predictive analytics

It is not a secret that the amount of data generated in the last decade is big enough to equate multiple times the knowledge that humanity build out since its conception. A big chunk of it, is generated by sensors and pieces of equipment, and only a small proportion of that information is used by companies and corporations to learn about their past to understand the present, and finally predict the future.

All the ingredients are out there, and leveraging the power of Predictive Analytics and the necessary data, it is possible to predict with amazing accuracy when a machine will fail.

The good news is that this new reality is starting to be noticed by the decision makers and executives of companies around the globe.

Recently, Bain & Co, surveyed executives at more than 400 companies around the world (most with revenues over a billion dollars). Of those companies, only 4% are really good at analytics, improving their processes and products using actionable information extracted of their own data. The difference is noticeable:

  • Twice as likely to be in the top quartile of financial performance within their industries
  • Three times more likely to execute decisions as intended
  • Five times more likely to make decisions faster

So, if the benefits are that good, why are only 4% of the companies investing in good analytics?

We think the organizations are just starting to realize those benefits and starting to figure out how to get started.

There are companies that generate data and don’t have the knowledge to transform that into actionable predictions or companies that think their data is not complete enough or is “too messy” to extract good information from it. It is important for those organizations to understand that with relative small amounts of data, but with the correct statistical and visualizations tolls and techniques, companies can go from that 96% of companies that storage data and become part of that exclusive 4% of companies that make their data work for them.