A day doesn’t go by without another analyst firm coming up with market size analysis for Predictive Analytics. While it’s a great sign that the space is heating up, some of the available statistics are sometimes hard to correlate. For instance, Transparency Research predicts the Predictive Analytics space would more than triple between 2012 and 2019 from $2B to $6.5B, and Markets and Markets highlights that the space would reach $5.2B in 2018.
Yet, if you consider Machine-to-Machine Analytics to be part of Predictive Analytics domain, you’ll be surprised to find out that it has been forecasted to reach $14B by 2018. Other might consider that the future of advanced analytics solutions is in the cloud, in which case they would consider that the predications that see that market grow to $16.5B by 2018 would be representative of the opportunity. The same data would become more confusing when looking at it from a specific industry lense; according to this other report, the market for advanced analytics in healthcare is bound to reach $20B in 2020…
So, why is it so hard to predict the size of a market like Predictive Analytics or Advanced Analytics – regardless if it’s in the cloud, on premises, in healthcare or any other industry?
The most obvious answer is different methodologies for calculating market sizes and varying definitions for Advanced Analytics even means. There is also another phenomenon happening: the marketing is changing so fast, the evolution of solutions is so rapid that it’s making it very challenging to define what fits under the umbrella of “Advanced Analytics” and accurately forecast it. Sure, we all know that Advanced Analytics is about Prediction, Recommendation and Optimization but the application of it has drastically changed.
Technologies like In-Cluster Analytics on top of Hadoop, Code-Free and Collaborative environments for Data Science have revolutionized the space. 2014 will see the emergence of what we call the “Predictive Enterprise”.
The Predictive Enterprise is characterized by the ability it creates for all its employees to be involved in the Data Science process. The Predictive Enterprise concept also rests on the idea that its technology stack supports its business needs regardless if the data is structured or unstructured, stored on premise, in the cloud, on standard data warehouses like Oracle, MPP databases like Greenplum or distributed data platforms like Hadoop.
If you consider the market to be more inclusive of people and data forms, you’ll indeed find that the market is not a mere $6B, it is potentially 10 or 20 times bigger. After all, Gartner predicted last year that Big Data would drive $232 Billion in IT Spending Through 2016.
So, how should you start getting engaged with this new opportunity? Feel free to watch the below video on how companies like Zions Bancorporation is describing the changes in the Predictive Analytics World.