What is Business Intelligence (BI)?
Business Intelligence (BI) is a set of applications, technologies and ideal practices for the integration, collection and presentation of business information and analysis. The motto of BI is to facilitate improved decision–making for businesses.
BI models provide present, past and projecting opinions of structured internal data for goods and departments. It provides effective strategic operational insights and helps in decision-making through predictive analytics, reporting, benchmarking, data/text mining and business performance administration.
Table of Content
Business Intelligence Definition
In 1958, IBM researcher, Hans Peter Luhn defined BI as “the ability to apprehend the interrelationships of presenting facts in such a way as to guide action towards a desired goal”.
In 1989, Future Gartner Group Analyst, Howard Dresner defined BI as “the concepts and methods to improve business decision-making by using fact-based support systems”.
According to Forrester Research, business intelligence is “a set of methodologies, processes, architectures, and technologies that transform raw data into meaningful and useful information used to enable more effective strategic, tactical, and operational insights and decision-making.”
According to Ghoshal and Kim, “Business Intelligence (BI) is a concept which refers to a managerial philosophy and a tool that is used in order to help organisations to man-age and refine information and to make more effective business decisions.”
Business Intelligence Example
Let us consider a few examples of some organisations that have benefitted from BI implementation.
Bituach Haklai, an insurance company from Israel, had successfully implemented InsFocus BI, an insurance BI system by InsFocus. The general manager of Bituach Haklai, Mr. Arieh Herman, states, “InsFocus BI had been tested and found to be the most suitable system for handling our company’s needs at Bituach Haklai, both today and in the future to come.
This system will allow us to continue to maintain our grasp in the market, improve our profitability and bring up-to-date and accurate data to the decision-makers in the company, which will improve and streamline our organisation”.
Rubio’s Restaurants, Inc. is a chain of restaurants from Mexico, which extends across six western states from California to Colorado. The director of IT for Rubio’s Restaurants, Paul Nishiyama, says, “BI has been extremely important to us. Finance is getting a whole series of more robust reports that it did not have before. Producing those reports without a business-intelligence system would be a manual process that would drain our small staff”.
Need for Business Intelligence
With the advancement and involvement of computers in our daily life, various computer-based techniques have improved the BI processes. The BI tools turn ‘data’ into ‘information’ and the ‘information’ further aids in taking ‘decisions’ on time. This results in data transparency, consistency and information reliability.
The decision-making process requires evaluating performance (what happened), testing hypotheses (why things happened and exploring relationships) and predicting the future events (what may happen). This implies that the strategies of an organisation are sound and they meet the required purpose.
In a nutshell, the BI system allows the user to answer the following questions:
- What happened?
- Did ‘what happened’ align with ‘what you expected to happen?
- Assuming X produces Y, are you executing X?
- How did it happen?
- How did X produce Y?
- Can you be certain that X will produce Y, or is it Z that is producing Y?
- Why did it happen?
- Did X cause Y to happen?
- If we execute X, then will Y happen?
- What may happen?
- If X occurs in the future, then will Y also occur?
- Assuming you executed X and it produced Y, can you assume that continuing to do X will continue to produce Y?
An effective BI solution must:
- Present a holistic picture and insight into tactical and strategic efforts
- Assist in fact-based decision making
- Accept or reject assumptions
- Discover non-intuitive relationships
- Provide prompt feedback regarding actions
BI for Past, Present, and Future
In a contemporary environment, organisations collect data on a routine basis to determine how their customers relate to their standard business processes. By analysing this data, organisations are gradually realising that they can uncover the hidden patterns to define new strategies to improve performance to achieve both short-term as well as long-term goals.
The Gartner Group, a leading research and advisory company, has made some notable observations about the usage of the BI system in contemporary organisations. Firstly, from 2009 to 2012, more than 35% of the top 5,000 global companies consistently failed to make insightful decisions about substantial transformation in their business and markets. In the present scenario, companies have become conscious of the need to make better decisions. Owing to this, organisations are more inclined towards increasing their investment in BI systems.
Secondly, as the importance of BI continues to grow, there are some major changes regarding their implementation in a contemporary organisation. The business units now play a bigger and critical role in implementing BI solutions. The BI systems that do not meet the requirements of the business managers are likely to be rejected, leading to a failed implementation. This will not only result in an adverse impact on the decision-making process but also a financial loss for the organisation.
Many organisations in the present scenario have a cross-functional BI unit that creates, maintains and updates all BI systems. This allows each unit to perform the functions they are best at and avail maximum resource utilisation.
To succeed in the next decade, BI experts should examine and adopt new methods. They need to get out of the idea that particular framework is suitable for all.
The current BI framework represents the next-generation BI ecosystem. This is a very flexible approach, which would help BI professionals tackle problems in a structured manner.
BI Value Chain
The process of converting data into information and then applying that knowledge in taking useful business decisions is known as the value chain. Let us understand the concept of the value chain by using the following examples.
Example 1: Yes, No, No, Yes, No, Yes, Yes, No, No, No
Example 2: 8692, 6215, 7190, 8204
The data sets given in the examples above have no meaning until they have a context and are processed into some usable value.
Information is the processed data. It is the subset of data that possesses context and meaning.
Let us check the relevance of the examples given earlier:
Example 1: Yes, No, No, Yes, No, Yes, Yes, No, No, No. This data becomes meaningful if it is a result of the marketing survey, “Can you switch from your favourite brand to another brand offering discounts?”
Example 2: The data in example 2 becomes meaningful if it reports about the monthly credit card bill of an account holder.
Knowledge represents the learning that is the internalisation of information, data, study and experience.
It serves as the basis for all skills and abilities. A factual and updated knowledge base helps organisations effectively make decisions and compete in the market.
Following actions can be taken based on earlier examples:
Action 1 (Example 1): A marketing manager could use this information to promote a particular brand.
Action 2 (Example 2): Based on the usage pattern of the credit card and the accountholder’s profile, the bank can offer different products, such as loans, insurance policies and add-on cards to the account holder.
The concept of transforming data into information and then to knowledge has been utilised in several organisations in different domains. For example, computers are data-processing machines that take input in the form of data and process it to generate meaningful information.
The knowledge obtained from this information helps organisations gain insights and derive appropriate conclusions.
Business Intelligence vs Business Analytics
Business Intelligence | Business Analytics |
---|---|
BI equips you with the information | BA gives you the knowledge |
Uses current and past data to optimise the current age performance for success | Utilises the past data and separately analyses the current data with past data as reference to prepare the businesses for the future |
Informs about what happened | Tells why it happened |
Quantifiable in nature, it can help you in measuring your business in visualisations, chartings and other data representation techniques | More subjective and open to interpretations and prone to changes due to ripples in organisational or strategic structure |
Studies the past of a company and ponders over what could’ve been done better to have more control over the outcomes | Predicts the future based on the learning gained from the past, present and projected business models for a given term shortly |
BI helps in bridging that gap between ground reality and management perspective on a pan-organisational basis. | BA helps you in knowing your business thoroughly. |
Another new trend is the skill to combine multiple data projects in one while making it useful in sales, marketing and customer support. One example is the CRM – Customer Relationship Management software, which sources raw data from every division and department, compiles it for a new understanding that otherwise would not have been visible from one point alone.
All these boils down to the interchangeable usage of the term ‘business intelligence’ and ‘business analytics’ and their importance in managing the relationship between business managers and data.
Owners and managers now, as a result of such accessibility, need to be more familiar with what data is capable of doing and how they need to actively produce data to create lucrative future returns. The significance of the data has not changed, its availability has.
Emerging Trends in BI
Some of the top BI trends are as follows:
High adoption rate of SaaS and Cloud
It has been observed that a lot of businesses are engaging in migrating to the cloud and looking to leverage all the benefits that are associated with cloudbased BI.
AI will be the new BI
Companies, especially after COVID, are ramping up their AI investments. This will ensure the complicities associated with it.
Automation
Automation is a popular concept and organisations are using AI for automating data analysis. Automation can take care of Tasks that are monotonous and are time-consuming and will be otherwise performed by humans are taken care of by the process of automation.
Analytics in real-time
Interactive presentations are replacing static reports. Business users may utilise responsiveness to explore and answer questions about data that is updated in realtime. Monitoring the most recent data allows analysts to respond quickly and accurately. Real-time data should be used in corporate presentations. To answer key business issues on the go, explore data dynamically and effectively. Real-time updates assist expedite insights and creating faster, more informed decision-making in reports and presentations.
Integration of data
A trend toward complete BI systems that handle data from numerous sources and in different ways is being fueled by increases in data volume, velocity and diversity. Massive volumes of data are now available from a variety of sources, necessitating the use of simple interfaces for quick data source integration.
For example, Power BI provides an easy-to-use solution for business users across the company to get insights buried in vast volumes of data. Power BI can handle data that is stored in the cloud in structured databases or unstructured data processed by Hadoop.
To convey social trends to co-workers, the Power BI visualisation features are used. Have real-time updates mirrored in your visualisations as social patterns shift, allowing for more flexible reactions to emergent market developments?
Technology for Business Analytics
Business analytics is a composition of various solutions that are used in building the model of analysis that will help in simulating and creating scenarios. This will hence help in understanding the realities and predict the future state of the business.
Predictive analytics, data mining, applied analytics and statistics are all part of the business analytics process, which is offered as an application that can be used by any business user. Such analytical solutions often come with industry content that is prebuilt and is targeted towards the process of industry business.
Technologies for BA include considerations for the following:
- Database
- Web
- Big data Computer network and equipment Data analysis and statistical packages Data visualisation tool
- Data Pre-processing tool
- Data Virtualisation tool
As far as the technology is concerned, the following trends in employment of business analysts are emerging:
- The Digital BA: BA helps organisations in adapting to the trend of digital transformations.
- DevOps: DevOps helps organisations in adapting a faster delivery of small changes. They do this while mitigating risks available in the production environment. This requires a different way of working and the adoption of new toolsets.
- Consulting in the Gig Economy: These are the times where a lot of people are preferring short consulting stints and avoid longterm employment. This trend is expected to grow further.
Business Analytics Tutorial
(Click on Topic to Read)
- What is Data?
- Big Data Management
- Types of Big Data Technologies
- Big Data Analytics
- What is Business Intelligence?
- Business Intelligence Challenges in Organisation
- Essential Skills for Business Analytics Professionals
- Data Analytics Challenges
- What is Descriptive Analytics?
- What is Descriptive Statistics?
- What is Predictive Analytics?
- What is Predictive Modelling?
- What is Data Mining?
- What is Prescriptive Analytics?
- What is Diagnostic Analytics?
- Implementing Business Analytics in Medium Sized Organisations
- Cincinnati Zoo Used Business Analytics for Improving Performance
- Dundas Bi Solution Helped Medidata and Its Clients in Getting Better Data Visualisation
- What is Data Visualisation?
- Tools for Data Visualisation
- Open Source Data Visualisation Tools
- Advantages and Disadvantages of Data Visualisation
- What is Social Media?
- What is Text Mining?
- What is Sentiment Analysis?
- What is Mobile Analytics?
- Types of Results From Mobile Analytics
- Mobile Analytics Tools
- Performing Mobile Analytics
- Financial Fraud Analytics
- What is HR Analytics?
- What is Healthcare Analytics?
- What is Supply Chain Analytics?
- What is Marketing Analytics?
- What is Web Analytics?
- What is Sports Analytics?
- Data Analytics for Government and NGO