Tag: Algorithm

The Point of No Return

The “Point of No Return” is a common expression that typically means you’ve reached an unrecoverable state if you continue to proceed with the current course of action.  When I clicked the “Publish” button for this post, I reached a point of no return (action).

From an accounting perspective, the term “Break Even” point is used to define the point where Total Costs equal Total Revenue.  The break even point translates to the quantity of parts that must be produced and sold to turn a profit.  Stock exchanges around the world serve as a constant reminder that investors are only concerned with PROFIT and return on investment (PROFIT).  In this context, a point of no return (profit) also exists.

Businesses exist for the customer or consumer.  Poor quality, missed delivery dates, short shipments, warranty returns, and poor customer service all lead to higher costs and may eventually cause customers to reach their “point of no return”.  Customers understand that the lowest price is not always the lowest cost option in the long run.  Business depends on repeat customers.

What’s the point?

In the simplest of terms, our actions must yield a return that is greater than the investment required to achieve it.  Delivering VALUE to the customer is one of the underlying principles of lean thinking and is measured by our ability to provide the highest quality products and services at the lowest possible cost, on time, delivered on time and in full.

This all sounds great on the surface but there will come a time where the cost to improve your systems and / or processes will exceed the return on investment – another point of no return.  Alternative, lower cost, solutions must be found to meet your continuous improvement objectives.

Where a significant capital investment is required, your company may require a payback period of one or two years.  A capital investment for a program that is soon to become obsolete is not a feasible option.  The point of no return (investment) is reached before any funding can even be considered.

The Bottom Line

Understandably, the team will become extremely frustrated when the very solution they proposed is rejected or declined.  While they may not doubt their own ability to provide viable solutions, they will doubt the company’s commitment to pursue excellence and continually improve.

For this reason, it is essential for the team to understand the reasons why.  It also underscores the need to identify and respond to improvement opportunities quickly and as early as possible during the launch cycle of any new system, process, or product.

Embrace Rejection

Rejection can sometimes be a gift.  As I have stated many times before, “There’s always a better way and more than one solution.”  Could it be that sometimes bad things happen for a good reason?

Rejection provides (forces) us with the opportunity to consider the present circumstances from a fresh perspective.  If the premise for the proposed solution was to “fix” the current system or process as it’s is now defined, perhaps a radically different and innovative system or process could better serve the company in the long term.

Is it possible that a new and lower cost alternative exists that could be at least as effective and perhaps even more efficient?  There are numerous examples of systems, processes, and technologies that exist today that were discovered by removing the limits that we unconsciously place on the scope of the problem that in turn limit the solutions we are able to develop.

The real problem with problem solving is the idea that the only solution is a “fix” to a system or process that is already be flawed from the onset.

Be Inspired

TED Talks are rife with examples of problem solving that yield radical and in some cases simple solutions.  The following TED Talks may serve to inspire you and your organization to look at problems and their solutions from a different perspective:

These TED Talks present problems on a different scope and scale than we may be accustomed to, however, the very discussion of alternatives alone should serve to inspire radical thinking that in turn inspires radical change.

You may have noticed from these TED Talks that some of the solutions presented were found outside of the context or circumstances from which the problem originated.  Is it possible that a “surrogate” solution exists elsewhere?

“Problems cannot be solved by the same level of thinking that created them.”

The point of no return is significant and literally requires “out of the box” thinking.  Many companies no longer grace our communities or employ our neighbours, losing business and opportunities for growth to lower cost manufacturers and distributors to continually emerging global economy.  The difference could very well be how we embrace the point of no return.

Consider that Toyota, as a new company to the North American automotive market, implemented innovative supply chain,  inventory management, and production techniques to remain competitive.  Radical change and innovation does not imply higher cost or investment.  At best it should simply imply “different”.

Other companies like Apple and GE managed to change their futures under the leadership of Steve Jobs and Jack Welch respectively.  Was it always pretty? Likely not from the books I’ve read.  However, the outcomes are undeniable.

The courage of Steve Jobs to solicit support from Microsoft’s Bill Gates was an extremely radical decision at the time.  This video, “Steve Jobs, Bill Gates and Microsoft – It’s Complicated“, clearly demonstrates the challenges faced in the relationship between Apple and Microsoft.  As for GE, I highly recommend reading “Straight From the Gut” by Jack Welch to best understand the radical changes in business and company culture during his tenure there.

Asking the right questions, open minds, radical thinking, and strong leadership coupled with a commitment to pursue excellence, continually improve, and solve problems may help everyone realize that the point of no return can be one of the greatest gifts you’ll ever receive.

To quote Albert Einstein, “A clever person solves a problem.  A wise person avoids it.” and so we … “look before we leap.”

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
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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

 

Lean Paralysis

Lean – Breaking Through Paralysis

Significant initiatives, including lean, can reach a level of stagnation that eventually cause the project to either lose focus or disappear altogether.  Hundreds of books have already been written that reinforce the concept that the company culture will ultimately determine the success or failure of any initiative.  A sustainable culture of innovation, entrepreneurial spirit, and continual improvement requires effective leadership to cultivate and develop an environment that supports these attributes.

When launching any new initiative, we tend to focus on the many positive aspects that will result.  Failure is seldom placed on the list of possible outputs for a new initiative.  We are all quite familiar with the typical Pro’s and Con’s, advantages versus disadvantages, and other comparative analysis techniques such as SWAT > Strengths, Weakness, Alternatives, Threats)

A well defined initiative should address both the benefits of implementation AND the risks to the operation if it is NOT.

Back on Track

The Vision statement is one starting point to re-energize the team.  Of course, this assumes that the team actually understands and truly embraces the vision.

Overcoming Road Blocks

The Charter: Challenge the team to create and sign up to a charter that clearly defines the scope and expectations of the project.  The team should have clearly defined goals followed by an effective implementation / integration plan.  The charter should not only describe the “Achievements” but also the consequences of failure.  Be clear with the expectations:  Annual Savings of $xxx,xxx by Eliminating “Task A – B – C”, Reducing Inventory by “xx” days, and by  reducing lead times by “xx” days.

Defining Consequences:  Competitive pricing compromised and will lead to loss of business.  This could be rephrased using the model expression:  We must do “THIS” or else “THIS”.  It has been said that the pain of change must be less than the pain of remaining the same.  If not, the program will surely fail.

The Plan: An effective implementation strategy requires a time line that includes reporting gates, key milestones, and the actual events or activities required.  The time line should be such that momentum is sustained.  If progress suggests that the program is ahead of schedule, revise timings for subsequent events where possible.  Extended “voids” or lags in event timing can reduce momentum and cause the team to disengage.

Focus: Often times, we are presented with multiple options to achieve the desired results.  An effective decision making process is required to reduce choices or to create a hybrid solution that encompasses several options.  The decision process must result in a single final solution.

Consequences: As mentioned earlier, a list of consequences should become part of the Charter process as well.  Failure suggests that a desired expectation will not be realized.  It is not enough to simply return to “the way it was”.  The indirect implication is that every failure becomes a learning experience for the next attempt.  In other words, we learn from our failures and stay committed to the course of the charter.

Example:

Almost all software programs are challenged to sort data.  We don’t really think about the “method” that is used.  We just wait for the program to do it’s task and wait for the results to appear.  At some time, the software development team must have chosen a certain method, also known as an algorithm, to sort the data.

We were recently challenged in a similar situation to decide which sort method would be best suited for the application.  You may be surprised to learn that there are many different sorting algorithms available such as:

  1. Bubble Sort
  2. Quick Sort
  3. Heap Sort
  4. Comb Sort
  5. Insertion Sort
  6. Merge Sort
  7. Shaker Sort
  8. Flash Sort
  9. Postman Sort
  10. Radix Sort
  11. Shell Sort

This is certainly quite a selection and more methods are certain to exist.  Each method has it’s advantages and disadvantages.  Some sorting methods require more computer memory, some are stable, others are not.  Our goal was to create a sorted list without duplicates.  We considered adding elements and maintaining a sorted “duplicate free” list in real-time.  We also considered reading all the data first and sorting the data after the fact.

The point is that of the many available options, one solution will eventually be adopted by the team.  Using the “wrong” sorting method could result in extremely slow performance and frustrated users.  In this case the users of the system may abandon a solution that they themselves are not a part of creating.  While a buble sort may produce the intended result, it is usually not the most efficient.

Another aspect of effective development is to document the analysis process that was used to arrive at the final solution.  In our example, we could run comparative timing and computer resource requirements to determine which solution is most suitable to the application.  Some algorithms work better on “nearly sorted” lists versus others that work better with “randomly ordered” data.

Engage the Team: The team should be represented by multiple disciplines or departments within the organization.  Using the simple example from above, the development team may create a working solution that is later abandoned by the ultimate users of the system due to it’s poor performance.  The charter should be very clear on the desired expectations and performance criteria of the final solution.

Creating a model or prototype to represent the solution is common place.  This minimizes the time and resources expended before arriving at the final  solution for implemention.

Vision: Leadership must continue to focus beyond the current steps.  A project or program is not the means to an end.  Rather it should be viewed as the foundation for the next step of the journey.  Lean, like any other initiative, is an evolutionary process.  Lean is not defined by a series of prescriptions and formulas.  The pursuit and elimination of waste is a mission that can be achieved in many different ways.

Management / Review

Regular management reviews should be part of the overall strategy to monitor progress and more so to determine whether there are any impediments to a successful outcome.  The role of leadership is to provide direction to eliminate or resolve the road blocks and to keep the team on track.

Breaking Through Paralysis

The objective is clear – we need to keep the initiative moving and also learn to identify when and why the initiative may have stopped.  Running a business is more than just having good intentions.  We must be prudent in our execution to efficiently and effectively achieve the desired results.

Until Next Time – STAY Lean!