Analytics for Human Information: New Top Ten Myths of Big Data - Myth #3

Part three of the New Myths of Big Data addresses a belief held by a great many skeptics both in business, and in Information Technology.  This belief is held by many who don’t see value in whatever is the latest trend. It is held by those who feel like the IT industry is constantly trying to sell them the latest  shiny new object.  It is held by those who feel that a “wait and see” attitude for technology investments is a best practice.

 

Big Data Myth #3: Big Data is Just Marketing Hype

Even today, there are many people who still believe that “Big Data” is just marketing hype. Indeed, the hype behind “Big Data” is second only to that other current megatrend in IT: “Cloud Computing”.  Whoever coined the term “Cloud” is a marketing genius because the word itself conjures up such great mental images.  “Cloud Computing” sounds so pleasant… clean… dreamy… easy...  These are much nicer subconscious associations than those produced by “Hyper-Fragmented-Ungovernable-Risk-Saturated Computing”, which is hard to fit on a business card in any event.

 

The same hype, misperceptions and expectations currently surround Big Data. Many feel that Big Data is nothing more than Business Intelligence (BI), only bigger.  While I used to collect, transform, warehouse and analyze maybe a few terabytes of old data, trying to gain insight, I now do the same analysis against perhaps a petabyte or more of data.  If this is what you are doing then you are not doing Big Data, you’re doing Big BI. 

 

Real World Example: The Transformation of Retail

Retail is a ruthlessly-competitive business where some new, unknown business can swoop in and eat your lunch before you even get a chance to see what kind of sandwich your mom packed for you. Margins in this business are small and getting smaller, which makes investing in new technologies very difficult.  Before players in this space will place such bets, they need to see solid business plans, rapid Returns on Investment (ROI) and a lot a reassurance that “this will work.”

 

Nevertheless, in a recent Big Data Report by McKinsey Consulting, analysts found that within the Retail Industry those companies who embraced Big Data technologies and techniques (these are not one in the same, by the way)  were achieving roughly 60% greater operating margins than their competitors who had not yet embraced Big Data.

Some of our customers have seen such results in practice.  One of our retail clients was looking to improve their operating results, and used Big Data to provide some clues as to where to look.  Using HP’s tools and techniques, this client married in-store video footage (unstructured data) with real-time register receipt information (structured data) and managed to conclude that whenever a customer took an item of clothing into a dressing room and actually tried it on, they were 50% more likely to purchase that item (HP’s HAVEn platform was specifically made to make it possible to both ask and answer questions like this).

 

With Big Data you can now blend your intangible business prowess with quantifiable facts, which together can lead to dramatically better results.  This is the potential power of Big Data, and this is why this trend is not merely hype, it is transformational; but only if you do it correctly.

 

This then creates an imperative, regardless of your industry.  If you are NOT making this sort of investment in Big Data and one or more of your competitors are, you’re toast.  They will not only eat the sandwich that your mom packed for you, they’ll take your carrot and celery sticks, too.

Just to be mean. No one ever eats those anyway.

 

New Big Data Myth #4 explores Hadoop: it’s not just for breakfast anymore! Do your homework: read my previous post as a primer.

 

Click below to continue reading about The New Top Ten Myths of Big Data :

 

Comments
jjsimonds(anon) | ‎11-08-2013 09:41 AM

Hi Chris,

I am enjoying your posts a lot.  I'm hoping to find links back to Myth 1 & 2 - other than those I think I'm uptodate.  I have a question on the example.  Although it is very interesting to see the correlation of trying something on with propensity to buy the thought of investing in cameras, storing and sending the video feeds, analyzing the images seems like a lot of effort to answer the question "Did they try the product on first?"  Can you comment on how knowing this will affect behavior?  Will clerks start pushing customers to 'try something on?  It would seem that plan would cause the 50% rate to decline. Can you expound a bit on this solution?  Thank you in advance.

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About the Author
Chris Surdak is a Subject Matter Expert on Information Governance, analytics and eDiscovery for HP Autonomy. He has over 20 years of consul...


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