These and many other insights are from the McKinsey Global Institute’s study The Age of Analytics: Competing In A Data-Driven World published in collaboration with McKinsey Analytics this month. You can get a copy of the Executive Summary here (28 pp., free, no opt-in, PDF) and the full report (136 pp., free, no opt-in, PDF) here. Five years ago the McKinsey Global Institute (MGI) released Big Data: The Next Frontier For Innovation, Competition, and Productivity (156 pp., free no opt-in, PDF), and in the years since McKinsey sees data science adoption and value accelerate, specifically in the areas of machine learning and deep learning. The study underscores how critical integration is for gaining greater value from data and analytics. Key takeaways from the study include the following:
Management consultant firm McKinsey Analytics’s latest report has outlined how various industries are integrating machine learning into their operations. Sectors such as energy, manufacturing, automotive, media and transport and logistics are using data capture and analytics to improve efficiency, utilising real-time optimisation, predictive analytics, forecasting and processing of unstructured data to streamline business operations. McKinsey Analytics lists enabling autonomous vehicles and offering more personalised advertising as the two “highest opportunity” use cases for machine learning. However it also notes a lack of talent as a major barrier across many sectors.