Also called: Business Analytics, Decision Support System, Business Performance Management, Corporate Performance Management, Business Process Intelligence, Business Activity Monitoring, and Operational Intelligence
See also: Competitive Landscape, Value Proposition Mapping, Product Metrics, Competitive Analysis, Competitive Intelligence, Competitive Landscape, Business Model Archetypes, Customer Acquisition Cost (CAC)
Relevant metrics: Conversion Rate, Customer Retention Rate, Customer Acquisition Cost, Return on Investment, and Customer Lifetime Value
How to calculate Business Intelligence:
BI = (Data + Analytics + Insights) / (Time + Resources)
What is Business Intelligence
Business Intelligence (BI) is a term used to describe the process of collecting, analyzing, and presenting data to help inform business decisions. It is a broad term that encompasses a variety of tools and techniques used to gather, store, and analyze data from multiple sources. BI can be used to identify trends, uncover insights, and make predictions about the future.
It is an important tool for product managers and user experience professionals, as it can help them better understand customer needs and preferences, as well as identify areas of improvement. BI can also be used to measure the success of a product or service, and to identify areas of opportunity. BI is a powerful tool that can help product managers and user experience professionals make informed decisions and create better products and services.
Where did Business Intelligence come from?
Business Intelligence (BI) is a term that was first coined in the late 1950s by IBM researcher Hans Peter Luhn. Luhn was looking for ways to improve the decision-making process of businesses and developed the concept of BI as a way to do this. He proposed that businesses should use data to make decisions, rather than relying solely on intuition and experience. This concept was revolutionary at the time and has since become an integral part of modern business operations.
Unlocking the Power of Business Intelligence
BI is a comprehensive term that encompasses a variety of data-driven activities, such as:
- Data mining. Involves extracting data from various sources, such as databases, spreadsheets, and web applications.
- Data analysis.Involves using statistical methods to identify patterns and trends in the data.
- Data visualization. Involves creating visual representations of the data, such as charts and graphs, to make it easier to understand.
Organizations can use BI to gain a better understanding of their customers, their markets, and their competitors. By analyzing customer data, organizations can identify customer needs and preferences, as well as develop targeted marketing campaigns. By analyzing market data, organizations can identify opportunities for growth and expansion. By analyzing competitor data, organizations can gain insights into their competitors’ strategies and tactics.
Organizations can also use BI to improve operational efficiency. By analyzing operational data, organizations can identify areas of inefficiency and develop strategies to improve them. By analyzing financial data, organizations can identify areas of cost savings and develop strategies to reduce costs.
The power of BI lies in its ability to provide organizations with data-driven insights that can be used to make informed decisions. By leveraging the power of BI, organizations can gain a competitive edge in their respective markets, as well as improve operational efficiency and customer satisfaction.
The Various Types of Business Intelligence in SaaS Product Development”
There are several different types of BI that are commonly used in the context of software products, each offering unique benefits and capabilities.
- Descriptive BI. Descriptive BI provides a comprehensive overview of past performance and trends, helping organizations understand how their products and services have performed over time. This type of BI typically includes dashboards, reports, and other visualizations that provide a clear and concise view of key metrics, including sales, customer engagement, and product usage.
- Diagnostic BI. Diagnostic BI goes one step further than descriptive BI, helping organizations understand why specific events or trends have occurred. This type of BI typically uses data mining and statistical analysis to identify patterns, correlations, and other insights that can be used to drive decision-making and improve product performance.
- Predictive BI. Predictive BI leverages advanced algorithms and machine learning to forecast future trends and performance. This type of BI can be used to identify potential risks and opportunities, as well as to make proactive, data-driven decisions about product development and marketing strategies.
- Prescriptive BI. Prescriptive BI takes things a step further, providing organizations with recommendations and actionable insights based on the data and analysis. This type of BI can be used to inform product development, sales and marketing strategies, and other business-critical decisions, helping organizations make the most of their data and stay ahead of the competition.
Important concepts within the field of Business Intelligence (BI)
BI is an umbrella term for various techniques, technologies, and tools that help organizations make informed decisions.
Raw Data: The Starting Point
The foundation of a successful BI solution is the data itself. This data can encompass anything from sales records, advertising keywords, salary and benefit tables, and profit and loss statements. A company’s data is typically stored in a multitude of databases, collected through various channels such as CRMs, ERPs, flat files, and APIs. To simplify the process of analyzing this fragmented data, modern BI solutions use data connectors that consolidate databases into a centralized data warehouse. This enables users to analyze insights jointly, enhancing cross-database analysis.
The Data Warehouse: Connecting the Pieces
The data warehouse serves as the logistical platform that connects all of a company’s databases, creating relationships between them. This technology has experienced significant advancements, particularly with the introduction of cloud-based BI tools. The legacy approach to data warehousing often involved a chaotic mix of Excel sheets, paper-based records, proprietary databases, and mainframe-style databases that had to be accessed by technicians. However, with the advent of modern systems, data warehouses have become far more sophisticated, updating in real-time and eliminating the need for manual updates by the IT department.
Data Access, Analytics, and Presentation: Making the Data Work for You
Once the data is connected and readily accessible, the next step is to use it effectively. This involves accessing the data, analyzing it to identify important trends, and presenting it in an easily understandable format. The steps of accessing, analyzing, and presenting data often overlap, especially with the use of interactive dashboards. Data presentation has come a long way, offering beautiful and intuitive dashboard examples that provide quick access to the information required.
Data dashboarding and reporting: Continuous monitoring and growth
The final and most essential component of an interactive dashboard is the ability to continuously track, monitor, and report on the data. With access to a flexible, customizable, and data-driven online dashboard, organizations can set targets, identify patterns, spot trends, and uncover insights that drive growth and improvement. By utilizing seamless data visualization, it is also possible to share discoveries within the organization in an inclusive and easily digestible manner. The best part is that today’s BI-based dashboard reporting is portable, allowing for 24/7 access to data, analysis, and sharing from anywhere in the world, on a multitude of devices.
Is Business Intelligence the same as AI?
Business Intelligence and Artificial Intelligence are complementary but distinct fields. Business Intelligence involves using data analysis, reporting and visualization tools to understand and improve business performance. AI, on the other hand, involves using machine learning and other advanced algorithms to analyze data and make predictions.
The two fields complement each other because AI can be used to automate and enhance some aspects of Business Intelligence, such as data analysis and visualization, providing more accurate and faster insights, while Business Intelligence provides the framework for informed decision making and helps to identify areas where AI can be used to improve business processes.
Benefits of implementing Business Intelligence
Business Intelligence can provide organizations with a competitive edge by providing them with the ability to make better decisions faster, to identify new opportunities, reduce costs, and improve customer service, and help organizations gain insights into their operations, customers, and markets. Not least of all: to make informed decisions that can lead to improved performance and profitability.
As the world generates a never-ending flow of data, it is imperative for organizations to leverage this information and put it to use for their benefit. The traditional human brain can no longer comprehend the sheer volume of data produced, making BI concepts a vital tool for decision-making and improved business efficiency.
- BI Will keep you from drowning in Data. On one hand, there is more information available than ever before. On the other hand, separating the signal from the noise has become a daunting task. Without utilizing the right tools, organizations risk the possibility of becoming overwhelmed by data.
- Provides a wealth of insights. With the right BI solutions, organizations can extract valuable insights that can enhance interdepartmental and external communications, problem-solving processes, online data analysis, financial efficiency, goal-setting, marketing, and profitability. Self-service BI tools allow organizations to gain insights that can help drive their success.
- Accurate Benchmarking. By working with BI-based key performance indicators (KPIs), organizations can set actionable goals and formulate strategies more effectively. With the right KPI templates, organizations can measure their progress and evaluate their goals on a deeper and more accurate level, leading to overall success.
- Predictive Analytics. Business intelligence also provides the ability to predict future trends. With the help of online BI tools and solutions, organizations can analyze patterns and information to predict future outcomes and put plans in place to either prevent potential disasters or take advantage of trends before their competitors.
- Powerful Data Visualization. Data visualization is an essential component of BI solutions. By visualizing data in a digestible format, organizations can communicate their insights effectively and tell a story with their findings. This can boost the success of the organization and make it more powerful than ever before.
- Improved Decision Making. Business intelligence can provide organizations with the data and insights they need to make informed decisions. This can help organizations make better decisions faster and with greater accuracy.
- Enhanced Customer Experience. Business intelligence can help organizations better understand their customers and their needs, allowing them to provide a more personalized and tailored customer experience.
- Increased Revenue. By leveraging business intelligence, organizations can identify new opportunities for growth and increase their revenue.
- Improved Risk Management. Business intelligence can help organizations identify potential risks and develop strategies to mitigate them, resulting in improved risk management.
Challenges of implementing Business Intelligence
One of the main challenges of Business Intelligence is the need to integrate data from multiple sources. Additionally, organizations need to ensure that the data is accurate and up-to-date. Additionally, organizations need to ensure that the data is secure and that the data is being used in an ethical manner.
- Cost. Business intelligence solutions can be expensive to implement, requiring significant investments in software, hardware, and personnel.
- Data Quality. Poor data quality can lead to inaccurate insights and decisions, so it is important to ensure that data is accurate and up-to-date.
- Data Integration. Business intelligence solutions require data from multiple sources to be integrated into a single platform, which can be a complex and time-consuming process.
- Security. Business intelligence solutions must be secure to protect sensitive data from unauthorized access.
- User Adoption. Users must be trained to use the business intelligence solution, and they must be motivated to use it regularly in order to get the most out of it.
Examples of how Business Intelligence can be applied
Here is a list of examples of how BI can be applied to different areas of a business to drive growth and efficiency:
- Streamlining the Sales Cycle with Analytics. The utilization of sales analytics can give you valuable insights into your sales reps’ performance, enabling you to identify the factors behind their success and replicate them on a wider scale. A sales cycle length dashboard tracks the progress of the sales funnel, offering a clear picture of each step in the process.
- Understanding Customer Behavior with Retail Dashboards. By analyzing customer acquisition channels, you can determine which sources are driving the most revenue and attracting the best customers. A retail store dashboard helps managers understand their customers’ behavior, breaking down sales volume by division and location, and providing key information for designing targeted marketing campaigns.
- Planning Effective Marketing Strategies with Predictive Analytics. Combining marketing analytics and predictive analytics can help you determine the most successful campaigns and the common factors that contribute to their success. A web analytics dashboard gives you an overview of your online presence, the performance of different marketing channels, and the results of various campaigns.
- Improving Customer Experience with Service Dashboards. Customer service and customer experience (CX) are critical to ongoing growth and success. BI solutions such as customer service dashboards provide insights into key customer service KPIs, including average response time and top agents, enabling businesses to consistently exceed customer expectations.
- Enhancing Procurement Operations with a Comprehensive Dashboard. Procurement is the backbone of many business operations and covers services, goods, and third-party vendors. Applying BI concepts to procurement helps keep operations fluent, cohesive, efficient, and consistent. A procurement dashboard provides a comprehensive overview of the operation, offering insights into areas for improvement, relationship management, and cost-saving opportunities.
- Elevating IT Project Management with BI Dashboards. The role of the IT department is more critical than ever, requiring the delivery of projects on time and to their full potential. A BI approach to IT project management helps manage and improve even the most stretched IT departments. An IT dashboard features key BI metrics and IT KPIs, enabling IT teams to tackle regular issues, deliver projects efficiently, and optimize internal support.
The tools below will help you with the Business Intelligence play.
Tableau is a data visualization tool that enables users to connect to data from a variety of sources, analyze and visualize it, and share insights in interactive dashboards, reports, and charts
QlikView is a self-service business intelligence platform that helps organizations make informed decisions by providing access to relevant, real-time data through interactive visualizations and dashboards
Power BI is a cloud-based business intelligence platform from Microsoft that provides interactive visualizations, insights, and dashboards on top of business data
MicroStrategy is a comprehensive business intelligence platform that provides organizations with data-driven insights to make informed decisions
Amazon QuickSight is a fast, cloud-powered business intelligence service that makes it easy to deliver insights to everyone in your organization
Looker is a modern, web-based platform for business intelligence and data discovery that helps organizations get more value from their data
Google Sheets is a web-based spreadsheet application that offers collaboration and data analysis features, making it a cost-effective and accessible solution for business intelligence tasks.
Excel is a powerful spreadsheet tool with advanced analytics and data visualization capabilities, making it a commonly used tool for business intelligence and data analysis.
By analyzing user data, the company is able to better target its ads and improve its overall ad performance. This has allowed Facebook to effectively monetize its vast user base, while also providing advertisers with highly effective and targeted advertising options. Through its use of business intelligence, Facebook has established itself as a leader in digital advertising and continues to drive innovation in the space.
By tracking and analyzing user behavior, Google is able to understand which features and products are most popular, as well as identify new opportunities for growth. This allows the company to constantly improve its products and services, staying ahead of the competition in the rapidly changing digital landscape.
The company uses data to determine which shows and movies to produce, as well as to personalize its recommendations to each individual user. This data-driven approach has helped Netflix stay ahead of the competition, as it is able to constantly refine and improve its offerings based on customer preferences and viewing habits.
Walmart uses business intelligence to analyze customer data and optimize their supply chain. This helps them to better understand customer demand and ensure that they have the right products in the right places at the right times.
What is the purpose of using Business Intelligence?
Hint The purpose of using Business Intelligence is to gain insights from data to make better decisions and improve business performance.
What data sources will be used to generate the Business Intelligence?
Hint Data sources used to generate Business Intelligence can include internal data sources such as customer databases, financial records, and operational data, as well as external data sources such as market research, industry trends, and competitor data.
What type of analysis will be conducted with the Business Intelligence?
Hint Types of analysis conducted with Business Intelligence can include descriptive analytics, predictive analytics, and prescriptive analytics.
What are the expected outcomes of using Business Intelligence?
Hint The expected outcomes of using Business Intelligence can include improved decision-making, increased efficiency, better customer service, and increased profitability.
What are the potential risks associated with using Business Intelligence?
Hint Potential risks associated with using Business Intelligence can include data security and privacy issues, incorrect or incomplete data, and incorrect analysis.
How will the data be stored and secured?
Hint Data can be stored and secured using secure cloud storage solutions, encryption, and other security measures.
How will the data be visualized?
Hint Data can be visualized using charts, graphs, and other visualizations.
What are the costs associated with implementing Business Intelligence?
Hint Costs associated with implementing Business Intelligence can include software and hardware costs, data storage costs, and personnel costs.
What are the benefits of using Business Intelligence?
Hint Benefits of using Business Intelligence can include improved decision-making, increased efficiency, better customer service, and increased profitability.
How will the results of the Business Intelligence be used?
Hint The results of the Business Intelligence can be used to inform decisions, develop strategies, and improve processes.
- Business Intelligence: A Managerial Perspective on Analytics by Thomas D. Cova (2017)
- Contemporary Strategy Analysis: Text and Cases by Robert D. Grant (2018)
- Information Dashboard Design: The Effective Visual Communication of Data by Stephen Few (2006)
- Big Data: Using SMART Big Data, Analytics and Metrics To Make Better Decisions and Improve Performance by Bernard Marr (2015)
- Management Information Systems: Managing the Digital Firm by Kenneth C. Laudon (2017)
- Introduction To The Basic Business Intelligence Concepts by Sandra Durcevic
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