Today every business is surfing in the ever-expanding sea of data & using analytics for getting the edge over their competition.
With the explosion of unstructured data on social media, audio-video steams, companies are rushing to use this for big insights.
There are mainly 3 types of analytics & it is based on the company’s maturity in analytics as to which one to adopt….Descriptive, Predictive & Prescriptive analytics.
Let me explain with examples.
What questions are answered?
How many customers?
Where revenue is less?
Why it is so?
What will happen next?
What trends will continue?
What if we change pricing?
What is the best course of action for a given situation?
What is the impact of seasonality?
How it is done?
Use of KPIs, dashboards, charts
Use of statistical methods to understand the relationships in input data & predict the outcomes.
Use of data mining, forecasting, predictive modeling.
Use of advanced statistical optimization & simulation techniques with inputs & constraints to recommend what actions to be taken.
How many customers have churned? Why did they churn?
How many customers will churn in the next few months?
What actions to be taken to retain these predicted churners?
Some of the Industry examples
Netflix uses data mining to find out correlations between different movies that subscribers rent & then recommend the one which you are most likely to watch
ING using personalized campaign offers in real time by predicting who will respond, to increase 30-40% response rates & reduce direct marketing costs by 35% per year.
Amazon.com using price optimization based on demand to increase the online shopping revenues.
· Consumer product companies are using it to maximize the marketing dollar spend
· Transportation & Logistics companies are using it to find the best route for their deliveries & backhaul
· Healthcare service providers are using it to decide how many beds they should increase in the hospitals
· Manufacturing giants are using it for inventory optimization to decide how much safety stock they should keep of each item, where to stock it based on the demand
· Telecom business is using it for providing on the spot offers to customers when they call the customer service centers
One daily life example - Imagine you are driving a car with a built-in GPS, which analyses all the data it collects from the satellite about traffic, accidents, weather etc. It tells you which routes will have heavy traffic (prediction), but also recommends you the alternate routes (prescription) with less traffic.
So Prescriptive analytics is where you know what the future is, but also know what to do with it, with alternatives of best outcomes J