How to solve problems effectively?

Problem solving can be challenging if the root cause is unknown and the problem needs to be solved right away. Everyone involved with the problem looks at it in different ways.

Listed below are some key perspectives as viewed by different people.
- The Problem Solver's view: Get to the root cause as quickly as possible and implement corrective actions to fix the problem.
- Management's view: The business is losing money or reputation because of the problem. Why is it taking so long to fix it?
- Process owner's view: We don't want to supply bad or suspect product or service to the customer, so we continue to be extra careful. Additional inspection levels, 100% inspection, quality audits are some of the ways to prevent poor quality product or service leaving the facility.

Because of the difference of opinion about the problem, most problems don't get fixed permanently. Usually the first symptom cause is considered the root cause and quickly fixed. That is why the problem re-appears after a while.

So how do we solve problems effectively?
1. Use structured problem solving method like the DMAIC approach
2. Solve problems that make business sense i.e. that will benefit the business
3. Use data to prove root cause and validate solutions!

Lean Six Sigma uses the DMAIC approach and tools for process/data analysis. DMAIC or Define-Measure-Analyze-Improve-Control are the phases of a Six Sigma project. Statistical tools at each phase of the project allow problem solvers to use process data to prove root causes and validate the solutions will fix the problem.

LSS projects focus on problems that make a business case and bring bottom line improvements.
The figure below shows key elements of an LSS project.

The clearly defined structure of LSS allows practitioners to solve problems effectively.

p, % and ppm for discrete data

Discrete or attribute data deals with counts. There are two types of attributes - defectives and defects.
Defectives are number of parts that are non conforming to a standard. Defective counts are parts that fail to meet a specific criteria set by the customer.
Defects on the other hand are non conformities or problems/issues within parts. A single part can have multiple defects i.e. the defect count can be greater than the total number of parts inspected.

It is important to understand the fundamental difference between defects and defectives because the statistics, tools are different for each. Here we will look at the stats/charts for defective data.

Defective data can be presented in several ways. There are 3 ways to calculate and chart defective data.
1. p or proportion
2. % or percent
3. ppm or parts per million

Most continuous improvement practitioners get confused between the 3 ways and this causes misinterpretation of the information presented. To clearly understand the difference, we will use sample data and perform the calculations.
For a set of 250 samples, quality inspection found 12 bad parts i.e. 12 defectives.

Cp, Cpk vs Pp, Ppk

In the last post we looked at the different process capability indices like Cp, Cpk, Cpm etc. But there is also Pp and Ppk indices that measure process performance. There is a fundamental difference between the two types of indices.
We will now try to understand the difference between process capability and process performance.
And when to use what capability index?

Process capability measures the ability of the process to consistently produce output within specification limits. Process capability indices are calculated assuming the process is statistically stable i.e. has only common cause variation.

Process Performance is an estimate of the process capability during initial setup. The indices are calculated assuming the process is unstable. Such a process has both common and special cause variation. A comparison between process capability and process performance helps understand the difference between the two.
 

 
Have you used Cp, Cpk or Pp, Ppk for measuring your process capability? We would love to hear from you at info@sybeq.com.

Histogram & capability analysis

In the last post we looked at tools for analyzing distribution of variable data. Histogram is the most popular distribution analysis tool. Using the histogram we can also predict the capability of the process.

Histogram shows the frequency distribution of the data. The curve shows shape of the distribution. Skew measures asymmetry of the distribution. A positive skew indicates a histogram with a longer right side tail whereas a negative skew has a longer left side tail.

So where is the tie in between the histogram and capability analysis?
Process capability analysis compares process performance against specifications. Histogram shows the distribution of process data. If the histogram graphically showed the specification limits then it is showing if the process is performing within specs or not. So visually the histogram would show if the process is producing good parts or not.

Numerically capability of a process can be analyzed by calculating the capability indices. There are several capability indices each showing an aspect of process capability. Most popular capability indices are Cp, Cpk, Pp, Ppk.

Read our White Paper on different capability indices and their uses.

What capability indices do you to determine process capability? How do you use the histogram for distribution analysis?

Distribution Analysis for variables

Distribution analysis for variable data is one of the critical analysis that help us understand how much
variation exists in the data. This in turn helps us understand how wide the process is and whether it falls within the specification limits.

There are several tools for studying distribution of variable data. The tools listed below are some of the popular ones:
1. Histogram
2. Stem and Leaf plot
3. Dot plot
4. Box plot

Histogram being the most popular to understand the nature of distribution of variable data. Dot and Stem & Leaf plot are more detailed versions for analyzing data distribution.
Box plots (also known as Box and Whisker plot) are used to compare distributions. Example for using a box plot would be to compare machine performance.

The figure below shows a comparison of the 4 tools.

We would love to hear which of the above tools have you used for analyzing distribution of variable data. Write to us at info@sybeq.com

Analytical tools for variable, attribute data

We have looked in the data analysis piece of Lean Six Sigma projects.
By now we know that data analysis is key in a Lean Six Sigma project. At the same time it is equally important to avoid analysis paralysis. A Green or Black Belt must know that there are different analytical tools for the type of data.

There are 2 data types
1. Variable or Continuous : Data that is measured and readings can have decimals. Eg. Weight, length, diameter. 3.56lbs, 4.5mm
2. Attribute or Discrete: Data that is counted and readings are integers. Eg. number of rejects, number or cracks

In attributes, there are 2 categories specific to the type of count.
Attribute types:
1. Defectives - The number of parts that are rejected are defectives. Also called non conforming units.
2. Defects - Number of specific problems with parts eg. burred, cracked, scratched parts. Defects could be fixed by repairing them. These parts are called non conformities.

For every data type there is a set of analytical tools. The figure below shows the commonly used tools by the type of data.

Types of analysis in LSS projects

LSS projects focus on data driven process improvements. Lean Six Sigma is all about data. Every phase of the DMAIC approach in LSS needs to be backed with data. Most of the data is collected in the Measure phase. This data gets analyzed, verified and validated using LSS tools.

Along with data analysis it is important to know about the process. So process analysis plays an equally important role in LSS projects. Knowledge about the current state of the process helps understand what the process steps of the current process. Here it is necessary to use the Go See Lean principle where the LSS team walks the process as it is currently running. Some Green and Black belts make the mistake on relying work instructions or hear say for the current state. However this may not represent what is actually being done on regular basis.

The figure below shows the types of analysis and some useful tools:


Analysis of critical parameters is the key to a successful Lean Six Sigma project. The challenge lies in identifying the critical parameters, gathering data and choosing the right analytical tools. Over and above knowledge about the process plays an important role too.

Have you experienced challenges related to analysis in your LSS project?

How to overcome Analysis-Paralysis in Lean Six Sigma?

We have established the fact that the Measure and Analyze phase of the DMAIC approach are the most challenging. LSS teams spend considerable time in these two phases. To overcome challenges of gathering and analyzing data, we must understand the purpose of the Measure and Analyze phases.

In the Measure phase, the LSS team is trying to establish the process map, baseline for the primary metric used in the project and the amount of process variation. Creating a process map requires the team to actually go see the process and create the map as they walk through the process steps.
Some popular tools for measuring baseline & process variation include:
Histogram, scatter diagram, trend chart for historical data, capability studies and gage R and R studies.

In the Analyze phase the LSS team is trying to determine root cause of the problem and validate it too. Fishbone diagram or Affinity diagram and Potential cause Prioritization matrix are the two tools for identifying root causes. Then comes root cause validation which requires establishing a hypothesis statement and choosing the appropriate statistical test for validating the hypothesis. Test the hypothesis with enough sample data. Most LSS teams struggle here.

The Green or Black Belt leading the LSS project has to ensure the team maintains focus on getting the required information using the necessary statistical tools.

What are some of the tools you have used to overcome analysis-paralysis in LSS projects?

Dangers of Analysis-Paralysis in Lean Six Sigma

Continuous improvement projects require teams to collect data and analyze it.
Lean Six Sigma method needs metrics and data to back up everything. Even the success of the LSS program is measured and tracked.

Sometimes Lean Six Sigma Green and Black belts analyze data more than needed. In LSS projects using the DMAIC approach the Measure phase is where hard data on the primary metric is collected. Preliminary data analysis begins in the Measure phase and continues into the Analyze phase where root causes are identified. Many LSS projects get stuck in the Measure or Analyze phase.

There are several reasons for this. Some of the key reasons are:
1. Data is hard to find/gather
2. There is too much or too little data
3. Incorrect data is collected
4. Green and Black belts over analyze the data
5. Preliminary data analysis does not reveal much so more data is collected

The Measure and Analyze phases of the DMAIC approach are most challenging. These phases take time and effort from the LSS team. The team needs to have the patience and persistance to get through these phases. The team leader (Green or Black belt) needs to get through the data collection and analysis portion efficiently/effectively. Without getting bogged down by data and not getting caught
in analysis-paralysis is the critical aspect to keep the project moving forward.

In our next blog post we will discuss the tools and techniques to overcome Analysis-Paralysis.

Have you experienced Analysis-Paralysis in an improvement project? How have you overcome it?

The need for "Lean lens" to remove waste

The question most Lean critics have is "If lean requires common sense thinking, why do we need Lean believers, Lean Practitioners to implement it?"

Lean concepts and principles are indeed easy to understand, lean tools are easy to apply to real world processes. But most people doing the work on a regular basis are usually not aware of the wasteful activities they are doing. In fact most people working the process are so busy doing the work that they don't have time to think about their way of doing it. They get so comfortable that they just stop thinking about what they are doing and why they are doing it?

Lean Practitioners help these people look at every process step with a lean lens. Using the Go See principle, practitioners walk the process with the people working it and map it on paper. When the people working the process look at the process map with the lean lens, it helps them identify value added and non value added activities in their process. Wasteful activities become obvious and every step of the process is looked at from the lean perspective. The lean lens looks at each activity in the process as value added or non value added. Everything is questioned and ways to improve the process are discussed.

Continuous improvement teams come up with unique ways to remove waste and focus only on value adding activities. Most of the times the teams see the wasteful methods they used all along. Teams often realize that they need to be working smart and not hard!

What motivates continuous improvement?

Continuous improvement programs are popular these days as all businesses are trying to find ways to cut costs by working smarter. Although CI programs are present everywhere they seem to deliver bottom line results only in certain places. Why?

If we analyze this logically you will see that it very simple. CI requires change in way processes work in an enterprise. It requires people working with these processes to change and think differently. Actually, it requires thinking outside the box.

We know that human beings by design are resistant to change. Researchers have proven that humans do not like change. So what would motivate change in a CI program?

Two key motivators for change are:
1. Threat - If people fear the consequences of not changing, then they would be willing to try to change. For example, fear of losing a promotion or job or a raise.
2. Reward - If the proposed change brings tangible rewards then people could accept change.

What strategy does your company use to make CI programs succeed?
Share your ideas at info@sybeq.com

What does "Leaning out a process" mean?

With the success of Lean Manufacturing, it is common these days to hear people say we are Leaning out the process. But do people really understand what Leaning out means.
I have come to realize that the phrase Leaning out means different things to different people. Here is the list of some of them...
- optimizing material movement
- removing obstacles in the process
- re-arranging the area
- re-arranging people
- removing clutter
- doing more with less

Although all of the above are good interpretation of the term "leaning out". I think most people undermine the true meaning of the term which is to remove all non value added activities in a process to improve flow. But why is flow important? And above all what should flow?
I think the term "leaning out a process" is used rather loosely at all levels of the enterprise without understanding the true meaning.

Have you heard the term "Leaning out"? What thoughts come to your mind when you hear this term? Drop us a line at info@sybeq.com

Continuously improve in 2011

The New Year has begun and every new year kicks off new projects/programs.
New programs in almost every function of the enterprise are planned for the entire year.And Continuous Improvement program also gets new goals, targets and plans.

Continuous improvement is tough in today's business climate.
Businesses are trying to do more with less. Less resources to take care of routine work. On top of this there is the CI program that needs resources too.
Most people devote time to CI projects after taking care of their routine responsibilities.

So how do you plan for Continuous Improvements in 2011?
1. Simple tools like 5-Why Analysis, PDCA, Cause and Effect diagram are easy to understand and use.
2. Create a learning environment where everyone learns by applying.
3. Encourage people to just try a new tool or technique for improving a process. Sometimes the best solution is to Just do it.
4. Plan for Continuous improvement with the end goal in mind. Sporadic improvements here and there are useful but won't get the CI program far.
5. Link each CI activity/project to financial benefits.
6. Communicate the progress of the CI program to all levels of the enterprise. Leadership needs to know what has been achieved and the goals for the CI program.
7. Periodically Measure how the CI program is actually doing compared to the goals/targets.
8. Tweak the program if it is not achieving the set goals but never give up on your CI initiative.
9. Know your CI toolkit and update your skills to use the tools in your improvement projects.
10. The key is to persist inspite of the challenges and never stop continuously improving your processes!

We would like to hear about your CI program in 2011. Are you planning for new tools you would try in your CI projects?
Drop us a line about your CI plans for 2011 at info@sybeq.com.

How to level the load in production?

The concept of load leveling requires careful analysis of production volumes and schedules so that production makes same quantity of parts both by volume and product mix everyday.

The steps for leveling the load include:
1. Take the total volume of customer orders in a period by product type.
2. Determine the quantity of parts by product so that the same volume needs to be produced by product type.
3. Analyze the time required to make a part by product type and time required for changeover.
4. Plan a stable production schedule so that plant floor doesn't have to deal with fluctuations.

The goal of leveling the load is planning to work at a consistent pace in production making a mix of parts so that the equipment and people are working at the same pace without stopping or being stressed.
Because of this production is not rushed for deliveries giving production folks enough time to implement standard work and avoid errors.

The key to find the mixed model that works for your process/line. Once the mixed model is determined, production has to make the same quantity, mix of products and repeat it everyday.

Load leveling presents many challenges:
- The concept of load leveling is counter intuitive to batch manufacturing where the focus is to run a batch of same product as long as you can and run it efficiently. Load leveling on the other hand says it is okay to changeover from one product to another. In fact load leveling encourages multiple changeovers in a day or a shift.
- Due to the mixed model approach, there may be some amount of finished goods inventory when implementing load leveling. This may make some Lean experts unhappy as they view inventory as waste.
Ultimately it is important to look at the risk of carrying some inventory to satisfy customer demand or make the customer wait for the product they need.
- Load leveling won't be successful without having quick changeovers i.e. reducing changeover time.

Taiichi Ohno explained this with the story of the race between the tortoise and the rabbit. The slow and steady tortoise wins the race. Ohno said it is desirable to be slower but consistent tortoise as it causes less waste than the speedy rabbit who races then stops to rest.

Load leveling is key to becoming lean

The last few posts on our blog focussed on Value Stream Mapping and other lean tools used for waste removal.
Removing waste is the main focus of lean manufacturing.
Value Stream Maps allow lean practitioners to get a true picture of activities done in a process. These maps make waste visible so that it can be removed.
Waste can be removed using lean tools.

In today's world, production volumes change based on customer demand and customer demand fluctuates. Plants practicing Just In Time start producing only when the customer signals for parts. Plants cannot possibly respond to such high variations in demand. So they carry some buffer stock for finished goods.
There may be raw material inventory or WIP necessary to prepare for such demand fluctuations.

Carrying enough inventory is the key to meet customer demands. If plants carry too much they are creating waste and hiding problems.
That is why it is important to level the load so that plants produce at a uniform pace without causing stress to equipment or people. Stressing the equipment could cause breakdowns and stressing people may cause errors or accidents.

But what is load leveling?
Load Leveling is the process of producing the same quantity and mix of parts without responding to every fluctuation in customer demand. This reduces unnecessary stress on equipment or people working in the plant resulting in fewer breakdowns and errors.

The question is how to level the load?
We will try to answer this in our next post.

VSM makes problems visible

Lean principles talk about making problems visible so that they can be solved. Value Stream Mapping focuses on charting activities as they happen in the process. The main goal of VSM is to make problems/waste visible.

But what happens next is equally important. Problems need to be acted upon. Lean practitioners need to identify what how to resolve problems or remove waste.
The following approach may help practitioners with problem solving:
1. Identify the list of problems in your area.
2. Measure the impact of the problem on external and internal customers and the organization's bottomline.
3. Prioritize by impact of the problem.
4. Undertake root cause analysis using 5 Why analysis or cause and effect diagram.
5. Identify root causes and corrective actions that can be implemented.

Problems are everywhere. Sometimes very prominent staring you in your face and other times hidden. The key is to find them as soon as they appear and fix them.

This actually resonates with what Philip Crosby said "It isn't what you find; it's what you do about what you find".

What problem solving technique do you use in your workplace? How do you identify problems? Send us your comments at info@sybeq.com.

Using a Pull system not so Lean

One of the key lean tools is implementing kanban which uses the pull system. Lean is all about moving away from the traditional push system toward the pull system. In a lean enterprise, it is always recommended not to push parts or information to the next process step. The focus is to pull parts when the downstream process step requests for parts/information.

Some Lean practitioners rave about the pull systems they have implemented. However experienced Lean practitioners don't give much credit to pull systems. This is because...
1. Lean is all about removing waste.
2. When waste cannot be removed, there is inventory in process or at the final stage. This inventory needs to be managed in the best way possible. In such situations, a pull system is used.

Implementing the pull system is an indication that waste is still present. This is a good starting point for reducing waste but it is definitely the final goal. The Lean implementation team should not stop at implementing the pull system. In fact the team should continuously work toward removing waste altogether and not use the pull system.

As rightly said by Jeffery Liker in the book Toyota Way "Flow where you can, pull where you must". The ultimate goal to make value flow as smoothly as possible.

Information on Value Stream Maps

Value Stream Maps are used to map the flow of information and material in the value stream. This generic statement explains the purpose the value stream maps.
But new users struggle with how much detail about the value stream should be captured on the VSM.

What should be captured?
How should this information be displayed on the map?
In this post we will try to answer these questions.

A value stream map is a picture of your value stream. It's purpose is to find what is happening now which will help identify waste in the value stream. Once waste becomes visible Lean tools can be applied to remove it.

The following information could be helpful if captured on a value stream map..
1. The layout of the area will become evident once the map is complete. The amount of distance between process steps or user motions at the step or the physical movement of material and information.

2. The amount of time required by the user to process a unit. For example time required to verify one insurance claim at the claims verification step.

3. The amount of wait time at the process step. Wait time could be people waiting for material/information (no parts or claims to process) or material/information waiting to get processed (Average wait time for raw material in the incoming warehouse or wait time for claims process to begin).

4. Total time per unit at each process step. This is the addition of processing and wait time per unit.

5. Total lead or throughput time for the entire value stream. This is the time needed to make a single part or process a single insurance claim.

6. Time for rework and repair activity. This information needs to be captured if rework/repair is being tracked as part of the value stream. If this is considered as another value stream this information can be left out.

7. Interruptions in the flow of value as reworked parts/claims get reintroduced at a specific step in the value stream.

What kind of information do you capture on Value Stream Maps?

VSM during early stages of Lean implementation

How many Value Stream Maps should be created at the start of Lean implementation?
We typically hear this question from...
1. Users who have recently learned the Value Stream Mapping tool
2. Organizations who are new to Lean implementation, just starting out on their lean journey

Start the Lean implementation with a few (say 2 to 3) value stream maps for processes that have the most non value adding activities (waste).

Why just 2 to 3?
Because of several reasons..
1. Creating Value Streams is a time consuming activity.
- Teams creating these maps have to walk the value stream and capture information
about material and information flows.
- Teams have to then create the current state map, identify waste and the Lean
tools they plan to use, create the future state map.

2. After creating the maps in the meeting room, now teams have to actually go and implement the Lean tools in the value stream. This is the most challenging part as this may take anywhere from a few days to few weeks. There are many aspects of the implementation like corporate culture, motivation level of people, management involvement, complexity of the process that could play a role.

3. Getting rid of all the waste in the process may require several cycles of going from the current to the future state. After all Lean is a journey of continuously removing waste.

How many value streams have you worked with? How many value streams did you start with when your organization was in early phases of Lean implementation?
Send us your questions or comments at info@Sybeq.com

Where to begin mapping Value Streams?

In the last post we talked about the different questions lean pratitioners have about implementing Value Stream Mapping.

The question of where to begin mapping value streams actually requires understanding the definition of value stream.
Lean practitioners need to have the ability to clearly identify and define a value stream.

A Value Stream is a stream of activities required to satify a customer need. The value stream starts with the customer who may be external or internal and ends where it is has a logical end. What this means is...
1. Start with the customer. First, define who is the customer and what do they need.
2. With this defined, start Walking the value stream backwards one step at a time.
3. Stop wherever it seems to be a logical stopping point.

While doing the above steps do not restrict the value stream by functions or departments. This is because a value stream may cross multiple departments. The ultimate goal of value Stream Mapping is to map how the stream works starting with the customer first and ends where it is a logical stopping point.

Do you face the challenge of where to begin mapping value streams? Tell us about your VSM implementation. Email: info@sybeq.com