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Reading UP: Big Data

Big Data: A Revolution That Will Transform How We Live, Work and Think by Mayer-Schonberger & Cukier has generated a lot of buzz. Is this something you should care about, or even be worried about? Let’s start with some background.

Here are some of the more interesting Big Data findings presented in this book:

– Google can now do a better job of predicting a flu epidemic than the CDC.

– A traffic analyzer program was able to predict a sharp spike in unemployment prior to the government reporting it based on lower volumes of traffic.

– Happiness is correlated with income up to a certain point, and then additional income does not create additional happiness.

– Apple received a patent in 2009 for their earbuds specifically for collecting data on heart rate & body temperature.

Perhaps these are interesting, but how can this help your business? Consider these:

– UPS was able to reduce its vehicle maintenance cost by millions by being able to delay certain preventative maintenance based on analyzing extensive amounts of vehicle failure data.

– Target knows when its female customers are pregnant; and they are pretty good at pinpointing the due date. They generate business by targeting the right coupons throughout the phases of the pregnancy.

– Walmart knows that before hurricanes strike, customers purchase lots of flashlights – and pop tarts. So they stock lots of pop tarts before a big storm.
Big Data Imagined
Big Data has been made possible based on the plethora of data available through the information age & also the cheap availability of processing power & storage to analyze and store all that information. Here are some key things to know about Big Data vs. Small Data (the data/analysis available in the past):

– Big Data is based on analyzing (virtually) all the data. Small Data was based on sampling much smaller data sets.

– Big Data is concerned with answering the what (correlation) but not the why (causality). This is a very significant point. The authors argue that knowing the what is for the most part all that you really need to know. Sometimes knowing the why is critically important – therefore Big Data is not always the right approach.

– Small Data involves having a theory before you started to analyze the data. Big Data lets “the data speak”. This is among the most important points. Algorithms will run on the data and reveal answers to questions that you didn’t think to ask. As Duncan Watts wrote, everything is obvious once you know the answer.

So should you care about this? Absolutely! Consider Google vs. Microsoft. Microsoft has the best spell checker in the world, right? In fact, Google does. With the most popular word processor on the planet for many years, you would expect that Microsoft was able to develop the best spell check algorithms. But they did not base it on Big Data. Google did. They collected every misspelled word that users entered. They applied Big Data processing on this data. Now, Google has the best spell checker on the planet.

What can you do? Think about what data you have – good and bad. Assemble your key staff and brainstorm on business innovations that you might be able to make based on your data. You might be able to dramatically improve your service levels. You might find an opportunity to launch a new product or service that will solve a recurring need for your clients. Or, you may be sitting on a gold mine of data and can use it to enter a new industry altogether. It’s not easy. The analysis requires specialized expertise. But, this revolution is here to stay. You should start to think of your data as a strategic part of your business.

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The Idea Factory by John Gertner

Who is your Harvey Nyquest?

Have you ever heard of Harvey Nyquest? Not many people have. In fact, with all the buzz about Apple, Google, and the like,Bell Labs doesn’t even come to mind very often. Bell Labs is probably the single most influential organization to the information and communications revolution we’ve been benefiting from for over a generation. Apple and Google stand on the shoulders of the Bell Labs giants.

A stylized replica of the first transistor inv...

A stylized replica of the first transistor invented at Bell Labs on December 23, 1947. (Photo credit: Wikipedia)

Most people probably don’t even recall names like Claude Shannon and Bill Shockley. Claude Shannon developed the concept of information theory which is the foundation of the communications and computer revolutions. The controversial Bill Shockley and his team invented the transistor and semiconductors which form the technical foundation of digital devices.

Bell Labs was the research and development arm of AT&T from the 1920s through divestiture in the 1980s. Bell Labs included both scientists and engineers. The scientists would come up with a new discovery and the engineers would turn it into a practical application. Bell Labs innovations included such diverse and important endeavors as the transistor, communications satellites, the laser, fiber-optic,s and the Unix operating system.

Bell Labs is chronicled in a The Idea Factory by John Gertner.  This history describes the key individuals, their personal histories, and the discoveries of Bell Labs. It also explains some of the cultural aspects of Bell Labs, such as the building design that supported collaboration, which many contemporary companies have adopted to generate a culture of innovation.

So what does this have to do with Harvey Nyquest? Unlike his colleagues, Nyquest never won a Nobel Prize. He is important in a very different way. One researcher attempted to find what the most successful Bell Labs scientists had in common. He discovered that the most productive individuals, based on number of patents, had one thing in common: they had breakfast or lunch with Harvey Nyquest.

Nyquest was not particularly creative or successful himself. His skill was that he asked the right questions to draw out other people’s thinking and help them generate their insights.

One of my favorite quotes from philosophy that I’ve found applicable in business is by Voltaire:

Judge a man by his questions rather than by his answers.”

Nyquest practiced this well.

One other relevant quote from The Idea Factory jumped out at me. Said of Bill Baker, head of the research division, by one of his researchers:

A small number of times in my life I have been in the presence of someone who didn’t necessarily answer the question I asked but instead answered the question I should have asked.”

My take-away from this is to be careful not to undervalue someone who doesn’t necessarily stand out and have the best ideas. Some of these individuals may just quietly be making the rest of an organization a whole lot more successful.