Any organization that sells products and services needs to communicate the value of its offerings to the target market. It is up to marketers to not only help the organization reach potential customers but convince them the offerings will provide the value they are looking for. That way, the customers will purchase the offering and the organization will make revenue.

To help organizations become profitable, marketers often launch campaigns to reel in potential customers. But sometimes this process can run into problems, which can lead to the expected return on investment (ROI) not being realized. In Six Sigma, the marketers are said to have experienced variation. This is a mismatch between what was expected and what has occurred.

In the face of variation, it is reasonable to ask what the cause is and how it can be resolved. Luckily, Six Sigma can help marketers get to the bottom of variation using a data-driven, scientific approach known as DMAIC (Define, Measure, Analyze, Improve, Control). 

Here’s how that would work for a marketing campaign.

Define

The first step is to define the problem being experienced. The team would come up with a problem statement. This is a document that will contain a clear and concise definition of the issue and how it is affecting the organization.

The team would look at the goals of the campaign, how they would benefit the organization and if they are S.M.A.R.T (Specific, Measurable, Achievable, Relevant, Time-Based). An example of a S.M.A.R.T goal would be to increase the ranking of the organization’s website on Google to be in the top three results by the end of the year.

Measure

In the Measure phase, the marketers will gather all the necessary campaign data and measure it. Then they would make sure that the measurement system used is effective and that data integrity was preserved. Examples of data they can collect for a marketing campaign include click-through rates, conversion rate, number of impressions, number of social shares, and number of backlinks.

Analyze

After gathering and measuring the data, the marketers will then analyze it to extract insights. They can look at, for instance, where most clicks are coming from. Or how long people are staying on the page when they visit it. After all, the more people visit a website and stay on it long enough, the more Google will think it’s relevant. The Google search engine algorithm will award points to the website, which will boost its ranking.

Improve

From the insights gained in the previous step, marketers will know which marketing channels to focus on to increase their SEO ranking. By shifting focus away from the non-performing channels, they would be saving a considerable amount of time and money.

Control

By understanding what works and what doesn’t, marketers can now control the marketing process. The goal would be to standardize the procedures they used to increase the ROI of the marketing campaign. It also involves continuously measuring the results from the procedures, as well as updating the procedures when they are improved. The result will be a set of guidelines and/or an SOP.

As you can see, Six Sigma is a valuable tool for marketers. It can help them see a return on investment on their marketing efforts when the expected results don’t match the actual results. Through the DMAIC methodology, marketers can improve their marketing processes and improve drive positive outcomes.

You can check our online training here.

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Understanding the basics of a viable Six Sigma practice begins with understanding DMAIC. Six Sigma DMAIC (Define, Measure, Analyze, Improve, Control) methodology can be thought of as a roadmap for problem solving and improvement. Organizations begin implementing Six Sigma by applying the DMAIC methodology, then subsequently adding DFSS (Design for Six Sigma) methodologies when the organizational culture and experience allows.

It can be considered the classic Six Sigma problem-solving process. This methodical approach can be applied to a problem with an existing, steady-state process or product and/or service offering. Variation is considered the enemy. Variations from customer specifications in either a product or process is the primary problem, but can take on many forms.

DMAIC resolves issues of defects or failures, deviation from a target, excess cost or time, and deterioration. Six Sigma reduces variation within and across the value-adding steps in a process. It also identifies key requirements, deliverables, tasks, and standard tools for a project team to utilize when tackling a problem.

What Does DMAIC Mean?

Define – Define the project goals and deliverables.

Measure – Measure the process to quantify the problem.

Analyze – Analyze to determine the root cause of the defects.

Improve – Improve by eliminating the defects.

Control – Control the future performance of the process.

The Tools That Drive DMAIC

Understanding DMAIC is just the beginning. Applying and mastering the concept involves the use of proper tools.

Define – Project Charter, Process Flowchart, SIPOC Diagram, Stakeholder Analysis, CTQ Definition and Voice of the Customer Gathering.

Measure – Process Flowchart, Data Collection Plan, Benchmarking, Measurement System Analysis/Gage R&R, Voice of the Customer Gathering and Process Sigma Calculation.

Analyze – Histogram, Pareto Chart, Time Series, Scatter Plot, Regression Analysis, Fishbone Diagram, 5 Whys, Process Map, Statistical Analysis, Hypotheses Testing and Non-Normal Data Analysis.

Improve – Brainstorming, Mistake Proofing, Design of Experiments, Pugh Matrix, QFD, Failure Modes and Effects Analysis (FMEA) and Simulation Software.

Control – Process Sigma Calculation, Control Charts, Cost Savings Calculations and Control Plan.

DMAIC is a powerful methodology. But the real strength lies in the structure and rigor of the practice.

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Leadership was required to support the initiative 100 percent. At the time, leaders were required to take a 13-day, 100 hour training program, with completion of a project by the end of 1998.

The primary focus at the time was improvement on the manufacturing side. It was at GE that MAIC (Measure, Analyze, Improve, and Control) actually started; but since GE Capital, the financial services side of the company, accounted for nearly 40 percent of the profits of the company, it didn’t make sense to just focus on improving the manufacturing aspect. So consequently, GE Capital got on board with Six Sigma, and through their processes eventually added the Define stage, creating the acronym DMAIC as we know it today.

When Six Sigma was officially implemented at GE in 1996, there wasn’t any money saved: the company invested $200 million, and only saw a cost savings of $170 million. This would change in 1997, when CEO Jack Welch made the choice to tie in leadership bonuses to Six Sigma results. It proved to work: that year, $400 million was invested in Six Sigma, with an overall savings incurred of $700 million.

That year also saw some significant changes in the methodology at GE. Three different initiatives started to become a stronger focus at the company:

• CQ (Commercial Quality) Applications: focusing on areas outside of manufacturing, such as inventory management processes and pricing
• Creation of Green Belts: This role was created primarily to support the Black Belts and Master Black Belts, helping to support and analyze problems involved in quality improvement projects. It also ensured that Six Sigma would be fully implemented and everyone would get into the methodology.
• Creation of Design for Six Sigma (DFSS): the objective was to determine the needs of customers and the business, in order to design a product or service, as opposed to improving an existing product or service.

The focus the first few years of implementation at GE was on internal cost savings; this began to change in 1998, where the attention changed to focus on the customer and issues impacting them, such as delivery and customer service.

So why was the Six Sigma program so immensely successful? Many attribute it to the focused, hands-on implementation by Welch and upper management. From surprise work floor visits from management, to consistent monthly reviews and reports, the Six Sigma team was all in in order to ensure a successful implementation. It certainly worked: over the course of five years, GE realized an overall cost savings of $12 billion.

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Define: Define the problem by understand the details and complexities. The description should include the challenges to the customer/business. The customer(s) project goals and timeframe for completion should be included.
Measure: Map out the current process and gather all related data. Identify the data that is available and a plan to gather it. Gather the data and summarize it, telling the story using graphic tools.
Analyze: Thoroughly investigate and identify all elements of what causes the problem. The analysis must be both statistical and qualitative, which will lead to the formulation and hypothesis testing about the root cause of the problem.
Improve: Implement a solution that will provide verifiable solutions to the problem. Directly address the root cause with an improvement. Brainstorm potential solutions and test if the solutions resolve the problem.
Control: Maintain the implemented changes and maintain the course. When the solution selected has resolved the problem, the improvements must be hardwired into the operations and culture of the organization. The project team must continue to monitor and measure the implementation and achievements to verify there results reported.

Some overall requirements define this approach. They come from the customer and/or the business, depending the problem scenario. These requirements are translated into what is critical-to-quality (CTQ), which defines what criteria to evaluate what the good looks like. It is critical that the project team must meet the requirements of each phase of DMAIC before declaring completion and closing it out.

The DMAIC method was structured to answer the following questions:

What does the customer define as the problem? Is the problem chronic or a one-time occurrence?
What characterizes the problem and how has it changed with time?
What are the root causes and what improvements correct them?
What controls should be implemented to sustain the improvement?

The process is this simple, as long as the DMAIC is followed. By following the process with focus and intent, you will be able to identify the cause(s) of the problem, implement a resolution based on fact and finally see resolution to the problem being addressed. Contrary to some of the information about Lean Six Sigma, the practice is simple and easily understood. Since the practice is based upon clear principles, it can be implemented in any organization, across any industry and in businesses from small to large. Like with any other process or practice, leadership in the organization must be committed to a climate of perpetual innovation. The entire must understand the level of commitment and the focus on creating an indelible cultural change.

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Six Sigma helps streamline processes by identifying root problems and eliminating them. The IT sector can immensely benefit from the approach which makes teams more agile and prepares them to optimize their offerings in tune with the voice of the customer.

The use of Six Sigma in IT management can have far-reaching consequences, as we shall explain in this article.

Understanding Six Sigma Principles

Six Sigma is a process improvement technique that helps bolster quality by reducing defects, i.e. bottlenecks. It helps manage quality and works to reduce variations in processes. Originating in Motorola, the technique rapidly expanded to other domains and is now used worldwide. Six Sigma has its origins in the statistical symbol Green sigma, which stands for standard deviation.

It helps companies with quality management through a well-defined series of steps. Six Sigma includes a DMAIC workflow which includes defining the problem, measuring the current state of processes, analyzing the data to discover problems, improving the processes, and controlling future iterations.

Another method employed in the Six Sigma approach is DMADV, where Six Sigma professionals define the goals, measure project state, analyze the project and create designs to improve processes and shortlist the best one, design and test processes, and finally verify the design. 

Six Sigma in the IT Industry

Six Sigma is a set of tools and techniques which help businesses improve their processes. Six Sigma can improve reliability and speed of operations in the IT sector. The technique helps analyze setups in a consistent manner.

It often begins with a problem statement to understand the root issue and its causes. Six Sigma takes that as the input and works to eliminate the challenges in a systematic manner. 

DMAIC is often used in conjunction with the voice of the customer (VOC). The goal is to understand customer pain points and develop specific solutions, even if they involve the use of existing systems to meet customer expectations.

When using Six Sigma, it is important to leverage the experience of professionals who are trained in the methodology. You might also need to train your internal workforce to prepare them for what lies ahead. It’s a delicate balance as excessive training can actually do more damage than good.

It’s All About Quality

Six Sigma is a time-tested methodology that works in diverse fields including in the IT sector. Teams should strive to be as agile as possible and understand customer pain points to address them in the best way possible. 

Six Sigma uses the DMAIC methodology to first formulate a problem statement and understand the challenges at hand. Teams will then work to systematically eliminate problems and reduce defects in processes. This has a direct impact on improving quality, reducing costs, and bolstering efficiency. Six Sigma helps IT achieve higher customer satisfaction levels across the board.

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Control Charts are a simple yet powerful tool that helps us understand if a process is “stable or in control.” Control Charts are used in the Control phase of the DMAIC (Define, Measure, Analyze, Improve, and Control) process. The charts help us track process statistics over time and help us understand the causes of the variation.

A process can be called stable or under statistical control if it has only one average and one standard deviation. What this means is that the process can still produce materials that are out of specifications. But the deviation is well within a predictable limit, and the whole process is completely under control. The control is specified by a single average, which means that the output quantity remains the same after the whole process is completed.

There are two types of general data: Variable and Attribute.

• Variable data is data that is in a continuum range and can be measured on any scale. For example, height, weight, etc., data can be measured between two numbers on an infinite scale. It is also known as continuous data.
  
• Attribute data is the type of data that has two types: discrete and numeric. Discrete attribute data assigns a numeric value to a qualitative characteristic of your project. For example, agree, strongly agree, disagree, etc. can be plotted on a scale of 1 to 5, based upon the increasing magnitude of the issue. Numeric attribute data is the type that can be counted. For example, the number of errors in the delivery of a product, customer waiting lines, defects produced in a process, etc.

Why do we need Control Charts?

Control Charts help us identify controlled and uncontrolled variations in a process. Let’s further understand what these variations are and how they affect the process.

Controlled Variation

• They are known as “common causes or inherent (noise) or random causes.” This kind of variation is always present in any kind of process due to the regular and repetitive nature of the input and conversion processes. This variation is natural, and we can never predict the next data point exactly. The common causes will have a brief effect on the process and will appear and disappear randomly, thus awarding it so many names.
  
• However, if the input and conversion process activities stably repeat themselves, then the common cause variation can be predicted, not accurately, but we can get a range or a band in which the noise variation can take place. A process is considered stable if it has only common causes.

How do we fix it?

• Common causes usually arise from the basics of a process. So, to fix it, fundamental changes are required. Also, there are many strategies to achieve the same goal, like the drill-down strategy, the disaggregate strategy, etc. Thus, as we take these approaches, we can find the noise and reduce or mend it permanently.

Uncontrolled Variation

• They are also called or known as “special cause variables or assignable variables” (signals). This type of variation is not usually present in the input or conversion activity of the process. They originate from outside the process and create changes in the process, making it difficult to identify and analyze common causes.
  
• Signals affect the natural variation of the process and are the major cause of irregularities or shocks in the process.

How do we fix it?

• You need to work with the data and make sure that the data is accurate and timely. Also, when signals arise, you need to immediately find the cause and fix it. Find or make some changes in the higher-level process to rule out special causes from repeating. And you should never make fundamental changes to fix special causes.

Note: All processes have common causes, but not all processes are affected by special causes.

As previously stated, noise cannot always be avoided because it is a natural variation that we must accept and work with. But signals are more like an anomaly that can point out major flaws in the process and, if fixed, can greatly benefit the entire process.

Types of Control Charts

There are two major types of Control Charts, which are further divided into subcategories, for better understanding the causes, controlling the process, and making it stable or in control. The types of Control Charts are Variable Control Charts and Attribute Control Charts.

Variable Control Charts plot statistics from the measurement data, such as height, length, width, etc. 

It is of three types:

• Individual and Moving Range (I-MR)
• X Bar Range Chart (X Bar/ R), X Bar Sample Chart (X-Bar/S)
• 3 Chart I-MR-R (Master Black Belt)

Attributes Control Charts plot a process statistic, which is plotted against a sample number or time.

It is of four types:

• Np-Chart
• P-Chart
• C-Chart
• U-Chart

As we read, there are 7 types of control charts. We will use them as per the data type and then proceed further to get the process stable or in control. Thus, if the data is continuous or variable, we use the I-MR Chart, X-Bar R Chart, and X-Bar S Chart.

If the data is discrete or attribute, then we use P, Np, C, and U Charts.

The charts mentioned below are used for continuous or variable data.

• I – MR Chart
  When we can’t subgroup data, we use the I-MR chart. This measures continuous data, as often we do not get many points, or maybe the process has a long cycle time, so we use this chart. As we learned earlier, there can be data on an infinite scale between two numbers. Thus, this chart proves helpful for plotting this kind of data.
  
• X-Bar R Chart
  When dealing with continuous data, we have 2 or more, but not more than 10 subgroups. Then we use the X-Bar R chart. This chart helps us determine if a process is stable and predictable. The X represents the mean of all subgroups, and the R represents the range of all subgroups.
  
• X-Bar S Chart
  When dealing with continuous data, if we have more than 10 subgroups, then we use the X-Bar S chart. We can also use this chart for more than 2 subgroup sizes. The X represents the mean of all subgroups, and the S represents the sample size.

Now let’s move on to discrete data. We use 4 types of charts as discrete or attribute data is divided into 2 parts, i.e., defective items and specific types of defects. So, different charts are used for each use case. The charts mentioned below are used for discrete or attribute data.

Under the category of defective items, we use two types of Control Charts – P and Np.

• P Chart
  The P chart is used to measure and plot the defective discrete data, checking the stability of the process. It plots the number of units that are not fit.
  
• Np Chart
  The P chart is used to measure and plot the defective discrete data, checking the stability of the process. It plots the proportion of units that are not fit.

Note: The main distinguishing factor between the two is that the P chart is used for varying sample sizes, while the Np chart is used when the sample size is constant.

Under the category of specific defects category, we use two types of Control charts – C and U.

• C chart
  The C chart helps us check the stability of a single unit, which might have one or more defects. For example, the number of defects in one remote. A C-chart plots the number of defects.
  
• U chart
  The U chart helps us check the stability of a single unit, which might have one or more defects. For example, the number of defects in one remote. A U-chart plots the number of defects per “inspection unit.”

The main distinguishing factor between the two is that the C chart is used when the sample size is fixed, and the U chart is used if the sample size is not fixed. Both charts are used if there is more than one defect.

For a handy approach, use the chart below.

Important points to consider when using Control Charts

• If the value of LCL is negative, assume LCL is 0.
• Because the sample size in the P and U charts varies, we can take the average sample size to obtain a fixed sample.
• Continuous data exhibits two charts, and discrete data exhibits a single chart.
• If the process is in control, it does not mean it’s stable, it just means it is consistent.
• Variable control charts are more sensitive to changes as compared to attribute control charts.
• Variable charts are highly useful for processes such as estimating tool wear and tear.
• Use an individual chart when a few samples are available. This should also be used when the subgroup is not known.
• The U-chart and the C-chart calculate the number of defective units.
• The P-chart and the Np-chart are highly useful for charting proportions. 
• Use a U-chart for continuous items, such as fabric, metal sheet, etc.
• C-charts are useful in comparison to U-charts, especially when there are a lot of possible defects, with a small chance of any defect occurring. For example, flaws in a roll of cloth, etc.

Conclusion

In this article, we learned about the importance of Control Charts and how greatly they can benefit the entire process. What must always be kept in mind while using them is to make sure to check and recheck if you are using the right one. Because if you know when to use which control chart, it will not only save you valuable project time but also provide meaningful information and opportunities for improvement in the process.

To conclude, the Control Chart is a boon for process improvement, enabling us to take necessary preventive action for causes that make a process unstable or out of control. A Control chart should be used at time intervals to check the performance of the process. It also works as a health check-up for your process.

In a Lean Six Sigma project, we use a Control Chart at the beginning of the project as well as at the end of the ‘Improve’ phase to implement required changes and keep the process stable or in control.

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Not many marketers would consider Six Sigma as a means of improving their marketing process. And it is no surprise since Six Sigma is mostly known in the manufacturing industry. The methodology is a disciplined and structured approach that uses various tools and techniques to make processes better. 

One of those tools is DMAIC, which stands for Define, Measure, Analyze, Improve, Control. You can use DMAIC to improve your marketing strategy, and here’s how.

Define

The Define phase is where you identify the needs of your target market. Doing this is a matter of researching the market, and this information will reveal what prospects find appealing about the product or service you’re offering. You can then use this information to formulate an effective marketing strategy that will deliver results.

Measure

In the Measure phase, you’ll collect and measure data to ascertain the performance of the current marketing process. This will give you a clear picture of the current marketing efforts, allowing you to measure them against critical performance measures and KPIs. It is important to use the tools that will help capture the data accurately.

For example, you can use Google Analytics to see the number of visitors, session duration, top traffic source, conversion rate and bounce rate. Once the metrics have been collected, you can form a baseline for performance. This is what you’ll use for comparison after improvements have been made.

Analyze

By analyzing the data from the previous, you can zero in on areas in the marketing process that could use improvement. Here you can use Six Sigma tools like the 5 Whys to identify the root cause of the marketing strategy underperformance. Furthermore, statistical tools like hypothesis testing can verify if you’re looking at the right cause.

Finding the root cause of the problem is important because eliminating it means the issue goes away for good. Anything less and the problem has a high chance of recurring at best, or you end up wasting resources fixing the wrong thing at worst.

Improve

With the root cause identified, it is time to eliminate it from the marketing process. For example, it could be that the marketing strategy is geared towards improving a website’s conversion rate, and you’ve discovered that the website has too many distractions that take people out of the experience. That means minimizing the distractions can maximize focus, allowing visitors to make it to the end of your website’s sales funnel.

Control

Control involves constantly analyzing the results and making further improvements. Six Sigma means you’re committed to ensuring that the previous problems don’t find other ways of creeping back into the process. It is not enough to complete the DMAIC once and call it a success; it is a long-term commitment.

Conclusion

If you’re experiencing a low ROI with your current marketing strategy, it might be time to consider using Six Sigma to improve it. By using DMAIC, you can systematically remove elements that are causing your marketing strategy to underperform. It is not just something that manufacturers can use, but everyone, even marketers.

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Despite all the negativity surrounding stress, it can actually be good for you. It can motivate you to succeed, build resilience, boost immunity in the short term and even make life more meaningful. However, it needs to be managed. 

Unmanaged stress can contribute to many health conditions, including hypertension, insomnia, depression and anxiety. It can also degrade your personal relationships and make you less productive at work, leading to more stress.

While there are many ways to alleviate stress, not many people know that Six Sigma can help. Here’s how.

Increases Your Efficiency

When you have too much to do in a day, you can barely find time to destress. Being efficient means completing tasks on time and with the least amount of effort. Six Sigma has a tool called DMAIC that can optimize processes in your daily life by eliminating efficiencies.

DMAIC is an acronym for Define, Measure, Analyze, Improve, Control. From cleaning the house to bathing the kids and taking them to school to doing your shopping, you can apply DMAIC to these processes and optimize them. In the end, you have less to stress about. 

In a nutshell, with the DMAIC, you can identify unnecessary steps in each process and eliminate them. The beauty is that once you improve one process, you can follow the same steps to optimize others.

Organizing Your Space

Clutter leads to stress because it can be tough to relax when your living space is in a messy state. Every time you sit down, you’re reminded that you have so much to do. The low-grade stress this creates can gradually drain your energy, making you less productive in other areas of life.

When it comes to organizing spaces, whether at work or home, Six Sigma has 5S, which stands for Sort, Set, Shine, Standardize, Sustain. Suppose you wanted to make your home a more organized space for relaxation. Here’s how 5S would help:

• Sort: Go through all your belongings, including furniture, appliances, electronics, clothes and other equipment. Find out what needs to remain and what needs to go.
• Set: Find a logical arrangement for the remaining items. For example, you can arrange them by type, how often they are used and where they can be stored to reduce unnecessary motion.
• Shine: This step is about putting everything in its place and then cleaning the house.
• Standardize: With everything in its place and the house in a clean state, keeping things this way needs to become a habit. For example, you can create cleaning schedules and a list of tasks, along with instructions
• Sustain: Sustain is maintaining order. The idea is to involve everyone by communicating that 5S is long-term and motivating them to get involved and keep it going.

Conclusion

Making you more efficient by streamlining your life processes and organizing your living space are just some of the ways Six Sigma can help you manage daily stress. As you can see, the methodology isn’t just for the workplace, but everywhere there is a process, including your everyday life.

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What is the Analyze Phase?

As the name suggests, the phase involves analyzing the problem to determine the root cause. This allows the Six Sigma project team to tackle the problem at a deeper level and get rid of it permanently. In a manufacturing process, for example, this means investigating what is leading to defects in the products. This is something the customer does not want, which is also known as variation.

Tools for Identifying Possible Causes

The Analyze phase involves identifying all possible causes. Since this is Six Sigma, it means that teams are in luck. There are tools that they can use to take the guesswork out of coming up with potential causes.

Here are the most widely-used tools for doing this:

• Process map – This is a flowchart that shows the process in its current state. This means all the steps, actions, inputs, outputs, and other details are illustrated for a better understanding of the process as is. This allows the team to visualize potential causes by looking at the changes in the process.
• Fishbone diagram – Also known as a cause-and-effect diagram or Ishikawa diagram, a fishbone diagram allows the team to group potential causes into related categories. The problem being experienced is written as the head of the fish. Each bone on the spine represents a category. Then lines are added to each bone, and these are the potential causes.

Tools for Root Cause Analysis

After identifying the potential causes, the team needs to perform a root cause analysis (RCA). The main idea behind RCA is to eliminate the problem at the root so that it does recur. This is important because it means that resources aren’t wasted on dealing with a superficial or wrong cause.

Here are some popular RCA tools:

• Chi-square test: This is a test performed to determine whether there is statistical significance between the expected and observed outcomes. If the difference is statistically significant, it means an independent cause is responsible. Otherwise, it could be because of chance and not worth further investigation.
• Regression analysis: Regression analysis is a series of statistical techniques that help identify variables that lead to a particular result. In this case, it can help tie which potential causes have an impact on the problem being observed. The team can then know which ones to ignore and which ones pay close attention to, as well as how they are related.

Conclusion

After analyzing the problem, improving it is the next step. This is why the Analyze phase is important, as it helps the Six Sigma team identify the exact cause of the problem at the root. This allows the team to eliminate it once and for all to reduce the incidence of defects.

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Have you heard the term Poka-Yoke and are wondering what it means? It’s quite simple. Poka-Yoke refers to ‘mistake proofing’ or “inadvertent error prevention”. 

It’s a Lean manufacturing mechanism designed to prevent mistakes from causing defects to products, services or processes. It’s a work standardization technique that can be applied to any manufacturing or service.

How does poka-yoke prevent mistakes from happening? By tackling human error. 

Origins of the term Poka-Yoke

Poka-Yoke originated in Japan in the 1960s when it was developed by Shigeo Shingo, an engineer working for Toyota. It was first called Baka Yoke but that meant ‘fool proofing’ or ‘idiot proofing’, which meant the term had to change to Poka (mistakes) Yoke (avoid).

How does Poka-Yoke work?

Poka-Yoke makes sure that all the best conditions are present before a process step is made and doing so prevents mistakes from ever taking place. Where the best conditions cannot be ensured altogether, Poka-Yoke detects defects and tries to remove them as early in the process as possible. 

Examples of Poka-Yoke being applied

One of the most easy-to-understand examples – especially for drivers – is when the driver of a car that has a manual gearbox has to press the clutch pedal before starting the car. This has to happen to stop any unintended movements of the car. 

Another easy-to-understand example is when a car with an automatic transmission has a switch that forces the car to be in ‘Park’ or ‘Neutral” before it starts. 

Another very basic example is when the washing machine doesn’t start without the door properly closed to prevent water from leaking out. These types of automation don’t allow mistakes or incorrect operations from the start. 

Why does Poka-Yoke matter?

Simple – because it helps people and processes function properly from the get-go, which in turn prevents mistakes from happening. 

Poka-Yoke and techniques similar to this one improve the quality and reliability of products, services and processes by removing defects altogether. 

The technique can also help with process designs such as those from Six Sigma – the DMAIC (Define – Measure – Analyze – Improve – Control) projects. Using Poka-Yoke in process design helps remove human and mechanical errors. 

When should Poka-Yoke be used?

• When a process step has been spotted where human error can lead to mistakes and defects, specifically in processes that depend on the worker’s attention, expertise or experience
• When dealing with service processes, especially where customers can make a mistake that affects the output
• At a step in a process called the hand-off, where the output or the customer is transferred to a second worker
• Where a small mistake at the beginning of a process can cause big projects further down in the process
• When dangerous or expensive errors can happen

The Poka-Yoke mechanism is highly important and valuable in Lean Management. It’s a way to guarantee quality. It can be implemented in any type of industry with many benefits – the main one being products, services and processes without defects. 

Learn more about our training and courses

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Six Sigma has benefits that make it an essential process improvement methodology no matter the industry. However, the origins and popularity of Six Sigma are in the manufacturing industry. For instance, it has seen tremendous success in adding value to production processes, leading to a quality output that not only increases customer satisfaction but the organization’s bottom line as well.

Anything that is Six Sigma-related can also have a similar impact on health systems like hospitals. Essentially, it can significantly improve patient care, which also improves customer satisfaction. Here are a few ways in which it can help with this through quality improvements. Six Sigma can:

• Make service delivery faster by reducing the number of times patients have to wait to be helped by a doctor
• Reduce errors made by nurses and other hospital staff, leading to better patient care.
• Allow patients to get their lab and other diagnostic results faster by minimizing the turnaround time
• Increase the rate at which insurance claims are processed for faster reimbursements.
• Make the hospital’s services appealing to customers by making sure that the customer’s voice is a major factor when formulating healthcare services
• Provide patients with their medical records, as well as other pertinent health information much faster

DMAIC (define, measure, analyze, improve and control) is what can play an integral role in helping hospitals realize the above-mentioned benefits through Six Sigma. Here’s a general overview of how it can be used in a hospital setting to improve patient care.

How Hospitals Can Utilize the DMAIC Methodology

One must keep in mind that quality improvement comes after solving significant problems within the system set in place. For that, the DMAIC method is the most used, highly-structured and data-driven approach for identifying and eliminating problems.

Let’s look at each one of the phases in the hospital context:

• Define: Patients are identified, along with what they want and need. On top of that, everything identified is defined in a clear and concise manner, along with the process’ end goals and capabilities
• Measure: How good is the current level of healthcare? This needs to be measured to get an accurate picture of what needs improving. A number of key permanence indicators (KPIs) can be used here, such as staff-to-patient ratio, patient wait time and patient satisfaction levels.
• Analyze: After the Measure phase, there will be data that needs to be analyzed using Six Sigma’s tools. To get an accurate picture of the problem that is affecting the quality, the team might have to utilize advanced statistical methods.
• Improve: This is where the patient care process goes through a number of changes to make it better. At this phase, it is crucial to make sure progress is tracked so that data is available to inform the team on whether the changes made are effective or not.
• Control: At this stage, the improvements made will be standardized. The team will create standard operating procedures, which may include protocols and policies, that will guide future patient care improvement efforts and ensure that the improvements made so far do not get undone overtime.

Conclusion

Six Sigma can make a huge and positive impact on hospitals, as far as improving patient care goes. And as more patients become satisfied, the hospital can get more patients and increase its bottom line. With the DMAIC method at the hospital’s disposal, improvement is more than likely.

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Six Sigma is a manufacturing methodology aimed at improving processes and reducing the occurrence of defects in products. However, defects are not just found in products, but in services as well. So if you’re wondering if Six Sigma can apply to something like the health insurance industry, the simple answer is “Yes”.

People need health insurance to pay their medical expenses, meaning errors (defects in this scenario) have a huge impact on their lives. This can range from health insurance being too expensive to afford to insurance claims being delayed or wrongly declined.

How Six Sigma Applies to the Health Insurance Industry

In 2011, a report by the American Medical Association (AMA) showed that the error rate in the health insurance industry is 19.3%. This costs the industry $17 billion annually (it is no wonder the cost of health insurance is high). So how can Six Sigma help insurance companies reduce their error rate?

First of all Six Sigma provides health insurance companies with a way of measuring the quality of performance. It uses a statistical model that gives a rating between 0 and 6. When the quality of performance measures at 0, it indicates that there is low-quality performance. On the other hand, a rating of 6 translates to high-quality performance and the achievement of Six Sigma (3.4 defects per million opportunities).

When insurance companies discover that they fall below reaching Six Sigma, they can work hard to improve their processes. Six Sigma is applicable wherever there are definable and repeatable processes. Thankfully, health insurance is full of such processes, from issuing policies to claims processing to insurance payouts.

One tool within the Six Sigma arsenal they can use to improve their processes is the DMAIC model. DMAIC, which stands for Define, Measure, Analyze, Improve (and Standardize) and Control, is a series of data-driven steps for process improvement.

3 Benefits of Six Sigma in the Insurance Industry

When health insurance companies utilize Six Sigma the right way, they can experience the following three benefits:

1. Standardization of Insurance Claims Submission

By putting in place consistent procedures for information gathering on insurance claims forms, these companies can standardize their insurance claims submission process. This can significantly reduce the number of insurance claims that are filed with inaccurate and/or insufficient information. Furthermore, it can also reduce the costs of processing insurance claims since customer follow-ups are dramatically decreased.

2. Reducing Escalation of Claims

When there are clear guidelines for escalating claims concerning coverages, the number of avoidable escalations can be greatly reduced. They can even be eliminated if other systems of daily performance measurement are put in place.

3. Improved Customer Satisfaction

One way customer satisfaction can be improved is by minimizing frustration. Frustrations can occur because of things like delays. By standardizing quality performance procedures, health insurance can minimize frustration and increase customer satisfaction.

Conclusion

Six Sigma applies to all industries that have repeatable and definable processes. This includes the health insurance industry as well. And when done properly, Six Sigma can lead to benefits that can decrease costs and increase satisfaction – both of these can boost the insurance company’s bottom line.

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In order for anything you attempt to work, there is a secret ingredient you must have and that is faith. Since this is Six Sigma and it is data-driven, maybe a better word is trust. Just look at the data provided by such companies such as Toyota, General Electric (GE), Amazon…the list goes on.

The online dictionary has the definition of faith as “belief that is not based on proof.” Well Six Sigma has proof, and this goes back in time. GE is living proof. They train all of their employees in Six Sigma — everyone is included, not just management. It is a complete collaboration, with mentoring included. 

Jack Welch knew in his gut this was going to be great. He had belief and trust in the Six Sigma system. Yes, there was proof in the system before Jack Welch, but only to those who were involved and chose to see it.

The belief you carry inside is the key to success in anything, including Six Sigma. What makes Six Sigma so special is that unlike anything else, Six Sigma has data to back it up, lots and lots of data. There is enough evidence and proof that Six Sigma works to keep the naysayers quiet; unfortunately to keep the yin and yang in our world they must exist. But for those who believe in what Jack Welch did, we say, “Success up and up” to you!

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1. Critical to Quality (CTQ): What’s most important to the customer, what does the customer require, or what must be included for the customer to spend their money at your business. The customer has to define what quality is, not the business.
2. Defects: Failing to give what the customer asked for; or failing to deliver what the customer wants. Example: When Coca Cola changed its original recipe and made New Coke. That was a major defect, the customers did not ask for that.
3. Process Capability: This is what your process can deliver. 
4. Variation: What the customer sees and feels. This is anything that the customer doesn’t expect in the product that they purchased from the company. There should never be any fluctuations.
5. Stable Operations: This refers to ensuring a consistent predictable process to improve what the customer sees and feels. This is ensuring top quality to what the customer expects from the product. 
6. Design for Six Sigma (DFSS): Designing to meet the customer needs and process capability. Designing a product or service that you currently don’t have to satisfy a customer request or redesigning a problematic process 

The Difference Between DMAIC and DMADV or (DFSS)

The DMAIC methodology is used when you want to improve an existing process not create an entirely new process.

The DMADV methodology (also known as DFSS) is focused on developing a new service or product. 

Define: The customer’s requirements and for the new process, service or product.

Measure: Measuring the customer’s needs to match the customer requirements.

Analyze: The design for the process

Design: Implement the new processes that are required for the new product or service.

Verify: The results and monitor performance.

For more information on our Lean Six Sigma courses and services, please visit 6sigma.com. 

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