For the last 6 years, the Department of Technology Management and Innovation at NYU Tandon School of Engineering – Polytechnic Institute has hosted a conference on Human Capital Innovation in Technology & Analytics. Each conference has focused on a different critical business issue, bringing thought leaders and experts who are on the cutting edge of human capital analytics and related technologies.1
The critical business issue addressed in this year’s conference was, “Career Path Analytics: New Ways in Identifying & Implementing Passages to Organizational Success.” “With intense competition for top talent, effective career paths can play a critical role in an organization’s achieving its human capital strategic goals. In recognition of this importance, firms have begun to focus on innovative research, including human capital analytics, to better understand the dynamics of career paths and the interventions that can promote success.”2
You can learn more about this conference and access a recording of it (coming soon) at https://wp.nyu.edu/careerpathanalytics/
Below is a recap of the 5 conference presentations from Mercer, PepsiCo, IBM, and the NYU Tandon School of Engineering.
Mercer
Analytics to Uncover the Drivers of Success in Organizations
Dr. Brian Levine, Partner and Innovation Leader, Workforce Strategy & Analytics
Dr. Levin discussed Mercer’s proprietary Internal Labor Market (ILM) Analysis. “At a basic level, it examines the flow of people into, through, and out of an organization to answer fundamental questions about a firm’s workforce: who gets hired, who performs well, who advances and who stays.
At a more advanced level, ILM analysis provides critical insights into the operation of an organization’s management system, reflecting actual (versus perceived) practices and their consequences. It focuses on causal links between critical workforce events and behaviors over time, revealing which attributes and management practices account for workforce outcomes.”3
The information compiled in the ILM Analysis can be summarized in an ILM Map which provides a visual representation of the data.
More information about Mercer’s ILM Analysis can be found at https://www.mercer.com/content/dam/mercer/attachments/global/Talent/workforce-strategy-and-analytics/mercer-internal-labor-market-analysis.PDF
PepsiCo
Understanding Critical Drivers of Careers: Perspectives and Behaviors
Jonathan Wang, OD Associate Manager, Workforce Planning & Analytics
Vanessa A. Jean, OD Senior Analyst, Enterprise Organization Development CoE, Culture & Engagement Team
PepsiCo built on Dr. Levine’s ILM discussion as they discussed a Career Strategic Insight Survey that was conducted in 2016. This survey was a partnership between the Workforce Planning & Analytics team (mostly Ph.D.s) and the Enterprise Organizational Development Center of Excellence – Culture & Engagement (mostly Industrial & Organizational Psychologists). This collaboration allowed PepsiCo to consider that results from an analytical and people point of view. “Practical implications, learnings from the project, and cross-team collaboration were discussed.”4
IBM
How Cognitive Computing is Helping Employees Shape Their Careers
Dr. Anshul Sheopuri, Director, People Analytics & Cognitive Offerings. IBM Distinguished Engineer
Dr. Sheopuri discussed IBM’s use cognitive computing. “Cognitive computing is the simulation of human thought processes in a computerized model. Cognitive computing involves self-learning systems that use data mining, pattern recognition and natural language processing to mimic the way the human brain works. The goal of cognitive computing is to create automated IT systems that are capable of solving problems without requiring human assistance.”5
IBM uses artificial intelligence (AI) and machine learning (ML) as it relates to helping companies identify ways to better attract, engage, and retain employees/ groups of employees. Watson is its best-known product. Watson began as an IBM Research project which has evolved into the world’s first and most-advanced AI platform.6
IBM
Changing Skills and Training along the Career Path: Machine learning applications
Dr. Michael Peran, Executive Program Manager, Chief Analytics Office
Dr. Ben Zweig, Managing Strategy Consultant, Chief Analytics Office
In the second IBM presentation, Drs. Peran and Zweig presented their work on skills analysis and identification. Job titles have different meanings depending on the company and job descriptions often fail to capture what is really necessary to succeed in the position. By focusing on skills, companies can utilize a common language. IBM is using machine learning (ML) to identify in-demand skills as well as skills that have become generic. The goal is to identify which skills are going to be crucial in the future as well as help individuals understand where they fall in the lifecycle of a specific skill. This process will help companies and individuals better prepare for the future. Specifically, if a skill is becoming generic in the marketplace, alternative adjacent skills are identified and thus, can be developed. These adjacent skills incorporate some of the knowledge of the prior skill. By keeping employees informed about upcoming and in-demand skills, employees can make better decisions about career paths and companies will be able to develop employees with the skills the company needs to continue to succeed.
NYU Tandon School of Engineering
Exploring Career Paths of Knowledge Workers: SAP-Sponsored Analytic Agenda
Dr. Harold Kaufman, Professor of Management, NYU Tandon School of Engineering
Dr. Paul Squires, Research Scientist, NYU Tandon School of Engineering
This discussion focused on knowledge workers. A knowledge worker is “an employee whose job involves developing and using knowledge rather than producing goods or services”7
The preliminary results of the Drs. exploratory research into the career paths of successful knowledge workers were presented. While just at the beginning stages of analyzing 6 years of biweekly data from a large financial institution, the goal is to learn how to better enable knowledge workers to make better career decisions and provide companies with strategies and tools for managing knowledge worker engagement and productivity.8
The conference concluded with a Panel Discussion Plus Q&A with All Presenters: Where We Are & Future Directions.
What are your thoughts on career path analytics? What are some other resources “Agents” should consult?
1 “Career Path Analytics Conference.” NYU Tandon School of Engineering. Department of Technology Management and Innovation at NYU Tandon School of Engineering, n.d. Web. 25 May 2017.
2 Ibid.
3 “Internal Labor Market Analysis® (ILM).” Mercer. Mercer LLC, n.d. Web. 25 May 2017.
4 NYU Tandon School of Engineering – Polytechnic Institute. 6th Annual Conference on Human Capital Innovation in Technology & Analytics Career Path Analytics: New Ways in Identifying & Implementing Passages to Organizational Success. New York: NYU Tandon School of Engineering – Polytechnic Institute, 2017. Print.
5 “What is cognitive computing?” WhatIs.com. TechTarget, n.d. Web. 25 May 2017.
6 “AI and Cognitive Computing.” AI and Cognitive Computing – IBM Research. IBM, n.d. Web. 25 May 2017.
7 “Definition of “knowledge worker”.” Cambridge Dictionary. Cambridge University Press, n.d. Web. 25 May 2017.
8 NYU Tandon School of Engineering – Polytechnic Institute. 6th Annual Conference on Human Capital Innovation in Technology & Analytics Career Path Analytics: New Ways in Identifying & Implementing Passages to Organizational Success. New York: NYU Tandon School of Engineering – Polytechnic Institute, 2017. Print.
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