What is Business Intelligence? An IT Leader's Complete Guide
Oct 20, 2020
Business intelligence is one of those domains that have a slightly different definition depending on who you talk to. End users might think about the reports and interfaces they see and work with. Creators will probably think of the processing steps that transform complex business data into information. And management often considers it as a method for improving efficiency, productivity, and decision-making.
All three viewpoints are correct from the perspective of each stakeholder. However, they don't quite get to the core of business intelligence.
The core of business intelligence is typically something that's in the realm of IT leadership. That's why we've created this guide. In the following sections, I'll go over what business intelligence is, why it matters, and the life cycle, including various activities and tools. I'll then talk about the differences between traditional and modern business intelligence, and who uses business intelligence tools, specifically self-service business intelligence. Finally, there's business intelligence strategy, as related to your position as an IT leader. This includes how it relates to digital transformation within an organization, selecting and implementing the right tools, how to make the most out of your processes in an ongoing setup, and the future of business intelligence. By the end of it, you'll hopefully be the resident expert on business intelligence in your company.
Business Intelligence Defined
So, with the various stakeholder viewpoints in mind, let's start from the bottom and build our way up. What is business intelligence from an IT leadership perspective?
Simply put, business intelligence is all about turning business data into meaningful insights. This involves the infrastructure, processes, and output that collect, store, analyze, and display data produced by business activities. Therefore, business intelligence refers to both the software tools that allow users to easily understand and interpret business data, and the methods for storing the data and processing it into information.
The purpose of all of this is to facilitate data-driven decision-making. Data-driven decisions reduce the guesswork involved in business practices, helping to ensure that your business hits the target more often than not. For example, business intelligence can help you monitor sales performance, compare yourself with competitors, analyze customer behavior, identify trends, optimize logistics and operations, uncover issues, and predict the success of alternate strategies.
The Business Intelligence Life Cycle
In my opinion, the best way for a leader to dive into a topic is to look at the workflow or life cycle. It helps to understand the purpose of the process, the ins and outs, and the stakeholders. So let's do just that!
If you're familiar with data life cycle management, the business intelligence life cycle fits neatly into steps two, three, and four: data storage, data use, and data sharing. It makes use of online analytical processing, or OLAP, which is a method for arranging and processing data into data warehouse "cubes" for analysis. Thus, the various data stores across the business are taken, processed, and arranged, so they can be used and the insights can be shared across the business.
Common Business Intelligence Activities
As you might imagine based on the above life cycle, business intelligence covers a broad range of activities. The following list describes common business intelligence activities that occur every day in various organizations. The activities can be performed individually or in concert. As long as they're turning business data into meaningful insights, they're part of business intelligence.
Collecting and preparing data can include tasks such as combining various data sources, selecting dimensions of interest, and defining measurements.
Querying the data can be performed through database technologies (e.g., directly via SQL) in applications that expose the data to users.
Data mining is easiest to think of as a step up from simple queries, in which statistics and machine learning techniques are applied to larger datasets to uncover trends.
Historical or descriptive analysis involves interpreting collected data to understand changes that have already occurred.
Statistical analysis looks further into historical or descriptive analysis to uncover the how and the why.
Reporting is the practice of summarizing the results of the analysis so they can be quickly understood by stakeholders, allowing them to make decisions.
Data visualization and visual analysis are two sides of the same coin. The former turns results of the analysis into graphs and charts so they can be more easily understood, while the latter uses the graphs interactively to tell stories and allow users to draw further conclusions.
Modern Business Intelligence is Not the Business Intelligence of Old
Before getting into the users and tools, we need to address the specter of traditional business intelligence and how it differs from modern practices.
Traditionally, business intelligence used a top-down approach with static reporting. Someone in the organization requested either a standalone or recurring report, and a member from the IT department produced it. To do so, they ran a few database queries and, if well organized, copied the results into a template. As you might imagine, this model was slow and full of potential problems. If the request wasn't written clearly enough or the member of IT misunderstood anything, a new report had to be generated. If someone wanted to ask a follow-up question, a new report had to be generated. And if the data changed? A new customer emerged? Processes changed? You guessed it.
Modern business intelligence, on the other hand, flips the model. Instead of generating static reports, tools and processes are implemented so the end users are able to directly interact with the data and build their own interactive reports. This moves the IT department from the position of conduit—taking requests, writing queries, and delivering results—into the position of facilitator—implementing software tools and processes to expose the data in easily understood formats. With the correct software tools, such as Plutora's business intelligence platform, users draw insights about their questions in real time.
Types of Users
I mentioned earlier that modern business intelligence allows the end users to directly interact with the data and build their own interactive reports. In order to best meet the needs of your organization, it's important to know the types of users. Depending on your company, the following order may differ, but for most organizations, these users will interact with business intelligence tools from most to least often:
Business users come from all across the organization. Depending on their role, they will interact with and/or build dashboards and visualizations in software systems. You can think of business users much the same as you do for other software systems. A few will be more like "power users" who require more permissions and features, while most will simply need access to a few specific components (or, in this case, interactive reports).
Data analysts and data scientists are where the picture diverges from most software systems. These users have strong statistical backgrounds and work toward generating complex and strategic insights. As a result, they will both interact with the software systems and require some input into the data processing and flow.
IT users mainly play a role in building, implementing, and maintaining the business intelligence software, processes, and infrastructure. Occasionally, IT users will also utilize business intelligence software—much the same as business users do—to gather insights about IT processes.
Organization leadership is the final segment of common business intelligence users. These users, generally speaking, aren't involved in making reports or processing data. However, they have their own set of executive dashboards, which make key business metrics easy and incredibly fast to digest.
Self-Service Business Intelligence
As you might imagine, facilitating the different types of users requires well-made data processing pipelines and specialized software tools. One of the ways these tools have developed over recent years is to become self-service portals. These provide intuitive UIs that allow users to find and transform data in easy-to-understand ways.
While these tools are designed to be easy to use, there are certain pitfalls you'll need to be aware of. First and foremost, users still require some training and instructional documentation. This is the single most effective step in preventing other problems. Training and instructions make it much more likely that users don't misuse the data and end up with conflicting, chaotic, and misleading information that varies between users and departments. Similarly, it's best to have a centralized approach to software licensing. This may seem like it comes with more work, but it helps to maintain proper access management and prevent high licensing fees. In addition, you'll need to be aware of potential data security and privacy concerns with so many users having access to business data.
Common Business Intelligence Software Features
With something like business intelligence, there are endless possible software systems and tools that can be implemented. The list of available tools and market leaders is ever-changing, so there's not much point in me listing my favorites or the pros and cons of the market as it sits. Instead, I'll introduce the most common features of software systems and tools:
Visual analytics and visualization features allow users to select different graphs or visual representations with which to present the data.
Dashboards are a specific type of visual analytics display. They contain a set of predefined graphs and metrics. Users have limited interactivity, such as showing and hiding metrics, or changing the focus so different metrics are highlighted.
Drill-down features are designed to introduce details in manageable chunks. They show an overview of the data and allow users to interactively look into certain aspects in more detail.
Reporting features bring traditional business intelligence into modern practice. They allow users to easily generate static and periodic reports with the insights they've gathered.
Data mining, meanwhile, is more likely to be used by data analysts and scientists. It's all about discovering patterns and trends in large data sets.
Extract-transfer-load (ETL) features are primarily in the domain of IT users. The features take the hassle out of importing data from one data store into another.
Business Intelligence Strategy
As an IT leader, you will have a major influence over business intelligence strategy. The best approach is to consider it a part of ongoing digital transformation. Business intelligence fits right in the mold.
When considering business intelligence strategy, it's best to take a careful and structured approach. Business intelligence tools take time to set up because of the data and processing they consume. Similarly, they're used across the business, so they're slow and difficult to swap out. Selecting the most popular tool and throwing data into it just won't cut it. A bad worker may blame their tools, but even a good worker will struggle to cut down a tree with a spoon.
Selecting the Right Tools for Your Organization
If you have a software selection process in place, apply it to business intelligence tools. If not, I suggest creating one for your business intelligence tool search with steps similar to the following:
Define requirements. Answer the key questions that matter to your business: Why are you implementing business intelligence? What data do you have available? How tech-savvy are your users? What are you using the data for? What else could you use it for? Then, build a list of software requirements to answer these questions.
Divide requirements by importance. Once you have your list of requirements, split it into must-haves and nice-to-haves. If that's not enough, add in more importance categories.
Research available tools and create a shortlist. Compare the tools to your requirements list and see which ones meet the most important requirements. In addition, look into licensing details and available pricing information.
Get a demonstration of your short-listed tools. Go into the demonstration with a list of questions and things you'd like to see. Rate and compare the tools in your shortlist.
Test, test, test. The vendors are there to sell. They're going to show off the best parts of their software and be clever in the way they answer your questions. Test any software in a proof of concept to see if it does meet your needs.
Negotiate a deal. Most of the modern tools follow a per-user or per-license model. Negotiate pricing or benefits to ensure that your decision makes financial business sense.
If nothing meets enough of your requirements, or the deals aren't right, go back to step two and see if there are alternative ways of splitting requirements. You may find that you need to look at a few different types of tools.
Implementing Business Intelligence Tools
Implementing business intelligence tools is more than setting up data processing pipelines and user accounts on your chosen software. That work is no doubt important and requires careful consideration, testing, and experimentation. However, the key to successfully implementing business intelligence tools lies with the end users.
Even though business intelligence tools are designed to be user-friendly, that doesn't mean they will be instantly accepted. With the introduction of any system, you're asking users to change their well-worn and comfortable workflows. Success hinges on these users changing their ways. Again, we fall back to training and documentation. It might sound boring, but well-designed training will demonstrate the benefits of business intelligence tools, and documentation will allow users to check things when they're testing the tools out.
Regular Reviews and Feedback
The users may be your hardest hurdle, but they're also your biggest ally in business intelligence strategy. Remember, the aim of business intelligence is to facilitate data-driven decision-making by allowing users to turn business data into meaningful insights. Data-driven decisions help to ensure that your business hits the target more often than not. Regular reviews of the software tools and processes, as well as feedback from users, will allow you to assess whether you're meeting these criteria.
The Future of Business Intelligence
As an IT leader, it's probably second nature for you to have an eye on the future. As such, I thought I'd briefly mention the future of business intelligence. And I'm sure that it will come as no surprise to find the words machine learning and artificial intelligence on the lips of business intelligence experts. The capabilities of these approaches will continue to grow. As a result, they will allow companies to be able to draw insights about data before the users see it. This will mean that users will be able to make more informed decisions about more of the data in the same amount of time. If you're familiar with decision support systems, you may consider it as business intelligence heading towards decision support.
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