Why Business Analytics Is Only One Part of Data Driven Decision Making

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Though you might not be keeping track of all of it, your business is generating tons of data on a daily basis. And when utilized properly, some of that data can tell you a lot and help clarify what aspects of the business are successful and what needs to be changed.

That’s where business analytics comes in. An unbiased way of deciphering trends in your business operations and at times, even predictive future outcomes using existing metrics, business analytics can be pivotal in steering business operations on a granular level.

But regardless of how helpful business analytics can be, it shouldn’t be the only part of your decision-making process. You may have formerly equated business intelligence (BI) with business analytics, but it’s a good idea to familiarize yourself with some of the differences between the two disciplines when making critical data-driven decisions at your company.

Business analytics vs. intelligence

Oftentimes, the data generated at or provided by a company is going to appear in large, disorganized batches. Though you can approach relatively unstructured data from both an analytics and intelligence lense, there are some critical differences between the two approaches. 

Fundamentally, while analytics is more about why something happened, intelligence is more about what happened and how it happened. More specifically, rather than returning a prediction of future performance based on empirical data, business intelligence instead assesses historical trends. Check out this resource page to learn more about the nuances that differentiate business intelligence from business analytics.

To companies, having access to these trends provides insight into what aspects of the business model have or haven’t been productive, and can naturally lead to informed decisions on how to improve future outcomes. 

Why you need more than just the analytics

Say you’ve extracted insights from your business analytics platform of choice. At this point, you might have some predictions about what can happen at the company, which is useful because you’ll be anticipate future outcomes. 

Let’s say you’re a publisher and through your Google Analytics dashboard, you now have a more specific idea of where your traffic is coming from geographically, alongside a prediction for the next week. 

Now, that’s pretty good, but it doesn’t really tell you how to act. In the end, it is up to you to make the final call on the interpretation of the data. Without a proper strategy to approaching the decision-making process, your extracted data could be rendered useless.

Adding a human touch to interpreting data

At this point, you may be looking to interpret the data and act on it. That’s great, but at this stage, you have to be careful of potential personal biases. Not keeping bias in check can cause trends to appear that support your wants rather than what the data actually represents. 

The best way to safeguard against this is to work in a team. That is, when the data is run through multiple people, you may be able to eliminate unfounded interpretations. 

Furthermore, your strategy should focus on answering specific business questions. This means that rather than analyzing every single piece of available data, you can instead focus on data that will answer your questions. This will decrease the time and money spent analyzing the data and increase the chance that your results are applicable.

What to consider when picking analytics and BI platforms 

Keeping in mind how business analytics and intelligence can be beneficial to your company, there are some critical considerations when picking data analysis software. Here are a number of considerations you should keep in mind to identify the best fit: 

  1. What types of data are you looking to analyze, and what insight do you want to gain? More specifically, is your source data a set of raw, unstructured files, or is it categorized and easy to access? This is useful to know for obvious reasons.
  2. Are you looking towards future success or trying to find the source of past errors? This will help you identify whether what you need is more analytics or intelligence if you were to choose one for an immediate need.
  3. How long has your company been in business? This usually has a fairly direct association with how much data you have to work with.
  4. How savvy are your employees when it comes to BI and analytics platforms? If your employees have worked with certain platforms before, choosing those could reduce your educational costs.


As your business continues to run, consistently recording and analyzing incoming data allows you to keep track of your standing and take action when necessary. Whether you choose to draw out this data by utilizing business analytics, business intelligence, or both, you should always think about what insights you’re looking to acquire about your company. 

But, ultimately, what matters most is not the analysis generated by a program, but rather how you make decisions based off of the data presented. Creating a strong analysis strategy that minimizes human error and focuses on specific questions will allow you to make decisions that will best set your company up for future success.

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