What Is Business Intelligence?

What is Business Intelligence?

Business intelligence (BI) refers to a variety of technology-driven process including data mining, data management, defined data analysis infrastructure, and data visualization that analyzes data to provide actionable insights. It helps executives, managers, and employees make informed decisions by transforming raw data into meaningful information, ultimately enhancing operational efficiency and strategic planning.

With around 80% of companies already taking advantage of it, business intelligence has proven itself to be a vital tool for organizations looking to stay competitive in constantly changing markets. 

Why Is Business Intelligence Important?

Effective use of BI tools allows business leaders to obtain a comprehensive view of their company’s performance through the use of effective data visualization practices. Complex business data can be made easy to digest through visually stimulating reports, charts, dynamic dashboards, and business summaries. 

The information that BI presents is accessible to teams across the business hierarchy, allowing for self-service analysis to pinpoint inefficiencies in real time. Its large-volume data management capabilities ensure that information is both unified and securely stored on a single platform, even scaling with the enterprise’s growth.

As a consequence of this unification of data storage, business analytics processes become more streamlined. The mere presence of such analytical capability also eliminates dependence on accumulated knowledge, intuition, and experience.

In essence, BI software’s prime importance lies in its ability to consistently help organizations make more data-driven decisions.

Business Intelligence vs. Business Analytics

While business intelligence and business analytics are often used interchangeably, they differ in certain aspects that must be highlighted. 

Firstly, BI tends to focus on data collection, data storage, knowledge management, and analyses to evaluate historical business data and better understand the present context. Business analytics, on the other hand, uses processes such as data mining, data modeling, and machine learning to analyze data related to market trends and projections to understand the causes of past events and predict future market scenarios.

Given these base definitions, it is possible to see distinct differences between the two. BI is seen as more descriptive and past- or present-focused, while business analytics tends to be predictive and future-focused. For example, BI is useful for understanding the sales prospects in the pipeline today, while business analytics would help firms plan sales strategies to improve prospects in the future.

Another difference between the two lies in the end users of both solutions. While business analytics typically requires knowledgeable data science experts to analyze and interpret its results, BI must be designed to facilitate a proper understanding of data and reports for non-technical end users.

How Does the Business Intelligence Process Work?

The BI process involves multiple stages to establish the workflow required to deliver effective results. A brief description of these stages is given below.

1. Data storage: At the beginning of the process, BI software stores the business data to be identified and processed in a large, singular data warehouse or smaller data marts with unique data from various departments. The data could be log files, text, and other types of structured or unstructured data.
   
   
2. Data preparation: Given the disparity in the type and quality of data, BI tools must consolidate, organize, and cleanse the raw data to begin the integration process. This is done through data management and integration tools that supply teams with accurate and consistent information.
   
   
3. Analysis: Once the data has been prepared, data analysis is the next step in the BI process, often done with the help of techniques like data mining, predictive modeling, statistical analysis, and big data analytics. The queries required for this process must be designed appropriately to derive workable insights and identify hidden patterns that may otherwise go unobserved.
   
   
4. Visualization: Upon identifying important data, trends, and insights, BI software focuses on visualizing them. In this step, the software is tasked with creating charts, graphs, and dashboards that present the analysis results in a simple, easily understandable manner. Such visual presentation promotes comprehension and encourages users to engage with the data.
   
   
5. Action plan: The final step is to create an action plan based on the data visualizations provided by BI tools. This generally involves comparing historical data versus key performance indicators (KPIs), which can lead to recommendations for changes in marketing strategies, resource allocation, customer experiences, and more.

Benefits of Business Intelligence

The practical implementation of BI following the standard procedure described above can reap benefits for businesses, as detailed below.

• Data-driven business decisions: A comprehensive BI strategy delivers accurate data and detailed reports, which business leaders can use to make better-informed and more timely decisions.
  
  
• Clearer reporting: BI software's ability to present data simply and understandably while highlighting valuable insights improves business reporting, which helps generate massive time savings for all teams.
  
  
• Increased organizational efficiency: Besides more transparent reporting, BI tools give leaders a holistic view of the company's performance on a single dashboard. This helps set up benchmarks that can later be used to pursue larger organizational goals and identify areas of opportunity.
  
  
• Deeper insights: BI tools dive deeper into a firm's business data to produce insights capable of making the company more competitive. These insights help improve ROI, enable better resource allocation, and provide a deeper understanding of customer behavior.
  
  
• Improved customer experience and employee satisfaction: BI software benefits both internal and external stakeholders by streamlining business functions and operations. Customers receive better service because the relevant teams are armed with useful data and insights. At the same time, the employees themselves work together more efficiently and with less friction.

Business Intelligence Use Cases

Since its widespread implementation in numerous industries, BI has had a significant impact across multiple business functions. The diversity of use cases is a testament to the utility of business intelligence software. Let’s take a look at a few of them:

• Customer service: BI can unify customer information and product details on a single platform, helping customer service agents identify issues quicker and enhancing customer satisfaction in the long run.
  
  
• Finance and banking: Financial firms need a real-time view of organizational health and the ability to trace risks before they affect the firm. BI tools facilitate decision making by providing these abilities through predictive analytics and data management on a single interface.
  
  
• Sales and marketing: BI software unifies incoming data on various factors, such as promotions, pricing, sales, and market conditions, which helps marketing and sales teams execute better planning and boost sales through well-thought-out campaigns.
  
  
• Statistical analysis: BI tools like descriptive analytics can help organizations spot potential trends hidden in raw data. They also allow companies to trace the reasons for these trends' development.
  
  
• Security and compliance: BI software provides companies with a unified dashboard that visualizes all of the company's data. This makes pinpointing security issues much more straightforward and, due to detailed reporting, helps with compliance regulations.

Challenges Associated With Business Intelligence

Despite the advantages BI offers, there are several challenges that companies wishing to implement it must overcome:

• Lack of communication: A common issue with BI implementation is communication regarding data parameters between teams that utilize the solution. Poor communication leads to inaccurate or contradictory results, leaving the solution seen as unreliable and, hence, unusable. To avoid this, teams must constantly communicate between themselves and with other stakeholders to ensure all parties agree on the solution's goals.
  
  
• High costs: BI software can be very costly, making organizations doubt its guarantees of future ROI. The cost of training and scaling can compound the issue, as these are necessary to fully integrate the solution into business functions. However, this problem can be worked around by streamlining the implementation process and practicing better strategic planning.
  
  
• KPI identification: The effectiveness of BI software depends on inputting the right KPIs that a company wishes to track. In many cases, firms fail to fully benefit from the capabilities offered by BI software due to inaccurate KPI definitions during the implementation process. Avoiding this fundamental mistake ensures that the software can gather and track the correct data to help the firm in the long run.
  
  
• Complex reporting: A core requirement of BI software is delivery of reports that can be understood by teams at all levels. Without active efforts to maintain simplicity, the reports and documentation from BI tools can become complex to the point where they’re only decipherable by IT or data analysis teams. Such complexity must be avoided; BI software must be calibrated to produce simple, visually appealing reports that can benefit teams across the hierarchy.

BI Best Practices

To get the most out of BI tools and make sure that they’re being used to maximum effect, there are a few pointers that must be kept in mind. Here are some best practices for effective BI implementation:

• Set clear business objectives: Companies must determine what kinds of information that they deem most valuable and actionable. This allows goals to be set for the BI system to meet regarding the type of data to be collected or sourced, which can make the delivery of such information possible.
  
  
• Comprehensive user training: BI systems are designed to be of value for users across all levels of the company’s hierarchy. To achieve the desired utility and ease of access, users across the board must be given training to attain a clear and comprehensive understanding of the tools they’ll use.
  
  
• Monitor data quality and relevance: Consistent and trustworthy data lies at the very core of effective BI. The quality of the output will only be as good as the quality of the input. Teams must vigilantly monitor the input data to eliminate bias and maintain security, relevance, accuracy, and usability.
  
  
• Ensure data access to decision makers: Up to 68% of data goes unleveraged by businesses due to inconsistent analysis. Developing a robust BI architecture will go a long way to consistently equipping organization leaders with relevant insights to drive their business decisions. 

Adopting BI for a Better Business Future

Businesses must accept the rapid pace of technology and the constant increase in data volumes generated across industries as inevitable. BI has already proven its utility as a solution capable of helping organizations harness the power of data and gain a competitive edge in the market. 

Despite the challenges that may arise in its implementation, BI software is a vital component of an organization’s arsenal to compete for success. Its data collation and management abilities, combined with its capacity for advanced analytics and data visualization, present enterprises with the insight necessary to enable better decision making. 

Solutions like Savant are committed to supporting companies by providing cloud-native BI tools that can help them achieve their business goals over time and scale to their needs in step with organizational growth

Contact us today to begin your journey towards smarter data operations and enhanced decision making for your business.