Summary: Intro | Measuring the importance of gossip | Too good to be true | Arbitrary measures produce arbitrary results | tl;dr
Disclaimer: The probability computation of the article is a recap of a talk delivered by Professor Mark Whitehorn at the University of Dundee in 2015, and at PASS Business Analytics Conference in San Jose, CA in 2014. Opinions expressed are my own.
Aren’t we post-NPS hype yet? Such was my thinking until a random article came up on my feed: as one of its core objectives, a tech giant was planning to improve its Net Promoter Score by 2020. A quick internet search told me there are some companies very excited about increasing their NPS. Google Trends suggests the Net Promoter methodology is on the steady growth rate since 2004; a mortal blow to my presumption. There is something problematic about the Net Promoter methodology that I’d like to talk about: on one hand an indicator of an outstanding business delivery, on the other a possibly dangerous framework for workforce assessment. This article decomposes the NPS algorithm, reviews its criticism, and tests its validity from the probability perspective. I have based the scenario and the probability computation on an excellent talk delivered by professor Mark Whitehorn. If you happen to be a manager, a person whose performance is scored with NPS, you are into probability computations, or simply you like debunking managerial fads then this is a tale for you.