Everyone seems to be rushing to "data analytics" today to help them find the secret to life. I have a huge surprise… there is no secret. There are only two things: questions and answers, and answers need questions.
Answers without questions are simply objects that exist. To really get answers out of your “big data” you need questions. Too many people today ask “What is the data telling us?” - without the question -“What do we want to know?”
It all goes back to seventh grade science class. Remember when they taught us “The Scientific Method”?
Wikipedia defines The Scientific Method as “a body of techniques for investigating phenomena, acquiring new knowledge, or correcting and integrating previous knowledge. To be termed scientific, a method of inquiry is commonly based on empirical or measurable evidence subject to specific principles of reasoning.” So we spent two to three weeks in class studying what could be the most important concept we will ever learn, then we moved on, abandoning the holy grail of education.
Figure 1 - Courtesy of Wikipedia
Notice the top of the graphic is “Make Observations” followed directly by “Think of Questions”. We CANNOT learn without a question. One of the most important things any analyst should think about are the questions that need to be answered.
When we apply this to data, of any type, the first thing we have to have are observations, followed by questions. If you are a manufacturer and you notice that you are seeing a higher number of returns, that is an observation. This will immediately be followed by the question “Why am I seeing more returns?”
Data can help you answer this question, but only if you are collecting the right data. Collecting the right data is another complete discussion all its own, so for the time let’s stick to the idea that indeed we do have the right data.
If you have the right data, and you have a question, then you are on to the next step: formulating a hypothesis. “I think we are seeing more returns because we are ordering raw material A from a new supplier.”
Now to the data-let’s analyze all returned items with our new supplier vs. our old supplier, are there actually more returns? If the answer is yes, then you are all done- if not we still learned a valuable piece of information.
In this hypothesis we learned that the new supplier is not an issue. Often people will have an idea they do not want to give up on regardless of what the data tells them. This costs them valuable time and resources, running down something that has already been proven.
Open your mind, listen to your data, be objective. A person with an agenda will skew data to make it look like the way they want it to, rather than tell the truth. A person with an agenda will filter data in a way to make it reflect what they want it to say.
This can be magnified with graphs. I have seen people graph data in a way that makes it look completely different than what it is really saying. If you are going to be successful with the scientific method then you must be objective. Being objective, is recognizing you need a new hypothesis; following this method will get you the answer you are looking for, AND it will be absolutely CORRECT!
Data analytics will absolutely be beneficial to any organization, there is no doubt. What everyone needs to keep in mind is that it is not magic. It requires good old fashioned 7th grade thinking to structure your methodology. It also requires an analysis that is totally objective. The ability to look at data objectively will lead you in the correct direction every time. So please don’t fight the data. The data is truly your friend.
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