Data Analysis Challenges that Small Businesses Face

data analysis

data analysis

We live in a data-driven world. Small businesses are bombarded with data-driven reports and systems that can be quite confusing. We’re all reminded on a regular basis just how important it is to make data-driven decisions, but then find that there are so many challenges blocking the way. Small businesses understand that they can gain a competitive edge by using big data, but those challenges make it too intimidating for some.

Some businesses have the money to invest in an expensive data scientist to help solve their problem while others delegate the task to an outside firm. You might feel that small businesses have lost the competitive edge with corporations installing expensive software systems and taking full advantage of big data.

Well I’m here to tell you that big data still offers tremendous benefits to small business once they are able to get through the challenges. Here are some of the major data analysis challenges that your small businesses is likely to face.

The Quality of Data is Often Poor

Usually when we think of quality, our mind goes to a physical object or some form of marketing content. But data quality is a huge challenge that every business will have to work through. Data is stored in large repositories and is often inconsistent or incomplete.

Consider back in the old days of snail mail marketing when you would receive the same marketing materials addressed to different variations of your name. That’s an example of poor data quality costing businesses valuable resources.

Raw data can contain several records that are just slight variations of the same information. This is still a problem, but it has evolved to email lists. Multiple emails are sent to the same individuals due to repeat records. My point is that raw data must be organised before it’s valuable to a business.

The Waters are Drowning Us With Data

Raw data is everywhere! Think about how a normal business operates:

  • Marketing departments collect data from people who download content, follow their social media pages, or attend live events.
  • Executives then try to use that data to define a new strategy.
  • Sales departments then collect data, often duplicates of what marketing has collected.
  • Customer support also collects customer data.

I could continue, but I fell you get the point. We end up with so much data that it’s overwhelming. We try to swim but end up drowning in our own frustration. That’s why it’s so important to develop systems to automatically sort and segment data so that we can easily make sense of it.

Data Volumes Are Always in a State of Growth

Everything I mentioned above will continue to grow as a business takes more steps forward. As a society, we are creating more data than ever before! That makes it much more difficult to comprehend. The truth is that we need help to develop systems to help us make sense of these large volumes of data. Until that happens, the challenge will only get worse!

The key is to transform unstructured data into information that can be used with a business’s current software.

Garbage will Always Remain Garbage

Data experts use the phrase “garbage in, garbage out” to describe the fact that data analytics software is only as good as the data being fed into it. A common theme that we have address throughout this post is leveraging data to work for us rather than against us. Dirty data is always going to lead to dirty decisions. You must be confident enough in the data being fed into your system that you can trust your decisions.

What are the biggest data analysis challenges faced by your business? Share it in the comments section below.