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.
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.
by Fronetics | Oct 2, 2014 | Big Data, Blog, Data/Analytics, Strategy, Supply Chain
Big data is big. It is revolutionary. It is transformative. But what the heck is it?
MIT’s Technology Review does a great job of outlining the hype and the confusion around big data:
“There is unanimous agreement that big data is revolutionizing commerce in the 21st century. When it comes to business, big data offers unprecedented insight, improved decision-making, and untapped sources of profit.
And yet ask a chief technology officer to define big data and he or she will stare at the floor. Chances are, you will get as many definitions as the number of people you ask. And that’s a problem for anyone attempting to buy or sell or use big data services—what exactly is on offer?”
Research conducted by Accenture highlights this dichotomy. Eight-nine percent of survey respondents reported that they believe big data will revolutionize business operations in the same way that the Internet did. Seventy-nine percent of respondents reported that “companies that do not embrace big data will lose their competitive position and may face extinction.” However, the research found that companies hold “differing views of data sources and uses,” and that “valuable data sources are omitted or overlooked.”
Big data and the supply chain
Accenture’s Global Operations Megatrends research looked at big data analytics in the supply chain. Ninety-seven percent of supply chain executive reported that big data analytics can benefit their supply chain. Their expectations for big data analytics include: creating an organizational ability to react more quickly to changes (48 percent); helping their company gain insights about the future (45 percent); and achieving a cross-functional view of the supply chain with the objective of optimizing overall supply chain performance (43 percent).
Although the majority of executives believe big data analytics will benefit their supply chain only 17 percent of survey respondents reported that their company has already implemented analytics in one or more supply chain processes/functions. Accenture makes this supposition:
“While there is considerable hype about, and a high level of general awareness of the value of, ‘big data,’ many companies still do not fully understand how to apply analytics to this data to drive higher supply chain (and overall enterprise) performance.”
Given Accenture’s research, as well as that conducted by Jonathan Stuart Ward and Adam Barker at the University of St Andrews in Scotland, I’d take this one step further. In spite of the hype (or perhaps because of it) there remains confusion regarding what big data actually is. Without a clear definition and understanding of big data, it is (and will continue to be) a challenge to implement big data analytics. Before we realize transformation we need to get to understanding.
by Fronetics | Oct 2, 2014 | Big Data, Blog, Data/Analytics, Strategy, Supply Chain
Big data is big. It is revolutionary. It is transformative. But what the heck is it?
MIT’s Technology Review does a great job of outlining the hype and the confusion around big data:
“There is unanimous agreement that big data is revolutionizing commerce in the 21st century. When it comes to business, big data offers unprecedented insight, improved decision-making, and untapped sources of profit.
And yet ask a chief technology officer to define big data and he or she will stare at the floor. Chances are, you will get as many definitions as the number of people you ask. And that’s a problem for anyone attempting to buy or sell or use big data services—what exactly is on offer?”
Research conducted by Accenture highlights this dichotomy. Eight-nine percent of survey respondents reported that they believe big data will revolutionize business operations in the same way that the Internet did. Seventy-nine percent of respondents reported that “companies that do not embrace big data will lose their competitive position and may face extinction.” However, the research found that companies hold “differing views of data sources and uses,” and that “valuable data sources are omitted or overlooked.”
Big data and the supply chain
Accenture’s Global Operations Megatrends research looked at big data analytics in the supply chain. Ninety-seven percent of supply chain executive reported that big data analytics can benefit their supply chain. Their expectations for big data analytics include: creating an organizational ability to react more quickly to changes (48 percent); helping their company gain insights about the future (45 percent); and achieving a cross-functional view of the supply chain with the objective of optimizing overall supply chain performance (43 percent).
Although the majority of executives believe big data analytics will benefit their supply chain only 17 percent of survey respondents reported that their company has already implemented analytics in one or more supply chain processes/functions. Accenture makes this supposition:
“While there is considerable hype about, and a high level of general awareness of the value of, ‘big data,’ many companies still do not fully understand how to apply analytics to this data to drive higher supply chain (and overall enterprise) performance.”
Given Accenture’s research, as well as that conducted by Jonathan Stuart Ward and Adam Barker at the University of St Andrews in Scotland, I’d take this one step further. In spite of the hype (or perhaps because of it) there remains confusion regarding what big data actually is. Without a clear definition and understanding of big data, it is (and will continue to be) a challenge to implement big data analytics. Before we realize transformation we need to get to understanding.
