Business intelligence vs. business analytics

Data analytics isn’t one single practice. There are a number of techniques and applications that fall under the data analytics umbrella. Two of the most common practices are business intelligence and business analytics. 

Yes, they sound like they could be the same thing. It’s a misconception that many companies have, which can have a real impact on your analytics strategy. In order to get the best intel out of your data, you need to understand how BI and BA work as separate practices. Below are the key differences between business intelligence and business analytics as well as information on how they work in tandem. 

The primary distinction between business intelligence and business analytics is the focus on when events occur. Business intelligence is focused on current and past events that are captured in the data. Business analytics is focused on what’s most likely to happen in the future. The two practices use the same data, but the timeline for applying the results is different. 

This difference can be summed up in a few questions:

          What is happening now and why? (Business Intelligence)

          What will probably happen next? (Business Analytics)

BI helps companies form strategies for current situations by making data actionable. The information is broken down so that a specific question that applies to what’s happening now can be answered. BA uses data insights to form strategies that affect future operations. The goal is to improve upon productivity and systems that are currently in place.

How the data is used and the analysis it provides varies between business intelligence and business analytics. Business intelligence is designed to tell you what has happened, what is happening now and point to reasons why. It’s descriptive. Business analytics, on the other hand, is a type of predictive analytics. It identifies trends and patterns in the business analytics data that suggest why things are happening and whether similar results will occur in the future. The end goal is to predict what will happen based on what’s already occurred and make decisions accordingly. 

The end-user is another consideration that differs between BI and BA. Business intelligence tools present data so that marketers, accountants and managers without technical expertise are able to decipher it and make informed business decisions. The visualization of key data points is done automatically within BI tools without the help of a data professional. Business analytics is a little more involved. More work is needed to parse out the useful information and interpret it. It’s a job that’s better suited for someone who’s had data analysis training. 

Here’s another way to look at it. BI requires only basic math to calculate results – and software can do that for the end-user. BI relies on the creation of mathematical models, querying, machine learning and artificial intelligence to make projections. Clearly, BI is something any professional can handle with the right tools whereas BA needs a data professional with an analytics skillset that knows how to build machine learning capabilities. 

As noted above, data is used and viewed differently depending on whether you’re conducting business intelligence or business analytics. BI is simplified. The data is arranged into easy-to-read reports that tell users what’s happening. (Dashboards and charts are also commonly used.) But with BA the data is taken a few steps further than reporting. Data applications and statistical analysis is done to look further into trends and determine why things are happening. So it’s a scenario of reporting data versus applying data in a new way.

Many companies ease their way into analytics by implementing a business intelligence strategy. It’s a good first step that will put a plan in place for gathering, storing and structuring data. Once the business intelligence strategy is underway and you get a feel for what the data is telling you, that’s when many businesses begin to dive deeper with predictive business analytics. In other words, before you jump into more advanced BA techniques that answer complex questions, it helps to have a firm handle on BI. 

In fact, BI can be the basis for BA. The data that is collected and stored during the BI process can be used by analysts for predictive analysis later on. 

While many organizations have leveraged business intelligence and found significant value in the tools, Bain & Co.’s Six IT Design Rules for Digital Transformation report notes that advanced analytics is the number one capability IT managers want most. However, the majority of IT managers don’t have BA technology in place yet.

Both business intelligence and business analytics give companies the ability to analyze data in order to make more informed decisions. Whether those decisions affect current or future operations depends on which one is used. And while BI tools are getting more powerful and providing advanced capabilities, data professionals are still needed for predictive business analytics. The best strategy is often starting with a business intelligence program and then incorporating business analytics to make projections aimed at improving efficiency, revenue generation, etc. moving forward.