23 Real-World Examples of Business Intelligence

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.

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. 
   

   Lotte.com: BI Increases Company Revenue

   Lotte.com 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.

11. 
    

    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.




12. 
    

    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.

    
    
    

13. 
    

    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.




14. 
    

    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.




15. 
    

    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.




16. 
    

    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.




17. 
    

    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.




18. 
    

    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.

    
    
    

19. 
    

    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.




20. 
    

    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.




21. 
    

    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.




22. 
    

    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.




23. 
    

    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.

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.