7 Warning Signs You’re Analyzing Your Data Wrong

Guest Post from Michele Nemschoff, VP Corporate Marketing, MapR

 

 

It doesn’t matter how much data you can store or process if your analysis isn’t yielding valuable business insights. Yet it seems many businesses tend to put all of their time and resources into storing and maintaining their data rather than taking meaningful action based on insights from the data analysis. These are seven warning signs that you may have fallen into the data collection trap and are not gaining the insights that you need and want.

 

1. Poor Data Quality

 

If the data you have is incorrect, incomplete or formatted badly, your data analysis is going to be incorrect. According to a survey by Harris Interactive, 75 percent of “Information Workers” said they had made bad decisions due to incorrect or incomplete data.[1] Common reasons for this include pages that aren’t tagged, campaigns that aren’t tracked consistently, key onsite behaviors that aren’t being tracked and open field texts that allow varying answers for the same category type. Failure to prevent bad data and fix bad data that gets through may not always affect your analysis, but it’s a huge gamble to allow and one you will regret eventually.

 

2. Justifying Current Practices Rather than Seeking New Insights

 

Business leaders have to prove that their efforts are effective and positively contributing to the company, so many sort through old data to look for “evidence” that their work has been a success. This kind of analysis doesn’t yield valuable business insights because it doesn’t show how to improve or change any processes that the company is already using. This problem also tends to occur when analysts are not informed of or understand the business problem needing to be solved. Data can be analyzed and placed into graphs all day, but unless there is a real business question being asked, the analysis is pointless.

 

3.  Analysis Requirements are Determined by Low-Level Employees

 

For business analysis to be successful, the business requirements need to be defined by senior executives.[2] Unfortunately, this assignment is often relegated to low-level employees who don’t have the information or experience to make the decision effectively. This generally leads to analyses that are focused on improving current processes based off of the problems low-level employees see. These problems are rarely the questions that need to be answered to make changes and move the company forward.

 

4. Employees Lack Analytical Skills

 

While Hadoop and Big Data have a huge potential to give companies new insights, failure to train employees in the skills they need to conduct the analysis effectively and to communicate actionable steps based on insights essentially makes the data worthless. To be effective, employees need to be familiar with scientific experimentation as well as mathematical reasoning, among other skills, all while continuing to see the b