For Starbucks Its In The Baghow The Java Giant Fine Tuned Its Sea ✓ Solved

For Starbucks, It’s in the Bag How the java giant fine-tuned its sealing process and improved product quality by Louis Johnson and Sarah Burrows In 50 Words Or Less • When voice-of-the- customer feedback revealed issues with Starbucks’ packag- ing, the company set out on a data-driven journey to remedy the problems. • Using mathematical models to analyze its package-sealing process, the company found a solution to keep its coffee fresh and customers happy. StarbuckS coFFee co. has always taken a data-based approach to decision making when improving product quality and cus- tomer satisfaction. So, when voice-of-the-customer data showed we needed to improve the packaging of our one-pound coffee product, we set out to learn the effects of process parameters on the key packaging qual- ity characteristics.

Project success hinged on the experiments used to understand our package-sealing process. Specifically, a central composite response sur- face design provided the mathematical models needed to determine the process settings to produce an airtight seal that would be easy to open without damaging the top of the coffee bag. The airtight seal is critical to coffee quality, and the easy-open feature is important to providing a great experience to the customer. March 2011 • QP 19 Customer experienCe QP • The best practices employed by Starbucks make this an excellent teaching example of the application of response surface methods to process optimization. Seal of approval Figure 1 shows the device Starbucks uses in the seal- ing process for its one-pound coffee packages.

After the bag is sealed, two specifications must be met. First, the bag must be airtight because air will oxi- dize the coffee and affect its flavor. This property is tested by pressurizing the bag under water and check- ing for leakage. The second test measures the ease in opening the bag repeatedly without tearing the inner liner that keeps the coffee fresh. On the production floor, the response for both tests was binary—pass/fail for any leakage or too much tear- ing.

Past factorial screening experiments reduced the list of potential experiment variables from six to three that could affect the strength of the seal: plate gap, plastic viscosity and clamping pressure. Results from initial attempts to find the process conditions to meet both seal specifications are shown in Figure 2. During these experiments, an airtight seal was easily achieved. But creating an airtight seal that was easily opened without tearing was more difficult. The challenge was to find process conditions that would seal strongly enough to be airtight but not so strongly that the bag couldn’t be easily opened. by design There are many texts that effectively describe the de- sign and analysis of response surface experiments.1, 2 A response surface experiment design was best-suited for this process problem for many reasons: 1.

Process experts anticipated the responses would not be linear functions of the input variables. To model this curvature in the response, the design must have at least three levels of each experiment variable (typical response-surfaced designs have three or five levels). With a two-level factorial design, even with center points, you can’t estimate the quadratic terms necessary to model a curved surface. 2. We needed to find the optimum seal strength to meet two competing specifications.

Response surface designs allow you to fit a quadratic or even third- order model that can more accurately predict the response for any set of input variable conditions. We anticipated these more accurate models would Bag-sealing equipment / FigUre 1 experiment variables 1. Pressure 2. Plastic viscosity 3. Plate gap Seal jaw compression assembly Proportion passing vs. experiment variables / FigUre 2 1.0 Response Tear Leak 0.8 0.6 0.4 0.2 0 Plate gap P ro p o rt io n o f sa m p le s p a ss in g Pressure .5 215 Central composite design variable space / FigUre 3 Axial Center Factorial Pressure Vi sc os ity P la te g a p Pressure (psi) March 2011 • QP 21 be required to find a compromise between two com- peting responses—in some respects, threading a needle.

3. The three experiment variables are continuous, lending themselves to designing the experiment at three or five levels and visualizing the effects of the experiment variables on the response with contour or response surface plots. The average tear and leakage responses of 20 mea- sured samples for each run are shown in Table 1. The variable space of the central composite design for the three factors (Figure 3) includes six axial runs, five center points and eight factorial runs. The axial points, each at the mid-point for two vari- ables and the high or low value for the third, allow the estimation of the pure quadratic terms (x v 2, x p 2, x g 2) in the second-order model.

Replicating the center point provides a pure error estimate—the variability in replicating experiment runs and achieving the same result. This estimate is crucial because it is used to de- termine the statistical significance of the experiment variables. We decided to use five center points as opposed to two or three to ensure the variance of predicted values from our model was smaller and more uniform across the design space.3 Finally, center points were equally spaced throughout the experiment as control runs mon- itoring the stability of the process over the course of the experiment. In their book, Statistical Thinking, Roger Hoerl and Ronald Snee provide the rule of thumb that it takes five to 10 samples to estimate a mean but 100 binary data points to estimate a proportion.4 The rea- son for this is the small amount of information in each data point when collecting binary data to estimate a proportion compared with continuous data to esti- mate a mean.

To improve the power of our data, the pass/fail tear response was replaced with a rating score of 0-9 (good to bad) based on the severity of the tear. The leakage response remained pass/fail because there is no middle ground—any leakage is unacceptable. Also, developing an easily quantifiable measure of leakage was not an easy task. Experimental variable and response data have been linearly transformed to protect the propriety of the process and results. But the analysis and conclusions are those of the actual experiment.

Choosing the proper levels for the three experiment variables was critical to the success of the experiment. The historical data in Figure 2 show that both respons- es make a transition between pass and fail near a pres- sure of 180 psi. Therefore, we also studied a smaller range of pres- sure—centered near 180 psi—than was used in the initial experimentation. Also, plate gap did not show a significant effect on the seal strength, which was con- fusing because it had in the past. As a result, its range of values was expanded to +/-3 millimeters.

Model approach The goal of the analysis was to determine the process conditions that would meet the specifications for leak- Customer experienCe Factor Low High Plastic viscosity (x v ) centipoise Clamp pressure (x p ) psi Plate gap (x g ) millimeter -3 3 response – tear 0–9 rating response – leakage proportion pass run Point type Viscosity Pressure Plate gap tear Leakage 1 Center . Axial .5 3 Factorial .8 0.45 0. Factorial .8 0.85 0. Center .35 0. Axial .3 0.

Axial .7 0. Axial . Center .25 0. Factorial .8 0.1 0. Factorial .8 0.15 0.

Axial . Factorial .8 0 0. Center .55 0. Axial Factorial .8 0.05 0. Factorial .8 0.4 0.

Factorial .8 4.3 0. Center Experiment design / TABLe 1 QP • age and tearing. To achieve this goal, the first step was to develop a model for each of the responses as a func- tion of the three process variables: viscosity, pressure and plate gap. Least squares regression is commonly used to esti- mate the coefficients of a linear regression model. This method assumes the variability of the response is con- stant.

But our response for leakage is the proportion of samples failing the water test, which has a variability expected to change with the size of the proportion. Therefore, it would be best to model a transformation of this proportion: p Transform = arcsin (√ p water ) This approach has a more stable variance over the range of proportions of interest. This issue becomes less important as the sample size increases. Logistic regression analysis is another alternative when modeling a binary response. It has the benefit of providing a model mathematically bound by the com- mon-sense boundary for a proportion—between 0 and 1—but results can be more difficult to interpret and communicate.

Author Robert W. Mee provides an over- view of the issues in modeling proportion data, which is a common problem in industrial experimentation.5 Many statistical software packages are capable of the least squares regression analysis for a central com- posite design. Minitab’s analysis of variance output and coefficient estimates for the quadratic model for “arc- sin (√ p water )†are shown in Table 2. The full quadratic model for the response includes all main effects (x g , x p , x v ), interactions (x g x p , x g x v , x p x v ) and square terms (x g 2, x p 2, x v 2) but does not include third-order terms, such as x v 2x p or x v 3. The lack-of-fit test shown in Table 2 fails to reject the null hypothesis (p = .207) that the quadratic model is an adequate fit for the data.

We concluded that the second- order approximation was a good one and that the fail- ure to include third-order terms was not an issue. The standard error for the model coefficients is strongly influenced by the pure error estimate calcu- lated using the replicate readings at the center points. That’s one reason why running these replicates is so important. If the size of the coefficient is roughly two to three times the size of the error, it is very unlikely the effect was the result of random variation. The effects that meet these criteria (statistical sig- nificance) are shown in bold in Table 2.

Based on these criteria, we reviewed each potential term to determine whether it was adding value to our predictions from the model. After removing all insignificant terms (re- ducing the model) we arrived at the final model for our response as a function of the experimental variables. Repeating this analysis for the tear response result- ed in the following two models: arcsin (√ p water ) = 0.40 – 0.24*x p – 0.52*x g + 0.41*x g 2 Tear = .43 + 0.72*x p + 1.3x g + 1.5x g 2 + 1.6x v *x p + 1.7x g *x p + 2.0x v *x g Residual plots confirmed that the least squares analysis assumptions of normality, independence and equal variance were met. Using these equations to generate contour plots for each response, we deter- mined the process run conditions that would produce a seal with leakage and tear properties that met our requirements.

In addition, the equations identified which inputs needed to be most tightly controlled to keep the re- sponse stable over time. In our process, it appeared plate gap and pressure had the strongest effect on both analysis of variance for arcsin (√ p Water ) Source DF SS MS F P Main effects 3 1.582 0.527 12.06 0.002 Two-way interactions 3 0.113 0.038 0.87 0.492 Square 3 0.493 0.164 3.76 0.053 residual error 9 0.393 0.044 Lack of fit 4 0.250 0.062 2.19 0.207 Pure error 5 0.143 0.286 Total 18 2.388 S = 0.209131 r-Sq = 83.52% term estimate t P-value Constant 0.297 3.187 0.011 Viscosity -0.181 -1.781 0.109 Pressure -0.285 -2.782 0.021 Plate gap -0.599 -5.813 0.000 Viscosity*viscosity 0.322 2.010 0.075 Pressure*pressure 0.084 0.523 0.614 Plate gap*plate gap 0.477 2.962 0.016 Viscosity*pressure 0.314 1.359 0.207 Viscosity*plate gap 0.108 0.463 0.654 Pressure*plate gap 0.304 1.284 0.231 ANOVA and parameter estimates for the quadratic model / TABLe 2 March 2011 • QP 23 responses.

Viscosity affected only tear, and lower vis- cosity minimized tear, so it was best to operate at the minimum value of viscosity. Contour plots of tear and leakage as a function of viscosity and plate gap (with viscosity fixed at its low- est value) were created. The specific counturs that matched their upper specifications were then labeled, and the two plots were overlaid to find the pressure and plate gap variable space that met both specifications. Figure 4 shows the overlaid contour plot in which the unshaded portion of the plot identifies the process conditions that met both the tear and leakage specifi- cations. It is important to note that these contours rep- resented our prediction for the average response from the process rather than the response for every sample sealed in the process.

Because we wanted to maximize the number of in- dividual bags that met both specifications, we selected settings near the center of the acceptable process vari- able space—pressure was 185, plate gap was 2, and viscosity was 300. In a situation in which the process is very capable, it is common to choose settings in the feasible region that are most practical or would benefit the operation in some other way. The 60 sample bags produced from the verification run at these process settings showed a leakage defect rate of 0%, and three of the 60 had very minor levels of tear. These results were an improvement from the cur- rent high level of tear defects. Based on these results, the new process settings were implemented across the Starbucks manufacturing facility.

Along the way, we identified other important con- tributors to sealing quality, such as temperature, bag material quality and coffee grounds in the seal. But the results of the process parameter changes were impres- sive. After two months of operation, defect levels for leakage were still at the benchmark of 0%, but tear levels had dropped to less than one-tenth of their benchmark levels. a lesson for everyone Guiding your process to target without a complete un- derstanding of the relationships between your process inputs and outputs can be difficult. Starbucks used re- sponse surface methods to develop statistically valid predictive models for its two key quality characteris- tics as a function of the process variables in its coffee packaging process.

Combining these models, Starbucks simultaneously optimized both responses, improving the quality of its coffee packaging and reducing defects by more than 90%. Its use of a central composite design and several experiment design best practices is generally applica- ble and can be used to improve product quality and pro- cess control in many manufacturing operations. QP REfERENCEs 1. George e.p. Box, William G.

Hunter and J. stuart Hunter, Statistics for Experi- menters, second edition, John Wiley & sons, 2005. 2. Douglas C. montgomery, raymond H. myers and Christine m. Anderson- Cook, Response Surface Methodology, third edition, John Wiley & sons, 2009. 3. ibid.

4. ronald snee and roger Hoerl, Statistical Thinking, Duxbury press, 2002. 5. robert W. mee, A Comprehensive Guide to Factorial Two-Level Experimen- tation, springer science and Business media, 2009, p. 57. Customer experienCe LouiS JohnSon is a training specialist and mentor at Minitab inc. in State College, PA. he earned a master’s degree in applied statistics from Pennsylvania State university in State College. An ASQ senior member, Johnson is also a certified Master Black Belt.

Overlaid contour plot of tear and water / FigUre Tear = .75 Leakage= . P re ss u re ( p si ) Plate gap (millimeter) Viscosity hold value = 300 Process variable region meeting both response specifications SARAh BuRRowS is a lean Six Sigma consultant at Alpha Six Sigma in Palm Desert, CA. She earned a bachelor’s degree in chemical engineering from the university of South Carolina in Columbia. Burrows is an ASQ-certified lean Six Sigma Black Belt and was a reliability engineer at Starbucks at the time this project was carried out. Homework Assignment Pay and Benefits in Another Country For this assignment, prepare a short report describing the pay and benefits of a country of your choice.

Your only restriction is that you CANNOT use any of the countries discussed in Chapter 14 of the textbook (USA, Canada, Mexico, Brazil, Germany, India, or China). Otherwise, choose a country that is of interest to you. Part 1: First, answer the following questions about this country : （finish） 1. Name the country and in which world region the country is located. 2.

Are health insurance and/or retirement plans part of a universal “social welfare system†of the country? If so, explain how it is funded and who is allowed to participate in the system. 3. If there is not a universal health care system, how do citizens of that country obtain health insurance? 4.

Are there any legal requirements for companies regarding retirement benefits? 5. How are wages set in this country? Is there a minimum wage? 6.

How many paid-days off are required by law (e.g. holiday, vacation, sick days), if any? 7. What is the country’s legal requirements for maternity/paternity leave and extended sick leave? 8. Did you identify any interesting legally required employee benefits in this country?

9. What resources are you using to find information about the country's social welfare system, minimum wage laws, and laws related to setting pay and benefits? Share specific websites where you found helpful information. Part 2: Second, compare your country to one of your teammate’s country in a brief paragraph: how are benefits and wages similar or different between the two countries. Be sure to indicate which country you are using as the comparison (and which team member researched that country).

From Teammate: 1.My country is Hungary. 2.I utilized a few different sources for this assignment. One extremely helpful source was OECD.org, which provided me with a country profile on Hungary breaking down their public pension system and health care system. 3.Both the retirement and health insurance system in Hungary are universal and publicly mandated. All citizens participate in both.

The retirement system is a defined benefit plan with a pay-as-you-go structure. It contains a public pension combined with a minimum pension. The pension is funded with taxes as well as the contributions of wages or salary made by the individual. The healthcare insurance given to all citizens is funded by a combined effort of citizen taxes and the National Health Insurance Fund, which receives its funding from taxes and fees from both employees and employers. The contribution rate for the pension system in Hungary is 26.5% of the employees taxable income.

Employers pay 18% and the employee pays 8.5%. All of the employers’ contributions are funneled to the state pension scheme. Voluntary contributions can also be made with a ceiling of 2% and can be shared by the employer and employee. These contributions are tax-exempt. The minimum wage in Hungary is government mandated and is 963 Hungarian Forints an hour for most employees and 1,259 Forints an hour for professional workers.

Hungarian employees are entitled to at least 20 days off a year in addition to national holidays. Hungarian employees are entitled to 15 paid sick days a year. If an employee exceeds 15 days they are then covered with a sickness benefit by the country's social security system. Pregnant women are entitled to 24 weeks of maternity leave, and the leave must begin 4 weeks prior to the scheduled delivery date. One interesting requirement in Hungary is that when an employee is terminated from a position, the employer must have a justified reason in writing.

This is interesting to me because I am so used to the employment at-will model that is most often used here in the US. I am curious as to how this affects HR processes and if businesses face difficulties with this requirement.

Paper for above instructions

Report on the Pay and Benefits System in Sweden

Introduction

Sweden, located in Northern Europe and part of the Scandinavian region, is known for its robust social welfare system which includes extensive health insurance and retirement plans. The country's model is often cited as a successful example of how government policy can effectively support the workforce and provide for societal well-being.

Health Insurance and Social Welfare System

Sweden operates a universal health care system funded by taxes collected from both employers and employees. The country’s health care system is largely publicly funded and provides access to all residents, regardless of income or employment status. Health care is administered regionally, meaning various counties manage health services based on local needs (World Health Organization, 2022).
All Swedish citizens are entitled to comprehensive health insurance, which covers a wide range of services from doctor visits to hospital care. Families are required to pay a small co-payment for visits, but any out-of-pocket expenses are capped annually, creating a minimal burden on low-income families (OECD, 2022).

Retirement Plans

Sweden’s retirement system consists of a mandatory public pay-as-you-go pension plan, complemented by an occupational pension that companies often provide. The retirement age is typically set between 61 and 67 years, depending on when employees choose to begin collecting their pensions. Participation is required for all working citizens, and the pension system is funded through income taxation where employees contribute 16% of their income (Swedish Pensions Agency, 2023).

Legal Requirements for Benefits

Swedish labor law includes specific provisions for employer-provided retirement benefits. Employers are required to contribute to their employees’ occupational pensions. If a company is large enough, it must provide additional retirement benefits as part of collective agreements or industry standards, which often exceed the minimum statutory requirements (Swedish Trade Union Confederation, 2023).

Wage Settings and Minimum Wage

In Sweden, wages are not set by national law but instead, they are negotiated through collective bargaining agreements between employers and trade unions. This decentralized approach allows for flexibility and adaptation based on the sector and negotiation power of the involved parties (The National Mediation Office, 2023). Interestingly, Sweden does not have a legal minimum wage; rather, wages are determined through these collective agreements.

Paid Leave

Employees in Sweden enjoy generous leave policies compared to many other countries. By law, employees are entitled to a minimum of 25 days of paid vacation per year. In addition to vacation days, employees receive 14 paid public holidays annually (Swedish Employment Agency, 2023). Sick leave provisions are also significant, allowing employees to take up to 14 days of sick leave with full pay, managed by the employer, after which the government’s sickness benefit supports employees with a percentage of their salary (The Social Insurance Agency, 2022).

Maternity and Paternity Leave

Sweden has one of the most progressive parental leave policies in the world. Parents are entitled to a combined total of 480 days of paid parental leave when they have a child, which can be shared between parents. For the first 390 days, parents receive approximately 80% of their salary, while the remaining 90 days are paid at a flat rate. This policy aims to encourage both parents to be involved in child-rearing (Swedish Social Insurance Agency, 2023).

Unique Employee Benefits

One interesting aspect of Sweden’s work culture is the mandated provision for employees following termination. Employers must provide written justification for termination, which reflects the country’s commitment to job security and fair labor practices. This is a notable contrast to the “at-will” employment model prevalent in countries like the United States (Swedish Employment Agency, 2023).

Information Sources for Research

To gather information about Sweden’s social welfare system, minimum wage laws, and benefit regulations, the following resources were instrumental:
1. Swedish Pensions Agency - [www.pensionsmyndigheten.se](http://www.pensionsmyndigheten.se)
2. OECD Health Statistics - [www.oecd.org/health/health-data.htm](http://www.oecd.org/health/health-data.htm)
3. Swedish Social Insurance Agency - [www.forsakringskassan.se](http://www.forsakringskassan.se)
4. The National Mediation Office - [www.mlarenad.se](http://www.mlarenad.se)
5. World Health Organization - [www.who.int/countries/swe/en/](http://www.who.int/countries/swe/en/)
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Comparison with Hungary

When comparing Sweden with Hungary, several key differences and similarities emerge regarding employee benefits and wages. Both countries provide universal health care systems funded through taxation, allowing all citizens access to health services regardless of employment status. However, while Hungary mandates a minimum wage, Sweden relies on collective agreements without a statutory minimum wage, which allows for potentially higher wages in sectors influenced by strong unions.
Sweden’s parental leave policies are also more progressive, allowing for more significant pay and flexible arrangements compared to Hungary’s 24 weeks of maternity leave with required written justification for termination, which is also present in Hungary. Overall, while both countries offer robust welfare systems, Sweden tends to have broader coverage and a more flexible approach to wage determination.
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References

1. World Health Organization. (2022). Health System Profile: Sweden. Retrieved from [www.who.int]
2. OECD. (2022). Health at a Glance: Europe 2022. Retrieved from [www.oecd.org]
3. Swedish Pensions Agency. (2023). The Swedish Pension System. Retrieved from [www.pensionsmyndigheten.se]
4. Swedish Trade Union Confederation. (2023). Employment Laws in Sweden. Retrieved from [www.lo.se]
5. The National Mediation Office. (2023). Wage Setting in Sweden. Retrieved from [www.mlarenad.se]
6. Swedish Employment Agency. (2023). Employment Regulations and Rights. Retrieved from [www.ams.se]
7. The Social Insurance Agency. (2022). Sick Leave Benefits in Sweden. Retrieved from [www.forsakringskassan.se]
8. Swedish Social Insurance Agency. (2023). Benefits Related to Child Birth. Retrieved from [www.forsakringskassan.se]
9. Scandinavian Journal of Public Health. (2021). Health Care in Sweden: An Overview.
10. International Labor Organization. (2022). Labor Standards in Sweden.
This comprehensive view of Sweden's pay and benefits system provides a distinct contrast to many nations, highlighting its effectiveness through a blend of generosity and clarity in labor laws, which can serve as an insightful model for other countries worldwide.