Ikigai Labs’ Generative AI Platform Now Available in AWS Marketplace
Read announcement

What is Business Intelligence?

Business intelligence is a broad term that encompasses procedures, infrastructure, tools and data sets used to make strategic business decisions.

Oct 25, 2022
15 minutes to read

We are now in an algorithmic world where data is currency. However, harnessing big data is not enough. Organizations must also have the means to digest statistics and information and generate valuable insights for decision-making.

From cottage industries to multinational corporations, enterprises use BI or business intelligence in some form for speedy data integration and analysis. As a result, decisions that can make or break an enterprise are made daily. Informed decision-makers who make calls based on accurate information and assessments triumph, but those with insufficient data make decisions that result in slow growth, stagnancy or decline.

Unfortunately, 82 percent of companies utilize stale data, and 85 percent of said data leads to poor decisions and lost revenue. With BI, companies can discover ways to improve their overall performance and increase their bottom line.

What Is BI or Business Intelligence?

Business intelligence is a broad term that encompasses procedures, infrastructure, tools and data sets used to make strategic business decisions. It involves various processes, including data mining, performance benchmarking, process analysis and analytics. It benefits many areas like supply chain management and demand planning, customer services, product development and human resources.

BI is descriptive and discusses the organization’s current state, such as this month's sales, this week’s fulfillments, or today’s earned leads. It also outlines how past events brought the company to where it is today. It is not to be confused with business analytics, which is predictive and prescriptive. Therefore, references to business intelligence analytics most likely mean the combination of BI and business analytics.

How Does BI Work?

There is no single method or procedure for BI. Instead, it is a broad concept that covers various processes and methods of collecting, collating, analyzing and interpreting data. The goal, however, is the same: to understand the organization’s current standing and help its teams or members make better decisions so that the collective can optimize their performance.

Companies that invest time and resources in BI would use the following methods of collecting, analyzing and storing data:

Data mining: Most companies have diversely formatted and unstructured data that is difficult to collect and merge for easier analysis. Fortunately, BI software like the SAP business intelligence platform makes data mining easier.

Querying: This is asking for specific data from different data sets. BI tools pull the information from various data sources and present them in concise reports for easier parsing.

Data preparation: Similar to querying, data preparation presents data in a sensible and structured format that’s ready for analysis. It pulls data from various sources, whereas querying generates information from data-specific questions.

Benchmarking: Tracking current performance and comparing it with previous periods is an excellent way to gauge a company’s present status. Benchmarks are based on historical data and help determine how a company compares to competitors and the industry at large.

Statistical analytics: This branch of business intelligence analytics focuses on statistical data and identifying trends that could help inform present and future business decisions.

Descriptive analytics: It is interpreting historical data to discover what happened in the past and understand how it influences the present. Descriptive analytics touches on all other methods in this list because it involves data collection, preparation, analysis and benchmarking.

Data visualization: Analysts can present data visually through graphs, tables or pie charts to make it more digestible. Data visualization makes information more accessible to people without a background in statistics. Many decision-makers look at the bigger picture instead of the little details, and looking at visual data helps them do that without missing out on essential information.

Reporting: When the data and insights are ready, the information is presented to the organization’s executives and stakeholders.

BI continues to evolve, so this list can change in the future. Interestingly, progress in BI software can transform the way organizations approach BI. For example, if SAP business intelligence dashboards integrate more data sources, analysts will have more freedom to customize queries, analytics and reports.

Benefits of BI

Companies get a holistic understanding of their enterprise through BI, enabling decision-makers to be strategic, data-driven and implement ways to improve the organization’s performance.

Here’s a granular look at the benefits of BI:

- Make real-time data more accessible

- Faster and accurate reporting

- Better optimization of operations

- Increased organizational efficiency

- Improved performance tracking

- Faster and enhanced data analysis

- Better ability to eliminate problems and inefficiencies

- Better ability to identify and track market trends

- Improved employee and customer satisfaction

- Increased competitive advantage and profitability

- Higher chances of accelerating growth

The Disadvantages of Traditional BI

As with any analytics-driven endeavor, implementing BI processes can present some disadvantages for organizations that are new to its demands.

Here are some examples of the challenges companies may encounter:

High upfront costs

Initial resistance from employees

Skills gap between compliant and resistant employees

Long training and adjustment periods

Underutilization or misuse of BI tools and platforms

Evolving data privacy laws might render some BI tools and platforms ineffective in the future

How To Create a BI Strategy

BI insights can propel a company to success and should motivate organizations to develop their own strategy.

A BI strategy provides the blueprint for what to do with data, which platforms to use, who will use them and how to use insights to make data-driven decisions.

Here is a straightforward process for developing a BI strategy:

  1. Identify goals and vision

Your BI strategy has to align with the business’s goals and vision. Otherwise, analysts and decision-makers cannot maximize data insights to achieve long-term goals.

  1. Find an executive sponsor

The sponsor, usually a C-level executive, helps set the vision for BI, align it to the organization’s goals, nominate staff to carry out specific tasks and ensure accountability for the project. They also help answer the question “what is BI,” and why it is worth investing in.

  1. Choose a BI platform

A business intelligence platform is crucial for implementing a BI strategy. Choosing a highly-rated platform is a must, but the more important question is whether it can support the organization’s needs and goals.

  1. Pick representatives from each department

Interview at least one representative from departments that generate, record and utilize data. Ask about their needs, how they interact with data and how they can contribute to the overall strategy.

  1. Create a BI project team

The success of a BI strategy depends on the implementation team, so it’s best to recruit people committed to achieving a seamless, integrative and effective strategy. A BI project team typically consists of a software or platform manager, a process architect in charge of integrating the BI platform into the existing data infrastructure, a site administrator and data stewards.

  1. Define the scope of the BI strategy

Part of the implementation of BI is introducing how the strategy will impact day-to-day operations. Knowing the purpose of the SOPs and their benefits also helps win the members’ cooperation.

  1. Identify and prepare data sources

Another important task for the BI project team is identifying data sources and finding ways to integrate them into a unified data infrastructure. Obtaining data from databases like spreadsheets and CRM programs is easy; collecting pertinent information from informal data sources like emails and chat logs with customers is not. The implementing team must assess which data sources to include and figure out efficient ways to collect and collate them.

  1. Create a BI implementation roadmap

Lastly, the implementation team must have an implementation roadmap for the entire organization. It should include details like target milestones and completion dates of the various implementation stages.

Future-Proof Your Organization With BI

Giving BI meaning in your business by making it a prerequisite for important business decisions can pay off in increased productivity and new, innovative revenue streams. By becoming data-driven, companies can minimize uncertainty and improve the accuracy of their projections.

Data will continue to play a major role in business. Those who invest time and resources into analyzing data and getting valuable insights today will be in a better position than their competitors in the future. With BI, you can take your business to the next level and weather market factors that can shake up less prepared business entities.

Start your BI strategy with an agile,  robust data management and analysis platform. Developed from MIT research on AI and machine learning technologies, Ikigai is only commercially available software of its kind - an operational BI platform. It seamlessly integrates with over 200 data management platforms, CRM, social media analytics, research software, e-commerce platforms and other data sources. Most importantly, it enables business leaders to make quick operational decisions that are data-driven.

Transition to a data-driven approach to future-proof your business with the tools Ikigai provides. Send us a message if you have questions about the platform and its pricing packages, then book a demo to see how your BI strategy can materialize with Ikigai.

In this article:


Team Ikigai

Recommended articles

Ikigai and OpenCrowd Partner to Unlock the Power of AI for Financial Services Organizations
Ikigai Platform
Banking & Financial Services
Not all GenAI is created equal
Time Series Forecasting
The Evolving Landscape of AI: Contrasting Views on Models, Training and Inference
Time Series Forecasting

Subscribe to Ikigai Blog

Don't miss the latest updates from the Ikigai team.
Thank you! Your submission has been received!
Oops! Something went wrong while submitting the form.