The Difference Between Data Analytics and Business Intelligence

Written by Sam Watson | 19 Feb, 2021

Business intelligence is only as intelligent as the data that goes into it, and only as smart as the people using that data. As companies (big and small) take up the arms race that is big data what’s getting lost in the process is the difference between gathering business intelligence and using data analytics to make business decisions that have a real impact.

Before you even think of what data analytics software you need, or what data you want, you need to understand the problem(s) you want to solve. In eCommerce this could vary from understanding:

the life time value of your customers;
the cost of acquiring each customer;
where your customers are coming from;
what your customers are buying;
which ad campaigns are performing the best;
your top and bottom selling products;
your website traffic and popular pages; and
much much more.

Data Analytics and Business Intelligence are Not the Same

If you are wondering what the difference is between data analytics and business intelligence you are probably not alone. Both terms are used interchangeably, with business intelligence being the generalised term that encompasses analytics, but there are some key distinctions.

The major difference between business intelligence and data analytics is that analytics is geared more toward future predictions and trends, while BI helps people make decisions based on past data.

Why Business Intelligence and Data Analytics are Not Enough

You cannot make smart decisions without the right information to act on. The right tool will help you illustrate data in a meaningful way, and then distribute this information to the right people at the right time. This is what business intelligence is all about.

However, you will never get the right answer without asking the right question. Unfortunately, with the rise of software tools touting business intelligence and automation, the new norm is thinking that having these tools will make or break your business.

Where most companies go wrong is attempting to adopt new technologies too fast across their entire organisation without having a plan in place for how they will actually use the tools to solve clearly defined problems.

Here’s why: We create 2.5 quintillion bytes of data daily, and that rate will only continue to accelerate. Incredibly, 90% of the data in the world has been generated within the past two years alone. The sheer volume of data being generated means that large organisations that are taking the first step toward adopting BI must first understand the problems they want to solve and create hypotheses about how BI will help solve these problems.

It is the process, or lack thereof, that either builds or kills the value found in data analytics and business intelligence tools. Therefore, in order for your organisation to get the most out of adopting data analytics and business intelligence software the first thing you need to do is set out a clearly defined problem that can be solved with BI.

The smartest organisations focus on scaling business intelligence targeting one problem at a time. It’s much more efficient to rally your board, C-suite and IT department around a single problem that will have a meaningful impact if solved.

You Need A Road Map

Whether you are starting from nothing, moving from spreadsheets, or looking to up-level the way your organisation uses data, you need a plan of action.

Here is how to implement business intelligence into your business:

Decide on what problem(s) you want to solve. Start with a clearly defined problem with goals that are smart, measurable, actionable, realistic and timely.
Understand what stakeholders will be involved. Proper planning prevents poor performance. What information do they need? How will they use it? What data will provide this information?
Figure out what data you need and how you will get it. One hundred percent pure quality data is a bit unrealistic, but you need to have a data management practice in place to make this work. Good data in means good analytics out.
Decide how success is measured using KPIs. What gets measured gets managed. You need an objective way to gauge the effectiveness and success of your rollout. Establish key performance indicators with your team that everyone will rally behind.
Set up systems and processes that turn data into action. Automate reporting. Create systems and processes that automate the delivery of information to the right people at the right time, and set deadlines for acting on information.

Software comes last. Business intelligence is not solved with a software solution alone. You need organisational buy-in. You need clearly defined problems and a process for solving them. All the intelligence in the world will go nowhere if your organisation isn’t structured to take action on the information you uncover.

Solve the people and culture challenge first, and business intelligence opens up a completely new way to streamline business processes, accelerate growth and uncover new opportunities.

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