How to use business intelligence effectively in the COVID-19 era?

Business Intelligence is becoming the new norm as businesses want to analyze their data in-depth and gain actionable insights

Akashdeep Arul
New Update
How to use business intelligence effectively in the COVID-19 era?

It is difficult to deny the importance of statistics in this data-driven world as it controls everything, from what we wear to what we eat. These days companies’ understand what we want a little too easily.


Same goes with running a company where even the minutest decision can either shape or destroy your business. This is where Business Intelligence (BI) comes into play.

BI helps users draw conclusions from data analysis. Data scientists dig into the specifics of data, using advanced statistics and predictive analytics to discover patterns and forecast future patterns. It is designed to answer specific queries and provide at-a-glance analysis for decisions or planning.

In an exclusive interview with Rajesh Murthy, Founder Architect & Vice President Engineering, Intellicus Technologies, find out his views and how he has adopted BI.


How has Covid-19 accelerated the business of your industry?

The pandemic has accelerated the digital revolution. Even in some of the most traditional sectors, there is now a rush to adopt new technologies and become digital. Companies that had adopted BI earlier are now extending its use across their organizations, while those that had not already, are now turning to BI to streamline their business operations.

Thus, BI is becoming the new norm as businesses want to analyze their data in-depth and gain actionable insights. Therefore, it is safe to say that digitization is the new normal, and BI is the penultimate stage of it.


According to you what are the five most important things that BI should be looking at today?

In today’s world, BI should consider the following appropriate data storage as every department and organization has a different purpose, we need to have an appropriate data source.

Therefore, when a data warehouse is designed, it should consist of multiple data engines that serve several purposes. It should be the job of BI to be able to gather data from disparate systems like e-commerce, finance, procurement, etc. This allows the applications to use their own respective powerful databases.


When BI is implemented and trusted by the top brass, data-centric reports become the standard norm in a company. Our client, one of India’s fastest-growing retail companies, implemented BI into their sales department within a month, making their operations altogether paperless. This happened because BI was seamlessly adopted by employees across the hierarchy.

BI should have artificial intelligence/machine learning (AI/ML). AI can go through business history and learn from it, which is ML. This intelligence gathered via ML can then be converted into a prediction model. This model, for instance, could predict the growth or decline of a sector, demand for products in a particular category, potential in a given region, the likelihood of hindrance to supply, and so on.

BI should not only bring in all internal data systems but external data systems as well. This will help businesses identify the external factors that harm business operations like commodity price, weather information, population information, etc.


What were the challenges you witnessed during the initial days of covid lockdown?

Initially, we were a little skeptical about upcoming business. Although BI is strategically vital, it is the third stage of digitization, so, we expected it to lose priority. However, this eventually proved to be false, as we witnessed new opportunities. Also, I am thankful to my team, who really stood up in these times and gave back-to-back successful deliveries.

What is the future of the tech industry? Some key things you suggest the industry should focus on.


The tech industry is going to be dominated by AI/ML. For instance, in the manufacturing industry, AI can empower machines to make crucial decisions like changing the RPM of a machine, changing the calibration, or even switching it off before any of these issues even come to human notice. Even the top management is leveraging AI/ML to make powerful data-driven decisions.

What is the future of learning in the next couple of years?

We have a lot of data passing through our systems. However, companies capture a minuscule amount of it in their databases which could be less than 3% of the total data available.

Businesses need to learn what data they need to capture in order to make business insights more valuable and overall business more efficient. Both the technical and business teams need to explore this next level of data required to start the next level of digitization. This could be IoT-based, sensor-based, camera-based, etc. And finally, AI will give us new outcomes with this data.