What is Business Intelligence?: BI 101

Business Intelligence has powerful implications to help companies make better decisions. Learn what it is, how to use it, and why business intelligence is important to direct better business performance.

What is business intelligence?

The term “Business intelligence” has increased in popularity over the recent years to the point that its definition has become diffused. Today, different people mean different things when they say Business Intelligence. To help clarify, and to define what we’ll be talking about in this article, we are referring to 1.) the ability to analyze data, 2.) the ability to use data to inform decisions, and 3.) the ability to use data to drive action for our business.

    • Analysis of data – BI starts with you having a lot of data and wanting to get value out of it. You may have data across many systems—trended data, historical data… you have so much data you don’t know what to do with it—but more importantly, you don’t know how to use it or how to get value out of it. So we start our definition by saying that business intelligence gives you the ability to analyze your data. But that’s just the starting point; once you can analyze your data, you’re ready for the next part of BI.
    • Informs decisions – Once you have a clear path to how you’re going to analyze your data, you understand what data that you’re going to analyze, and you have a good process for analyzing it, you can start using your data to make better decisions— which is hopefully why you began collecting that data to begin with, isn’t it?

      You wanted to understand and get ahead of current trends; learn how to increase what is working well in your business and decrease what is not; or find opportunities you may not be taking advantage of yet. As you begin making better decisions, you can then start putting them into action.

  • Drives action – The real value of BI is only realized once you start behaving in ways that are different than you’ve done before. The aim of BI is to drive smarter actions to improve your business.

So that’s the core of business intelligence: pulling in data from wherever it lives, bringing it together in a way that allows for meaningful analysis, from which you can make better decisions and act in ways that generate more value for you and your organization.

How do you “do” business intelligence? (BI methodology)

Just like the term Business Intelligence has many definitions, there are also many answers to the question of how you perform BI. There are some common denominators, though, and I’m going to run through the essence of the process, bypassing the details, to paint a broad picture of how you apply BI to get value out of your data.

Before discussing the process, though, let’s start with a note about your tools. As with all such tool evaluations, finding the “right” BI tools are defined by some basic questions such as: What do you need to do? What other, complementary tools do you already have? What’s your budget? Some tools are comprehensive and enable you throughout an entire BI initiative, while others help more narrowly with a specific part of the BI process, but in deep and powerful ways.

Here is a totally non-exhaustive list of some of the tools you might use: 

Step One: (Define your goals/ Identify your big questions)

 

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The first step is to identify your goals. Most likely there’s more data out there than you will or should use. Your goal not to make all that data pretty; the goal is to get value out of this data. So your questions need to start with how do we get value out of all that data.

  • What do you want to accomplish?  This simple question is the starting point for a successful BI project. Before diving in,  stop and think about why you’re gathering data and what we’re going to use it for. Is there a pain you need to alleviate? Some questions you need the answers to?  Are there things happening in your business and you want to know why? Don’t go out and gather all possible data before thinking about these questions—there’s far too much to gather and sift through, and you’ll drown in it before you produce anything of value. Instead, think through these questions and only then go after the data you think will help accomplish your purpose. 
  • Begin with the end in mind. As you think through your goals and questions, it’s important to have a vision for how you can answer those questions. You don’t need to plan the visual layout of your dashboard before you gather your data (in fact, you probably shouldn’t), but you should put thought into what you need to see and how you need to see it in order to answer your big questions.

    Maybe you’ll need to see trends, or comparisons, or outliers. Maybe you’ll need to compare different business units against each other or understand your performance against certain benchmarks. Whatever you need to see, starting with a clear vision of what you want to create will organize and streamline your efforts.

    Once you have goals in mind and you know what you want to get out of a BI project, you’re ready for the next step.

Step Two: Connecting and transforming data

 

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Connecting your data means finding your data in all of the sources where it lives right now. It might live in many sources that you’ll want to bring into your BI tool.  By doing this, you can start putting data together and transforming it in the way that you need in order to visualize it usefully.

For example, I might have marketing data in AdWords and sales data in Salesforce. I want to know how efficient my marketing is and how well it leads to sales. How much money do I spend on a sale?  What’s the quality of the sales that I get? Do different marketing efforts lead to different quality leads?  I can’t do that when my data is in two different systems, but when I can pull them into a BI tool, I can bump them up against each other and then start making comparisons. I’ll be able to see, for example, month over month, how much I spent in marketing and how much in sales I got in return; which salespeople are most effective and which are most efficient; which tactics are effective and which are losing money; which types of leads are more valuable in the long run.

Putting that all together can give me a much fuller picture of the actual value I’m getting out of marketing.  By pulling data in, connecting it, then transforming it, I can begin the process of developing better insights and getting to those better decisions.

  • This begins with planning. You don’t want to use all your data, or you’ll get overwhelmed. Think about the precise data you need to answer your questions. Go into your systems and pull that data out. Often, a mapping process can be helpful to help you think about what visuals you want and why, what data will be displayed there,  and how it will help you answer your questions, where that data needs to come from, and what needs to happen to make that data useful. Work backward from what you want in order to remove noise and extract the data you need.

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  • Next, connect your data. Go into your systems, connect the data, pull it into your BI tool. This can be very straightforward, or it can be quite difficult; it depends on the tools you have available and the source data that you need to pull from (eg., in-house CRM data is typically far easier to access than external financial data you’d need for detailed cost analyses). This is the first technical step, and it will enable you to make your data available for your analysis.
  • Next,  transform your data. Take all the disparate data pieces and connect them, so that you can begin telling a broader data story. In this step, you often must also transform and manipulate that data so you can use it for what you need. For example, you may need to aggregate data by region so you can compare regional performance against each other, or you may need to calculate complex business rules against items you sell so that you can make apples-to-apples comparisons and understand which categories of inventory drive the most value to your business. Once your data is all connected and transformed, you should end up with data that’s ready for you to start analyzing to build your visualization.

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Step three: Visualize and analyze

This is where you start turning data into knowledge. You can use that knowledge to start doing things differently. Raw data sets turned into visualizations give you the ability to tell the stories that you needed when you started asking your questions.

At this point, you can create some visualizations! You can bring your data to one place and combine it in a way where you can visualize and understand what’s going on. For example, you can trend over time your actual performance with your forecasted performance, or you can see data broken out across different segments. This allows you to absorb a tremendous amount of information very quickly and easily, in a way that helps you focus on what’s important. You can see where things actually stand.

But visualizing how things are right now is just the first step. Almost always, that knowledge leads to new questions, such as “Why is this happening?” and “How do I fix it?” That’s where BI becomes much more powerful: instead of just a snapshot of how things are going, it gives you the tools to answer those more meaningful questions, which in turn drive more valuable behaviors.

Dynamic dashboards
Often, you want a dashboard that’s dynamic enough to enable you to ask these follow-up questions. Dynamic dashboards allow you to focus on the data that’s important to you or on complementary data that gives additional context. For example, if I see sales spike over time, I’d want to break it out to understand why. Maybe there’s a particular region that’s doing well or a sales team that’s crushing it. And if I see it is a sales team, I may want to dive in to see who the star performance-driving salespeople are. Once I understand that, I can start asking about what that region or group does so well, and how I can share that across the rest of my organization.

Why is business intelligence important?
Wrapping this all up, the core of Business Intelligence is a process that accesses and transforms the relevant raw data across multiple systems into one cohesive place to allow you to answer your vital business questions and generate meaningful insights about your business. These answers and insights become a springboard that allows you to make data-driven decisions to direct better performance for your business, by answering:

  • What’s going on?
  • Why is that happening?
  • What should I do about it?

There are a lot of other details that get involved in this, such as how you connect your data; how you validate it and how you transform it; and what are the other pieces to integrate with your BI processes to create a holistic data strategy that drastically improves your overall performance. But if you distill business intelligence to its essence, this is what it comes down to.

If you want to learn more about how you can get more value out of your data - whether that means embarking on your first BI project, or elevating your BI program to a more sophisticated level - reach out to our team and let’s talk!

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