Fascinating research of how ONA can help us better understand who is being included and who isn't. Sadly, one of the things we see often in network analysis is the stratification of men and women. In this case, women are largely shut out of decision making, idea sharing, and emotional support networks. Thank you David Green 🇺🇦for sharing.
Co-Author of Excellence in People Analytics | People Analytics leader | Director, Insight222 & myHRfuture.com | Conference speaker | Host, Digital HR Leaders Podcast
Showcasing my collection of the best HR and people analytics resources for February: https://lnkd.in/e-gsi8QX With many companies and institutions – particularly in the US – cutting back on their DEI programs, a recent edition of Serena H. Huang, Ph.D. From Data to Action newsletter was well timed. Serena explains how people data and analytics can help reverse this trend and highlights a number of helpful resources. One of the resources Serena highlights is a seminal article by Bogdan Yamkovenko, PhD and Stephen Tavares originally published in Harvard Business Review. It provides a case study of a professional services firm that used organisational network analysis to identify that women were largely shut out of its decision making, idea sharing, and emotional support networks (see Figure). #humanresources #peopleanalytics #diversity #culture #inclusion #organizationalnetworkanalysis #hrtech #employeeexperience #leadership
Thanks David and Michael for sharing, indeed fascinating and eye opening data. ONA is at the tipping point of helping us quantify critical data like this, better understanding and taking action.
That's easily fixed. Don't rely on serendipity or 'good intentions' for idea-sharing to happen but structure this intentionally. Cross-silo, cross-gender, cross-anything. Asynchronous, network-driven, collaboration at any scale, as a deliberate way of getting something done, together. Psychology research shows that people tend to look for like-minded others which leads to underperformance in time. When collaboration and collective intelligence is well-structured, with the help of AI, people will encounter non-like-minded, which leads to outperformance.
Gordon Ritchie
3mo
It’s so Intersting given how matriarchal society survival really is.
Sarah J. Haggard
3mo
This is fascinating research! What I'd love to see is a comparison of this data from a Professional Services firm that had a technology (like tribute) that fostered cross-company connections vs. one that didn't. Part of my working thesis at Tribute is that we can democratize decision making, idea sharing and emotional support across organizations through meaningful connection.
Georg Peters
3mo
Stunning insights and evidence Michael Arena David Green 🇺🇦! That's where ONA-derived intelligence about lived organizational dynamics can turn into an "ONO!" ( 😉) experience with a huge reality check of how we tend to rely on confirmation bias to assure the organization that all is in order. What a powerful tool to leverage in our organization design approaches.
Account Executive and Partnerships Manager at Polinode
3moThank you for sharing this! It would be interesting to see if females have any mentorship in this organization, and at what level that stops. Typically we find that at a certain level female mentorship stops, basically reinforcing the "glass ceiling".