Typically, most organizations fall in either of the two categories; those that have no data and those that are flooded with data but no use.

Neither of these categories is good.

The ones with no data lack visibility and the ones with tons of data without use; are just confused.

What if you could actually take the right decisions about what might happen in the future and possibly give you the best recommendations based on heuristic data.


From long, statisticians have been juggling with numbers to provide descriptive analytics on various fronts. With the evolution, the term statistician became sexier and is now known as a data scientist.

These data scientists help us make sense of the big data and provide analytics in various formats.

Descriptive analytics

It is merely showing the raw data is a more meaningful manner so that it makes sense to the human eye. It focuses only on the historical data, uses the basic arithmetic and visualization to show the data in various graphical formats.

Predictive analytics

As the term says, predict the future. It uses the historical data and rather than just presenting the data, it analyzes the data and estimates the likelihood of a similar outcome in the future.

The foundation is based on probabilities of predicting the future occurrence based on the historical data.

Prescriptive analytics

The most advanced analytic tools help advise possible actions and guide towards a solution. These tools analyze and quantify the outcome of multiple possible actions before you actually take a decision.


The Way Forward

Getting rid of the uncertainties of the future surely takes the stress out of planning business strategies. Although this technology won’t give you physic superpowers; however, it can make successful predictions by utilizing the heuristic data and creating patterns.

The move from the descriptive analytics to predictive analytics is a giant leap and adds immense value to the users, by assessing which actions are likely to be more profitable at specific times.

Most businesses use descriptive analytics by utilizing the raw data and putting counters on it. The problem with descriptive analytics is that it only gives you the hindsight on the action that has already happened.

Predictive analytics, on the other hand, allows foresight, by creating the data which is not available yet for making successful predictions.

In a specific on-demand delivery use case, our startup utilized geo-location data to predict the demand and suggest users the best locations to place the drivers.
It helps to be able to predict the future.

Imagine being able to know ahead of time when an order was expected to come in? Your drivers could position smarter, you could efficiently prepare orders for pick up and even become extremely smart at dispatching jobs that were to be heading in the same direction!

Prescriptive analytic tools will be able to predict and prescribe the possible outcomes and recommend the best course of action which will be profitable to the users.

These tools will utilize a variety of statistical and analytical techniques to study recent and historical data, thereby making predictions about the future.

Meanwhile, they won’t always be able to predict the exact outcomes, not 100% though.

The idea is not to tell you what will happen in the future. The idea is to give you a hint of what might happen in the future and possibly give you the best options based on heuristic data.