S. R., (2008). Annual summary of vital statistics: 2006. Pediatrics, 121(4), Retrieved from http://pediatrics.aappublications.org/cgi/reprint/121/4/788 doi:10.1542/peds.2007-3753

Post Author: Royce Williard

Copyright 2009, The Williard Group

Thursday, August 20, 2009

Continuous Improvement, Lean Sigma, and Health Care Reform

It seems you can’t pick up a newspaper or turn on your television these days without hearing something about the current health care situation within the United States. Some claim the US has the best health care available in the world today. Others claim the current US health care system costs an excessive amount while providing inferior care. Some favor radical change, while others don’t want to change a thing. Rarely are any of these claims accompanied by facts, as viewed recently at various town hall meetings.

As a Lean Six Sigma champion and natural skeptic, I decided to let the numbers speak for themselves by conducting my own analysis using publicly available data. This article simply presents a factual review of the current state of US health care.

The source for the data is the World Health Organization (WHO). My analysis utilized the most recent data available from the WHO and was retrieved as of August 3, 2009. There are 193 countries contained in this report. To focus on “more bang for the health care buck”, I limited my analysis to the top 29 countries with the highest per capita total expenditure on health care at the average exchange rate (US$).

The countries in the top 29 in order based on total per capita health spend are (1) United States, (2) Luxembourg, (3) Monaco, (4) Norway, (5) Switzerland, (6) Iceland, (7) Denmark, (8) France, (9) Canada, (10) Ireland, (11) Sweden, (12) Austria, (13) Netherlands, (14) Germany, (15) San Marino, (16) Belgium, (17) United Kingdom, (18) Australia, (19) Finland, (20) Italy, (21) Andorra, (22) Qatar, (23) Greece, (24) Japan, (25) New Zealand, (26) Spain, (27) Portugal, (28) Israel, and (29) Slovenia. I focused on 25 variables over these 29 countries.

Executive Summary

After extensive review of 25 key performance measures in the 29 countries with the highest per capita health expenditure, it is clear that US residents pay a premium rate for a health care system that produces less than premium results. Residents in the US have the worlds most expensive per capita cost system. The total health expenditure in this country represents a staggering 15.3% of our Gross Domestic Product (GDP).

In spite of the huge expenditure, life expectancy in the US ranks 27th of the 29 countries in the study. Additionally, only 1 country in this study has a higher infant mortality rate! These are unquestionably dismal results.

Surprisingly, the US government ranks 3rd in the study for general government expenditure on health as percentage of total government expenditure. The current US government expenditure seems extremely high when compared to the countries with national systems. This would seem to imply that enough waste might exist in the current system that health care reform could be accomplished without raising taxes.

While there is no single issue that would resolve all of the issues with the US health care system, there is a void in the current system where those without insurance are going without the basic care available to those with insurance. This void is unquestionably resulting in loss of life as the US system ranks:

  • 2nd amongst countries in the study in infant mortality rate
  • 2nd amongst countries in the study in probability of dying by age 5
  • 1st amongst countries in the study in the probability of dying between ages 15 – 60

The current US health care system is fundamentally flawed and requires immediate and dramatic action to lower the current cost, reduce mortality rates and improve life expectancy. This will most likely mean providing access to health care insurance for the uninsured and under insured.

Lean Six Sigma is based on a foundation of continuous process improvement. However, before we can improve upon health care reform, we must first define/implement our initial efforts. We simply need to implement a plan and begin the PDCA (Plan, Do, Check, Act) cycle.Unfortunately, our government currently seems more interested in arguing over the Plan and never gets to the Do, Check, and Act.

Cost of Health Care


  1. The mean is the average of all 29 countries included in the study.
  2. The median is the middle value of all 29 countries included in the study.

Based on the WHO data retrieved August 3, 2009, the US has the highest total health care spend per capita in the world! Additionally, the US has the world highest total spend as a percent of the GDP of any country in the Top 29 list reviewed.

The US spends 15.3% of the GDP on health care. This expenditure is “out of statistical control” when compared to the Top 29 countries. Of particular note, is the fact the US government currently ranks 3rd of the Top 29 countries by spending 19.1% of it’s total spend on health care.

Simply put, the current health expense incurred by the US government is surprisingly high when compared to other countries that offer a more nationalized system. All of this data supports the fact that the US health care system is extremely expensive.

Quality of Health Care

Assuming that a key measure of success of a nation’s health care system would be a long life expectancy and low mortality rates, the US system’s performance can best be described as dismal when compared to the other countries in this analysis.

  • The mean life expectancy for the 29 countries studied is 80.28 years as compared to 78 years in the US.
  • Of the 29 countries in this analysis, 26 of the countries rank ahead of the US in Life Expectancy at birth for both sexes.
  • The US is tied with Slovenia with a life expectancy of 78 years and ahead of only Qatar (77 years).

Additionally, I reviewed the data from the Healthy life expectancy (HALE) at birth (years) both sexes.

  • The mean Healthy life expectancy for the 29 countries is 71.41 years while US residents can expect 69 years.
  • 25 of the 29 countries studied posted results higher than the US in this key measure.

In terms of mortality rates, US residents had the highest probability of dying between ages 15 and 60 of any of the 29 countries included in the study. Only 1 of the 29 countries (Qatar) studied had a higher infant and under 5 years old mortality rate.

Health Care Risk Factors

It is interesting to note that while the US has the highest percentage of obese adults of countries in the study, this fact had not dramatically impacted the mortality rate for cardiovascular disease in the country as the US ranks 10th in the study.


The current system of health care in the US is expensive and life expectancies are low as compared to the countries in this study. Assuming that US medical personnel, technology, and infrastructure is at a minimum equal to the countries with higher performing systems, we are left with the question why is the life expectancy in the US less than top performing nations? The answer is simply that health care services are not available to the uninsured and under insured in a timely manner.

As the result, in America, those without health insurance are more likely to not receive timely treatment and simply die sooner. Additionally, many of those without health insurance often seek initial medical advice later, which results in higher costs in treating conditions, which worsened due to lack of timely intervention. We simply cannot allow life expectancy in this country to be dictated by an individual’s social economic status. In a great country such as ours, access to health care must be a right and not a privilege. In order to improve the performance of our health care system, we must provide for affordable health care insurance without disqualifying individuals due to pre-existing conditions.

For whatever reason, the US government has failed to undertake dramatic reform measures prior to this date. Our government has been paralyzed as our elected officials argue over one plan or another. They are failing to recognize a very basic principle in Lean Six Sigma, continuous process improvement. Our representatives should select the best plan currently available and implement. This plan should be improved upon in the upcoming years. The time for action is now. Doing nothing is simply not an option.

According to information retrieved from the National Coalition on Health Care on August 11, 2009, (http://www.nchc.org/facts/coverage.shtml ) approximately 46 million Americans (or 18% of the population below age 65) were without health care in 2007. This number issued by 2.2 million people between 2005 and 2006 and has grown by more than 8 million people since 2000. To reduce mortality rates and improve life expectancy in this country, steps must be taken to provide for access to health care for the uninsured and under insured.

Fact, many Americans today are a pink-slip away from losing their health insurance. Therefore, we can expect an increase in the number of uninsured and under insured, due in part, to the slow economy.

So, how do we get “more bang for our health care buck?” By implementing a meaningful reform package in conjunction with a continuous process improvement plan; this will ensure that the US health care system provides premier performance results for years to come.

Author’s note

In recent weeks, both sides of the health care debate have tossed around outlandish statements. In order to help separate the fact from the fiction, I would encourage reader’s to checkout the 2009 Pulitzer Prize winning site http://www.politifact.com/truth-o-meter/subjects/health/?page=1 for a honest fact check on statements made in the health care debate.

Friday, May 22, 2009

Promoting the importance of “The Customer” in Lean Times

I saw a quote from Brian Buck (@BrianBuck) on Twitter the other day that really resonated with me.  The quote was attributed to Gandhi and stated ….

“A customer is the most important visitor on our premises, he is not dependent on us. We are dependent on him. He is not an interruption in our work. He is the purpose of it. He is not an outsider in our business. He is part of it. We are not doing him a favor by serving him. He is doing us a favor by giving us an opportunity to do so.”

While most business people would say they agree with Gandi, how many truly promote the importance of “The Customer” within their business?  Is it engrained in their culture?  What do they really know about their clients?  With today’s technology, many businesses capture specific customer data on their clients, but fail to use it!  It cannot be stressed enough that increased customer loyalty can make or break a company in slow economic times.

During times of economic expansion, many companies view customer service as an expense that drains the bottom line.  In lean times, companies cannot afford this type of “relationship arrogance.”  In fact, companies need to maintain and enhance their business relationships.  One way to maintain and grow these relationships is to invest in customer service by ensuring that your customer’s most critical needs/requirements are being fulfilled.

Can Lean Six Sigma tools help you gain an understanding about your customers?  Yes, histograms are a perfect tool to visually display your customer detail or any other data that can be easily ranged into groups.  Classically, a histogram would be defined as a graphic summation and display the frequency of data items in successive bins/classes.  The most common histogram has the dependent variable (frequency) plotted on the vertical axis and the independent variable is plotted on the horizonal axis.  The independent variable data is grouped into bins (data ranges). 

The Lean Six Sigma graph below demonstrates a histogram being used to graphically display the grades of students in an Online Discussion Forum.  In this example, the grade occurring with the highest frequency was B. The histogram also shows that the grades are skewed to the right (toward the lower end of the grading spectrum).

As a histogram is being constructed, it is necessary to group the data into equal size bins/classes.  In the case of the example, the bins are grades.  While the bin groupings are arbitrary, care must be taken when they are established.  Too few or too many bins can distort the conclusions drawn from the data.

Histograms are the perfect tool for looking at frequency of occurrence within groups of data.  When looking specifically at customer information, the applications are endless with potential independent variables such as age, gender, average sale, etc.  Collecting data and not using it is the ultimate waste.

Not recognizing the importance of “The Customer” is equivalent to not unlocking your doors at the start of the business day.  Remember, “The Customer” is a company’s most important asset.  Without customers, you have no business. 


To learn more about the Histograms, Lean Six Sigma and Statistical Process Control, please contact the author at royce_williard@williardgroup.com


Learn more about the author by visiting my LinkedIn profile: http://www.linkedin.com/in/roycewilliard


Follow the author on Twitter at: http://twitter.com/rwilliard


Related Article: “It’s Never About the Number, It Is What the Number is Saying about the Business.” http://bit.ly/13PDem


To visit Brian Buck’s blog and see more improvement quotes: http://bit.ly/cbkUg


Post Author: Royce Williard

Copyright 2009 The Williard Group



Monday, May 11, 2009

It’s Never About The Number, It’s What The Number Is Telling You

It’s Never About The Number, It’s What The Number Is Telling You

Successful Control Charts For Every Business Environment

All successful leaders know how to see around corners. What is their secret? They use Key Performance Indicators (KPIs) complete with early warning systems. Both are components of any successful Lean Six Sigma program.

If it can be measured, it can be improved. But how do you know if the process is stable, and producing predictable results? The answer is simple, use control charts.

Many people often think the use of control charts as being limited to a manufacturing environment. This is an incorrect assumption. The application is much more widespread and successful, especially in today’s economic environment. These charts, commonly used in Lean Six Sigma, are appropriate for any process that can be measured.

A control chart is useful for…

  • determining the capability of the process (expected range).
  • determining if the process is under statistical control (stable).
  • identifying special cause variation in the process.
  • determining when and if corrective actions are required to the process.

By definition, a control chart is a graphical depiction of variance about a centerline over time. The mean (often referred to as an average) is commonly the centerline used in business applications. When using a mean as the centerline, the control chart is referred to as an `X (X bar) control chart. `X is nothing more than a fancy way of referring to the mean.

It is important to note that when a process is deemed to be out of statistical control, investigation is required. The cause of the variation must be identified and correction measures implemented when necessary.

The use of control charts can be extremely valuable when managing processes. However, to be of value these charts can’t sit in dusty binders in the manager’s office. The charts belong at the work location and should be reviewed during the leader’s Gemba Walk.

Furthermore, control charts should not be viewed as the only tool necessary for continuous improvement. Control Charts are only one of many tools available in the lean enterprise’s arsenal in the war on waste.

While statistics are crucial in the measurement of business processes, it is never about the number. It is about what the number is telling the leaders about their business and what is being done differently because of the number.

Constructing a Zone Control Chart

To assemble an `X control chart, enough data must be collected to calculate the mean (average) and standard deviation (std dev). After calculating the standard deviation, you determine the mean (average) + 1, 2, and 3 standard deviations (std dev). Finally, plot the Excel line chart including the data points, mean, 1 std dev, 2 std dev, and 3 std dev. Text labels are recommended for the right side of the graph to label the mean and + 3 std dev (upper and lower control limits).

Process control charts can be broken into three zones on each side of the mean (average) for ease of analysis. Zone “C” is closest to the centerline and is bounded by the mean and + 1 times the standard deviation. Zone “B” is the area bounded by + 1 and + 2 times the standard deviation. Zone “A” is the area bounded by + 2 and + 3 times the standard deviation.

Having assembled the control chart, the next step involves understanding what the data is revealing about the business. More specifically, is the process data under statistical control? A process only has two states, in control and out of control. There is a series of rules that are used to detect abnormal conditions in which the process is said to be out of statistical control.

While there is some disagreement among experts over the rules for determining when a process is out of statistical control, these rules were defined by Dr. Douglas Montgomery in his 2005 book entitled Introduction to Statistical Quality Control.

1. One point or more points outside of the control limits (i.e. beyond Zone A)

2. Two out of three consecutive points three points > 2 std devs from the mean, on the same side of center, and within the control limits (i.e. in Zone A)

3. 4 out of 5 points > 1 std dev from the mean and on the same side of the mean (i.e. in Zone B or beyond)

4. Eight consecutive points on the same side of the center line (i.e. Zone C and beyond)

5. Six points in a row steadily increasing or decreasing

6. Fifteen points in a row on both sides of the centerline in Zone C.

7. Fourteen points in a row alternating up and down.

8. Eight points in a row on both sides of the centerline and beyond Zone C.

9. An unusual or nonrandom pattern in the data.

10. One or more points near a warning or control limit.

Learn more about the author by checking my LinkedIn profile at http://www.linkedin.com/in/roycewilliard


Montgomery, Douglas C. (2005). Introduction to statistical quality control, Fifth edition. USA: John Wiley & Sons, Inc..

Post Author: Royce Williard

Copyright 2009, The Williard Group LLC