The Working Principle of Business Intelligence and More!

Business intelligence works on a straightforward principle - each company has a few targets and questions. It is essential to gather the correct data to fulfill targets and provide answers to these questions. Post-data collection comes with analysis and its deduction into various patterns, trends, and insights that channel growth. This efficiently solves several business problems, helps create newer goals, and helps optimize business performance.

How does Business Intelligence (BI) Work?

BI refers to the tools, technologies, systems, strategies, and applications used to collect, categorize, analyze, and present information in a meaningful and actionable manner.

Organizations use BI and data analysis insights to improve strategic decisions, identify problems, spot market trends, and find new revenue or business opportunities.

BI helps users to access various types of data - historical and current, in-house and third-party data, and semi-structured and unstructured data. Users (typically management) use the information to gain insights into their business and make strategic decisions based on the same.

For example, a company has been losing customers lately due to poor customer service. Many customers are unsatisfied with their overall experience when buying products or services from a shop or online. This is where the management depends on BI as BI tools would provide statistical evidence showing how many people have complained about specific problems during each transaction over time. The administration can track the issues according to the data thrown up and course correct.

History of Business Intelligence

The term business intelligence was first used in 1865 by author Richard Millar Devens when he cited a banker who collected intelligence on the market ahead of his competitors. Around the late 1950s, IBM explored using technology to gather business Intelligence. This was a big step as the introduction of computers helped analyze the data more accurately than before, making it possible for users to create more accurate models for predicting future trends.

The next big step was the more profound usage of software to operate BI. This enabled organizations to deal with large volumes of complex data. As technology was integrated deeply into the business, it also made it easier for people across the organization to access the data.

Some of the more recent developments in the field of BI have been the implementation of cloud-based BI solutions. This has helped in extending the reach of BI across geographies. These solutions help in crunching and analyzing data in real-time. The latest development in this space is self-service BI applications which have democratized BI as even non-expert users can now access and analyze data at any given time.

Business Intelligence vs. Business Analytics

Business Intelligence and Business Analytics are often used interchangeably by professionals. While both processes leverage data to improve business, it is essential to understand the differences as it can help organizations choose the right tool and talent to achieve their goals.

Let us understand the difference between these two with the help of an example; India Coffee is a small business that sells a variety of coffee beans and powders through an online store. BI provides helpful reports on the past and current state of the company. BI helps with why sales of filter coffee have spiked in Bangalore in the past three months. As a result, they decide to make more filter coffee to keep up with demand.

On the other hand, business analytics will help understand why filter coffee sales spiked in Bangalore. By mining the website data, they would learn that a majority of traffic has come from a post by a Bangalore-based food blogger who spoke about the product. This insight helps them decide to send complimentary coffee hampers to a few other prominent food bloggers throughout their target markets. They use the previous sales information to anticipate how many filter coffee packets they will need and how many supplies they will need to keep up with demand if the sales spike after the bloggers' post.

In short, BI uses historical data to decide how a company should run. In contrast, business analytics uses historical data to foresee what might happen in the future or how an organization can move forward.

Business Intelligence Strategy

A robust BI strategy acts like a roadmap for using the available data. After all, there is no point in getting all those graphs and not knowing what to do with them. BI strategy is about more than just choosing or implementing the right software. It is also about how the data will be managed and how the users will be empowered to make well-informed and data-driven decisions. Typically, BI was always handled by a few people in the organizations. The IT team was the primary user of BI tools. As BI tools have evolved and helped democratize the data, users across the organization have access to BI tools. While traditionally, the IT team used BI for in-house data, the more advanced BI tools help people from various departments access and filter data from multiple sources.

It would be wise to use classical BI for certain types of reporting, like financial reports and modern BI for sales and marketing-related queries where business users need insights into quickly changing dynamics.

Self-service Business Intelligence

Self-service business intelligence (SSBI) is an approach to data analytics that enables business users from various fields, such as sales, marketing, product development, IT, finance, and operations, to access and explore data sets even if they don't have a BI background. An organization implementing self-service BI enables business analysts, executives, and other users to run queries and create their dashboards and reports. This helps in faster data analysis & decision-making.

SSBI has challenges like lack of adoption, data privacy, uncontrolled deployments, etc. This is why a solid BI strategy needs to be in place. If the structure is set correctly, it will ensure that the organization will have the proper infrastructure to implement and support the organization-wide use of SSBI.

It is straightforward for businesses that using BI in their processes is now imperative, and they can already agree that innovative business intelligence processes can also aid in hiring better employees, distributing the workforce, and getting better, realistic targets. In our next blog from the BI series, we will discuss the benefits and examples of BI to get deeper into our understanding of the technology. Stay tuned!

Read other Extentia Blog posts here!