Facebook uses data as a compass for making decisions. Leveraging their infrastructure to help the company make critical business decisions, drive product changes, and push the company forward.
Facebook is recognized today as a data-driven company, it wasn’t always the case. When it started more than 10 years ago they were collecting a lot of data but not making decisions based on it. Around 2006, they started to release features with a more data-driven approach and deciding if a feature was finally implemented based on the engagement rate.
They continued their quest for a more data-driven way of making decisions and build tools internally. The first one was Hive, a data warehouse infrastructure built on top of Hadoop for providing data summarization, query, and analysis. Although many Facebook employees were using Hive to access the data they needed to perform their daily jobs, the majority of the company were unable to write the SQL code. So, the engineering team built a web-based interface to query Hive data and called it HiPal.
With the help of HiPal, more Facebook employees were able to query the data-sets available directly with ease enabling them to have a better understanding of the business and make more informed decisions.
“We expect companies that were born digital to accomplish things that business executives could only dream of a generation ago. But in fact the use of big data has the potential to transform traditional businesses as well. It may offer them even greater opportunities for competitive advantage (online businesses have always known that they were competing on how well they understood their data).”
Being data-driven will be key for 21st century companies. Several trends are now merging together creating an unprecedented opportunity: consumer behaviors are moving online, cost of data collection is declining empowering businesses to capture more data.
These “Big Data” are becoming a core asset in the economy, creating new industries and disrupting old
New processes based on data found their way into organizations creating significant competitive advantages for companies willing to grab this opportunity. Those companies are now one step ahead in our constantly changing hypercompetitive global economy.
Decisions are being taken everyday, with or without data to inform them. All those decisions are opportunities for your business to be improved. By choosing to take these decisions under the data spectre, you make sure your business is heading into the right direction.
Ultimately, data-driven companies win because they have made listening to and understanding their customers a basic component in their decision-making process.
“Historically, managers relied on “gut instinct” for decision-making simply because they lacked the data to do otherwise. Today, it’s more scientific, and many managers are not accustomed to making decisions this way. It’s a whole new culture.”
How can we make it happen?
Prescriptive Analytics recommends course of actions or decisions using optimisation and simulations algorithm.
What will happen?
Predictive Analytics uses predictive modelling using statistical and machine learning techniques to forecast metrics evolution.
Why did it happen?
Diagnostic Analytics is a form of advanced analytics using techniques such as drill-down, data discovery, data mining and correlations.
Descriptive Analytics helps you gain insight from historical data with reporting, scorecards, clustering etc.