Peter Drucker seems to be more popular than in the past, greatly surpassing some of the best management thinkers and business leaders-even Jack Welch, the celebrated former CEO of General Electric.
Those are the conclusions sucked from a recent text analysis of Peter Drucker's popularity conducted inside a Drucker School Social networking Analytics course taught by Research Associate Professor Chris S. Langdon. In the class, students learn about text and sentiment analysis and use machine learning methods-a branch of artificial intelligence based on automated systems that may study from data, identify patterns, making decisions with minimal human intervention-to create recommendation engines, software that analyzes data and makes recommendation to users-think Amazon's recommendations. For any illustration showing text analysis, Langdon utilized Google Books Ngram Viewer-a one-of-a-kind online tool that tracks the regularity of words or phrases within the countless books digitized by the Google Books project.
When Langdon's class entered Peter Drucker's name and various other top names in business and management-including Harvard Business School theorist Michael Porter, economics Nobel laureate Daniel Kahneman, and influential marketing scholar Philip Kotler-the results were stunning: Peter Drucker's name came out on the top.
For Langdon, who also runs the school's Drucker Customer Lab, this analysis shows a minimum of two effects: \”Firstly the extent of the popularity of 'Peter Drucker' over decades, and secondly, how enduring it remains within this digital age.\”
The names were tracked in the 1930s towards the late 2000s.
For the newest years, Peter Drucker's name comes up much more frequently compared to Jack Welch, the legendary business executive who served as chairman and CEO of Whirlpool from 1981 to 2001. And while the frequency of Jack Welch's name drops off sharply within the mid-2000s, Peter Drucker's remained largely steady during this span-even after his death in November 2005.
This in-class example underscores the key role of massive data, analytics, and real-life experiments in implementing the type of innovation that's cultivated within the Drucker Customer Lab, Langdon says
Lab participants gain firsthand experience working with telemetry and biometric sensors for data collection, cloud-based machine-learning systems for analytics, and app-enabled rapid prototyping toolkits for experiments. Drucker wrote that innovation results from analysis, systematic review, and hard work-all which may be taught, replicated, and learned.
\”We actively implement Peter Drucker's ideas, his views, his thinking,\” Langdon said.
