New developments in analytics that enterprises can’t afford to ignore

By : |November 9, 2016 0
Organizations who aggregate and visualize data from multiple sources quickly will grow faster than competitors. New developments in analytics platforms can enable this for enterprises. Souma Das, Managing Director-India, QlikTech India, tell us the new trends in analytics and why enterprises can’t afford to ignore them. Excerpts....

What do you trust more for business decisions? Your gut-feel or facts and figures provided by data? If you said the former, then you’re not alone. According to a survey conducted by QlikTech recently, 65% managers said they rely more on gut feel than real data for their business decisions. But the times are changing, with increasing competition, decisions have to be taken quickly, and one wrong decision can cost you dearly. What’s badly needed is quick access to data based facts to Souma Dasvalidate your gut feel decisions. New developments in analytics and data visualization technologies promise to make this possible, and to understand the trends better, we had a face to face chat with Souma Das, the India Managing Director for QlikTech. Here are the excerpts.

What are some of the key trends in the analytics space today?

We’re living in a connected world where a humongous amount of data is being generated. So if you’re not able to see the whole picture from this data to take decisions and make some meaningful inferences, then this data has no meaning. But the challenge is that you’re spending money to generate this data.


So one of the shifts we’re seeing across all enterprises is essentially how the decision making process is changing. Traditionally, BI is nothing new. It’s the same old decision support system, coined into a new term called Business Analytics. What’s different is the way it’s being driven today than how it was a few years ago. Earlier, you would develop a certain set of reports at the back-end to help you take decisions. Statisticians and analysts would work with the business to understand their requirements and then create reports. These reports were mostly static and restricted business decision makers to what was predefined. If the business user needed something different, then it had to be sent back and re-built.

Today, the business scenario has completely changed. Studies show is that almost 65 to 70% of businesses need to take decisions within 24 hours. You don’t have the luxury to wait for a couple of days, because something major could disrupt your business over this time.

What you need is control and a ‘holistic’ view of your data. That’s because data today resides and is being generated by multiple business applications, be it your CRM, ERP, expense management system, or even your HR system that computes employee performance, appraisals, etc. All these sources should be able to provide data, and data managers should be able to associate and come up with a data set that can be given to users to take decisions.

You need to be able to deliver analytics to both internal and external users, so that they can take decisions quickly.

Can you illustrate this trend with some examples?

Let’s take insurance as an example. Agents are out in the market selling insurance. They need data to offer the right policy to prospective customers, and to be able to close the deal quickly. The decisions need to be taken instantaneously by the agent, else they will lose the customer to someone else. The same thing happens for a home loan.

If an agent can’t process a home loan quickly enough, and requires going back to office multiple times to check the data, then he/she could lose the customer. Time is therefore money in this industry.

The bottom-line here is that you need to monetize data by empowering the intelligence that already exists within your organization. Moreover, there’s an entire supply chain involved in any of the processes we talked about. They all need to work in collaboration and not in silos.

How ready are enterprises in terms of being able to embrace or get that data ready and bring it to a level where it can be analyzed?

When we talk about data driven decisions, the first thing that comes is data literacy. If you can empower more people and make them more data literate, where they can read, work with, analyze, and give narrative or argue with data, then your organization’s chances to be more successful are that much higher.

Any change of any new thing you want to adopt in an any organization is never easy. And when we talk about data driven culture, it has to be a hygiene. Can only a top down approach work? It’s easier said than done. Your people have to see value in it too in order for it to work.

For that, the right examples have to be looked at, and one of them is of Uber. It’s a fine example of a company running a multi-billion dollars business without owning a single car. They do it by capturing, analyzing, and then monetizing the huge amount of data they generate. They get data from their GPS and car positioning system, the destinations chosen by customers, the types of cars they chose, they distance they traveled, etc. They analyze this data to understand customer behavior.

A lot of people still make business decisions based on their gut feel. How do you change that to data driven decision?

It’s ironic that 65% people still sometimes take gut feel decisions. It happens either because they don’t have visibility or they don’t trust their data as it may not be up to date. It’s one of the things that Qlik addresses the best. We bring in data from multiple sources and make it available to enable you to get the whole picture.

Another thing you have to fix is to get people to start trusting their data. For that, they have to have a process to go scrutinize the results of all their gut-feel based decisions. For that again, you need data to substantiate those decisions. We’re trying to build a culture through our Qlik Analytics platform, where using and visualizing data becomes so easy that people start using it. As they start using and seeing positive outcomes, the use of data driven decisions will increase.

How do you establish trust amongst people to use data instead of going by gut-feel?

Gut-feel decisions have their own importance because they come from knowledge and experience. What you need is to have data that can validate your gut-feel.

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