Business intelligence (BI) provides data that helps companies make timely and informed decisions. We explain how implementing BI software can give companies of any size a competitive edge. Plus, we share examples of how some of the most tech savvy companies are using BI.

What Is Business Intelligence (BI)?

Business intelligence refers to the technology that enables businesses to organize, analyze and contextualize business data from around the company. BI includes multiple tools and techniques to transform raw data into meaningful and actionable information.

BI systems have four main parts:

  1. A data warehouse stores company information from a variety of sources in a centralized and accessible location.
  2. Business analytics or data management tools mine and analyze data in the data warehouse.
  3. Business performance management (BPM) tools monitor and analyze progress towards business goals.
  4. A user interface (usually an interactive dashboard with data visualization reporting tools) provides quick access the information.

German market research firm Statista estimates the volume of data created worldwide by 2024 will be 149 zettabytes. This vast amount of data, or "big data," has made business intelligence systems relevant for companies that want to harness its power for a competitive advantage. Many BI systems use artificial intelligence (AI) and other capabilities as a part of business analytics.

Key Takeaways:

  • Business intelligence offers a wide variety of tools and techniques to support reliable and accurate decision-making.
  • The most successful companies use BI to make sense of ever-increasing amounts of data in a fast and economical way.
  • BI-based, data-driven decision-making helps companies stay relevant and competitive.

Where Is BI Used?

Sales, marketing, finance and operations departments use business intelligence. Tasks include quantitative analysis, measuring performance against business goals, gleaning customer insights and sharing data to identify new opportunities.

Here are examples of how various teams and departments use business intelligence.

  • Data scientists and analysts:

    Analysts are BI power users, and they use centralized company data paired with powerful analytics tools to understand where opportunities for improvement exist and what strategic recommendations to propose to company leadership.

  • Finance:

    By blending financial data with operations, marketing and sales data, users can pull insights from which decisions can be acted upon and understand factors that impact profit and loss.

  • Marketing:

    Business intelligence tools help marketers track campaign metrics from a central digital space. BI systems can provide real-time campaign tracking, measure each effort’s performance and plan for future campaigns. This data gives marketing teams more visibility into overall performance and provides contextual visuals for sharing with the company.

  • Sales:

    Sales data analysts and operation managers often use BI dashboards and key performance indicators (KPIs) for quick access to complex information like discount analysis, customer profitability and customer lifetime value. Sales managers monitor revenue targets, sales rep performance along with the status of the sales pipeline using dashboards with reports and data visualizations.

  • Operations:

    To save time and resources, managers can access and analyze data like supply chain metrics to find ways to optimize processes. Business intelligence can also ensure that service level agreements are met and help improve distribution routes.

In a genuinely data-driven company, every department and employee can take advantage of BI-generated insights.

What Is the Value of Business Intelligence?

Business intelligence's highest value is its ability to support data-driven decisions. BI transforms pools of raw data into useful information that informs decisions and leads to actions that yield positive bottom-line impact.

BI systems drive decisions based on historical, current and potential future data.

  • Descriptive analytics:

    These analytics reveal what has happened or is happening and are part of dashboards, business reporting, data warehousing and scorecards. When managed well, you’ll have a better understanding of problem areas in your business and can find opportunities to improve.

  • Predictive analytics:

    These advanced analytics use data mining, predictive modeling, and machine learning to help make projections of future events and assess the likelihood that something will happen.

  • Prescriptive analytics:

    These analytics reveal why you should take a particular action. Prescriptive analytics enable optimization, simulation, decision modeling and provide the best possible analysis for business decisions and actions.

BI software gathers sales, production, financial and many other business data sources. Many companies use industry data to benchmark performance against competitors.

The Benefits of Business Intelligence

Benefit Description
Visualization Advanced interactive dashboard representations of data using simple user interfaces offer the ability to visualize information in a graphical format to understand data more insightfully.
Connection The ability to manage and meld access to various data sources provides a 360-degree view of your business and your company that is not possible in a siloed data environment.
Collaboration Tools enable data-informed improvements in various business functions like marketing, finance, sales, operations, finance, support, HR and customer care individually and together.
Multi-Platform, Multi-User BI applications work online and in mobile environments. Tools improve system performance so enterprises can distribute more information to targeted users faster. In multi-terabyte data warehouses, these tools provide excellent query performance.
Scalability Many systems offer user scalability to support advanced reporting and analysis. Dashboards and reports are available to many users, not just restricted to the organization's data analysts or executives.
Speed and Competitive Edge BI can perform faster reporting, analysis and planning because of access to global data. The system's analysis capabilities make it possible to react to market or other conditions quickly.
Trusted Data and Accuracy Reports can be highly customized, and KPIs monitored using more than one data source. Real-time generated reports offer relevant data, which helps organizations, and their employees make better decisions. These reports provide insights, access, accuracy, and relevance.
Analysis and Insights BI processes vast amounts of data to forecast, budget, plan, and stay current. Competitive analysis helps companies understand the competition and benchmark competitor performance. This business intelligence enables product and service differentiation.
Decision-Making Support Companies gain a competitive edge when they can leverage the existing data at the right time to make accurate decisions faster.
Efficiency and Productivity A 360-degree view of all activities helps companies identify issues, improve operations, increase sales, and in turn, increase revenue.
Customer Satisfaction BI can help you identify what services or products you're lacking and improve customer satisfaction by making necessary changes. Reports help you understand customer behavior, develop user personas, and use real-time data on the customer's feedback to make corrective changes and improve customer service and, therefore, satisfaction.
Employee Satisfaction Using BI data, you can assess team members' strengths and weaknesses and assign relevant training modules to support success. BI tools can automatically recognize positive behavior while regularly tracking worker contributions and improvement.
Savings BI insight into the corporation's raw data will help decision-makers analyze cost-saving opportunities like excess inventory, human resource redundancies, marketing overages, too many vendors or waste in facilities management.
Savings and Profitability BI tools can analyze any discrepancies, inefficiencies, or errors. BI helps to increase profit margins by providing insights that lead to future sales and guide where to spend future budgets.
Strategic and KPI Targeting BI assists companies in gaining a competitive edge by helping them find new opportunities and build smarter strategies. Use the data to identify market trends and help improve profit margins for the company. Reports based on tracking established KPIs ensure the enterprise stays on course to match or exceed goals.

Business intelligence has many benefits and can be a useful tool to achieve positive outcomes for your business.

Case Studies: Real-World Examples of Business Intelligence at Work

Fast, data-informed decision-making can drive success. High customer expectations, global competition and narrow profit margins mean many organizations, regardless of size or sector, look to BI for a competitive advantage.

What is an example of business intelligence? Using data to serve up personalized ads based on browsing history, providing contextual KPI data access for all employees and centralizing data from across the business into one digital ecosystem so processes can be more thoroughly reviewed are all examples of business intelligence. Here are some case studies that show some ways BI is making a difference for companies around the world:

  1. BI Increases Company Revenue is the leading internet shopping mall in Korea with 13 million customers.

    • Challenge: With more than 1 million site visitors daily, company executives wanted to understand why customers abandon shopping carts.
    • Solution: The assistant general manager of the marketing planning team implemented customer experience analytics, the first online behavioral analysis system applied in Korea. The manager used the information to understand customer behavior and implement targeted marketing and transform the website.
    • Results: With the insights from the new BI analytics program, there was an increase in customer loyalty after one year and an increase of $10 million in sales. The changes came from identifying the causes of shopping cart abandonment, such as a long checkout process and unexpected delivery times and remedying the situation.
  2. Cementos Argos: BI Improves Financial Efficiency

    Cementos Argos is a cement company with operations in the U.S., Central and South America and the Caribbean.

    • Challenge: The company looked for an overall competitive advantage and a way to support better decision-making.
    • Solution: Cementos Argos created a dedicated business analytics center. The company invested in experienced business analysts and data science teams and used BI to leverage data.
    • Results: The company standardized the finance process and applied big data to gain more in-depth insight into customer behavior which yielded a higher profitability level.
  3. Baylis & Harding: BI Provides Decision Making Process Support

    Baylis & Harding is a wholesale distributor specializing in world-class toiletries and gift sets found in major and independent resellers.

    • Challenge: The company needed to give managers and executives greater visibility into financial, customer and sales data to make better decisions and expand the business.
    • Solution: Managers and executives used business intelligence tools to create standard and ad hoc reports.
    • Results: Company executives and managers now have instant access to the business data they need to act proactively. They can create custom dashboards with KPIs relevant to their areas of focus and share the goals and performance details with their teams without having to request a custom report from IT.
  4. Sabre Airline Solutions: BI Accelerates Business Insights

    Sabre Airline Solutions provides booking tools, revenue management, web and mobile itinerary tools, as well as other technology, for airlines, hotels and other companies in the travel industry.

    • Challenge: The travel industry is remarkably fast paced. And Sabre's clients needed advanced tools that could provide real-time data on customer behavior and actions.
    • Solution: Sabre developed an enterprise travel data warehouse (ETDW) to hold its enormous amounts of data. Sabre executive dashboards provide near real-time insights in user-friendly environments with a 360-degree overview of business health, reservations, operational performance and ticketing.
    • Results: The scalable infrastructure, graphic user interface, data aggregation and ability to work collaboratively have led to more revenue and increased client satisfaction.
  5. Spear Education: BI Streamlines Internal Processes and Workflow

    Spear Education is a leader in continuing education for dentists.

    • Challenges: Spear's phone system was lacking functionality that could make its customer service reps work more efficiently and provide better customer service. For example, their phone system didn’t record calls and wasn’t connected to a customer relationship management (CRM) tool.
    • Solution: After some research, Spear connected its call center software with its BI solution to maintain more thorough customer interaction records and provide a complete view of customer interactions.
    • Results: After implementing a new solution for their contact center, Spear increased agent efficiency and saved the company 35 hours of rep time per week. Spear's agents now reinvest that time by placing 4,000 more outbound calls every week.
  6. Univision: BI Increases Market Spend Efficiency

    Univision is an American Spanish-language, free-to-air television network. It’s the largest provider of Spanish-language content in the country.

    • Challenge: Univision wanted more visibility into its data to unify and focus on targeted ad campaigns.
    • Solution: Programmatic TV is an automated and data-driven approach to buying and delivering ads against video content on television, including ads served across the web, mobile devices and connected TVs, as well as linear TV ads served across set-top boxes. With BI powered with information from applications like Facebook, Google Analytics and Adobe Analytics, the company can obtain more value from its programmatic advertising.
    • Results: Univision achieved an 80% growth in yield during the first quarter after implementing business intelligence.
  7. New York Shipping Exchange: BI Reduces IT Dependency

    New York Shipping Exchange (NYSHEX) is a shipping-technology company working to improve the process of shipping overseas.

    • Challenge: To make sense of overall company performance, NYSHEX would manually extract data from its proprietary application and various cloud apps and then import it into Excel. This was a laborious process and few people had access to the data, and most of the requests for reports fell on the engineering team to execute.
    • Solution: NYSHEX invested in BI, centralized its data into one system and gave the entire company access empowering those with no coding knowledge to dive deep into analysis.
    • Results: Thanks to business intelligence and other efforts, in 2019, the company more than tripled its volume shipping between Asia and U.S.
  8. Stitch Fix: BI Connects Departments, Data and Processes

    Stitch Fix provides online personal clothing and accessory styling services. The company uses recommendation algorithms and data science to personalize clothing items based on size, budget and style.

    • Challenge: The company wants to reduce returns, keep repeat customers and generate word-of-mouth business with recommendations from customers to their friends and family.
    • Solution: Stitch Fix collects data within BI throughout the buying process, meaning the more a customer shops with Stitch Fix, the better the styling team comprehends their taste in clothing. The company hired astrophysicists to decode the different personal style components—intricate work that would be impossible without the powerful analytics of BI.
    • Results: Using business intelligence to profile buyers and their preferences, the company, which started in 2011, reported a customer base of 3.4 million in 2020 and revenues of $1.7 billion in fiscal year 2020.
  9. SKF: BI Streamlines Manufacturing Processes

    SKF is a Sweden-based global manufacturer and supplier of bearings, seals, mechatronics and lubrication systems with 17,000 distributor locations.

    • Challenge: SKF's broad geographic coverage and product diversity required consistent market size and product demand forecasting to adjust its manufacturing. The company needed to simplify the complex Excel files used to produce a demand forecast.
    • Solution: Management realized it needed to implement a business intelligence to serve as a single source of reliable information. Maintaining the system is easier than trying to manage everything with Excel, and now employees don’t have to rely on outdated spreadsheets and can access simple-to-understand reports and dashboards.
    • Results: By centralizing data assets into a single system, SFK was quickly able to share data and analyses between several departments — including sales, manufacturing planning, application engineering, business development and management. SKF now combines demand forecasts between departments and has improved the planning process.
  10. Expedia: BI Builds Customer Satisfaction

    Expedia is the parent company of some top-tier travel companies, including Expedia, Hotwire and TripAdvisor.

    • Challenge: Customer satisfaction is essential to the company's mission, strategy and success. The online experience should mirror a good trip experience, but the company had no visibility into the voice of the customer.
    • Solution: The company had mountains of data they were manually aggregating, leaving little time for analysis. Using business intelligence, the customer satisfaction group was able to analyze customer data from across the company and link results with 10 objectives related directly to corporate initiatives. Owners of those KPIs build, manage and analyze data to discover trends or patterns.
    • Results: The customer service team can see how well it is doing against KPIs in real-time and take corrective steps if necessary. Plus, other departments can use the data. For example, a travel manager can use BI to discover high volumes of unused tickets or offline booking and create strategies to adjust behavior and increase overall savings.

Use Cases: Examples of Business Intelligence Strategies Prominent Companies Use

The most successful companies use BI to drive revenue, customer loyalty, operational effectiveness, ad delivery, drive shareholder value, predict customer behavior and develop new business opportunities.

Examples of How Leading Companies Use BI to Propel Their Success

What companies use business intelligence? From financial institutions like American Express to social media giant Facebook and outdoor retailer REI, the most advanced and successful companies in the world leverage BI. Here’s how some are using BI to power their prosperity.

  1. American Express:

    Business intelligence is instrumental in the finance industry. American Express has been using the technology to develop new payment service products and market offers to customers. The company's experiments in the Australian market have rendered it capable of identifying up to 24% of all Australian users who will close their accounts within four months. Using that information, American Express takes steps to retain customers. BI also helps the company accurately detect fraud and protect customers whose card data may be compromised.

  2. Chipotle Mexican Grill:

    The restaurant chain has more than 2,400 restaurants worldwide. It implemented BI to track operational effectiveness. Chipotle can now monitor every restaurant's operational efficiency and serve up detailed information in dashboards. By standardizing the reporting and working from the same data ecosystem, Chipotle was able to make uniform KPIs for benchmarking and sharing improvement and success stories. That solution saves thousands of hours for the company.

  3. Coca-Cola:

    With 35 million Twitter followers and a whopping 105 million Facebook fans, Coca-Cola benefits from its social media data. Using AI-powered image-recognition technology, the company can tell when photographs of its drinks post online. This data, paired with the power of BI, gives the company important insights into who is drinking their beverages, where they are and why they mention the brand online. The information helps serve consumers more targeted advertising, which is four times more likely than a general ad to result in a click.

  4. Delta Airlines:

    Big data and BI support customer service and differentiate the Delta experience. Flight attendants now have the tools to personally thank and recognize valued corporate travelers. Positive customer experience coupled with thoughtful programs help position Delta as a leader in the business travel space. While any Delta customer can receive personal recognition, the airline goes the extra mile to serve corporate travelers and its medallion members. This enhancement provides more opportunities to thank flyers and build customer loyalty.

  5. Ellie Mae:

    The company processes 35% of U.S. mortgage applications. Record low-interest rates created a high demand for loan processing. To make data more accessible for lenders, Ellie Mae developed a hosted data warehouse model that allows lenders to analyze data by connecting a BI application directly to their systems without replicating the data to a local data warehouse. Capital market teammates can use that data to navigate volatile markets, allowing them to provide excellent service and process loans for their customers.

  6. Lowe's:

    The home improvement company uses business intelligence to merge what the customer tells them with actual behavior occurring online and in the store. They use this data to discover deeper insights that lead to better product assortment and staffing at specific store locations. The process of data analysis drives sales and also serves the customer. For instance, Lowe's uses predictive analytics to load trucks specific to individual zip codes, so the right store gets the right type and amount of product.

  7. Netflix:

    The online entertainment company's 148 million subscribers give it a massive BI advantage. How does Netflix use business intelligence? Netflix uses data in multiple ways. One example is how the company formulates and validates original programming ideas based on previously viewed programs. Netflix also uses business intelligence to get people to engage with its content. The service is so good at targeted content promotion that its recommendation system drives over 80% of streamed content.

  8. REI:

    REI uses its business intelligence platform for customer segmentation analysis, which helps inform decisions like member lifecycle management, shipping methods and product category assortments. BI-based decisions also inform member acquisition initiatives with detailed demographics on factors such as gender to personalize ads. The insights from BI help determine everything from how to display content on the website and how to segment email campaigns.

  9. Starbucks:

    Through its popular loyalty card program and mobile application, Starbucks owns individual purchase data from millions of customers. Using this information and BI tools, the company predicts purchases and sends individual offers of what customers will likely prefer via their app and email. This system draws existing customers into its stores more frequently and increases sales volumes.

  10. Tesla:

    The innovative automotive company uses BI to connect their cars wirelessly to their corporate offices to collect data for analysis. This approach links the carmaker to the customer and anticipates and corrects problems such as component damage, traffic or road hazard data. The result is a high customer satisfaction score and better-informed decisions on future upgrades and products.

  11. Twitter:

    The social media company deploys BI with AI to fight inappropriate and potentially dangerous content on its platform. Algorithms rather than human users identify 95% of suspended terrorism-related accounts.

    BI and AI also support fine-tuning to improve the overall user experience. Twitter personnel and its business intelligence tools monitor live video feeds and categorize them based on subject matter. They use this data to enhance search capabilities, and help algorithms identify videos users might be interested in viewing.

  12. Uber:

    The company uses business intelligence to determine multiple core aspects of its business. An example is surge pricing. Algorithms monitor traffic conditions, journey times, driver availability and customer demand in real-time, meaning prices adjust as demand rises and traffic conditions change. Dynamic pricing in real-time action is akin to what airlines and hotel chains use to adjust cost based on need.

  13. Walmart:

    The retail behemoth uses BI to understand how online behavior influences online and in-store activity. By analyzing simulations, Walmart can understand customer purchasing patterns, for example, how many eyeglass exams and glasses are sold in a single day, and pinpoint the busiest times during each day or month.

How to Improve Your Business Intelligence to Make Your Company a Leader

BI and tools like AI may seem complicated. However, current user interfaces are straightforward and easy to use. So even smaller companies can take advantage of data to make profitable and positive decisions.

Examples of Business Intelligence Tools and Techniques

What are examples of business intelligence tools? Predictive modeling, data mining and contextual dashboards or KPIs are just some of the most common BI tools. Here are more tools and how they’re used.

  • Analytics:

    A BI technique that probes data to extract trends and insights from historical and current findings to drive valuable data-driven decisions.

  • Dashboards:

    Interactive collections of role-relevant data are typically stocked with intuitive data visualizations, KPIs, analytics metrics and other data points that play a role in decision-making.

  • Data mining:

    This practice uses statistics, database systems and machine learning to uncover patterns in large datasets. Data mining also requires pre-processing of data. End-users use data mining to create models that reveal patterns.

  • Extract Transfer Load (ETL):

    This tool extracts data from data-sources, transforms it, cleans it in preparation for reports and analysis and loads it into a data warehouse.

  • Model visualization:

    The model visualization technique transforms facts into charts, histograms and other visuals to support correct insight interpretation.

  • Online Analytical Processing (OLAP):

    OLAP is a technique for solving analytical problems with multiple dimensions from various perspectives. OLAP is useful for completing tasks such as performing CRM data analysis, financial forecasting and budgets.

  • Predictive modeling:

    A BI technique that utilizes statistical methods to generate probabilities and trend models. With this technique, predicting a value for specific data sets and attributes using many statistical models is possible.

  • Reporting:

    Reporting involves gathering data using various tools and software to mine insights. This tool provides observations and suggestions about trends to simplify decision-making.

  • Scorecards:

    Visual tools, such as BI dashboards and scorecards, provide a quick and concise way to measure KPIs and indicate how a company is progressing to meet its goals.

Examples of Business Intelligence Trends

BI is continually evolving and improving, but four trends – artificial intelligence, cloud analytics, collaborative BI and embedded BI – are changing how companies are using expansive data sets and making decisions far easier.

  • Artificial intelligence:

    AI and machine learning emulate complex tasks executed by human brains. This capability drives real-time data analysis and dashboard reporting.

  • Cloud analytics:

    BI applications in the cloud are replacing on-site installations. More businesses are shifting to this technology to analyze data on demand and enrich decision-making.

  • Embedded BI:

    When BI software is integrated into another business application, it’s called embedded BI or embedded analytics. Some of the benefits of embedded BI include enhanced reporting functionalities, and it’s been shown to improve sales and increase customer retention.

Many companies look to cloud-based or software-as-a-service (SaaS) instead of on-premise software to keep up with growing warehousing requirements and faster implementations. A growing trend is the use of mobile BI to take advantage of the proliferation of mobile devices.

Examples of Business Intelligence Software and Systems

BI software and systems provide options suited to specific business needs. They include comprehensive platforms, data visualization, embedded software applications, location intelligence software and self-service software built for non-tech users.

Here are some examples of the latest BI software and systems:

  • Business intelligence platforms:

    These are comprehensive analytics tools that data analysts use to connect to data warehouses or databases. The platforms require a certain level of coding or data preparation knowledge. These solutions offer analysts the ability to manipulate data to discover insights. Some options provide predictive analytics, big data analytics and the ability to ingest unstructured data.

  • Data visualization software:

    Suited to track KPIs and other vital metrics, data visualization software allow users to build dashboards to track company goals and metrics in real-time to see where to make changes to achieve goals. Data visualization software accommodates multiple KPI dashboards so that each team can set up their own.

  • Embedded business intelligence software:

    This software allows BI solutions to integrate within business process portals or applications or portals. Embedded BI provides capabilities such as reporting, interactive dashboards, data analysis, predictive analytics and more.

  • Location intelligence software:

    This BI software allows for insights based on spatial data and maps. Similarly, a user can find patterns in sales or financial data with a BI platform; analysts can use this software to determine the ideal location to open their next retail store, warehouse or restaurant.

  • Self-service business intelligence software:

    Self-service business intelligence tools require no coding knowledge to take advantage of business end-users. These solutions often provide prebuilt templates for data queries and drag-and-drop functionality to build dashboards. Users like HR managers, sales representatives and marketers use this product to make data-driven decisions.

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How NetSuite Improves and Increases the Value of BI for Your Organization

BI tools can have an enormous impact on your business. They can help you improve your inventory control, better manage your supply chain, identify and remove bottlenecks in your operations and automate routine tasks. But for BI tools to be most effective, you first have to centralize data that’s stored in multiple disparate systems.

NetSuite business intelligence tools take the data stored in your enterprise resource planning (ERP) software and provides built-in, real-time dashboards with powerful reporting and analysis features. By centralizing data from your supply chain, warehouse, CRM and other areas with an ERP, NetSuite business intelligence tools can help you identify issues, trends and opportunities, along with the ability to then drill down to the underlying data for even further insight.

It’s likely your business has large amounts of data that could be used to boost your profitability. The challenge is organizing and structuring your data in such a way that you can then glean insights. From there, you need to create clear, concise and actionable reports and data visualizations and distributing them to key stakeholders on your team. None of this can be done without advanced software, such as ERP products that collect and manage all your data.