by Jennifer Hart Yim | May 14, 2015 | Blog, Strategy, Supply Chain
This article is part of a series of articles written by MBA students and graduates from the University of New Hampshire Peter T. Paul College of Business and Economics.
Sarah Hebert is currently a full-time MBA student at the University of New Hampshire, having previously completed her Bachelor’s of English Language and Literature at the same institution in 2014. Following the completion of her Master’s degree, she hopes to find a job in Marketing and Advertising.
When “Food with Integrity”meets the bottom-line.
As Chipotle’s nation-wide gastronomic success has propelled their brand into the fast-casual limelight, so followed the news of their carnitas crisis, as the chain announced in January 2015 that they were and would be experiencing a significant strain in their Responsibly Raised® Pork supply for the foreseeable future.
Chipotle®, a Mexican fast-casual restaurant chain that has built its brand on self-established food quality standards, such as organic, local vegetables and ethically raised animals, made waves with their voluntary decision to cut their pork supply due to a supplier violation of their animal welfare standards. As stated by the chain, pigs living within these pork farms must be:
- Raised with outdoor access or deeply bedded pens
- Free of breeding, gestation, and farrowing crates
- Never treated with antibiotics
Upon discovering that this particular supplier did not allow their animals to have outdoor access and did not supply the alternative pens that were required under those conditions, Chipotle immediately ceased their business with the farm in question. As a result, 1/3 of their chain-wide supply was eliminated, directly affecting the 7-8% of total sales that are accounted for by their pork-consuming customers.
Rather than keeping mum about this potentially destructive development, Chipotle defied expectations and proactively embraced this supply-chain debacle as a strategic PR opportunity, fully acknowledging their decision and citing their core values as their motive. On the front end of their business, Chipotle addressed this issue across all channels—attention grabbing signage on storefronts, disclaimers at the launch of their online ordering services, an FAQ page on their website solely dedicated to their carnitas shortage, and countless press releases provided to news sources across the country.
On the back end, the chain exercised several strategies to try to compensate for the consequences of their actions. In a short-term attempt to alleviate the additional, compensatory pressures faced by their remaining pork suppliers and to satisfy pork-consuming customers where possible, Chipotle chose to geographically rotate their carnitas supplies around the country every 6 weeks. Realizing that their characteristically high standards for food sourcing would continue to be tested as the chain continues to grow at an astronomical pace (currently operating approximately 1800 locations nation-wide), Chipotle wasted no time to begin addressing their long-term supply concerns, exploring solutions such as acquiring additional suppliers, integrating new cuts of pork into their carnitas option, and feasibly increasing the amount of meat secured from their current providers in order to best insulate themselves from future supply constraints.
Since their notorious announcement back in January, it is estimated the Chipotle’s decision to stand by their ethically-poised brand and diminish their supplies volume will cost them nearly a year of operating at full capacity, projecting that the chain’s shortage will not completely recover until the end of Q4. Translation? No carnitas until December 2015. At the conclusion of the first quarter of 2015, Chipotle fell 1.3% short of their projected 11.7% sales growth put forth by Wall Street, achieving a growth rate of only 10.4% total.
Despite Chipotle’s applaud-worthy success at capitalizing on this marketing opportunity by means of reinforcing their “Food with Integrity” adage and raising awareness for animal welfare, the question shifts from a concern regarding their recovery timeline to one of sustainability and future growth. As the chain continues to mature and prosper, are their sourcing practices and business model sustainable? At what point do you scale back your growth for the sake of maintaining your brand integrity, or to better meet your demand with an already constrained supply? While the admirable decision made by the chain played nicely into the hands of their marketing and public relations teams, one has to wonder about how these decisions may jeopardize the future of their consumer dependability–ultimately, at what cost is your pride more important than your profits?
To say that Chipotle turned the tides on their self-inflicted disaster would be an understatement—more than ever, the chain is being commended for their devotion to their ethical standards and continues to gain national attention for their damage control tactics. As the problem has yet to be completely rectified and the light is still being brightly shone on Chipotle’s radical supply-chain stance, the eyes of the consumers remain locked on the positive statement being made in the here and now. After the storm passes and carnitas are back in the hands of Chipotle customers, the reliability and sustainability of their sourcing practices will undoubtedly come into question. With growth of business comes increased demand, and as the company has yet to establish a long-term supply solution for its Responsibly Raised meats, it’s certainly not irrational to wonder if the fast-casual kingpin will be as lucky to weather the storm the next time around.
by Jennifer Hart Yim | May 14, 2015 | Blog, Strategy, Supply Chain
This article is part of a series of articles written by MBA students and graduates from the University of New Hampshire Peter T. Paul College of Business and Economics.
Sarah Hebert is currently a full-time MBA student at the University of New Hampshire, having previously completed her Bachelor’s of English Language and Literature at the same institution in 2014. Following the completion of her Master’s degree, she hopes to find a job in Marketing and Advertising.
When “Food with Integrity”meets the bottom-line.
As Chipotle’s nation-wide gastronomic success has propelled their brand into the fast-casual limelight, so followed the news of their carnitas crisis, as the chain announced in January 2015 that they were and would be experiencing a significant strain in their Responsibly Raised® Pork supply for the foreseeable future.
Chipotle®, a Mexican fast-casual restaurant chain that has built its brand on self-established food quality standards, such as organic, local vegetables and ethically raised animals, made waves with their voluntary decision to cut their pork supply due to a supplier violation of their animal welfare standards. As stated by the chain, pigs living within these pork farms must be:
- Raised with outdoor access or deeply bedded pens
- Free of breeding, gestation, and farrowing crates
- Never treated with antibiotics
Upon discovering that this particular supplier did not allow their animals to have outdoor access and did not supply the alternative pens that were required under those conditions, Chipotle immediately ceased their business with the farm in question. As a result, 1/3 of their chain-wide supply was eliminated, directly affecting the 7-8% of total sales that are accounted for by their pork-consuming customers.
Rather than keeping mum about this potentially destructive development, Chipotle defied expectations and proactively embraced this supply-chain debacle as a strategic PR opportunity, fully acknowledging their decision and citing their core values as their motive. On the front end of their business, Chipotle addressed this issue across all channels—attention grabbing signage on storefronts, disclaimers at the launch of their online ordering services, an FAQ page on their website solely dedicated to their carnitas shortage, and countless press releases provided to news sources across the country.
On the back end, the chain exercised several strategies to try to compensate for the consequences of their actions. In a short-term attempt to alleviate the additional, compensatory pressures faced by their remaining pork suppliers and to satisfy pork-consuming customers where possible, Chipotle chose to geographically rotate their carnitas supplies around the country every 6 weeks. Realizing that their characteristically high standards for food sourcing would continue to be tested as the chain continues to grow at an astronomical pace (currently operating approximately 1800 locations nation-wide), Chipotle wasted no time to begin addressing their long-term supply concerns, exploring solutions such as acquiring additional suppliers, integrating new cuts of pork into their carnitas option, and feasibly increasing the amount of meat secured from their current providers in order to best insulate themselves from future supply constraints.
Since their notorious announcement back in January, it is estimated the Chipotle’s decision to stand by their ethically-poised brand and diminish their supplies volume will cost them nearly a year of operating at full capacity, projecting that the chain’s shortage will not completely recover until the end of Q4. Translation? No carnitas until December 2015. At the conclusion of the first quarter of 2015, Chipotle fell 1.3% short of their projected 11.7% sales growth put forth by Wall Street, achieving a growth rate of only 10.4% total.
Despite Chipotle’s applaud-worthy success at capitalizing on this marketing opportunity by means of reinforcing their “Food with Integrity” adage and raising awareness for animal welfare, the question shifts from a concern regarding their recovery timeline to one of sustainability and future growth. As the chain continues to mature and prosper, are their sourcing practices and business model sustainable? At what point do you scale back your growth for the sake of maintaining your brand integrity, or to better meet your demand with an already constrained supply? While the admirable decision made by the chain played nicely into the hands of their marketing and public relations teams, one has to wonder about how these decisions may jeopardize the future of their consumer dependability–ultimately, at what cost is your pride more important than your profits?
To say that Chipotle turned the tides on their self-inflicted disaster would be an understatement—more than ever, the chain is being commended for their devotion to their ethical standards and continues to gain national attention for their damage control tactics. As the problem has yet to be completely rectified and the light is still being brightly shone on Chipotle’s radical supply-chain stance, the eyes of the consumers remain locked on the positive statement being made in the here and now. After the storm passes and carnitas are back in the hands of Chipotle customers, the reliability and sustainability of their sourcing practices will undoubtedly come into question. With growth of business comes increased demand, and as the company has yet to establish a long-term supply solution for its Responsibly Raised meats, it’s certainly not irrational to wonder if the fast-casual kingpin will be as lucky to weather the storm the next time around.
by Jennifer Hart Yim | May 13, 2015 | Blog, Leadership, Strategy, Supply Chain
This article is part of a series of articles written by MBA students and graduates from the University of New Hampshire Peter T. Paul College of Business and Economics.
Corey Ducharme is Green Belt Certified in Six Sigma. He has a BA in Business and is currently in the MBA program at the University of New Hampshire. He has consulted at major corporations including Johnson & Johnson, Universal Studios, Sony Pictures, Oklahoma Oil & Gas, and Suncor as a management consultant at D&A Management. He can be reached via e-mail.
We all use Six Sigma problem solving whether we know it or not
How do humans tend to solve problems? Consciously or unconsciously humans use a four-step method that is defined as:
Table 1: Traditional Problem Solving Process
In the above example, the root cause is identified – exercise and eating less equals losing weight – and verified. The conventional wisdom is proven true and there is little need to consider a more robust or analytical method. Most humans solve their day-to-day issues in this manner whether consciously or unconsciously. My root-cause analysis in this case (I exercise and eat less) is verified by the fact that I lost ten pounds and sustainable until my goal is achieved. (Losing 20 pounds).
Six Sigma Problem Solving 
What if the root-cause lies outside of conventional wisdom or is difficult to determine?
These needle-in-a-haystack problems – due to limited business resources – cause businesses to lose revenue and lead to process failures, poor quality, and poor customer service. These types of problems are at the heart of Six Sigma Problem Solving and are a way to find the needle-in-the-haystack.
The Six Sigma methodology is based on the DMAIC process and using our weight loss example we begin to see the similarities between the two methods.
- Define Phase: What is the problem and set the end goal.
- Measure Phase: What is the current state?
- Analyze Phase: 1. Develop cause-and-effect analysis of problem. What are the real causes and prove cause and effect links.
- Improve Phase: Action
- Control Phase: 1. Verify improvement and 2. Sustainability
What differs between the phases of conventional and Six Sigma problem solving begins in the Analyze Phase. Six Sigma methodology demands the proof of cause be determined before a clear course of action is taken. The proof of cause must be data-driven as root-cause analysis is at the core of Six Sigma problem solving. It is also the reason that the Analyze phase is divided into the development of cause-effects and proof of cause-effect links.
The second difference is in the fifth phase. In the Traditional problem-solving methodology, verification comes in the form of losing weight. I can prove it by weighing myself. In Six Sigma problem solving, a two-step process is needed. Verification is essential (Did I improve?) and if so, a plan to sustain our gains is created. This is not necessary in a Traditional methodology because our cause-effect is proven (exercise/eat less = weight loss); however, in the Six Sigma methodology our cause-effect must be tested and verified.
The Linguistics of Six Sigma: Y=f(X)
To speak in the language of Six Sigma, we need to change ‘problem’ with ‘Y’ and ‘cause’ with ‘X’. The Y is the output and the X(s) are any inputs that are involved in producing the output. In other words, the Y = 100% customer satisfaction and X(s) are the variables that affect the level of customer satisfaction. For more, click the following link: Y=f(X).
Using Six Sigma linguistics and the DMAIC process, we can combine the Traditional problem solving steps in Table 1 and we see that our four-step process has become a more robust seven-step process. We can now use DMAIC to ask ourselves the most essential question:
If our root-cause analysis is discovered and proven true, then can the problem be solved or reduced by controlling or removing the cause(s)?
Table 2: DMAIC Problem Solving
Real World Example: Boeing
Boeing’s Six Sigma team in Everett, WA discovered that root cause analysis is often like finding a needle-in-a-haystack, especially for the maker of the world’s largest commercial twin-engine airplane with millions of components. (To read the entire story, click the following link: Problem-solving approach helps team pinpoint solution). Boeing discovered that recirculating air fans were being rejected during production, costing Boeing money in waste, removal, testing, and cost of replacing the component.
Boeing assembled a cross-functional ‘detective squad’ that included employees from Engineering, Quality, Manufacturing, Supply Management, Procurement, and their supplier Hamilton Sundstrand who began the problem-solving techniques of the DMAIC process by examining data from the fans and beginning root-cause analysis.
This analysis determined that Foreign Object Debris (FOD) damaged the fans and the test tools. Job done, right? Not according to Kent Kuiper, Six Sigma expert at Boeing, the team had to dig deeper. “For example,” he said, “when we found that FOD was a problem and determined the source for it, removing the FOD and replacing the fan wasn’t going to get us where we needed to go. We had to figure out a way to keep the FOD from happening again.”
Further inspection led the team to discover failures in ductwork caps and plastic sheeting – two items ironically intended to prevent FOD damage and two electrical issues. One failure of improperly modified test equipment and the second issue related to crimping procedures in manufacturing process that improved connections in the fans. The results? Although the FOD in the fans was the main X, the results were clear. “After 18 fan failures in two years, we went four and a half months without a rejection,” said Max Limb, a supplier field service representative. “We haven’t completely eliminated the rejections, but we’re close.”
“Our team has become well-versed in the concept of Six Sigma,” said Valerie Feiberti, Supply Management and Procurement Director of the Lean Promotion Team. “We feel very strongly that it provides a way to correct production-related problems and proactively design-in quality.”
Summary
The DMAIC methodology is essentially a series of common sense questions to determine root-cause analysis, identification of X(s), elimination of problems, and maintaining of gains. The DMAIC process asks the following questions:
- Define: What is the Y that is performing poorly?
- Measure: What is Y’s current performance?
- Analyze: What are the X(s)? Are they real?
- Improve: How can X(s) be controlled/eliminated?
- Control: How can X(s) be controlled to sustain gains in Y?
Six Sigma problem solving is the data-driven representation of the conscious or unconscious thinking we use to solve problems in our lives and can be used to solve may needle-in-a-haystack problems that vex businesses.
by Jennifer Hart Yim | May 13, 2015 | Blog, Leadership, Strategy, Supply Chain
This article is part of a series of articles written by MBA students and graduates from the University of New Hampshire Peter T. Paul College of Business and Economics.
Corey Ducharme is Green Belt Certified in Six Sigma. He has a BA in Business and is currently in the MBA program at the University of New Hampshire. He has consulted at major corporations including Johnson & Johnson, Universal Studios, Sony Pictures, Oklahoma Oil & Gas, and Suncor as a management consultant at D&A Management. He can be reached via e-mail.
We all use Six Sigma problem solving whether we know it or not
How do humans tend to solve problems? Consciously or unconsciously humans use a four-step method that is defined as:
Table 1: Traditional Problem Solving Process
In the above example, the root cause is identified – exercise and eating less equals losing weight – and verified. The conventional wisdom is proven true and there is little need to consider a more robust or analytical method. Most humans solve their day-to-day issues in this manner whether consciously or unconsciously. My root-cause analysis in this case (I exercise and eat less) is verified by the fact that I lost ten pounds and sustainable until my goal is achieved. (Losing 20 pounds).
Six Sigma Problem Solving
What if the root-cause lies outside of conventional wisdom or is difficult to determine?
These needle-in-a-haystack problems – due to limited business resources – cause businesses to lose revenue and lead to process failures, poor quality, and poor customer service. These types of problems are at the heart of Six Sigma Problem Solving and are a way to find the needle-in-the-haystack.
The Six Sigma methodology is based on the DMAIC process and using our weight loss example we begin to see the similarities between the two methods.
- Define Phase: What is the problem and set the end goal.
- Measure Phase: What is the current state?
- Analyze Phase: 1. Develop cause-and-effect analysis of problem. What are the real causes and prove cause and effect links.
- Improve Phase: Action
- Control Phase: 1. Verify improvement and 2. Sustainability
What differs between the phases of conventional and Six Sigma problem solving begins in the Analyze Phase. Six Sigma methodology demands the proof of cause be determined before a clear course of action is taken. The proof of cause must be data-driven as root-cause analysis is at the core of Six Sigma problem solving. It is also the reason that the Analyze phase is divided into the development of cause-effects and proof of cause-effect links.
The second difference is in the fifth phase. In the Traditional problem-solving methodology, verification comes in the form of losing weight. I can prove it by weighing myself. In Six Sigma problem solving, a two-step process is needed. Verification is essential (Did I improve?) and if so, a plan to sustain our gains is created. This is not necessary in a Traditional methodology because our cause-effect is proven (exercise/eat less = weight loss); however, in the Six Sigma methodology our cause-effect must be tested and verified.
The Linguistics of Six Sigma: Y=f(X)
To speak in the language of Six Sigma, we need to change ‘problem’ with ‘Y’ and ‘cause’ with ‘X’. The Y is the output and the X(s) are any inputs that are involved in producing the output. In other words, the Y = 100% customer satisfaction and X(s) are the variables that affect the level of customer satisfaction. For more, click the following link: Y=f(X).
Using Six Sigma linguistics and the DMAIC process, we can combine the Traditional problem solving steps in Table 1 and we see that our four-step process has become a more robust seven-step process. We can now use DMAIC to ask ourselves the most essential question:
If our root-cause analysis is discovered and proven true, then can the problem be solved or reduced by controlling or removing the cause(s)?
Table 2: DMAIC Problem Solving
Real World Example: Boeing
Boeing’s Six Sigma team in Everett, WA discovered that root cause analysis is often like finding a needle-in-a-haystack, especially for the maker of the world’s largest commercial twin-engine airplane with millions of components. (To read the entire story, click the following link: Problem-solving approach helps team pinpoint solution). Boeing discovered that recirculating air fans were being rejected during production, costing Boeing money in waste, removal, testing, and cost of replacing the component.
Boeing assembled a cross-functional ‘detective squad’ that included employees from Engineering, Quality, Manufacturing, Supply Management, Procurement, and their supplier Hamilton Sundstrand who began the problem-solving techniques of the DMAIC process by examining data from the fans and beginning root-cause analysis.
This analysis determined that Foreign Object Debris (FOD) damaged the fans and the test tools. Job done, right? Not according to Kent Kuiper, Six Sigma expert at Boeing, the team had to dig deeper. “For example,” he said, “when we found that FOD was a problem and determined the source for it, removing the FOD and replacing the fan wasn’t going to get us where we needed to go. We had to figure out a way to keep the FOD from happening again.”
Further inspection led the team to discover failures in ductwork caps and plastic sheeting – two items ironically intended to prevent FOD damage and two electrical issues. One failure of improperly modified test equipment and the second issue related to crimping procedures in manufacturing process that improved connections in the fans. The results? Although the FOD in the fans was the main X, the results were clear. “After 18 fan failures in two years, we went four and a half months without a rejection,” said Max Limb, a supplier field service representative. “We haven’t completely eliminated the rejections, but we’re close.”
“Our team has become well-versed in the concept of Six Sigma,” said Valerie Feiberti, Supply Management and Procurement Director of the Lean Promotion Team. “We feel very strongly that it provides a way to correct production-related problems and proactively design-in quality.”
Summary
The DMAIC methodology is essentially a series of common sense questions to determine root-cause analysis, identification of X(s), elimination of problems, and maintaining of gains. The DMAIC process asks the following questions:
- Define: What is the Y that is performing poorly?
- Measure: What is Y’s current performance?
- Analyze: What are the X(s)? Are they real?
- Improve: How can X(s) be controlled/eliminated?
- Control: How can X(s) be controlled to sustain gains in Y?
Six Sigma problem solving is the data-driven representation of the conscious or unconscious thinking we use to solve problems in our lives and can be used to solve may needle-in-a-haystack problems that vex businesses.
by Jennifer Hart Yim | May 12, 2015 | Big Data, Blog, Data/Analytics, Strategy
This article is part of a series of articles written by MBA students and graduates from the University of New Hampshire Peter T. Paul College of Business and Economics.
Josh Hutchins received his B.S. in Business Administration from the University of New Hampshire in 2005. He is currently pursuing his MBA at the Peter T. Paul School at the University of New Hampshire; on course to graduate in May 2016.
“Working with data is something I do every day as a financial analyst. I enjoy crunching the data and experimenting with various data analytic techniques. I’ve found that my love for playing with the data and thinking in unconventional ways has led me to be efficient and successful at work. The way data is being used is revolutionizing the way we do business. I’m glad I can be part of this wave of the future.”
The responsibility of big data
Data is coming into businesses at incredible speeds, in large quantities, and in all types of different formats. In a world full of big data it’s not just having the data – it’s what you do with it that matters. Big data analysis is becoming a very powerful tool used by companies of all sizes. Companies are analyzing and using the data in order to create sustainable business models and gain a competitive advantage over their competition. However, as one company would come to learn – with big data comes big responsibility.
Solid Gold Bomb T-Shirt Company
In 2011, Solid Gold Bomb, an Amazon Marketplace merchant based out of Australia, thought of an ingenious way to create fresh slogans for t-shirts. The main concept behind Solid Gold Bomb’s operation was that by utilizing a computer programming script, they could create clever t-shirt slogans that no one had thought of previously. The company created various t-shirt slogans that played off of the popular British WWII era phrase Keep Calm and Carry On. Under the systematic script method, Solid Gold Bombs was able to create literally millions of t-shirt offerings without the need to have them on hand in inventory. With the substantial increase in product offerings, the chances of customers stumbling upon a Solid Gold Bomb shirt increased dramatically. By utilizing this new on-demand approach to t-shirt printing, Solid Gold Bomb was able to reduce expenses, while simultaneously increasing potential revenue by offering exponential products at little additional marginal cost.
Use of ‘Big Data’
The computer script relied on the following to operate: a large pool of words, associated rule learning, and an algorithm.
Large Pool of Words – Solid Gold Bomb gathered a list of approximately 202,000 words that could be found in the dictionary. Of these words, they whittled it down to approximately 1,100 of the most popular words. Some of the words were too long to be included on a t-shirt, so the list was further culled. They settled on 700 different verbs and corresponding pronouns. These words would be used by the computer script to generate t-shirt slogans.
Associated rule learning – Associated rule learning is the degree to which two variables in a given list relate to each other. The first step in associated rule learning is to identify and isolate the most frequent variables. The second step is forming rules based on different constraints on the variables – assigning an “interestingness” factor. In the case of Solid Gold Bomb, the associated rule learning assigned an interestingness factor to verb-pronoun combinations.
Algorithm – The algorithm designed by Solid Gold Bomb was very simple. Each shirt would begin with “Keep calm and”. The algorithm script would then search through the word pool and pull back the most highly associated verb and pronoun combinations. The words would then be put into the typical format of the Keep Calm and Carry On. An image of each individual combination would be mocked up and posted to their Amazon merchant account. The process would continuously loop, creating millions of combinations.
The Big Data Blues
With one innocent mistake, Solid Gold Bomb fell apart in the blink of an eye. Amazon started getting complaints about offensive slogans on Solid Gold Bomb’s t-shirts. Images of t-shirts with phrases such as “Keep Calm and Rape Her” and “Keep Calm and Hit Her” were being sold on their Amazon merchant account. Their typical weekend orders for around 800 shirts were reduced to just 3 – few enough to count on one hand. Amazon ended up pulling their entire line of clothing, essentially putting Solid Gold Bomb out of business.
What went wrong?
While Solid Gold Bomb had a good handle on how to use data that they had gathered and how to use it to their advantage, they neglected to consider the potential hidden consequences of unintentional misuse of the data. When culling 202,000 words down to 700 useable words, words such as “rape” should have been eliminated from the useable word pool. From a high level perspective, the human mind is incapable of naming all the potential combinations of the 700 useable words without the assistance of a computer program. However, the end user needs to be aware that the computer program logic will create every potential combination based on the word pool.
Moral of the Story
Big data by itself is not beneficial to a company. The real value is in the analytics that are applied to the data. The results of the analytics can be utilized in numerous ways – to make more informed decisions, create new revenue streams, and create competitive advantages, to name a few. When a company makes the decision to utilize big data analytics, each process needs to be mapped out to have an intimate understanding of how the data will be used. In the case of Solid Gold Bomb, they failed to have this intimate understanding of how the data would be used throughout the process. As a result, they paid the ultimate price; they were not able to sustain themselves through this debacle. The morale of the story: With big data comes big responsibility. Know your data and know the potential uses of the data better. Don’t be afraid to think outside the box, but know the potential consequences.
For information about another big data faux pas, learn how Target predicted that a 16 year old girl was pregnant before her father knew.
