Data & Analytics

While doing an in-depth audit for an organization question their leadership team asked was:

"What can we do to collect the right data, analyze and interpret that data into actionable steps?"

Most organizations think they are not tracking or collecting the right data. But what most of them don't realize is that, majority of the problem is not in collection and tracking, rather it's their inability to analyze and interpret the data into actionable steps.

Because until you don't know how to interpret data, you cannot take strategic decisions, predict or forecast outcomes and identify opportunities for growth.

There are 4 types of analytics. The more complex an analysis is the more value it brings:

Descriptive Analytics: Answers "What Happened" - It gives you valuables insights into the past.

Diagnostic Analytics: Answers "Why Something Happened" - It gives you reasons why something happened.

Predictive Analytics: Answers "What is Likely to Happen" - It gives you predictions and forecasts.

Prescriptive Analytics: Answers "What Actions to Take" - It gives you an action and implementation plan. This is the highest form of analytics which uses AI & machine learning.

2016 Global Data and Analytics Survey: Big Decisions, 2,000 executives were asked to choose a category that described their organization's decision-making process best.

Descriptive analytics dominated (58%) in the “Rarely data-driven decision-making”

Diagnostic analytics topped the list (34%) in the “Somewhat data-driven” ;

Predictive analytics (36%) led in the “Highly data-driven” category