Tag: Leadership

Happy Anniversary

Happy Anniversary

It’s hard to believe that today marks our 7th anniversary.  I still remember writing that first post and wondering who would be interested in what we had to offer.

After more than 293,000 views, thousands of free downloads, and visitors from more than 120 countries, we can say that we’ve successfully helped more than a few people and companies get started with their OEE training and implementation.

We would like to thank all of our subscribers and visitors for your feedback, support, and many “thank you” notes over the years.

Your feedback matters

If you have any comments, questions, or topics you would like us to address, please feel free to leave your comment in the space below or email us at feedback@leanexecution.ca or feedback@versalytics.com.  We look forward to hearing from you and thank you for visiting.

Until Next Time – STAY lean

Versalytics >> Analytics
Advertisements

Method Matters and OEE

English: This figure demonstrates the central ...
English: This figure demonstrates the central limit theorem. It illustrates that increasing sample sizes result in sample means which are more closely distributed about the population mean. It also compares the observed distributions with the distributions that would be expected for a normalized Gaussian distribution, and shows the reduced chi-squared values that quantify the goodness of the fit (the fit is good if the reduced chi-squared value is less than or approximately equal to one). (Photo credit: Wikipedia)

Tricks of the Trade

 

Work smarter not harder! If we’re honest with ourselves, we realize that sometimes we have a tendency to make things more difficult than they need to be. A statistics guru once asked me why a sample size of five (5) is commonly used when plotting X-Bar / Range charts. I didn’t really know the answer but assumed that there had to be a “statistically” valid reason for it. Do you know why?

 

Before calculators were common place, sample sizes of five (5) made it easier to calculate the average (X-Bar). Add the numbers together, double it, then move the decimal over one position to the left.  All of this could be done on a simple piece of paper, using some very basic math skills, making it possible for almost anyone to chart efficiently and effectively.

 

  1. Sample Measurements:
    1. 2.5
    2. 2.7
    3. 3.1
    4. 3.2
    5. 1.8
  2. Add them together:
    • 2.5+2.7+3.1+3.2+1.8 = 13.3
  3. Double the result:
    • 13.3 + 13.3 = 26.6
  4. Move the decimal one position to the left:
    • 2.66

To calculate the range of the sample size, we subtract the smallest value (1.8) from the largest value (3.2). Using the values in our example above, the range is 3.2 – 1.8 = 1.4.

 

The point of this example is not to teach you how to calculate Average and Range values. Rather, the example demonstrates that a simple method can make a relatively complex task easier to perform.

 

Speed of Execution

 

We’ve written extensively on the topic of Lean and Overall Equipment Effectiveness or OEE as means to improve asset utilization. However, the application of Lean thinking and OEE doesn’t have stop at the production floor.  Can the pursuit of excellence and effective asset utilization be applied to the front office too?

 

Today’s computers operate at different speeds depending on the manufacturer and installed chip set. Unfortunately, faster computers can make sloppy programming appear less so. In this regard, I’m always more than a little concerned with custom software solutions.

 

We recently worked on an assignment that required us to create unique combinations of numbers. We used a “mask” that is doubled after each iteration of the loop to determine whether a bit is set. This simple programming loop requiring this is also the kernel or core code of the application.  All computers work with bits and bytes.  One byte of data has 8 bit positions (0-7) and represents numeric values as follows:

 

  • 0 0 0 0 0 0 0 0 =   0
  • 0 0 0 0 0 0 0 1 =   1
  • 0 0 0 0 0 0 1 0 =   2
  • 0 0 0 0 0 1 0 0 =   4
  • 0 0 0 0 1 0 0 0 =   8
  • 0 0 0 1 0 0 0 0 =  16
  • 0 0 1 0 0 0 0 0 =  32
  • 0 1 0 0 0 0 0 0 =  64
  • 1 0 0 0 0 0 0 0 = 128

To determine whether a single bit is set, our objective is to test it as we generate the numbers 1, 2, 4, 8, 16, 32, 64 and so on – each representing a unique bit position in binary form . Since this setting and testing of bits is part of our core code, we need a method that can double a number very quickly:

 

  • Multiplication:  Multiply by Two, where x = x * 2
  • Addition:  Add the Number to Itself, where x = x + x

These seem like simple options, however, in computer terms, multiplying is slower than addition, and SHIFTing is faster than addition.  You may notice that every time we double a number, we’re simply shifting our single “1” bit to the left one position.  Most computers have a built in SHL instruction in the native machine code that is designed to do just that.  In this case, the speed of execution of our program will depend the language we choose and how close to the metal it allows us to get.  Not all languages provide for “bit” manipulation.  For this specific application, a compiled native assembly code routine would provide the fastest execution time.  Testing whether a bit is set can also be performed more efficiently using native assembly code.

 

Method Matters

 

The above examples demonstrate that different methods can be used to yield the same result.  Clearly, the cycle times will be different for each of the methods that we deploy as well.  This discussion matters from an Overall Equipment Effectiveness, OEE, perspective as well.  Just as companies focus on reducing setup time and eliminating quality problems, many also focus on improving cycle times.

 

Where operations are labour intensive, simply adding an extra person or more to the line may improve the cycle time.  Unless we change the cycle time in our process standard, the Performance Factor for OEE may exceed 100%.  If we use the ideal cycle time determined for our revised “method”, it is possible that the Performance Factor remains unchanged.

 

Last Words

 

The latter example demonstrates once again why OEE cannot be used in isolation.  Although an improvement to cycle time will create capacity, OEE results based on the new cycle time for a given process may not necessarily change.  Total Equpiment Effectiveness Performance (TEEP) will actually decrease as available capacity increases.

 

When we’re looking at OEE data in isolation, we may not necessarily the “improved” performance we were looking for – at least not in the form we expected to see it.  It is just as important to understand the process behind the “data” to engage in a meaningful discussion on OEE.

 

Your feedback matters

 

If you have any comments, questions, or topics you would like us to address, please feel free to leave your comment in the space below or email us at feedback@leanexecution.ca or feedback@versalytics.com.  We look forward to hearing from you and thank you for visiting.

 

Until Next Time – STAY lean

 

 

 

Versalytics Analytics

 

Its not what you know …

It’s not what you know but what you understand that matters most.  ~ Redge

Discerning  perceived knowledge from understanding is a challenge for many leaders. For example, it is possible for anyone to memorize facts and figures and to correctly answer related questions simply by recalling this same information from memory. Similarly, many of us “perform” simple multiplication from recall – without even thinking about the calculations involved.

Why this matters

Having knowledge of metrics is not necessarily the same as understanding what the metric is measuring or what it means. Consider that the formula for Overall Equipment Effectiveness, or OEE, is the product of three factors:  Availability, Performance, and Quality. After basic training, anyone can recite the formula and calculate OEE correctly. This basic knowledge does not necessarily equate to any real level of understanding what is actually being measured.

OEE measures how effectively an asset’s time was used to produce a quality part. Confusion as to what is really being measured typically occurs when the Quality factor is calculated. For a single run, numerous texts teach that we can calculate the quality factor as:

Quality Factor = (Good Parts Produced / Total Parts Produced) x 100.

While the calculation will yield the correct result for a single instance, the formula isn’t quite complete as presented and doesn’t work when attempting to calculate OEE for multiple parts running through the same machine. The Quality formula should actually be stated as:

Quality Factor = (Good Parts Produced x Cycle Time / Total Parts Produced x Cycle Time)

or

Quality Factor = Pure Time to Produce Good Parts / Pure Time to Produce ALL Parts.

When expressed this way, we can state how much time was spent producing good parts, total parts, and defective parts! The time lost to produce defective or scrap parts is given by the formula:

Lost Quality Time = Time to Produce ALL parts – Time to Produce Good Parts.

OEE is not complicated when we understand what it is we’re measuring. By way of example, assume a production shift consists of 435 minutes of scheduled production time where breaks and lunches have already been accounted for. For the sake of simplicity, we will assume the process is running at rate (performance = 100%).  A part having a cycle time of 2 minutes was scheduled to run for the entire shift where 160 good parts from a total of 180 parts were produced.

From this basic data and assuming the process was running at rate – (Performance = 100%) – we can derive the following:

Availability = Up Time / Total Time = ((180 x 2) / 435) x 100 = (360 / 435) x 100 = 82.76%

Performance = 100% (assuming run at rate) = 100%

Quality =Time to Produce Good Parts / Time to Produce ALL Parts

Quality = ((160 x 2) / (180 x 2)) x 100 = (320 / 360) x 100 =  88.89%

OEE = A x P x Q = 82.76% x 100% x 88.89% = 73.56%

Cross Check:  435 x OEE = 435 x 73.56% = 320

Before calculating the percent values for each factor, we can see that time is common to all factors. We can readily determine that we lost 40 minutes due to the production of defective parts (360 -320) and that we also lost 75 minutes due to unplanned downtime events.

To calculate OEE for a given machine, shift, department, or plant we can easily sum the total “time” based values for each factor and calculating the percentages accordingly.  These calculations are clearly conveyed in prior posts and in our free downloads (see our free downloads page or on the widget on the sidebar).

What you know is taught, what you understand is learned. ~ Redge

When we truly understand what is being measured, the data that forms the basis for our calculations becomes more meaningful too. We can even challenge the data before the calculations are made.  The greatest frustration occurs when the results are not what we expected and the reasons are either in the very data that generated them or worse, when someone doesn’t understand the calculation they’re actually performing.

Many years ago I recall reading a sign that stated, “The proof of wisdom is in the results“. While their is truth in this statement, the implication is that we understand the results too!

Your feedback matters

If you have any comments, questions, or topics you would like us to address, please feel free to leave your comment in the space below or email us at feedback@leanexecution.ca or feedback@versalytics.com.  We look forward to hearing from you and thank you for visiting.

Until Next Time – STAY lean

Versalytics Analytics

International Women’s Day

Today, March 8, is International Women’s Day and an opportunity to recognize the many contributions that women have made around the world.

So many women have changed history and so few have received the recognition they deserve for doing so.  This day also serves to remind us that so many more opportunities for women remain open.

Celebrate and embrace International Women’s Day.

Your feedback matters

If you have any comments, questions, or topics you would like us to address, please feel free to leave your comment in the space below or email us at feedback@leanexecution.ca or feedback@versalytics.com.  We look forward to hearing from you and thank you for visiting.

Until Next Time – STAY lean

Versalytics Analytics

The Pulse of Leadership

In theory, Employee Opinion Surveys provide a pulse of the workforce and the workplace in general.  In practice, they measure the performance of executive leadership and the management team.  They serve as a tool to understand what is working and to identify opportunities for improvement.

Unfortunately, collecting and compiling survey data is very time-consuming and only represents a snapshot in time.  While the survey data captures the essence of what is occurring, every good leader knows, things can change very quickly – even too quickly, as  in times of crisis.

The attitude of Leadership is reflected in the gratitude of their Employees. ~ Redge

Leaders who are actively engaged with their teams are likely to dismiss the need for an employee opinion survey and we would tend to agree with them.  The attitude of Leadership is reflected in the gratitude of their employees.  The only way to get a real pulse for what is happening is to regularly walk the floor and engage with your teams.

Make the time to take the time to engage with your teams.  A regular “walk and talk” will yield more benefits to you and your teams than any survey could ever provide.  Acting on their suggestions and offering regular feedback will foster a culture of trust, respect, accountability, integrity, and open communication.  For that, your employees will be truly grateful.

Your feedback matters

If you have any comments, questions, or topics you would like us to address, please feel free to leave your comment in the space below or email us at feedback@leanexecution.ca or feedback@versalytics.com.  We look forward to hearing from you and thank you for visiting.

Until Next Time – STAY lean

Vergence Analytics
Enhanced by Zemanta

Welcome to 2014

Happy New Year and welcome to 2014. We wish you the best of continued successes in the year ahead. After a much needed break, we’re excited to get back to work.

We recently celebrated 5 years of blogging here on WordPress, reaching over 160 countries and more than 160,000 views. While this is very encouraging, we are motivated to share our lean leadership insights and experiences on the simple premise that:

“Life isn’t worth living, unless it is lived for someone else” ~ Albert Einstein

Thank you for allowing us the privilege and pleasure of sharing our thoughts and insights and for providing our services to you in 2013. We proudly look forward to continuing to do so in 2014.

Your feedback matters

If you have any comments, questions, or topics you would like us to address, please feel free to leave your comment in the space below or email us at feedback@leanexecution.ca or feedback@versalytics.com.  We look forward to hearing from you and thank you for visiting.

Until Next Time – STAY lean

Vergence Analytics

Desk Jockey Leaders – Where Did That Come From?

desk jockey
desk jockey (Photo credit: notorious d.a.v.)

The inspiration that tipped the scales and served as a motivator to write about Desk Jockey “Leaders” came from a headline that appeared on the front page of Friday’s edition of the Toronto Sun (October 25, 2013):

“Despite $862M repair backlog, housing boss says: I need a bigger office! – Keeping Up With the Jones – TCHC Eyes $2-Million Reno to Rosedale HQ”

I would like to think that when people are struggling to survive with the most basic necessities of daily living, renovating the offices of the very corporation that’s helping them would be the last thing on everyone’s mind.

At least one city councillor echoed the voice of reason stating, “I don’t think it’s something we can justify to either the taxpayer of the City of Toronto or our tenant base.” I’m certain this statement also resonates with most people who read the accompanying article.

The CEO of the TCHC (Toronto Community Housing Corporation) suggested that a more professional environment would be more appealing to visitors and tenants and a larger office could be used to host meetings.

I would suggest that focusing on the purpose of the corporation’s existence is first and foremost. Could it be that some people have decided to make a career out of an ever-growing problem that should never have risen to the scope and scale that it has

Whatever hardships the CEO and fellow TCHC employees must endure to perform their work could hardly compare to the conditions that the tenants must live with each and every day.

What could make this any worse? Knowing that our Liberal government wasted $1.1 Billion to cancel the construction of two gas plants – a decision that was sure to win them a few more seats in the last provincial election. No one is accountable and no one is responsible. Unfortunately, the one’s who suffer most are the taxpayers who fund it all.

As I complete this follow-up, there is some good news. The CEO of the TCHC has withdrawn the motion to renovate their headquarters. Maybe there is some light at the end of the tunnel after all.

Two of my greatest pet peeves are working with people who 1) attempt to manage everything behind their desk , and 2) believe meetings are the answer to resolve everything else that can’t. This article presented a CEO who was planning to do both – in the same office!

As many quickly discover, being a desk jockey “leader” simply just doesn’t work.