Business intelligence is a specially curated infrastructure that is a collection of various processes and tools that help to enhance the visualization of the data. This enhanced data visibility aids businesses in making actionable decisions.

The main aim of BI is to make data available and easy to read so that important information is not lost. This further culminates into a progressive decision-making process that is efficient, time-saving, and effective.

History of Business Intelligence

The term Business Intelligence was first coined by Richard Miller Devens. He used it to describe a real-life scenario when a person named Sir Henry Furness made good use of data analytics to beat his market competitors. In a rather recent time, Hans Peter Luhn who is an IBM computer scientist discussed the many ways BI can benefit the e-commerce world.

In the 60s, there were only a handful of people who were aligned with the required skills to translate data or project the data into mapping future scenarios. The data was stored in fragments and the record-keeping process was tiring Data sorting was a major problem at that time. Because for successful projections, data management was inevitable.

Edgar Codd was the first person to recognize this issue. He then published a paper in 1970. His in-depth and carefully drafted paper was a tremendous success among the business community, leading to the worldwide adoption of his “relational database model”.

This led to the development of the world’s first-ever database management system “Decision Support Systems”. Historians still believe that BI is a modern extension of DSS. Then, in 1980, with the expansion of the business community, there was a surge in the development of related tools which would make the whole process of data management, more manageable.

How Business Intelligence Works

Business intelligence processes are the roadmap of data organization and data sorting that ensures data transformation from a raw form into a structured form.

BI consists of three main components:

  • Data
  • Analytics
  • Visualizations

Data

Data is the amalgamation of all the necessary information that is helpful for the conduction and successful execution of a company’s operations. Data can be of various types such as:

  • Statistical information
  • Raw analytical data
  • Customer Feedback data
  • Sales number
  • Miscellaneous yet necessary information

It is a crucial business asset, whose absence, mishandling, and loss can hamper business activities.

Analytics

Business intelligence and analytics is the assessment of algorithms for feeding the data and generating future predictions and outcomes. It is a collection of tools, methods, and techniques that help to contain, process, manage, and streamline data which further helps in decision-making.

Visualizations

Visualization is the act of presenting the available data in graphical form to ensure an easy understanding of the available information. Some of the common formats of data visualization in Business Intelligence are:

  • Maps and plots
  • Graphs
  • Charts
  • Dashboards

This is a helpful tool as it increases the readability of the static data whose understanding would otherwise take hours and days.

Importance of Business Intelligence

Business intelligence is a vital part of modern business strategies. Here are some of the main benefits of using business intelligence which justifies the hype of it in the corporate world.

Business Operations Visibility

The incorporation of business intelligence in any business’s operations enhances data visibility and control. Business intelligence makes the best possible use of data sorting and data analytics which help to identify and rectify the errors on an early basis.

Customer Retention

Business intelligence helps businesses to better understand their customers’ buying patterns and behaviors. This way businesses can do customer segmentation.

Customer segmentation is a process that allows businesses to sort their customers into various segments depending on their product preferences. This provides them an insight into the buying behavior of customers i-e how often they are buying a product, what product they are buying, and what is customer feedback.

All of this, helps businesses to draft a customer-tailored product which enhances customer satisfaction and increases customer retention of the businesses.

Access to Real-time Data

Business intelligence solutions allow businesses to have direct access to real-time information and data. This enhanced availability of data is necessary to minimize unprecedented errors. Moreover, it also identifies the functional gaps that are hampering the overall operational capacity of businesses.

Market Competitiveness

One of the biggest perks of using BI solutions is that they provide you with insights into the operational prowess of your competitors. Knowing, understanding, and having access to this sort of information gives businesses a competitive advantage in their industry. Not only does it help update the products accordingly but it also enables businesses to provide a more fulfilling customer experience.

Sales and Revenue

Business intelligence provides organizations with adaptable and contemporary solutions that boost the marketing prowess of businesses. This surge in marketing campaigns further boosts ROI generation. BI solutions are highly helpful because they provide an in-depth analysis of your business’s current growth and can predict future outcomes. It is especially important for the development of stronger marketing campaigns by utilizing metrics such as customer acquisition cost, cost-per-lead, and click-through rate.

Types of Business Intelligence

Descriptive Analysis (What Happened)

Descriptive analysis is the assessment of the data management methods and previously used data analysis techniques within the company.

Diagnostic Analysis (Why this Happened)

Diagnostic analysis is the use of tools to determine, assess, evaluate, and identify the underlying trends and correlations between various data variables. You can either conduct a diagnostic analysis with the help of software such as Excel or manually by entering the data inside the sheet.

Predictive Analysis (What Could Happen)

A novel approach that combines the information from descriptive analysis and diagnostic analysis to predict future trends and outcomes. Some of the commonly used techniques for predictive analysis are as follows:

  • Logistics and Linear Regression Model
  • Neural network
  • Decision trees

Prescriptive Analysis (What Can We Do About It)

It is an approach in which tools and techniques are used to analyze data flow and methodologies. This is done to derive an optimized and actionable plan to achieve the company’s long-intended goals.

Business Intelligence Trends

As more and more businesses are warming up towards the idea and worth of business intelligence, the dependency of the corporate world on BI and its many uses is also expanding. That is why effective data collection and analysis is the need of the hour.

Here are some of the business intelligence trends that will be ruling the business market in 2023:

Automation

It is the age of automation and one cannot argue otherwise. Businesses can now rely on business intelligence for automation as well as no-code and low-code frameworks. With the aid of business intelligence, the otherwise sluggish and tedious task can become swift and exciting.

Augmented Analytics

Augmented analytics is a type of analysis where data interaction and management are fueled by machine learning and AI. The use of machine learning and its incorporation into business operations is inevitable. This is what allows the non-technical assets of the company to understand the data in a more organized manner. It is a rising business intelligence trend, one that provides contextual information and relevant insights to the seekers.

Predictive Intelligence

Predictive intelligence is the use of available data to formulate future projections. It acts as a guiding light to business owners so that they can have an insight into the future outcomes of their current business protocols. This serves as both a reliable platform for business analysis and a risk assessment tool. Predictive intelligence can successfully identify the gaps and can provide alternative solutions which can then improve the overall results.

AI-Powered Intelligence

You are living under a rock if you haven’t heard about AI. AI is everywhere and is the talk of the town. Nowadays, businesses demand real-time data analysis, and business intelligence is expected to craft AI models that are adaptive and suggestive.

Conversational Intelligence

Conversational intelligence works by decoding speech or text-based data to analyze and drive business decisions. The year 2023 is expected to see more involvement of conversational intelligence in other sectors of business operations apart from sales and marketing.

Main Elements of a Business Intelligence Strategy

Vision (The End Goal)

For the successful development of an effective business intelligence strategy, having a vision is necessary. Without an understanding of the company’s goals, it is impossible to craft a BI strategy that sits well with the overall company’s growth.

People (The Expert)

A person in charge who understands the company’s work module and is aligned with the BI workings is an important element in the development of a successful business intelligence strategy. The person in charge should train the subordinates on how to use the tools and educate the department regarding the most suitable data analysis method.

Process (The Road Map)

The analysis of the current process and how they are inefficient in providing the necessary outcomes. Moreover, the identification of the areas that can be improved and drafting the ways how the improvements can be implemented.

Architecture (The Infrastructure)

Understanding the whole infrastructure of the company such as its technical departments, non-technical departments, security requirements, software usage, and tools analysis, so that a comprehensive and company-centric BI strategy can be drafted.

Tools (The Methodology)

Determining which software will best suit the company’s operational prowess.

How to Develop a Business Intelligence Strategy

1. Analysis of the Current Ecosystem

Make sure to conduct an in-depth analysis of your business’s needs and requirements. Learn about the data requirements at every possible level and in all of the departments. The data tools and their requisition will differ from sector to sector. For instance, sales staff might need a tool for real-time customer data input. Therefore dissecting the business in-depth is a must.

2. Appointment of a Project Sponsor

To ensure seamless integration and incorporation of Business Intelligence strategy in the company-wide goals, choosing the project manager is critical. The project sponsor will appoint the right person for the right job and will educate the staff about the Business Intelligence elements and trends.

3. Identification of the Key Stakeholders

The next step is identifying those people who are going to be affected by the BI strategy and its various tools. Identification of these people helps to evaluate and update the BI strategy accordingly. This will lead to better and improved results in a short period.

4. Recruiting a Chief Data Officer

Data is of key importance and its management is a daunting task. Therefore a successful BI strategy development requires a Chief Data Officer. This commanding officer will evaluate the data quality and will improve the overall data management and performance.

5. Establishing a Governance Team

After the completion of the aforementioned steps, the evaluation of the BI is crucial. But keep in mind that while assessing the performance of BI you have to pay attention to its infrastructure. The BI infrastructure is necessary because it paints the necessary picture of how well the BI is incorporated into the whole business scenario.

6. Determination of Objectives

The past data analysis describes the current operational performance of your business. The new strategy needs to tell how far you want your business to reach. The BI goals and development strategy should be aligned with your business goals and vision.

7. A Data Map

Data modulation is a vital step. Data extraction from multiple sources and then its assortment so that its visibility is enhanced is a necessary measure in BI strategy development. A key thing to remember is that you have to add the data type as well. This way the overall productivity of the process is enhanced.

8. Choosing the Right Platform and Tools

BI platforms offer a wide range of services such as data analysis, data reporting, data sorting, data integration and so much more. Therefore, analyze your business needs before choosing a BI platform. Make sure to choose one that is aligned with your operational requirements and provides the services that you are looking for.

9. Preparation of the Data Infrastructure

Three main things make up the data infrastructure:

  • The BI architecture
  • Prepared Data
  • Data Integration plan

The BI software allows the business to combine data from various sources and not just data warehouses. The next step is the draft of a data infrastructure accordingly.

10. KPIs

KPIs are the abbreviation for Key Performance Indicators. These are the metrics that help you assess the performance of the existing and newly implemented BI Strategy and how it is performing against the company’s goals and objectives.

11. Roadmap

This is the step where you have to present everything that you have done so far to the stakeholders. Stakeholders need to have access to the visual representation of how BI is going to help the business and what will be the end goals of using BI for the business. A roadmap is a visual of where you currently stand and where you want to go with the help of BI.

12. Data Sharing Protocols

You need to set some SOPs of how your staff will be sharing or getting access to specific data sets. This determination of data sharing protocols and their advertisement across the company is a vital step. This way you are informing and educating all the team members regarding the necessary instructions and standards for data sharing and analysis.

13. Documentation of the Strategy

Every step that you have taken in drafting a BI strategy is worth documenting. This will increase the authenticity of your process and will allow you to reduce the chances of scope creep. Scope creep is something that happens when changes are made to a project without any control procedure. Documentation of the whole process is necessary to avoid this from happening.

14. Conduct a User Acceptance Testing

UAT is the last stop of your software development and the first step in testing the newly implemented software from the user end. Not only the installation of the software is necessary but its performance tracking is also essential.

15. End-User Training

The end users of a BI are the decision makers, people who draft policies, and anyone who needs access to data to formulate processes. Therefore, their training so that they can understand the whole process of BI simulation is critical.

16. ROI

To ensure maximum efficiency and a high level of productivity, your business intelligence strategy and company end goals should be aligned with each other. All of this leads to better decision-making and improved data collection which has a direct impact on the ROI of your business.

17. Annual Review

Last but not least, an annual review of the BI strategy is inevitable. This review will help you to assess where you are standing in your real-time integration of the BI strategy and whether the strategy agrees with your company’s operational prowess or not.

How to Choose the Right Platform

A successful implementation is only possible with the right tools and resources. Therefore choosing the right tools is paramount for any business’s success. Some of the most essential traits that you need to keep an eye on include the following.

Built-in AI

While choosing the right BI platform the most important thing to look out for is a built-in AI. A built-in AI is necessary for data understanding, and for the identification of crucial data set attributes.

Data Preparation

Is the BI Platform that you are choosing for your business capable enough to morph and merge various data sets collectively? Moreover, the platform should be able to read user-defined variables such as sizes, sets, and groups.

Data Visualization

The BI platform should offer a wide range of data visualization options apart from the traditionally available data graphics such as pie, charts, and flow diagrams. The platform should support highly interactive user-based dashboards and data manipulation venues.

Manageability

There are two questions that you need to answer in the context of a BI platform manageability. Is the platform easy to manage and supports navigation across multiple tabs or not? Does the platform support multiple channels for sharing information?

Product Usability

This one is directly linked to the prospects of better user engagement and enhanced user experience. It is important to verify whether the interface of the BI platform is easy to understand or is bouncing over the user’s head. In case a user is unable to navigate, understand, and comprehend the workings of the BI platform then the platform is not for your business or target audience.

Examples of Tools

BI tools offer in-depth data analysis and a user-friendly interface. Listed below are some of the most commonly used BI Tools.

  • SAP Business Objects
  • Datapine
  • MicroStrategy
  • SAS BI
  • Yellowfin BI
  • QlikSense
  • Zoho Analytics
  • Sisense

The Bottom Line

Business intelligence is the use of technology to derive and formulate business strategies that help produce progressive and long-lasting results. The information extracted from BI software is what allows the executives to make informed decisions, leading to better operational performance.

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