Over the course of the next 20 years, we will see changes in the way we have been working for the last 2000 years.
The way we work is changing. There have been 4 major areas in human history that defined the way we work; the Hunter and Gatherer Age lasted several million years, the Agricultural Age lasted several thousand years, the Industrial Age lasted a couple of centuries, and the Information Age lasted only a few decades. And now, we are at the beginning of a new age in human history; the Augmented Age. In this new age, we will be augmented by machine intelligence.
During the information age, one of the important enablers was the Internet. It was most commonly about disruption of distribution, availability of information and rethinking the value chain. The next age will be about disruption of information, intelligence, and advice. Augmented Age will bring about a massive rethink of processes involving dynamic decision making, pattern recognition, and advisory services as machine intelligence optimizes those processes and feedback loops.
Let’s have a look at how Business Intelligence and Analytics market has been evolving during the information age, and will continue to evolve during the Augmented Age. In the 2017 BI and Analytics Magic Quadrant, Gartner described three “waves” of business intelligence:
1. IT-Centric Semantic-Layer-based Approach
2. Visual-Based Data Discovery
3. Smart Data Discovery
Here is my take on these three waves. During the first wave, the analytics systems were passive. They were providing answers to business questions with exactly what the user asks for. However, they were never given the opportunity to harvest the data. The users were limited to pre-canned reports where they never got access to the full texture and variety of the data underlying those numbers.
During the second wave, the systems became easier to use with self-service visualization capabilities. The business users were empowered, but they were limited to analyze data with one visualization at a time, and with a few dimensions and measures. They were interested in the “forest” of data, but they only got a beautiful little stick to explore it.
Forest vs Stick
During these 2 waves, Qlik’s associative difference helped the users analyze the whole “forest”, allowing them to see the whole story that lives in their data. It enabled them to probe all possible associations that exists in their data. The users were not limited with a beautiful little stick, but were able to explore the whole forest.
The 3rd wave is an evolution of data discovery that automates the analytics workflow through machine learning. I think about the 3rd wave as “generative”. With the increased power of computation and the use of advanced algorithms, the business intelligence systems will auto-generate analysis for the users and will find statistically significant insights in the data. But generating insights without the user input and intuition would not lead to the best decision-making results.
Generative + Intuitive + Associative
That is why our approach to analytics in this 3rd wave is not only generative, but intuitive and also associative. We are going after designing an experience that puts human intuition in the middle of data and advanced algorithms. We are designing solutions that use;
the human at what the human is good at; awareness, perception and ultimately decision making
the machine at what the machine is good at; running advanced algorithms on large scale data to find statistically significant insights in associative ways.
This approach is known as Augmented Intelligence. So to drive value, we believe that smart data discovery capabilities should work in combination with human centric analysis and exploration, to satisfy the full range of users and use cases in an organization.
That is why we are creating purposefully crafted user experiences with a smart system. They will truly enable the human to see beyond numbers and explore interesting phenomena, and generate new hypothesis with the support of a smart and associative system.