If you take a Six Sigma Green Belt or Black Belt training class, Analysis of Variance (ANOVA) is a core analysis tool that is taught. It is used to split variability from a data set into two key groupings: random factors (noise) and systemic factors (significant).

The ANOVA test is a useful tool that helps you establish what impact independent variables (inputs) have on dependent variables (outputs) within a regression model, experimental design or multi-variable study. For instance, ANOVA can be used to determine differences in the average Intelligence Quotient (IQ) scores of people from different countries (e.g. Spain vs. US vs. Italy vs. Canada).

In this example, the IQ scores would be considered the dependent variable, and countries would be an independent variable.

ANOVA provides a statistical test of whether the averages of several groups are equal, and therefore generalizes the traditional t-test to more than two groups, referred to as an F-test. If there were statistical differences between the average IQ scores within each country, then we would conclude that country is a systemic (significant) factor in explaining variation in IQ scores.

Many statistical packages can perform ANOVA analysis and help you determine which of your independent variables are significant, which makes the calculations much easier these days.

The History and Purpose of ANOVA

For the purpose of this type of comparison test, which was developed during the 20^th century, t-tests were the primary analysis tools available to analysts until 1918, the year when Ronald Fisher created ANOVA.

However, the term only became a buzzword in 1925 after it appeared in his book, Statistical Methods for Research Workers.’ Initially, the method found application in experimental psychology, but was later employed to wider applications such as farming and manufacturing. As a nod to its creator, the test is also known as the Fisher Analysis of Variance.

The ANOVA test is the first step when analyzing the factors that affect a data set, after assumptions have been validated. After the test has been completed, you can perform further tests on the factors which contribute to the variability, or discover that there are more factors not captured in your data that are missing from your analysis.

From the ANOVA analysis, a percentage of explained variation can be calculated (called an R-squared value), which is a number between 0% and 100%. If your analysis shows a percentage of only 33%, likely you are missing some important variables from your data set, and should find ways to gather additional data and re-run your analysis.

Types of ANOVA

Analysis of variance comes in two distinct forms: one-way and multiple. In a one-way ANOVA, the evaluation carried out is with regard to the impact of a single factor on only one dependent variable. This analysis helps to determine if all categories or groups studied are the same within that variable (such as each country). The purpose of the one-way ANOVA is to establish if there are statistically significant differences in the average of two or more unrelated groups within your dependent variable.

The multiple ANOVA extends the one-way ANOVA to two or more dependent variables. An example of a multiple ANOVA is where a company seeks to compare productivity of its workers on the basis of four independent variables…

Dependent: Productivity (average number of quality documents produced per hour)

Independent:

1. Age (Under 30, 30-50 years old, over 50)
2. Job experience in company (less than 5 years, 5-10 years, over 10 years)
3. Previous related work experience or education (no or yes)
4. Education Level (no high school degree, high school educated, college educated)

In addition to determining which of the 4 variables influence the productivity, it can also identify if any of the variables interact with each other, creating a more complicated relationship. An interaction in this example might be where previous related work experience does not matter for workers with over 10 years experience in the company, but makes a big difference for workers who are under 30 years old and with the company less than 5 years. The impact on productivity changes when you look at the groups of another variable (it’s not consistent across the board).

How Is ANOVA Used?

You will find ANOVA tables displayed in the these 3 popular Six Sigma tools: Regression Analysis, Gage Repeatability and Reproducibility (R&R) studies, and Design of Experiments (DOE).

For instance, a researcher could test students from different colleges in order to find out if the students attending one college are consistently outperforming those from the rest of the colleges. Another example of the applications of the ANOVA test is a researcher testing two different manufacturing processes to find out if one process used to create a product is more cost effective than the other.

You could even compare the beer consumption between regions of the world to see if they are similar or different.

Here is an example of an ANOVA analysis. The bottom section represents the ANOVA table, showing the Region, Error and Total terms. We will not go into the details of this calculation in this article.

Conclusion

If you are familiar with the traditional t-test, you will be excited to learn that the ANOVA test can replace the t-test, as it can handle more complex analyses that are difficult or impossible to perform with the t-test alone. Due to the increase in computing speed over the last few decades, ANOVA has become one of the most popular techniques used to compare group averages, which is needed to understand many research reports and conduct successful Six Sigma projects.

If you would like to learn more about t-tests, F-tests and ANOVA, sign up for Six Sigma Green Belt training with 6sigma.US >>>

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But why invest the time and money in Green Belt training? How will it benefit you in the long- and short-term? Today, we shed light on how Green Belt training can be highly advantageous for individuals or corporations. Here are our top 10 reasons why you should sign up for a Six Sigma Green Belt training course.

Top 10 Reasons for Six Sigma Green Belt Training

• 1. Positive Change.

  By training employees to become Six Sigma Green Belts, they will master Six Sigma methods in the workplace. This can only be a benefit for your organization, as they can then make positive changes from within.

• 2. Time-Effective Training.

  Green Belt training provides a wide-ranging, intensive study of Six Sigma methodology in an accelerated timeframe. Green Belts aren’t required to take on the same level of management responsibility as Black Belts, so training requires significantly less time investment.

• 3. Incentive for Promotion.

  With promotion comes new responsibilities and required skills as well as numerous benefits. As an employer, you can use Six Sigma Green Belt training as an incentive for promotion. Moreover, as an employee, Green Belt training will grant you additional knowledge and skills to help bolster your job progression.

• 4. Impress Employers.

  Companies all over the world use Six Sigma, and job candidates with Six Sigma certification are in high demand. Equally, Green Belts are one of the most versatile and effective Six Sigma practitioners. Show employers why they should hire you through your resumé.

• 5. Pathway to Black Belt Training.

  Six Sigma doesn’t end with the color Green, and Green Belt training can also open doors for Black Belt progression. With the combined knowledge and capabilities of Green and Black Belts on your staff, you will reach optimum efficiency in no time.

• 6. Teambuilding.

  Don’t just train one Green Belt. Train a whole group of them. Green Belts typically train in groups, and by investing in multiple employees, their training also builds team spirit and group work skills.

• 7. Flexible Training Plans.

  Your Six Sigma Green Belt training, when given in-company, is flexible enough that you can adjust it to suit your needs. It can focus on the most pressing areas affecting your company so that you can get the most benefit.

• 8. Easy to Evaluate.

  You can evaluate the success of your Six Sigma Green Belts’ work based on their awarded certification, completed project work, and demonstration of Six Sigma knowledge. This also makes it easy to measure the success and capabilities of your Green Belts for specific tasks.

• 9. Productivity Prevents Problems.

  Green Belt training encourages high productivity and continuous improvement culture. Six Sigma Green Belts can implement preventative measures to ensure problems do not continue to recur. Moreover, this helps you reach a state of near-complete operational excellence.

• 10. Hone Your Analytical Skills.

  Much of Six Sigma involves varying levels of data analysis. Especially for techniques like DMAIC and Analysis of Variance. Furthermore, Six Sigma Green Belt training allows you to develop these key analytical skills. From basic comparisons to quantifying profits. With their range of skills, Green Belts are also prime management material.

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Drop shipping involves a retailer making an arrangement with a wholesale distributor to ship their product after a customer has purchased it. The retailer sells it, and the wholesaler distributes it with the retailer’s label on the item’s packaging. This is a mutually advantageous relationship in which both parties benefit. The wholesaler acquires more product sales and new outlets for retail. Similarly, the retailer benefits from the percentage they earn from each sale. A further advantage for the retailer is that they don’t have to concern themselves with the shipping or carrying of inventory. The wholesaler takes care of it all on their behalf. Today, we look at some of the advantages of drop shipping and how Six Sigma ideas can help you make the most of it.

Why is Drop Shipping Beneficial?

Drop shipping is beneficial as it does not require retailers to maintain an inventory. Not does it require them to handle shipping. They can simply buy at wholesale prices and sell directly to the customer at retail prices, with the distributor supplying product information as well as new products. Amazon, Alibaba, and Overstock all use drop shipping in their online operations. Using this method has helped them cultivate a prosperous online business presence with virtually no initial inventory investment required. By having wholesalers source and dispatch the items they sell, Amazon makes substantial revenue to dominate the online market.

When a retailer sets up a website to sell goods, customers buy the goods, paying the retailer plus any shipping costs. For example, a $10 item may necessitate $3 shipping. It’s then up to the retailer to contact the wholesale distributor, informing them of the details regarding the order. The wholesaler can then package and ship the item to the customer using the retailer’s label. The retailer pays the wholesale price of the product(s) and shipping while retaining a 30% profit. This is how sites like Amazon have managed to make billions of dollars.

Going Where No Retailer Has Gone Before

Certain markets regularly become flooded as multiple retailers try to woo customers with competing products. There is a way around this, though, and Amazon is a great example of ingenuity here. Moreover, Amazon has gone a step further than most as they are both retailers for external products and wholesaler for their own-branded goods. But not only that, Amazon is not just a retailer and distributor, but also a manufacturing and technology giant too. The AmazonBasics line of products aims to provide affordable alternatives to a vast array of everyday essentials. Everything from batteries and phone chargers to backpacks and fashion items. Using Six Sigma principles, they have managed to significantly streamline their manufacturing, distribution, and retail processes for their own-branded products. This affords them a substantial market advantage over competing vendors. Why pay more when you can pay less?

Supply Chain Management

Supply chain managers have a lot on their plate. Their work is often externally focused, requiring them to work with outside partners to source goods or parts to produce products. This is integral to the way modern retailing works. For wholesale distributors and delivery companies, supply chain managers source the inventory retailers require, selling it to them so that they can sell it on again to make a profit. Supply chain managers often work for large corporations, particularly online stores and retail giants like Alibaba and Amazon. They negotiate contracts with distributors to maintain inventory on in-demand goods. Using Six Sigma, you can make a real difference to your wholesalers and how you deal with them. This will help improve efficiency and increase revenue for both.

Improving Delivery Businesses with Six Sigma

As a retail supply chain manager, it’s up to you to decide which products you want to sell. Six Sigma uses raw data to make justifiable decisions about process changes. Without a strong plan to follow, you won’t make the most of Six Sigma strategy. Think about the market you are targeting. Make certain that the products you want to sell are in demand. Search engine analytics are a great way to shed light on what is trending, on which products and services people want. The more you know, the more prepared you are to drive successful change. The more data you have, the greater control you have over the value chain, allowing you to predict potential future demand.

It’s important to utilize reliable drop shippers to ensure success. Be wary, though, as there are plenty of charlatans out there masquerading as good drop shippers. If you chance upon a bad egg, get rid of it quickly, as they will cause more problems for you later. A reliable drop shipper demands lots of pertinent information to do their job. This is your golden ticket. You can expect them to ask for references from other suppliers as, remember, they want to benefit from the arrangement just as much as you do. Once you get going, we recommend applying tools like Root Cause Analysis and DMAIC as regular assessments of your business operations.

Additional Six Sigma Improvement Tools

If you keep running into similar problems, like missing product information and shipping alternative or defective items, apply Root Cause Analysis to identify the source of the issue. Similarly, DMAIC can help you take control of inefficiencies to improve your business processes. It can also help you locate sources of variation that lead to defective products using Analysis of Variance. Applying Lean principles will also help eliminate sources of waste such as over-processing and human error. Black Belt-led improvement projects can also actively seek out inefficiencies and replace them with innovative solutions. All these tools and techniques coalesce to make significant improvements across the board. Cultivating a Kaizen culture of continuous improvement is also a beneficial strategy to stay on top of these problems and ensure future success. This not only benefits the customer but, of equal importance, you as well.

Learn more about our training and Courses

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