All employees must "toot their own horn" if they want a promotion or payrise, but women are particularly timid about doing so, according to an expert in sales psychology.

US-based behavioral scientist Shannon L. Goodson says the fear of self promotion is holding back competent and deserving workers from being recognized for their contributions and prohibiting them from earning what they're worth.

She says "the fear of self-promotion can make you invisible in the workplace", and workers who believe they can advance their careers without self-promotion are "dreamers".

These people have "innocent expectations" and "romantic idealities" around their careers, she says.

Toot your own horn

"Recruiters (and their candidates) need to realize that the hardest-working, best producing and most deserving workers aren't necessarily the ones who rise to the top," Goodson says.

"Getting to the top of any organization requires a two-part approach: competent performance supported by assertive self-promotion."

"Competent performance without assertive self-promotion creates a recognition vacuum. If you don't take credit for who you are and the contributions you have made, someone else in the organization - probably less deserving - will."

She adds: "As an employee, you are responsible for yourself. If you don't talk it up, don't count on someone [else] doing it for you."

Women are their own worst enemies

Goodson's recent study of more than 28,000 employees identifies a clear difference between men and women with respect to self-promotion.

Women, overall, are more hesitant to network and less comfortable drawing attention to their skills, abilities and contributions than men.

"Men are more willing to draw attention to contributions they did (and sometimes did not) make and to participate in social and professional networking opportunities where they can direct attention to their skills and competencies," she says.

"Women are less comfortable promoting their competencies. Many still cling to the myth that all self-promotion is socially unacceptable, un-lady-like, and morally suspect. They believe hard work alone is sufficient to put them on salary and status par with their male counterparts."

"Good work is important, but good work alone does not, as the myth says, 'speak for itself'' - you have to give it a voice," she says.

Among women, however, differences emerge between countries and cultures.

"Professional women in the UK, US and China are among the least reluctant to promote their interests, whereas women in New Zealand and Sweden are the most timid, followed by Australian and Canadian women."

Goodson says her study found that Australian women specifically struggle with "stage fright" and sensitivities about appearing too forward, pushy or intrusive.

Women are unsupportive of their female colleagues

Goodson's study also aimed to explore whether women who had climbed to the top of the ladder tended to "pull the ladder up behind them", as an Australian study claimed a few years ago.

She says her latest research has found that women executives may not be as encouraging or supportive of other women as once thought. "There is a perception that successful women may sabotage the career hopes of aspiring women further down the ladder, and this has led many women in the study to prefer male to female managers," she says.

She notes that while women did not create the glass ceiling, "they help maintain it".

To help you be, know, and do; (U.S. Army, 1973) follow these eleven principles of leadership. Know yourself and seek self-improvement - In order to know yourself, you have to understand your be, know, and do, attributes. Seeking self-improvement means continually strengthening your attributes. This can be accomplished through self-study, formal classes, reflection, and interacting with others.

1. Be technically proficient - As a leader, you must know your job and have a solid familiarity with your employees' tasks.
2. Seek responsibility and take responsibility for your actions - Search for ways to guide your organization to new heights. And when things go wrong, they always do sooner or later -- do not blame others. Analyze the situation, take corrective action, and move on to the next challenge.
3. Make sound and timely decisions - Use good problem solving, decision making, and planning tools.
4. Set the example - Be a good role model for your employees. They must not only hear what they are expected to do, but also see. We must become the change we want to see - Mahatma Gandhi
5. Know your people and look out for their well-being - Know human nature and the importance of sincerely caring for your workers.
6. Keep your workers informed - Know how to communicate with not only them, but also seniors and other key people.
7. Develop a sense of responsibility in your workers - Help to develop good character traits that will help them carry out their professional responsibilities.
8. Ensure that tasks are understood, supervised, and accomplished - Communication is the key to this responsibility.
9. Train as a team - Although many so called leaders call their organization, department, section, etc. a team; they are not really teams...they are just a group of people doing their jobs.
10. Use the full capabilities of your organization - By developing a team spirit, you will be able to employ your organization, department, section, etc. to its fullest capabilities.

Another school of thought suggest there are four major factors in leadership:

Leader
You must have an honest understanding of who you are, what you know, and what you can do. Also, note that it is the followers, not the leader who determines if a leader is successful. If they do not trust or lack confidence in their leader, then they will be uninspired. To be successful you have to convince your followers, not yourself or your superiors, that you are worthy of being followed.

Situation
All are different. What you do in one situation will not always work in another. You must use your judgment to decide the best course of action and the leadership style needed for each situation. For example, you may need to confront an employee for inappropriate behavior, but if the confrontation is too late or too early, too harsh or too weak, then the results may prove ineffective.

Various forces will affect these factors. Examples of forces are your relationship with your seniors, the skill of your people, the informal leaders within your organization, and how your company is organized.

Recently I had the unpleasant experience of staying at the Westin Kierland Resort & Spa in Scottsdale Arizona who is owned by Starwood Hotels & Resorts. Starwood has had an active Lean Six Sigma Program for almost 8 years now, but if your giving lip service to quality (Six Sigma) and efficiency (lean) and low cost value to customers (both lean and Six Sigma) then customers will naturally stop doing business with you.

You decide if Starwood’s is "walking the talk".

- They believe in transparent invoicing and financial reporting. Is this lip service or walking the talk?

I say lip service. Why? Because during a recent conference at the hotel where I registered under the conference code, they sent me the hotel contract agreement that clearly mentions room cost, taxes, etc... But a new $4.00 a day maid service was added to my bill at the end. Now I happen to know that this charge was not contractually negotiated, it clearly was not on my contract, and it was not communicated to me any time, but was added to my bill. Did the hotel manager correct this when this issue was raised? No, because they are too busy tripping over dollars to pick up dimes. I was nickel and dimed every minute of the stay. $4 to print my airline ticket. $13 for a baby size - 4 oz - bottle of ginger ale and 2 Pepto Bismol, when I was trying to recover from food poisoning. $20 per day if I had left my vehicle in Valet parking over night. Good thing I caught that print on my ticket when I was checking in so I could move the vehicle to self-parking. Oh and if you want a drink, enjoy the everyday low $12 drinks - that's their happy hour price. Oh and don't get me started on the mini bar. Oh did I mention $15/day internet connection but that is just in your room, it’s over $50 if you want access across the rest of the hotel.

Is the customer important? Walk the Talk or Lip Service? I had 2 guests over for drinks in my room as we had a nice view over the golf course - for the discounted $250 / night - I was enjoying that view. We must have gotten loud and a guest complained twice. Instead of calling my room and asking that we quiet down, they sent a thug up to my room. This Hells Angel looking security guard would not stop banging on my door until the guests left - which he escorted back to their rooms - like a good chaperon. Look, I have no problem with quieting down, but to have a hotel security agent get in my face and threaten me, then continue to get hostile with my guests, is unhelpful. What is Starwood hiring x-convict or steroid macho security personnel to cut costs or is that supposed to represent a reasonable approach?

I am all for Starwood doing Lean Six Sigma - but walk your talk and don't give lip service to customer service, quality, or efficiency. Marriott and Hilton and many others provide a full refund with their 100% guest satisfaction policy - that shows they have skin in the game and are committed to the customer experience being positive. Starwood did respond to my complaints with an offer to have me return if in the area so they can try to improve upon my last visit and nickel and dime me some more. I don't think so - no Do Over's in real life. No they have lost me as a customer, lost the $80k as a returning conference sponsor next year, lost the over 130 guest’s stays and special service banquets that we held.

Let this be a lesson to other businesses. If you say your going to practice Lean Six Sigma and then mistreat your customers, over and/or mischarge them, and not have any skin in the game with competitive value propositions, then don't be surprised when you lose customer loyalty, have to read about the "Voice of Your Customers" such as stories like this, and the many more blog postings and reviews I am in-process of publishing.

Walk the talk Starwood - and until they do, consider this forewarning should you decide to stay in Scottsdale Arizona - avoid the Westin Kierland Resort & Spa, least you get robbed as I have.

There are not many Lean Six Sigma Professionals on the open market or at least not for long before they are snatched up quickly. The skills and leadership of Black Belts, Master Black Belts, and experienced Deployment Champions are in such high demand, that they are usually placed in a new role in less than 2 weeks.

Therefore recruiters need to plan a strategy to target these candidates. Here are some pointers.

1. Build a relationship in advance - since most are working an existing job and are very busy, establish some trust by understanding their goals and timeline.

2. Most Lean Six Sigma Professionals are on a 1-2 year rotation, so find out where they are in their rotation and when they want to begin reviewing job opportunities.

3. Do not bombard them with uninvited calls and e-mails of potential jobs they should consider or if they know any others that could be a good fit. This is a major turnoff. It is better to discuss the kinds of positions they are interested and the specifics that they are interested in, such as if relocation is involved, travel, compensation range, reporting structure, etc... Then if not a fit for them, understand why so you can improve on locating the right fit.

4. Be careful with terminology. It is common that different organizations call the same skill a different name, so check for understanding or clarifications. For example, an employer is seeking a Kaizen Leader - this is also known as a Lean Sensei, TPS Practitioner, and Rapid Improvement Event Facilitator. Review the job descriptions with an experienced Master Black Belt (MBB) to ensure you understand the job description so you can match the right candidate qualities and experience.

There are of course many more tips with working with these high performing individuals, so please add your builds for others to benefit.

Run Charts

Adding the element of time will help clarify your understanding of the causes of variation in your processes. A run chart is a line graph of data points organized in time sequence and centered on the median data value. The patterns in the run chart can help you find where to look for assignable causes of variation.

What can it do for you?

Histograms or frequency plots can show you the general distribution or variation among a collection of data points representing a process, but one histogram or one frequency plot can not show you trends or help pinpoint unusual events. Sometimes, a normal-looking distribution will hide trends or other unusual data. To spot those trends, the data must be considered in time order. Plotting data on a run chart can help you identify trends and relate them to the time they occurred. This will help you in your search for the special causes that may be adding variation to your process.

Run charts are especially valuable in the measure and analyze phases of Lean Six Sigma methodology.

How do you do it?

1.      Select a characteristic from one of your processes. This characteristic could be presenting a problem because excessive variation often drives it outside of specification limits, or it could be a cause of customer complaints.

2.      Measure the characteristic over time intervals and record the data. Note the time or the time period that is associated with each data point.

3.      Find the median data value. To do this, list the data values in numeric order. Include each data point, even if it is a repeat value. If the number of data points is odd, the median is the middle value. If the number of data points is even, the median is halfway between the two values nearest the middle. For example, if the collected data points were: 5, 1, 18, 8, 12, 9, the ordered values would be: 1, 5, 8, 9, 12, and 18. The middlemost values are 8 and 9. The median is the average of those values, or 8.5. (Remember, the numerically-ordered data is only for determining the median. The data must be plotted in time order on the run chart to be of any value.)

4.      Set up the scales for your run chart. The vertical scale will be the data values, and the horizontal scale will be the time. Make the horizontal scale about two to three times the distance of the vertical scale.

5.      Label the vertical scale so that the values will be centered approximately on the median and so the scale is about 1 ½ to 2 times the range of the collected data.

6.      Draw a horizontal line representing the median value.

7.      Plot the data points in sequence. Connect each point to the next point in the sequence with a line.

Some special cause variation reveals itself in unusual run-chart patterns. These clues can direct you in your search for causes. Count the number of runs. Runs are sequences of points that stay on one side of, either above or below, the median line. One way of counting the runs is to circle these sequences and tally them. Another way of doing this is to count the number of times the run-line crosses the median, and then add one. Compare the number of runs you count to the accompanying chart.

·         Numbers of runs outside the range shown for the number of data points are statistically unusual.

·         Too few runs (below the lower limit) generally indicate that something cyclic is systematically shifting the process average.

·         Too many runs could point to a problem of consecutive, over-compensating process adjustments or indicate that the data points actually came from two sources with different process averages.

·         Look for sequences of ascending or descending values. Seven or more continuously increasing or continuously decreasing points indicates a trend that is shifting the process average. When counting points, ignore any points that repeat the previous value. Repeated values neither add to the length of the run nor break it.

·         Search for seven or more consecutive points on the same side of the median line or 10 of 11 points or 12 of 14 or 16 of 20. (Ignore any points that are exactly on the median.) Such a sequence indicates that something has occurred to shift the process average in that direction.

·         A sequence of 14 or more data points alternating up and down suggests a variation related to sampling (such as one reading early in the day and one reading toward the end) or that the data is coming from two sources with different process averages (such as from two machines making the same part.) In looking for up-and-down alternation, ignore any points that are exactly the same as the preceding point.

·         A sequence of seven or more points with exactly the same value usually should signal you to look for a special cause. While it is possible that your process has improved to the extent that the existing measurement technique is no longer sensitive enough to measure variation, it is usually more probable that a gauge is stuck or broken or that someone is making up the data.

Now what?

Run charts can be very valuable in helping your search for sources of variation. They are easy to plot and easy to interpret. The sampling is uncomplicated, and there are no statistical computations to make. They can also be applied to almost any process or any data.

On the other hand, they are not an instant indicator. They are best used for spotting trends; short shifts in the process cannot always be detected with run charts. In addition, special causes that produce general piece-to-piece variation will not be readily detected on run charts.

Finally, a simple run chart cannot establish the natural capabilities of a process, so it isn’t possible to use one to predict what specifications a process can actually meet. To do that, you need to create a control chart, a run chart with statistical control limits.

Steven Bonacorsi is a Senior Master Black Belt instructor and coach. Steven Bonacorsi has trained hundreds of Master Black Belts, Black Belts, Green Belts, and Project Sponsors and Executive Leaders in Lean Six Sigma DMAIC and Design for Lean Six Sigma process improvement methodologies.

The AIT Group, Inc.
Steven Bonacorsi, Solution Provider
Lean Six Sigma Master Black Belt
3135 South Price Road, Suite 115
Chandler, AZ 85248-3549
Phone: +(1) 888.826.2484
E-mail: americas@theaitgroup.com

http://www.theaitgroup.com

Histograms

An important aspect of total quality is the identification and control of all the sources of variation so that processes produce essentially the same result again and again. A histogram is a tool that allows you to understand at a glance the variation that exists in a process. Although the histogram is essentially a bar chart, it creates a “lumpy distribution curve” that can be used to help identify and eliminate the causes of process variation. Histograms are especially useful in the measure, analyze and control phases of the Lean Six Sigma methodology.

What can it do for you?

A histogram will show you the central value of a characteristic produced by your process, and the shape and size of the dispersion on either side of this central value. The shape and size of the dispersion will help identify otherwise hidden sources of variation. The data used to produce a histogram can ultimately be used to determine the capability of a process to produce output that consistently falls within specification limits.

How do you do it?

1.      Decide which Critical-To-Quality characteristic you wish to examine. This CTQ must be measurable on a linear scale. That is, the incremental value between units of measurement must be the same. For example, a micrometer or a thermometer or a stopwatch can produce linear data. Asking your customers to rate your performance from “poor” to “excellent” on a five-point scale probably will not.

2.      Measure the characteristic and record the results. If the characteristic is continually being produced—such as voltage in a line or temperature in an oven, or if there are too many items being produced to measure all of them, you will have to sample. Take care to ensure that your sampling is random.

3.      Count the number of individual data points. Add the values for each of the data points and divide by the number of points. This is the mean (or average) value.

4.      Determine the highest data value and the lowest data value. Subtract the lower number from the higher. This is the range.

5.      The next step is determining how many “classes” or bars your histogram should have.

To make an initial determination, you can use this table:

Number of data points      Number of classes

under 50                                5 to 7

50 to 100                                6 to 10

100 to 250                             7 to 12

over 250                                 10 to 20

6.      Divide the range by the trial number of classes you selected. The resulting number will be your trial class interval (the horizontal graduation or width) for each bar on your chart. You may round or simplify this number to make it easier to work with, but the total number of classes should be within those shown above. In determining the number of classes and the class interval, consider how you are measuring data. Increase or decrease the number of classes or modify the class interval until there is essentially the same number of measurement possibilities in each class.

7.      Determine the class boundaries. You can do this by starting at the center of the range. If you have an odd number of classes, center the middle class approximately at the mid-point of the range, then alternately add or subtract the class interval to define the other class boundaries. If you have an even number of classes, begin the process of adding or subtracting the class interval at approximately the center of the range.

8.      Tally the number of data points that fall in each of the classes. Add the frequency totals for each class. This number should equal the total number of data points. Divide the number of data points in each class by the total number of data points. This will give you the percentage of points falling in each class. Add the percentages of all the classes. The result should be approximately 100.

9.      Graph the results by beginning with the lowest measurement-value class. Make the bar height correspond to the percentage of data points that fall in that class. Draw the bar for the second class to the right and touching the first bar. Again, make the height correspond to the percentage of data points in that class. Continue in this way until you have drawn in all the classes.

10. Draw a vertical dotted line through your histogram to represent the mean value of all your data points.

11. If there are specification limits for the characteristic you are studying, indicate them as vertical lines as well.

12. Title and label your histogram.

Now what?

The shape that your histogram takes tells a lot about your process. Often, it will tell you to dig deeper for otherwise unseen causes of variation.

The symmetrical or bell-shaped type of histogram: The mean value is in the middle of the range of data. The frequency is high in the middle of the range and falls off fairly evenly to the right and left. This shape occurs most often.

The “comb” or multi-modal type of histogram: Adjacent classes alternate higher and lower in frequency. This usually indicates a data collection problem. The problem may lie in how a characteristic was measured or how values were rounded. It could also indicate an error in the calculation of class boundaries.

If the distribution of frequencies is shifted noticeably to either side of the center of the range, the distribution is said to be skewed. When the histogram is positively skewed. The mean value is to the left of the center of the range, and the frequency decreases abruptly to the left but gently to the right. This shape normally occurs when the lower limit, the one on the Left, is controlled either by specification or because values lower than a certain value do not occur for some other reason.

If the skewness of the distribution is even more extreme, a clearly asymmetrical, preci