What is business intelligence (BI)? Definition, purpose, and importance.

Business intelligence (BI) is the brains behind many business decisions — yet it may feel difficult to capitalize on its potential. Learn how to develop a business intelligence strategy with Adobe.

Transform raw data into easy-to-use insights and put plans into action with this guide to business intelligence.

In this guide we’ll cover:

• What is business intelligence in simple terms?
• How does business intelligence work?
• What do organizations use business intelligence for?
• Why is good data governance important?
• What is a business intelligence platform and its core functions?
• How can I develop a business intelligence strategy?
• How does business intelligence help improve a company’s efficiency and decision-making?
• What are some of the challenges you might face implementing business intelligence?
• Examples of business intelligence use cases.
• What will business intelligence look like in the future?
• Can I hire an outside agency to manage my company’s data?
• How does business intelligence differ from business analytics?
• Getting started with business intelligence.

Functionally, business intelligence is a form of data analytics — this process involves gathering, analyzing, and visually presenting data. With proper knowledge, this data can then be transformed into actionable insights to inform decision-making.

Simply put, it analyzes data and makes it actionable. Usually, this is done through BI tools, using a wide range of data both in-house, third-party, current and historical.

Why is business intelligence so important?

Business intelligence (BI) is essential for organizations seeking to leverage data-driven insights for smarter decision-making. Companies that integrate BI effectively will gain a competitive edge, drive innovation, reduce risk, and improve overall business performance.

According to McKinsey, in 2025, data-driven enterprises will significantly outperform competitors by using advanced analytics, AI, and automation to anticipate market trends, enhance customer experiences, and optimize business processes.

When looking at how business intelligence works, it’s worth looking at the core processes and methods that form it:

• Data collection (mining). Data collection, also known as mining, is when data is collected from a range of sources. For example, this could be website analytics, customer purchase data from a POS system, or information about customer behaviors.
• Data preparation. Once collected, data preparation and storage ensure your data is accurate, consistent, and usable for generating meaningful insights.
• Analysis. To provide insights, data must first be analyzed, checked, and consolidated into meaningful information to ensure accurate reporting.
• Reporting. The reporting process involves organizing and presenting data in a structured format to support decision-making. It is then distributed to those decision makers.
• Data visualization. Data visualization is about making the data-driven insights easier to digest and will usually take place alongside reporting if desired. Reports, dashboards and graphs help communicate information visually for clearer decision making.

These core processes come together to generate actionable insights by analyzing data in comparison to key performance indicators (KPIs) to develop an action plan. This plan can lead to optimizing processes, refining marketing strategies, resolving supply chain challenges, or enhancing the customer experience for improved business performance.

Companies use business intelligence solutions to understand how to improve their decision-making based on the reporting and the visuals they’re seeing. The goal of BI is to improve business operations using data — which can help improve anything from strategy to execution.

For example, let’s say that your company comes out with three new products. You assign quotas and performance metrics to salespeople, customer success managers, and others to help sell the new products. Business intelligence tools would delve into financial data sources each quarter, visualize the data into a report, and then use that report to determine what is and isn’t working. The best part of BI software is the ability to view lots of different types of historical data in a single environment, to make better, more informed business decisions.

Different sectors may use business intelligence to monitor different metrics, but the goal is the same. So, whether you’re a retail chain looking at cost-saving methods by comparing different chains from region-to-region, a sales company creating a detailed targeting report, or a security firm trying to boost your protection — BI can provide the data necessary for more effective decision making. That means you spend more time on action than accumulation.

Lots of new businesses don’t think to set up their data analytics and business intelligence, because they want to focus on sales and other seemingly more important parts of a business. But a huge part of business intelligence is having good data governance to make sure data is used and managed correctly.

A key issue that arises with modern business intelligence is the slow pace of receiving answers to data queries. A business intelligence tool could take anywhere from two days to two months to answer a query about stored data. To counter this, we’ve seen the rise of something called self-service BI, a system where you can get answers faster, but the data is not always 100% correct. This system is not necessarily bad, because the answers can still be fairly accurate, but without good data governance, your company could have several different people making conclusions about company data, and these conclusions might clash.

Constant (and consistent) data monitoring is also important to ensure there are no leaks — data must be accurate, but it must also be secure and private. Usually, you’ll rely on a data analyst who can ensure that the criteria are met for safe and accurate data, implementing the correct access controls and security protocols, as well as distributing data in a usable and understandable way.

While this may seem like a difficult undertaking, it’s important to start these initiatives in the early stages of implementing BI. Additionally, as this information is sensitive there is likely a need to keep it in-house.

A business intelligence platform is a technology that helps businesses in gathering, processing, and visualizing data to make data-backed decisions. If business intelligence is a concept, a business intelligence platform is what realizes it.

Business intelligence core functions.

• Business monitoring and measurement. Business intelligence tools can track important statistics, such as KPIs. While other systems may have been able to pull reports in the past, with current BI tools you can get that information fast — allowing for quicker decision making and proactivity.
• Data analysis. Tracking data is one thing, but analysis is much more. BI tools can run data to provide insights on important business decisions, leading to quicker and more strategic decision-making.
• Reporting and information delivery. While data is useful, it can also obstruct operations — or, if misunderstood, lead to poor decisions. BI tools enhance your data delivery methods, allowing you to visualize what people need to see. This means data is readable, quickly understood, and actionable without needing to write up a long-winded report by hand.
• Predictive analysis. BI analyzes historical data alongside real time. The introduction of predictive analysis enables data forecasting, enabling you to query and plan for all those what if scenarios, mitigating risk and hitting trends right as they happen.

1. Collect and transform data from multiple sources.

You want data from multiple sections of your business. ETL (extract, transform, load) processes are an essential function to gather both structured and unstructured data from a plethora of sources into a unified, easily accessible repository. This means that you can use BI best practices on multiple areas of your business, with clean, consistent, up-to-date data.

2. Build strong data management processes.

Building a strong data management process is essential to make data usable, secure and manageable. Strong data management also means that your BI tools are fed high-quality, relevant data. Without a strong data management process, your data could become untrustworthy or compromised. This could lead to bad decision making.

3. Select the right BI tools.

One of the quickest steps to BI success is selecting the relevant BI tools for your business. In some instances, you may need several BI tools to meet multiple departmental needs.

Ultimately, you want to align your tool selection with your specific business needs and user requirements to ensure your business intelligence solutions are suited specifically to your businesses structure and goals.

4. Uncover trends and inconsistencies.

Data mining uses exploratory, descriptive, statistical, and predictive analytics to identify trends, patterns, and anomalies in your data. Automation can help enhance this process by rapidly processing large datasets, improving accuracy, and enabling real-time insights.

5. Use data visualization to present findings.

Translating complex data into easily understood visual formats is essential to informing decisions. Clear, concise communication of findings results in clear direction and quicker decisions. Dashboards, charts, graphs and maps are all great tools for visualizing complex data for easier communication.

6. Act on insights in real time.

Data is great to have, but without action it can become outdated and stagnant fast. BI empowers real-time decision-making by providing immediate access to relevant data and insights. That means your business can make short and long-term changes to address challenges, adapt to market changes, prepare for predicated outcomes, and boost operational efficiency.

Business intelligence tools, methods and practices aren’t just add-ons — they change the way your business thinks and operates. Properly implemented, BI encourages a culture shift and brings with it a list of benefits:

• Data consolidation. BI pulls your data into one place, including both internal and external data. That means a complete analysis, so you’ve got the full picture when designing your business strategy or implementing changes.
• Clear reporting. Data reports are made clear, so you can ask questions and get answers in a format that is clear and understandable.
• Efficiencies. Businesses can monitor their operations against KPIs or performance benchmarks to improve processes through data-insights. For example, you could use BI to eliminate supply chain issues, staff performance, and determine where organizational changes might be necessary.
• Data insights. Implementing BI practices and tools transitions your business to becoming more data-driven, resulting in new opportunities, increased performance and productivity, and a competitive advantage. Data insights can provide information on customer trends, preferences or behaviors, as well as notable market changes, giving you the information to quickly capitalize.
• Customer and employee satisfaction. Giving your customer service staff the capacity to analyze information can result in quicker or proactive solutions for customers. Internally, BI can empower employees to make informed decisions, expediting workflows through access to information, or by streamlining mundane tasks.

The comprehensiveness, scope, and reach of business intelligence across an entire business is great for decision-making because it helps you understand what has happened in your business using several different data channels. Understanding the key goings-on in your company helps you to rethink the strategies established in your business.

Better decision-making goes together with efficiency, because the more efficient you can be, the better and faster you can be at making data-driven decisions. Business intelligence helps you extract better insights to be more efficient, especially if you’re using a tool like Adobe Analytics with Adobe Customer Journey Analytics. Other BI tools are much slower and do less, compared with Adobe Analytics. Being able to immediately pivot and use BI or augmented analysis to answer the questions you need to answer in real time is critical.

How does business intelligence evolve, and how does that affect a business?

As a business’s big data evolves, its business intelligence will evolve as well. With business intelligence, you can have many different data channels in one storage place: financial data, supply chain data, and even HR data. And while you might not have all your data channels together at the same time, you can add new ones. Each one of those new data sets will give you new insights about your company as it’s combined with the other sets.

These are insights that you wouldn’t gain if you were looking at each data set separately, and they only serve to improve your business’s efficiency.

Conflicting interpretations and bias in self-service BI.

Self-service BI tools, while empowering for individual teams, can lead to conflicting conclusions and hinder a unified organizational strategy. Unconscious bias can influence data and skew data analysis, resulting in a negative impact on decision-making. It is important to remain critical, impartial and logical when handling data.

Data integration complexity and skills gap.

Data integration comes with a high level of complexity, especially when unifying raw data from diverse sources, before it’s filtered into digestible reports. Specialisms in data science, engineering, and architecture are essential for your team, as well as your data accuracy and reliability.

High upfront investment and long-term ROI.

You can’t dip your toe into business intelligence — it’s a system that requires a high upfront investment in terms of knowledge and implementation. Likewise, you won’t see immediate, sweeping changes to your ROI. It’s a long-term effort that boosts decision-making and operational efficiency, rather than bringing in instant cashflow.

Customer service.

With a unified data source, your customer service staff can solve customer queries and determine pain points in their purchase journeys. In turn, this can lead to a better experience for the customer, and the ability for customer service staff to better provide an enjoyable experience with your brand.

Retail.

Retailers can use BI to analyze behaviors in response to marketing campaigns, regional sales data, and take note of inventory. Additionally, they could identify and solve supply chain issues.

Sales and marketing.

Sales teams can utilize BI tools to leverage customer data, determine market trends, assess campaign performance, and make data-backed decisions to implement new strategies to boost sales.

Healthcare.

With BI, you can save your staff time, as inventories become easier to track and manage, meaning less time checking and calculating. Ensure you have the necessary medication in stock and give customers the means to get the answers they need to time-consuming questions without waiting for medical personnel.

Finance.

Financial firms can use predictive data to make current-day decisions for future success. Identify opportunities for investment, determine metrics branch-by-branch and make informed decisions with granular information.

Business intelligence as a technology has gone through many evolutions — not only have technologies improved, but users have learned to better harness their potential. As we look forward, there are some notable changes to expect:

• Emergence of new analytics approaches. New forms of BI analytics are constantly emerging, giving users access to a suite of analysis tools. There are several new areas of BI, such as composable analytics which takes a building-blocks/modular approach to the development of BI applications by utilizing a range of tools. Additionally, methods like continuous intelligence harnesses BI and AI to provide real-time data analytics and insights consistently, meaning you’re aways in the know.
• Increased focus on governing BI use. Governance is an essential component to BI use — regulatory requirements grow as the technology does, and remaining compliant is essential. Likewise, as companies rely more and more on BI, data security is going to hold even more weight.
• Low-code and no-code development. No development and low-code development are initiatives led by BI vendors to allow for applications to be made without coding experience.
• Efforts to improve data literacy. Data-literacy is necessary, especially with the rise of self-service BI and its importance in the day-to-day operations of most businesses. That means data literacy is set to become an important part of company training efforts.
• Shift to the cloud. BI systems have begun their migrations to the cloud, as cloud data warehouses are becoming more common.

Because of the breadth, scope, and confidential nature of your company data, it wouldn’t be wise to employ a third-party team to manage your data. Besides security purposes, the reason an in-house team is better is because every business is going to have different processes, different goals, and different needs. Coming up with a data governance plan tailored to your company is much easier with an internal team. This doesn’t have to be the team’s sole responsibility if that doesn’t work for your company, but it should be one of the roles for a group in your organization.

Additionally, you may want to consider the costs of outsourcing data management versus developing your own, in-house team. Not only does this provide you more control, but your team be easily expanded and expertise unique to your company can be accrued.

There are some fundamental differences between business intelligence and business analytics, even though they are often used interchangeably. They share a relationship, but business intelligence functions as a subset of business analytics.

Business analytics tend to look forward through processes like data mining, modeling, and machine learning to predict future events. Business intelligence on the other hand focuses more on evaluating past business data to clarify or give meaning to existing information. It’s about historical data and business KPIs guiding business decisions, rather than purely predicting the future.

Before you get started with business intelligence, you need a solid understanding of its core components like data analysis, data visualization and database management. With those skills in-hand, you can start using business intelligence solutions to encourage better data-driven decisions and growth by transforming raw data into actionable insights.

Tools like Adobe Customer Journey Analytics provide real-time, omnichannel insights by consolidating data from various channels, enabling enhanced, data-driven decision-making for your business.