Data analytics is the science of analyzing raw information for use in optimizing performance. If you want to see a practical example, watch the movie Moneyball.
The development of analytics parallels that of the automobile industry, which evolved in three broad phases.
In the late 1800s, custom coachmakers assembled expensive horseless carriages for the well-heeled. But in the early 1900s, Henry Ford’s invention of the assembly line made cars affordable for the average consumer and set the world on wheels.
Today Elon Musk and others are revolutionizing the industry again, creating environmentally-friendly electric cars that drive themselves, powered by analytics.
Analytics is evolving the same way, only much faster. Twenty-five years ago, it was considered an art and a science and largely confined to geeks. Then came the second stage and analytics was democratized by outsourcing it to countries like India.
Now the industry is entering the equivalent of the self-driving stage. Three dimensions will define this next phase:
1. It will be always “on”. Artificial intelligence will analyze reams of data to generate insights continuously. Marketing departments are already transitioning from term-specific advertising campaigns to continuous engagement through digital and social media. They will need to constantly come up with new insights and ways to measure their impact.
2. Analytics will be automated through machine learning and artificial intelligence. If we cannot answer business questions fast enough, we will miss our windows of opportunity. Automating analytics will be critical to staying on top of business trends. We need to evolve from periodic reports to models that analyze multiple data sources to deliver insights more frequently.
3. Information and interpretation will be shared. Industries have specialized departments (ie, sales, marketing, etc,) to expedite their operations. However, this can lead to a siloed and fragmented approach to understanding the consumer and the marketplace. Analytics will link departments by providing a unified view. Methodologies like market mix modeling (MMM) offer a shared view of ROI and optimization opportunities.
We are approaching the day when the availability of data and artificial intelligence will combine to offer the equalivant of a driverless car.
