Monday, March 2, 2015

How To Avoid the 3 Simplest Ways to FAIL with Big Data

Big Data Fail by Jonah Engler

Big data science provide a huge opportunity for business of every size, scope and industry. However, as with anything different, there are a few potential issues that could arise. In fact, there are some people out there failing with big data. We don’t like to admit it, but human nature being what it is, people make mistakes. Those mistakes often lead to failure. It’s important to know, though, that these failures are often not because of the system, but because of clearly and easily avoided mistakes. Sometimes, you simply don’t know what you don’t know…and that can always come back and bite you.


Let’s take a look at four ways you COULD fail with big data…if you allow yourself to make these mistakes.

1 – Install the wrong leadership

Look, it’s okay if you don’t have the foggiest idea how all this big data stuff works. That doesn’t make you a bad leader or even the wrong leader for your business. However, you DO need a leader who understands the science if you want to achieve success. And here we’re not talking about the “concept” or the “buzzwords” or the “results.” Nope. We’re talking about the actual working science. If you don’t get it, you can’t make it better…and you certainly can’t fix it if it goes wrong. To do that, you need a leader who understands both the NEED and the SCIENCE.

2 – Making decisions based on incomplete or substandard data

So, you’ve got your pipeline going, and it is delivering some stellar data. You get excited and start looking for (read: demanding) answers immediately. Sorry, it doesn’t work that way…and you can’t make it work that way either. That’s the thing about science. You can manipulate the numbers, but you can’t manipulate the reality. You have to accept and address the reality. When you make decisions based on incomplete or substandard datasets, you get incomplete or substandard decisions. They may not be precisely “wrong” answers…but they sure won’t be the best answers.

3 – Leaping before looking

Some will tell you that one of the “secrets” of big data is that you can’t know what you will learn. While, partially, that’s true, it makes the process seem too much like magic. It’s not. In this world, you can’t just go in without knowing what you are looking for and expect to get optimum results. Well, you can go in that way, but you won’t like what you end up with. Big data analysis sometimes yields surprises like a treasure hunt, but you should not approach the process like a pirate with a map looking for an “x.”

Avoid these big data mindset miscues, and you will achieve much better results in your big data programs and protocols.

Jonah Engler is a successful entrepreneur, investor, franchise owner and coffee lover who hails from New York City.

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