Analytics

We live in a world driven by numbers.  We use them to conduct trade, we use them to monitor time, and we use them to analyze data.  We often here about surveys, statistics, and how companies and organizations use analytics to quantify data.  This information has a place in our decision-making process, but we also must be aware that outside factors can skew results. 

Purpose

The reason most organizations use some type of analytical data is it provides measurements and facts on a situation.  Most companies and countries have been using statistical data to make decisions for years.  When deciding for a large group of people, most leaders want to understand the opinions and feelings of the group they represent, and polls and surveys can provide insight.  Knowing a large percentage of a population is against a law can help an elected official decide to vote against the issue.  In contrast, knowing that a large group of people in your community is in favor of a tax levy for additional school funding lets a local school board to know to put the levy to a vote.  The information that statistics provide can be used in a countless way to help make educated decisions.

Analyzing Results

Having a large amount of statistical data can help someone make an informed decision; however, it is not a good idea to be too dependent on the numbers.  There must be an element of human instinct that is involved.  In any poll or survey there is always outlying data and results are meant to be measured with an open mind.  For example, judging if everyone had fun at a baseball game seems like a simple question, but other factors come into play.  If it rains on the day of the game or it is excessively hot and humid people are likely to be more uncomfortable.  This factor can have a drastic impact on how people quantify if they enjoyed the outing.  Additionally, the information that factors into the statistics depends on the questions that are asked.  For example, trying to figure out a groups average age is simple and does not leave a lot to speculate on.  In contrast, trying to judge if a customer was satisfied with an experience depends on how the question is asked.  If you ask someone if they were satisfied, yes or no, you will get simple answers.  However, if you ask the same people if they were highly satisfied, satisfied, indifferent, or dissatisfied makes the result more complex.  Some people will always be satisfied but never highly satisfied.  Others might say they were indifferent when they said they were satisfied if asked a yes or no question.  How you ask matters.

Part of The Puzzle

The dangerous part of dealing with analytics is knowing when to listen to results and when to discount them.  Making the wrong decision can lead to disastrous consequences.  When dealing with statistical data we must remember to use it as a reference tool and not to make definitive decisions.  We must take data for what it is worth.  We must be open minded to the factors that are affecting the results.  Ignoring them does not put us in a position to succeed.  It is important to ask the right questions, it is important to know when the questions were asked, and it is important to be aware of outside influences on the results.  If we are open minded and understand all the factors that affect results, we will put ourselves in a position to make a well-rounded decision. 

Numbers and statistics will always be part of our lives.  We must come to terms with this fact; however, we must remember to not depend entirely on the results.  If we do factor in human intuition, we are not making the best decisions possible.  Computers and empirical data can only tell us so much.  We must never forget that the most powerful computer we have is our own brains.  So, next time you are looking at quantifiable information remember to keep an open mind and consider everything before deciding.  If we take every factor, both measurable and nonquantifiable, into account we will put ourselves in the best position to succeed.