Data and Machine Learning change competitions

A few of companies takes advantage of value of data

Most companies are capturing only a fraction of the potential value from data and analytics. Location-based services and retail are areas of showing the advanced data analytics based business by digital native companies. Manufacturing, public sector, and health care have captured less than 30 percent of the potential value. Further, making the gap between the leaders and laggards even bigger than before

Extracting value from data and analytics is not done in organizational

Many struggle to incorporate data-driven insights into day-to-day business processes. Another challenge is attracting and retaining the right talent — not only data scientists but business translators who combine data savvy with industry and functional expertise

Data and analytics are changing competition

Leading companies are using their capabilities not only to improve their core operations but to launch entirely new business models. The network effects of digital platforms are creating a winner-take-most dynamic

Data is a critical asset for business

The value of data is tied to its ultimate use. While data itself will become in commodity, the value of data is to accrue to the owners of scarce data, to players that aggregate data in unique ways, and to providers of valuable analytics

Data and analytics underpin disruptive business models

New types of data sets can disrupt industries, and massive data integration capabilities can break through organizational and technological silos, enabling new insights and models. Digital platforms can match buyers and sellers in real time, transforming inefficient markets. Segmented data are used to personalize products and services. New analytical techniques can fuel discovery and innovation. Data and analytics can enable faster and more evidence based decision making

Advances in machine learning use to solve a tremendous variety of problem and deep learning is pushing the boundaries even further

Systems enabled by machine learning can provide customer service, manage logistics, analyze medical records, or even write news stories. The value potential is even in industries that have been slow to digitize. These technologies could generate productivity gains and an improved quality of life along with job losses and other disruptions. 45 percent of work activities could potentially be automated by current technologies. Machine learning can be an enabling technology for the automation of 80 percent of those activities. Natural language processing could expand that impact even further

Data and analytics are already shaking up multiple industries

The effects becomes more pronounced as adoption reaches critical mass. An even bigger wave of change is looming on the horizon as deep learning reaches maturity. Organizations that are able to harness these capabilities effectively will be able to create significant value and differentiate themselves, while others will find themselves increasingly at a disadvantage

** This article is adopted from “The age of analytics” by McKinsey Global Institute, December 2016