Organisations are confronted with an overwhelming volume of information generated from countless sources. The ability to convert unprocessed data into useful insights that inform strategic decision-making has made business intelligence an indispensable tool.
According to a recent report, 55% of organisations consider business intelligence a top priority, underscoring its significance in shaping business strategies. Staying ahead at a time when a company’s destiny can be decided by its agility and strategic vision requires good data utilisation.
What is Business Intelligence?
Business intelligence is a process that involves collecting, analysing, and delivering data to help organisations make informed decisions. It integrates business analytics, data management, reporting tools, and methodologies to provide actionable insights.
This tool enables organisations to collect data from both internal systems and external sources, prepare it for analysis, and use data visualisation tools, dashboards, and reports to inform operational decision-making and strategic planning.
The primary goal of business intelligence is to drive better business decisions, allowing organisations to increase revenue, improve efficiency, and gain a competitive edge. The focus of modern BI systems is on speed to insight, self-service analytics, and flexibility, allowing business users to swiftly adjust to changes in the market and get rid of inefficiencies.
Although BI currently stresses user empowerment and agility, its origins may be traced back to the 1960s as an organisational information exchange system. Since its coining in 1989, the phrase “business intelligence” has developed into a sophisticated method of turning data into insights that can be put to use. This signifies the transition of BI from conventional, IT-driven approaches to modern, approachable alternatives.
The Difference Between Traditional and Modern Business Intelligence
Traditional business intelligence followed a top-down approach, where the IT department controlled access to data and handled all reporting requests. Users relied on static reports generated by IT, and any follow-up questions or requests had to go back through a lengthy queue. This process was slow and often frustrating, as it limited users’ ability to make timely, data-driven decisions based on the latest information.
In contrast, modern BI prioritises self-service analytics and faster insights. While IT still has a role in managing data access, users across various levels can now create their own dashboards, generate reports, and visualise data with ease.
Modern business intelligence tools empower users to interact with data in real-time, answering their own questions and making decisions more quickly and efficiently. This shift allows businesses to be more agile and responsive to current trends and insights.
How Does Business Intelligence Work?
Business intelligence transforms raw data into actionable insights to help organisations make informed decisions and track performance against their goals. This involves a series of technical and analytical steps, starting with data collection and ending with strategic decision-making.
Business intelligence data, sourced from various systems, is stored in either a central data warehouse or smaller data marts for specific departments. Increasingly, data lakes, often based on big data systems, are used to manage large volumes of unstructured or semi-structured data, such as log files or sensor data.
Before data can be used in business intelligence applications, it undergoes preparation, which includes integration, consolidation, and cleansing to ensure accuracy and consistency.
BI platforms then allow users to analyse this data through analytical querying, with results visualised in the form of charts, graphs, and dashboards. Initially, BI tools were primarily for IT and BI professionals, but self-service BI tools now allow business users to query data and create visualisations independently.
Advanced analytics, including data mining, predictive modelling, and statistical analysis, often supplement BI initiatives, helping organisations conduct what-if analyses and forecast future outcomes. These advanced analytics projects are typically handled by specialised teams, while business intelligence teams focus on more straightforward data queries and performance tracking.
Is Business Intelligence Important?
Yes, business intelligence is important for enhancing an organisation’s operations by leveraging data to inform decision-making. Companies that effectively use BI tools can transform their raw data into valuable insights, helping them optimise business processes and strategies.
Without BI, organisations miss the opportunity to capitalise on their data, leaving decision-making to rely on intuition, past experiences, and instinct. While such methods may sometimes yield positive results, they also carry a higher risk of errors and missed opportunities due to the lack of solid data to support them.
Business Intelligence vs Data Analytics
While “business intelligence” and “data analytics” are often used interchangeably, they have distinct meanings. Business intelligence primarily focuses on descriptive analytics, which helps users understand what has happened in the past.
Data analytics, on the other hand, often refers to more advanced techniques like predictive analytics (modelling future outcomes) and prescriptive analytics (recommending actions based on data).
Business intelligence integrates data analytics to provide actionable insights. Data analytics go deeper into the “why” behind events and forecast what could happen next, while BI takes these insights and presents them in a more accessible form for decision-makers.
Business Intelligence Methods and Tools
Business intelligence covers a range of processes, methods, and tools designed to collect, store, and analyse data to optimise business performance.
It provides a comprehensive view of operations, allowing organisations to make informed, actionable decisions. Over the years, BI has expanded to include various techniques and technologies aimed at improving performance.
The most common BI methods and tools include:
Core BI Methods
- Data Mining: Uses databases, statistics, and machine learning to identify trends in large datasets.
- Reporting: Delivers analysis results to stakeholders, allowing data-driven decision-making.
- Performance Metrics and Benchmarking: Tracks current performance against goals using historical data and custom dashboards.
- Descriptive Analytics: Analyses historical data to understand what happened in the past.
- Querying: Allows users to ask specific questions about the data, with BI tools providing answers from datasets.
- Statistical Analysis: Expands on descriptive analytics to understand why trends occurred and how they developed.
- Data Visualization: Converts data into visual representations (charts, graphs, histograms) for easier interpretation.
- Visual Analysis: Combines data storytelling with interactive visuals to communicate insights in real-time.
- Data Preparation: Compiles and cleans data from multiple sources, preparing it for analysis.
Types of BI Tools
- Ad Hoc Analysis: Allows users to create and run queries on the fly to explore specific business issues. Often incorporated into reports and dashboards.
- Online Analytical Processing (OLAP): Enables multidimensional analysis, ideal for complex queries and calculations, traditionally using OLAP cubes but now increasingly running directly on databases.
- Mobile BI: Delivers BI tools and dashboards to smartphones and tablets, typically focusing on data viewing rather than analysis.
- Real-Time BI: Analyses data as it’s generated, providing up-to-date insights into business operations, customer behaviour, and financial trends.
- Operational Intelligence (OI): A form of real-time BI designed for operational decision-making, helping frontline workers and managers respond quickly to issues.
- SaaS BI (Cloud BI): Provides BI tools through cloud computing, often priced on a subscription basis, offering multi-cloud support for flexibility.
- Open Source BI (OSBI): Offers free, community-driven BI software, with commercial editions available for organisations requiring vendor support.
- Embedded BI: Integrates BI and data visualisation directly into business applications, allowing users to analyse data within the tools they use daily.
- Collaborative BI: Combines BI tools with collaboration features, enabling teams to work together on data analysis and share insights.
- Location Intelligence (LI): Specialises in analysing geographic and spatial data, useful for location-based decision-making in areas such as retail site selection, logistics, and marketing.
Benefits of Business Intelligence
There are several advantages for businesses that use business intelligence (BI) to evaluate and act on data from supply chain management to customer service.
Some of the top advantages of implementing BI include:
- Data Clarity: BI provides a clear and comprehensive understanding of business data, enabling better analysis and decision-making.
- Increased Efficiency: Organisations can boost productivity, streamline procedures, and improve operational efficiency with real-time access to performance indicators.
- Improved Customer Experience: Analysing customer data helps enhance marketing, sales, and service efforts, creating more personalised and effective interactions.
- Better Employee Satisfaction: HR managers can use BI to monitor employee productivity and manage workforce data, resulting in improved satisfaction and performance.
- Faster Decision-Making: Executives and managers can monitor performance and respond quickly to issues or opportunities, speeding up decision-making processes.
- Problem Identification: BI tools help spot potential business problems early, allowing organisations to address them before they escalate.
- Identifying Trends and Opportunities: BI enables companies to detect emerging market trends, adjust strategies, and capitalise on new opportunities.
- Increased Revenue: Businesses can boost income and solidify their place in the market by increasing sales and streamlining processes.
Along with these more general advantages, business intelligence (BI) also helps in more specialised domains like project monitoring and competitive intelligence, which helps firms maintain an advantage in a business environment that is always evolving.
Real-Life Examples of Business Intelligence Use Cases
Business intelligence has been implemented across various industries, including healthcare, information technology, and education, transforming operations through data-driven insights.
While the extensive capabilities of BI can be overwhelming, real-world examples illustrate its impact.
General use cases for enterprise business intelligence:
- Monitoring Business Performance: BI tools track key performance metrics to assess organisational effectiveness.
- Supporting Decision-Making: BI aids strategic planning by providing actionable insights.
- Evaluating and Improving Processes: Organisations can analyse workflows to identify areas for enhancement.
- Operational Insights: BI delivers crucial information about customers, equipment, and supply chains to operational staff.
- Trend Detection: BI identifies patterns and relationships in data that can inform business strategies.
Industry-specific examples:
- Financial Services: Charles Schwab utilised BI to gain a comprehensive view of branch performance across the U.S. This centralised platform enables branch managers to identify clients with changing investment needs and allows leadership to track regional performance. This results in optimised operations and improved customer service.
- Meal Kit Delivery: HelloFresh automated its reporting processes using Tableau, significantly reducing the time its digital marketing team spent on reporting—from 10 to 20 hours daily. This automation allowed the team to focus on creating more targeted and segmented marketing campaigns.
- Retail: Retailers use BI for managing marketing campaigns, planning promotions, and monitoring inventory levels, ensuring that they can respond quickly to market changes.
- Manufacturing: Manufacturers rely on BI for real-time analysis of plant operations, aiding in production planning, procurement, and distribution management.
- Travel and Hospitality: Airlines and hotel chains leverage BI to track flight capacities and room occupancy rates, optimise pricing strategies, and schedule staff effectively.
- Healthcare: In healthcare, BI aids in diagnosing diseases and enhancing patient care by analysing patient data and treatment outcomes.
- Education: Universities and school systems employ BI to monitor student performance metrics and identify individuals who may require additional support.
How to Develop a Good Business Intelligence Strategy?
A strong business intelligence strategy directs the use of data in your company and acts as a road map for success. This approach must be carefully planned, communicated, and in line with your company’s objectives.
Here’s a step-by-step approach to creating a BI strategy from the ground up:
- Understand Your Business Strategy and Goals
Start by aligning your BI initiatives with the overall business strategy. Identify key objectives, such as improving operational efficiency, enhancing customer satisfaction, or driving revenue growth.
- Identify Key Stakeholders
Engage stakeholders from various departments, including IT, marketing, finance, and operations. Their insights will help ensure the BI strategy addresses the needs of different areas within the organisation and garners broader support.
- Choose a Sponsor from Key Stakeholders
Select an executive sponsor who is invested in the success of the BI strategy. This individual will champion the initiative, allocate resources, and facilitate collaboration among stakeholders.
- Select Your BI Platform and Tools
Evaluate and choose the appropriate BI tools and platforms that align with your business needs. Consider factors such as scalability, ease of use, integration capabilities, and cost. Popular options include cloud-based solutions, self-service BI tools, and advanced analytics platforms.
- Create a BI Team
Assemble a cross-functional BI team comprising data analysts, data engineers, and business users. This team should be equipped with the skills necessary to analyse data, generate insights, and drive the BI strategy forward. Clearly define roles and responsibilities to guarantee accountability.
- Define Your Scope
Determine the scope of your BI strategy by identifying the key areas of focus, such as sales analytics, customer behaviour analysis, or operational reporting. Establish boundaries to keep the project manageable and aligned with business priorities.
- Prepare Your Data Infrastructure
Assess your current data infrastructure and make necessary adjustments to support BI initiatives. This may involve integrating disparate data sources, ensuring data quality, and implementing data governance practices to maintain consistency and accuracy.
- Define Your Goals and Roadmap
Set clear, measurable goals for your BI strategy. Create a roadmap outlining the implementation timeline, key milestones, and metrics for success. This will provide direction and help track progress over time.
- Foster a Data-Driven Culture
Promote a culture that values data-driven decision-making across the organisation. Provide training and resources to empower employees to utilise BI tools effectively and encourage collaboration between teams.
- Iterate and Improve
BI strategies should be dynamic and adaptable. Continuously monitor the effectiveness of your BI initiatives, solicit feedback, and make adjustments as necessary to ensure that the strategy remains aligned with evolving business needs.
How Can Business Intelligence Improve Your Business?
Business intelligence can improve your business in many ways. Here are some of the best ways in which BI can improve your business:
- Enhanced Decision-Making
BI enables organisations to analyse vast amounts of data quickly and accurately. This data-driven approach allows decision-makers to gain deeper insights into market trends, customer behaviour, and operational efficiency.
Your team can shift from intuition-based decisions to evidence-based strategies, ultimately leading to more effective outcomes.
- Improved Operational Efficiency
Businesses can identify inefficiencies within their processes and workflows when using BI. BI provides a clear view of performance metrics and operational bottlenecks, allowing organisations to streamline processes and allocate resources more effectively. This leads to reduced costs and increased productivity.
- Increased Competitive Advantage
BI helps organisations monitor market trends and competitor performance, enabling them to adapt their strategies proactively. Businesses can find new avenues for innovation and expansion by employing sophisticated analytics.
- Better Customer Experience
BI allows companies to analyse customer data to understand preferences, behaviours, and pain points. This insight enables businesses to tailor their products and services to meet customer needs better, ultimately leading to enhanced customer satisfaction and loyalty.
- Informed Strategic Planning
Businesses can develop more solid and well-informed strategic strategies with BI. Businesses will be able to set reasonable objectives and make calculated investments that are in line with their long-term vision by evaluating past data and predicting future trends.
Improve your Business With Corpim
Within this context, Corpim is a leader in transforming the structure and delivery of business intelligence. Corpim is a software and consultancy specialist that helps a variety of customers, including big businesses and startups, understand complicated business environments.
Corpim provides customised solutions that improve decision-making and boost business performance through skilled architecture leadership and advanced DataTech services. Together with services like cloud computing and data systems modernisation, their industry-specific SaaS products enable businesses to take full advantage of their data.
Through collaboration with Corpim, companies can advance their BI skills, gaining fresh perspectives and cultivating a data-driven culture that encourages growth and innovation.