Decision Analytics

Make data-driven facts-based decisions

Decision Analytics is about making the right business decisions at the right time.

Why is Decision Analytics Important?

A business survives and thrives only when the right decisions are taken in a timely manner. However, many businesses struggle in making decisions. This is because of three reasons: First, there is insufficient information. Second, they lack the skills and techniques to use the information. Third, they cannot do it within the stipulated time.

Unavailability of information and facts hinders effective decision-making. In the absence of data, executives rely on their gut-feel to make decisions. However, there is a dearth of confidence in such decisions. So they are rarely acted upon.

Even if the data is available, the shortage of the right skills to analyze data can be a challenge. Too much data may cause analysis-paralysis.

Moreover, no decision is worse than any decision taken in a timely manner. In the absence of a strong decision-making process, executives are apprehensive about making the wrong decisions.

A lack of efficient and effective decisions can push businesses into decline.

What is Decision Analytics?

Decision Analytics is the technique to make effective decisions, efficiently.

Decision Analytics uses past and current data to help you make decisions. Such decisions are objective, timely, and fact-based. So, they support executives to secure buy-in from stakeholders. Since they are facts-based, executives feel confident in implementing such decisions.

Furthermore, you can use decision analytics in all kinds of situations, as long as you have reliable data. This can result in increased credibility among your partners and collaborators.

Decision Analytics Case Study from a super-speciality hospital


A cardiologist from a leading super-specialty hospital


A cardiologist from a leading super-specialty hospital wanted to decide between mid sternotomy and a minimally invasive surgical approach for mitral valve replacement procedures.


Intuitively, one approach appeared better than the other. So, it was important to have a sufficient sample size to remove implicit bias. The objective was to study the effectiveness of the new method of cardiac surgery compared to the conventional way of performing the same procedure.


We statistically analyzed 27 different patient health parameters associated with both the mitral-valve replacement procedures. We performed a comparative analysis to uncover hidden insights relevant to both surgical procedures.


The observations helped the surgeon to understand the differences between the two surgical approaches. The results would help them make a fact-based policy decision to embrace the right procedure for their center.

Schedule Your Complimentary Session with us Today!

We promise you will come away with insights on utilizing your business data productively and cost-effectively. This session will be free of charge and there is no obligation.