Business Analytics has become an important function in every business organization:

We all agree that it’s an era of customers and that era is not going anywhere. For many decades, post the invention of computers, there has been an intelligent breed of strategy makers who have always relied upon the power of bringing intelligence into business decision-making with the help of statistical tools and technologies by creating data sets for analytical decision-making.

Business analytics, business intelligence & Data analytics, and big data & data science are some of the terms That are used interchangeably concerning understanding customers and their behavior but all of them have their specific definitions and meanings.

I still remember My stint working with an IBM and Hyperion partner in India wherein, I first worked on a solution called Brio from Hyperion. It was a business intelligence tool platform, and I was involved in Pre-sales consulting and training of the solution to large system integrators like Wipro, Infosys, etc. I was also doing proof of concepts (POCs) With companies like indiatimes.com & Bharti Airtel Ltd. It was fun working with a large set of customer databases and trying to make some meaningful insights from them. It involved combining data coming from multiple tables and creating pivots and charts on a large set of databases, which was not possible via Excel sheets as a techno-functional consultant.

The business intelligence reporting tools were costly & the manpower working on the solutions was scarce. Then business intelligence solutions were very high and technology solutions and CTO / CIOs were talking about it. I am talking about the years 2003-2004. However, a large number of traditional & B2B organizations were still unable to understand the advantages of business intelligent solutions.

Today, in 2024, post the popularity of the term big data, Business intelligence solutions and data sciences are the most important strategic tools for organizations of any scale and size. These rules are required for a better understanding of customers' behavior, customer profitability, customer segmentation, and predicting all of these. Conceptually business analytics is of multiple types which include descriptive analytics, prescriptive analytics, and predictive analytics.

These tools help you create dashboards and visualization of customer data for the easy understanding of the top management team members. The key executive gets real-time or near real-time Data and insights about customers, which becomes an important input for any business decision-making. However, it makes more sense for companies operating in BFSI, Telecom, e-commerce, utilities, Retail, FMCG, and consumer packaged goods (CPG) Industry a lot where the number and volume of customers are way beyond management. Still, few studies are emerging in other industries as well.

The advantages of implementing business analytics solutions are manyfold. Some of these benefits are as follows:

1 Helps improve strategic decisions by evaluating and making informed choices. Business owners still make a lot of decisions based on Gut. With these tools and solutions, they have access to a lot of information and insight.

2 These solutions help in identifying Industry and customer trends and help you to draw patterns of similar trends and behavior. This is especially helpful in creating new products and services in adjusting the current ones to stay relevant in the market.

3 The solutions also help in driving better performance from existing teams and resources and help in increasing revenues. When you have access to real-time or near real-time reporting of performance at the global level you can better instruct teams and resources for improving performance in certain specific areas.

4 These solutions are costly to implement initially but in the long run, help in improving operational efficiency and reducing the cost of operations. There are innovative solutions from companies like Amazon to get the test of cloud-based analytics at very economical rates.

5 With the help of predictive analytics, organizations can find improvement opportunities through predictions in various workflows and processes. These predictions help in improving operations, reducing costs, and improving revenue.

6 The solutions enable your organization to be smarter with an excess of graphical dashboards, visualization, and drill-down charts with faster reporting. So, it helps the board of directors and key leadership team members to have a real pulse of the organization for faster intervention by monitoring KPIs from sales, marketing, customers, manufacturing, supply chain, and finance.

These are the best ways to implement business analytics in your company

1 Have a companywide Business Intelligence and data analytics strategy. Companies should know their long-term goals, Current assessment of the RI infrastructure, and what they want to achieve. The company typically lies in 5 stages of data enablement and the stages are data Resistant, data-aware, Data guided, data-savvy & data-driven.

2 Discuss and gather Key Performance Indicators. Companies need to go beyond traditional KPIs Which are Sales, marketing, financial, project management, human resources, and customer hygiene factors. Companies should also look at ways to store and measure data around the speed of implementation of any new initiative, innovation, Employees' skill sets, learning index, and behavior, and how will they be prepared for any disruption.

3 Appoint team, consultants, trainers, stakeholders, and companies to start rolling out. If you don’t already have a business insights department or people responsible for the same, please create one. Depending upon the scale and size and budget availability, recruit team members and Consultants. BI core team members may include analysts, data mining experts, database admin, and data scientists and build a strong in-house business insights function. BI can answer Multiple questions: what, where why, and how. From a transformation perspective let them focus on the last two.

“To get qualified manpower for implementing business analytics in your organization. You can tie up with a leading IT training institution like Jetking Info train Ltd, which has several programs for big data and business analytics. You can easily find qualified manpower by contacting them.”

4 Evaluate and select tools by doing multiple POCs in various functions with the help of different tools. There are a variety of tools available so depending upon the suitability of the tool from a business function perspective do the proof of concept Four multiple rules and depending upon the strategy of its usage for a particular and core business function go for that tool.

5 Create a reporting server, data storage, environment, and platform for business intelligence. You have multiple options to get OLTP, OLAP, relational databases, and data cubes. From silos of data lying all across your organization, you can create a structured data warehouse, reporting server, and data lake. You can choose from the on-premise server, cloud server, or even a hybrid strategy depending upon the criticality and confidentiality of the data.

6 Have functional experts or subject matter experts start gathering business requirements and preparing the data input process and workflow. The most important aspect of this stage is not only data quality but also defining the right set of questions that your business intelligence will answer.

7 Run advanced Statistical models and sophisticated analysis if need be. After creating reports and building hypotheses, we use advanced statistical modeling tools to create new frameworks and data models.

8 Roll out enterprise-wide dashboards to have ready and combined access to multiple BI systems such as Ad-hoc analysis, online electrical processing, and operational and Real-time business analytics.

9 Regularly monitor KPIs for improvement and have monthly meetings with the board on new insights developed that require their urgent attention.

Business intelligence and data analytics have been there for ages but when we shift our focus to generating new insights about customers, products, and services and try to answer who and how-based questions, that is where start realizing the full potential of our business intelligence investment. Being a data-driven company ensures that major business decisions are backed up by Data logic rather than depending upon the gut and intuition-based decision of one key person Which may land the company in trouble.

Author information.

The above information is taken from a chapter of Mr. Ajay Chhabra‘s work-in-progress textbook on Digital Transformation. Ajay Chhabra is a veteran in the digital marketing industry in India with over 25 years of overall experience working with global digital marketing agencies and organizations. He is currently researching and working as a professor of practice in Digital Marketing at Woxsen University Hyderabad. He is also a visiting Professor at Flame University Pune, India. He can be reached at
https://www.linkedin.com/in/ajaychhabra
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